Patent Publication Number: US-9840026-B2

Title: Systems, methods and apparatus for providing comparative statistical information for a plurality of production facilities in a closed-loop production management system

Description:
This application is a Division of U.S. application Ser. No. 14/139,734 filed Dec. 23, 2013 which is a Continuation-in-Part of PCT/US2013/041661 filed May 17, 2013, the contents of each of which are incorporated herein by reference. 
    
    
     TECHNICAL FIELD 
     This specification relates generally to systems and methods for managing a production system, and more particularly to systems and methods for providing comparative statistical information for a plurality of production facilities in a production management system. 
     BACKGROUND 
     In many industries, consumers order a product based on a specification, and subsequent to their order, the product is manufactured based on a formulation that specifies a plurality of components and a particular method, procedure, or recipe to be followed. Once the product is made, it is shipped by the producer to the consumer. In such industries where an order is placed prior to manufacturing, orders are based on expected characteristics and costs of the product. When the product is made at a later date, it is important that the product be made and delivered according to the expected characteristics and costs. 
     In practice, however, changes often occur during the manufacturing and shipping process due to a variety of factors, such as an unavailability of components, a failure to include the correct quantity of a component specified in the recipe, or the addition of a component that is not listed in the formulation. Such changes may occur due to human error, either accidental or deliberate, or due to malfunction of a device involved in the production system, or due to unforeseen events. Furthermore, a component specified in the formulation may be incorrectly batched, or knowingly or unknowingly replaced with assumed equivalent components because the raw materials are not available, or for other reasons. One well known example is the use of either sucrose or high fructose corn syrup in soft drinks. Typically, during production of a soft drink, one of these two sweeteners is selected and used depending upon the cost and availability of the sweetener at the time when the soft drink product is manufactured. 
     Similar practices are used in the ready mix concrete industry. A given mixture of concrete, defined by a particular formulation (specifying types of components and quantities thereof), may be produced differently at different production facilities and/or at different times, depending a variety of factors. For example, the types and quantities of cement and Pozzolanic cementitious materials, chemicals, different types of aggregates used often varies between batches, due to human error, or for reasons which may be specific to the time and location of production. Some components may not be available in all parts of the world, a component may be incorrectly batched, components may be replaced deliberately or accidentally, etc. Furthermore, in the ready mix concrete industry, it is common for changes in the mixed composition to occur during transport of the product. For example, water and/or chemicals may be added due to weather, or due to the length of time spent in transit to the site where the ready mix concrete is poured. Changes to a mixture may also occur during the batching process. For example, an incorrect amount of a critical component such as water or cementitious may be added. Similarly, an incorrect amount of fly ash or other pozzolans, such as slag, may be used to make the cementitious portion. 
     Due to the reasons set forth above, a customer often receives a product which differs from the product ordered. The quality of the product may not meet expectations. Furthermore, any change made to a product may impact the producer&#39;s cost and profits. 
     In addition, in many industries, various activities important to a producer&#39;s business, such as sales, purchasing of raw materials, production, and transport, are conducted independently of one another. The disjointed nature of the sales, purchasing of raw materials, production, and transport creates an additional hindrance to the producer&#39;s, and the customer&#39;s, ability to control the quality and cost of the final product. 
     Accordingly, there is a need for improved production management systems that provide, to producers and to customers, greater control over various aspects of the production system used to produce a product, and thereby provide greater control over quality and costs. 
     SUMMARY 
     In accordance with an embodiment, a production management system is provided. The production management system is used in the production of a product made from a formulation specifying a mixture of individual components, where the customer orders the product prior to its manufacture. System and methods described herein allow a user to manage costs, and the quality of the product, from the point of order, through the production process, transport of the product, and delivery of the product to the customer. In one embodiment, a master database module communicates with the sales, purchasing, manufacturing and shipping systems to monitor and control costs and quality of the product at various stages in the sales, production, and delivery cycles. 
     In one embodiment, systems used for sales, purchasing of raw materials, manufacturing of the product, and shipping of a product are tied together to allow for the management and control of cost and quality of the product. Systems and methods described herein allow for different ownership of different data while allowing others to use the data so as to perform their function. Thus, a user may own the mixture data but allow the manufacturer to use the mixture data in order to make the product. Such ownership is accomplished by having a single gateway to add data to the system and by using a single master database. 
     By using a single master database which stores all of the data relating to the mixture, the components to make the mixture, the method to make the mixture, specifics about the products to include its costs, methods of shipment as well as costs associated with each one of these items, quality and costs are managed during production. 
     Furthermore, changes made at any point during the manufacturing process are transmitted to the master database so that a record is maintained on the product. This allows real time costs and real time quality control of the product. Thus, variations are minimized between budget goals and operations, both theoretically and actually. 
     In addition, alerts may be issued when the actual values vary from the theoretical values. Thus, if one component is replaced with an equivalent, the master database is notified and an alert may be generated if the replacement component is not within specified tolerances. Alternatively, if one or more components are batched in the manufacturing process in amounts exceeding specified tolerances as compared to the target, theoretical amounts for each component, then an alert may be issued. 
     By tying together the systems used for sales, purchasing of components and raw materials, maintaining formulations of mixtures, production of the mixtures and products and the shipping of the products, through a master database, improved management of quality and costs may be achieved. 
     Actual and theoretical data may be captured and stored in the master database. For example, statistical data for each batch produced at a particular production facility may be generated and stored. Comparisons between theoretical and actual values are made and alerts are generated when the actual falls outside the tolerances set by the theoretical. Such alerts are done in real time because each of the separate units used for purchasing, manufacturing and transport provide feedback to the master database. 
     In another embodiment, comparative statistical information may also be generated for a plurality of production facilities, and benchmarks may be established in order to provide information that may be used by a producer to improve the efficiency of one or more production facilities. 
     In accordance with an embodiment, a quality control and cost management system can be defined as comprising: a database module having stored therein a concrete recipe, a first tolerance and a second tolerance, the first tolerance associated with an informational alert and the second tolerance associates with an actionable alert; an input module in communication with the database module and transmitting the concrete recipes, the first tolerance and the second tolerance to the database module; a production module in communication with the database module, the production module associated with a concrete production facility that makes a concrete mixture based on the concrete recipe and transmitting the concrete mixture to the database module; a comparative module in communication with the database modules, comparing the concrete mixture to the concrete recipe, determining if the concrete mixture meets or exceeds the first tolerance and determining if the concrete mixture meets or exceeds the second tolerance; and an alerts module in communication with the comparative module, generating the informational alerts if the concrete mixture meets or exceeds the first tolerance, and generating the actionable alert if the concrete mixture meets or exceeds the second tolerance. In another embodiment, the database module, the comparative module and the alerts module are all housed in a single, master module at a single location. Suitably, the single master module is a first computer processing unit at a first location. 
     In another embodiment, the input module is housed in a second computer at a second location. The production module may be housed in a third computer at the concrete ready-mix facility. 
     In another embodiment, there is a single database module which houses the plurality of concrete recipes, a plurality of first tolerances and a plurality of second tolerances. 
     In another embodiment, there are a plurality of production modules each of which is associated with a different production facility. 
     In another embodiment, there is a single comparative module and a single alerts module. In another embodiment, each of the modules is a computer. 
     In one embodiment, the quality control management system employs a quality control management method comprising: inputting to a database a concrete recipe, a first tolerance for generating an informational alert and a second tolerance for generating an actionable alert; making a concrete mixture based on the concrete recipe; inputting to the database the concrete mixture; comparing the concrete mixture to the concrete recipe; determining if the concrete mixture meets or exceeds the first tolerance; determining if the concrete mixture data is within the second tolerance; generating the informational alert if the concrete mixture data is not within the first tolerance; and generating the actionable alert if the concrete mixture data is not within the second tolerance. 
     In one embodiment, the formulation for the concrete mixture includes detailed specifics about proposed ingredients, proposed amounts of the proposed ingredients, and proposed costs of the proposed ingredients. 
     In another embodiment, the formulation for the concrete mixture includes detailed specifics about actual ingredients, actual amounts of the actual ingredients and actual costs of the actual ingredients. 
     In another embodiment, the comparing step comprises comparing the actual ingredients to the proposed ingredients, comparing the actual amounts of the actual ingredients to the proposed amounts of the proposed ingredients, and comparing the actual costs of the actual ingredients to the proposed cost of the proposed ingredients. 
     In accordance with another embodiment, a method of managing a production system is provided. For each of a plurality of production facilities, a series of actions is performed. For each of a plurality of batches of a concrete mixture produced at the respective production facility based on a formulation, a first difference between a measured quantity of cementitious and a first quantity specified in the formulation is determined. A first standard deviation is determined based on the first differences. For each of the plurality of batches, a second difference between a measured quantity of water and a second quantity specified in the formulation is determined. A second standard deviation is determined based on the second differences. The first and second differences may be expressed as a percentage or as a real number, for example. A first benchmark is selected from among the first standard deviations, and a second benchmark is selected from among the second standard deviations. An amount by which costs may be reduced by improving production at the production facility to meet the first and second benchmarks is determined. 
     In one embodiment, the formulation is stored at a master database module, and a localized version of the formulation is provided to each respective production facility. 
     In another embodiment, the plurality of production facilities are managed by a producer. The producer is allowed to access, via a network, in real time, a page showing the first differences, the second differences, the first benchmark, the second benchmark, and the amount by which costs may be reduced. 
     In another embodiment, for each of the plurality of production facilities: a first percentage value equal to first difference divided by the first quantity specified in a formulation is determined, and a first standard deviation is determined based on the first percentage values. A second percentage value equal to second difference divided by the second quantity specified in a formulation is determined, and a second standard deviation is determined based on the second percentage values. 
     In another embodiment, a generalized benchmark is determined based on the first and second benchmarks. An amount by which costs may be reduced by improving production at the production facility to meet the generalized benchmark is determined. 
     In accordance with another embodiment, a method is provided. A formulation associated with the product, the formulation specifying a plurality of components and respective quantities required to produce the product, is transmitted to a production facility, in response to receiving an order for a product from a customer. Data relating to the product produced at the production facility is received, in real time. The data is compared, in real time, to at least one pre-established tolerance. An alert is transmitted, in real time, to the customer if the data is not within the pre-established tolerance. 
     In one embodiment, the product is delivered to a site specified by the customer. 
     In another embodiment, a difference between a quantity of a component specified in the formulation and an actual quantity of the component in the product produced is determined. A determination is made as to whether the difference is within the tolerance. 
     In another embodiment, a difference between a cost of a component specified in the formulation and a cost of the component in the product produced is determined. A determination is made as to whether the difference is within the tolerance. 
     In another embodiment, a method of determining a measure of concrete strength performance quality for concrete produced at a production facility is provided. For each of a plurality of batches of concrete produced at a production facility, a first difference between a measured quantity of cementitious and a first quantity specified in a formulation is determined. A first standard deviation is determined based on the first differences. For each of the plurality of batches, a second difference between a measured quantity of water and a second quantity specified in the formulation is determined. A second standard deviation is determined based on the second differences. A measure of concrete strength performance quality for the production facility is determined based on the first standard deviation and the second standard deviation. A measure of a cost of adjusting the formulation is determined based on the measure of concrete strength performance quality. 
     In accordance with another embodiment, a system comprises a memory and at least one processor. The processor is configured to perform a series of actions. For each of a plurality of production facilities, the processor determines, for each of a plurality of batches of a concrete mixture produced at the respective production facility based on a formulation, a first difference between a measured quantity of cementitious and a first quantity specified in the formulation. The processor also determines a first standard deviation based on the first differences. The processor further determines, for each of the plurality of batches, a second difference between a measured quantity of water and a second quantity specified in the formulation. The processor determines a second standard deviation based on the second differences. The processor selects a first benchmark from among the first standard deviations, and a second benchmark from among the second standard deviations, and determines an amount by which costs may be reduced by improving production at the production facility to meet the first and second benchmarks. 
     These and other advantages of the present disclosure will be apparent to those of ordinary skill in the art by reference to the following Detailed Description and the accompanying drawings. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1A  illustrates a product management system in accordance with an embodiment; 
         FIG. 1B  shows an exemplary menu that may be presented to a customer in accordance with an embodiment; 
         FIG. 1C  is a flowchart of a method of managing a production system in accordance with an embodiment; 
         FIG. 2  is a flowchart of a method of producing a mixture in accordance with an embodiment; 
         FIG. 3  is a flowchart of a method of handling an order received from a production facility in accordance with an embodiment; 
         FIG. 4  illustrates a method of responding to an alert when a production facility replaces an ingredient with a known equivalent, in accordance with an embodiment; 
         FIG. 5  is a flowchart of a method of responding to an alert indicating a difference between a batched quantity and a specified quantity in accordance with an embodiment; 
         FIG. 6  is a flowchart of a method of managing transport-related data in accordance with an embodiment; 
         FIG. 7A  shows a production management system in accordance with another embodiment; 
         FIG. 7B  shows a production management system in accordance with another embodiment; 
         FIG. 7C  shows a production management system in accordance with another embodiment; 
         FIG. 8  illustrates a system for the management of localized versions of a mixture formulation in accordance with an embodiment; 
         FIG. 9  is a flowchart of a method of generating localized versions of a mixture formulation in accordance with an embodiment; 
         FIG. 10  shows a mixture formulation and several localized versions of the mixture formulation in accordance with an embodiment; 
         FIGS. 11A-11B  illustrate a system for synchronizing versions of a mixture formulation in accordance with an embodiment; 
         FIG. 12  is a flowchart of a method of synchronizing a localized version of a mixture formulation with a master version of the mixture formulation in accordance with an embodiment; 
         FIGS. 13A-13B  comprise a flowchart of a method of managing a closed-loop production system in accordance with an embodiment; 
         FIG. 14  shows an exemplary web page that displays information relating to purchase, production and delivery of a mixture in accordance with an embodiment; 
         FIG. 15  shows a production management system in accordance with another embodiment; 
         FIGS. 16A-16B  comprise a flowchart of a method of producing and analyzing a mixture in accordance with an embodiment; 
         FIG. 17  is a flowchart of a method of producing a formulation-based mixture in accordance with an embodiment; 
         FIG. 18  is a flowchart of a method of determining a measure of concrete strength performance quality for concrete produced at a production facility in accordance with an embodiment; 
         FIGS. 19A-19B  comprise a flowchart of a method of providing comparative statistical information relating to a plurality of production facilities in accordance with an embodiment; 
         FIG. 20  shows a web page containing statistical information for a plurality of production facilities in accordance with an embodiment; and 
         FIG. 21  is a high-level block diagram of an exemplary computer that may be used to implement certain embodiments. 
     
    
    
     DETAILED DESCRIPTION 
     In accordance with embodiments described herein, systems and methods of managing a closed-loop production management system used for production and delivery of a formulation-based product are provided. Systems, apparatus and methods described herein are applicable to a number of industries, including, without limitation, the food manufacturing industry, the paint industry, the fertilizer industry, the chemicals industry, the oil refining industry, the pharmaceuticals industry, agricultural chemical industry and the ready mix concrete industry. 
     In accordance with an embodiment, a method of managing a closed loop production system is provided. An order relating to a formulation-based product is received, wherein fulfilling the order requires production of the formulation-based product at a first location, transport of the formulation-based product in a vehicle to a second location different from the first location, and performance of an activity with respect to the formulation-based product at the second location. First information relating to a first change made to the formulation-based product at the first location is received, from the first location, prior to transport of the formulation-based product. Second information relating to a second change made to the formulation-based product during transport of the formulation-based product is received during transport of the formulation-based product. Third information relating to the activity performed with respect to the formulation-based product at the second location is received from the second location. The first, second, and third information are stored in a data structure, and may be displayed with an analysis of the impact of selected information on the cost of the product. 
     In one embodiment, the processor operates within a product management system comprising a plurality of modules operating at independent locations associated with various stages of the ordering, production, transport and delivery of the product. 
     In accordance with an embodiment, the product is a formulation-based product. In one embodiment, the product is a formulation-based concrete product. In other embodiments, the formulation-based product may be any type of product that is manufactured based on a formulation. For example, the formulation-based product may be a chemical compound or other type of chemical-based product, a petroleum-based product, a food product, a pharmaceutical drug, etc. Systems, apparatus and methods described herein may be used in the production of these and other formulation-based products. 
     In another embodiment, statistical information concerning a plurality of production facilities is generated and provided to a producer and/or a customer. For each of a plurality of production facilities, a series of actions is performed. For each of a plurality of batches of a concrete mixture produced at the respective production facility based on a formulation, a first difference between a measured quantity of cementitious and a first quantity specified in the formulation is determined. A first standard deviation is determined based on the first differences. For each of the plurality of batches, a second difference between a measured quantity of water and a second quantity specified in the formulation is determined. A second standard deviation is determined based on the second differences. A first benchmark is selected from among the first standard deviations, and a second benchmark is selected from among the second standard deviations. An amount by which costs may be reduced by improving production at the production facility to meet the first and second benchmarks is determined. 
     The terms “formulation,” “recipe,” and “design specification” are used herein interchangeably. Similarly, the terms “components” and “ingredients” are used herein interchangeably. 
       FIG. 1A  illustrates a production management system in accordance with an embodiment. Product management system  10  includes a master database module  11 , an input module  12 , a sales module  13 , a production module  14 , a transport module  15 , a site module  16 , an alert module  17  and a purchasing module  18 . 
     Master database module  11  may be implemented using a server computer equipped with a processor, a memory and/or storage, a screen and a keyboard, for example. Modules  12 - 18  may be implemented by suitable computers or other processing devices with screens for displaying and keep displaying data and keyboards for inputting data to the module. 
     Master database module  11  maintains one or more product formulations associated with respective products. In the illustrative embodiment, formulations are stored in a database; however, in other embodiments, formulations may be stored in another type of data structure. Master database module  11  also stores other data related to various aspects of production management system  10 . For example, master database module may store information concerning acceptable tolerances for various components, mixtures, production processes, etc., that may be used in system  10  to produce various products. Stored tolerance information may include tolerances regarding technical/physical aspects of components and processes, and may also include tolerances related to costs. Master database module  11  may also store cost data for various components and processes that may be used in system  10 . 
     Each module  12 - 16  and  18  transmits data to master database module  11  by communication lines  21 - 26 , respectively. Master database module  11  transmits data to modules  13 ,  14 ,  17  and  18  by communication lines  31 - 34 , respectively. Each communication line  21 - 26  and  31 - 34  may comprise a direct communication link such as a telephone line, or may be a communication link established via a network such as the Internet, or another type of network such as a wireless network, a wide area network, a local area network, an Ethernet network, etc. 
     Alert module  17  transmits alerts to customers by communication line  35  to site module  16 . 
     Master database module  11  stores data inputted from modules  12 - 16  and  18 . Master database module  11  stores data in a memory or storage using a suitable data structure such as a database. In other embodiments, other data structures may be used. In some embodiments, master database module  11  may store data remotely, for example, in a cloud-based storage network. 
     Input module  12  transmits to master database module  11  by communication line  21  data for storage in the form of mixture formulations associated with respective mixtures, procedures for making the mixtures, individual ingredients or components used to make the mixture, specifics about the components, the theoretical costs for each component, the costs associated with mixing the components so as to make the product or mixture, the theoretical characteristics of the product, acceptable tolerances for variations in the components used to make the product, the time for making and delivering the product to the site and costs associated shipping the product. 
     The terms “product” and “mixture” are used interchangeably herein. 
     Data transmitted by input module  12  to master database module  11  and stored in master database module  11  may be historical in nature. Such historical data may be used by the sales personal through sales module  13  to make sales of the product. 
     In one embodiment, sales module  13  receives product data by communication line  31  from master database module  11  relating to various products or mixtures that are managed by system  10 , the components that make up those products/mixtures, the theoretical costs associates with the components, making the mixture and delivery of the mixture, times for delivery of the mixture and theoretical characteristics and performance specifications of the product. 
     Sales module  13  may present all or a portion of the product data to a customer in the form of a menu of options.  FIG. 1B  shows an exemplary menu  55  that may be presented to a customer in accordance with an embodiment. Menu  55  comprises a list of mixtures available for purchase, including Mixture A ( 61 ), Mixture B ( 62 ), Mixture C ( 63 ), etc. Each mixture shown in  FIG. 1B  represents a product offered for sale. For example, each mixture may be a respective concrete mixture that may be purchased by a customer. Menu  55  is illustrative only; in other embodiments, a menu may display other information not shown in  FIG. 1B . For example, a menu may display the components used in each respective mixture, the price of each mixture, etc. 
     From the menu, the customer may choose one or more products to purchase. For example, a customer may purchase Mixture A ( 61 ) by selecting a Purchase button ( 71 ). When the customer selects a mixture (by pressing Purchase button ( 71 ), for example), sales module  13  generates an order for the selected mixture and transmits the order by communication line  22  to master database module  11 . The order may specify the mixture selected by the customer, the components to be used to make the selected mixture, a specified quantity to be produced, the delivery site, the delivery date for the product, etc. An order may include other types of information. 
     In accordance with an embodiment, the customer may input a specialty product into system  10 . Such input may be accomplished through input module  12 . 
     Customer orders are transmitted to master database module  11 . Master database module  11  uses an integrated database system to manage information relating to the orders, as well as the production, transport, and delivery of the ordered products.  FIG. 1C  is a flowchart of a method of managing a production system in accordance with an embodiment. At step  81 , an order relating to a formulation-based product is received, wherein fulfilling the order requires production of the formulation-based product at a first location, transport of the formulation-based product in a vehicle to a second location different from the first location, and performance of an activity with respect to the formulation-based product at the second location. As described above, the customer&#39;s order is transmitted to master database module  11 . Master database module receives the order from sales module  13 , and stores the order. 
     Based on the order inputted to master database module  11 , master database module  11  places a production order for production of the product to production module  14  by communication line  32 . Production module  14  is located at a production facility capable of manufacturing the purchased product in accordance with the order. 
     In the illustrative embodiment, the product is a formulation-based product. Thus, the product may be produced based on a formulation defining a plurality of components and respective quantities for each of the components. The formulation may also specify a method, or recipe, for manufacturing the product. The production order provided to the production module  14  may include the mixture or product to be made, the components to be used to make the mixture or product, the specifics about the individual components, the method to make the mixture and the delivery dates. The product is produced at the production facility and placed in a vehicle for transport to a delivery site specified in the order. 
     At step  83 , first information relating to a first change made to the formulation-based product at the first location is received from the first location, prior to transport of the formulation-based product. If any changes are made to the product at the production facility, production module  14  transmits information relating to such changes to master database module  11 . For example, a particular component specified in the formulation may be replaced by an equivalent component. In another example, a quantity of a selected component specified in the formulation may be altered. Master database module  11  receives and stores such information. 
     At step  85 , second information relating to a second change made to the formulation-based product during transport of the formulation-based product is received during transport of the formulation-based product. If any changes are made to the product during transport of the product, transport module  15  transmits information relating to such changes to master database module  11 . Master database module  11  receives and stores such information. 
     Upon arrival at the specified delivery site, the product is delivered. At step  87 , third information relating to the activity performed with respect to the formulation-based product at the second location is received from the second location. For example, site module  16  may transmit to master database module  11  information indicating the time of delivery, or information relating to the performance of the product after delivery. 
     In the illustrative embodiment, information transmitted among modules  11 - 19 , and to a producer or customer, may be transmitted in the form of an alert. An alert may be any suitable form of communication. For example, an alert may be transmitted as an electronic communication, such as an email, a text message, etc. Alternatively, an alert may be transmitted as an automated voice message, or in another form. 
     In one embodiment, information is transmitted to master database module  11  in real time. For example, strict rules may be applied requiring that any information concerning changes to a product that is obtained by any module (including production module  14 , purchase module  18 , transport module  15 , site module  16 , etc.) be transmitted to master database module  11  within a predetermined number of milliseconds. 
     Various embodiments are discussed in further detail below. 
     As described above, in some embodiments, the product is made at a production facility in accordance with a predetermined formulation. Production module  14  operates at the production facility and has stored data as to the specifics of the individual components or raw ingredients on hand at the facility.  FIG. 2  is a flowchart of a method of producing a mixture in accordance with an embodiment. At step  210 , an order to make a product/mixture from specified components is received. Referring to block  220 , if the exact components or ingredients are in stock, the production facility proceeds to make the mixture/product (step  230 ). If the production facility does not have on hand the exact components needed to make the mixture/product, then the method proceeds to step  260  and determines whether an equivalent component is in stock. If an equivalent component is in stock, the method proceeds to step  270 . At step  270 , production module  14  makes the product using the equivalent component and alerts master database module  11  of the change. Such a replacement may change the cost of the raw materials and/or the characteristics of the mixture/product which is finally made. 
     Returning to block  260 , if there is no equivalent component in stock, the production module  14  may send an order by communication line  32  to master database module  11  (step  240 ) for the specified component (or for the equivalent component). When the order is received, production module  14  makes the product (step  250 ). 
     In another embodiment, production module  14  alerts master database module  11  if the method of manufacture specified in a mixture formulation is modified. For example, a step of the method may be changed or eliminated, or a new step may be added. Master database module stores information related to the change. Master database module  11  may also determine if the change is within acceptable tolerances and alert the customer if it is not within acceptable tolerances. For example, master database module  11  may compare the modified method to stored tolerance information to determine if the modified method is acceptable. 
       FIG. 3  is a flowchart of a method of handling an order received from a production facility in accordance with an embodiment. At step  310 , an order is received from production module  14 , by master database module  11 . At step  320 , master database module  11  places an order by communication line  34  to purchase module  18  to purchase the needed components or raw materials. Purchase module  18  transmits by communication line  26  the specifics of the components that it has purchased and the estimated delivery date to the production facility as well as the costs associated with the component. Purchase module  18  is associated with a raw material/component supply facility. At step  340 , master database module  11  receives the specifics on the components actually purchased by purchase module  18 . 
     Referring to block  350 , if the components purchased (by purchase module  18 ) are the same as the order placed, the method proceeds to step  380 , and the product is shipped to the production facility. If the components purchased (by purchase module  18 ) differ from those specified in the order, the method proceeds to block  360 . Master database module  11  compares the components purchased, either those replaced by the production facility or those purchased by the purchase module  18 , to stored tolerance information (which may include tolerances regarding physical/technical aspects of a component and/or cost tolerances). Referring to block  360 , if the replacement components fall within acceptable tolerances both for performance characteristics and cost, then production is continued and, at step  370 , the order is shipped to the production facility. If the cost or characteristics of the raw ingredients fall outside acceptable tolerances, then the method proceeds to step  390 . At step  390 , master database  11  transmits an alert by communication line  33  to alert module  17  and the components are shipped to the production facility. Alert module  17  receives the alert from master database module  11  and, in response, transmits by communication lines  35  an alert to the customer. As shown in  FIG. 1 , the alert from alert module  17  is transmitted by communication lines  35  to site module  16 . 
       FIG. 4  is a flowchart of a method of responding to an alert in accordance with an embodiment. Specifically,  FIG. 4  illustrates a method of responding to an alert when a production facility replaces an exact ingredient with a known equivalent, in accordance with an embodiment. At step  410 , an alert indicating an equivalent replacement is received by master database module  11  from production module  14 . Referring to block  420 , a determination is made by master database module  11  whether the equivalent component is within acceptable tolerances. If the equivalent component is within acceptable tolerances, the method proceeds to step  430  and the product is made. Master database module  11  instructs production module  14  to proceed with manufacturing the mixture. If the equivalent component is not within acceptable tolerances, the method proceeds to step  440 . At step  440 , and an alert is transmitted and the product is made. For example, an alert may be transmitted by master database module  11  or by alert module  17  to the customer. 
     At step  450 , the variances of actual versus theoretical cost and performance factors are stored at master database module  11 . 
     As described above, production module  14  receives instructions from master database module  11 , prior to production of a mixture, specifying the recipe and components required for producing the mixture. However, from time to time the batched amounts of each component (i.e., the amount of each component in the batch actually produced) differs from the amounts specified in the recipe received from master database module  11  due to statistical or control factors. 
     When quantity variances are outside the specified tolerances, alerts are transmitted and the actual amounts produced, and cost variances from target costs, are provided to master database module  11 .  FIG. 5  is a flowchart of a method of responding to an alert indicating a difference between a batched quantity and a specified recipe quantity in accordance with an embodiment. At step  510 , an alert is received indicating a difference between a batched quantity and a specified recipe quantity. The alert typically indicates variances of actual versus theoretical cost and performance factors. Referring to block  520 , if the differences are within acceptable tolerances, the method proceeds to step  530  and the product is delivered. If the differences are not within acceptable tolerances, the method proceeds to step  540 . At step  540 , an alert is transmitted and the product is delivered. An alert may be transmitted to the customer, for example. At step  550 , the variances of actual versus theoretical cost and performance factors are stored at master database module  11 . In other embodiments, variances are not stored. 
     After production of the mixture, the production facility uses one or more transport vehicles to transport the product/mixture from the production facility to the customer&#39;s site. Such transport vehicles may include trucks, automobiles, trains, airplanes, ships, etc. Each transport vehicle is equipped with a transport module such as transport module  15 . Transport module  15  transmits by communication line  24  to master database  11  information concerning the transport of the product/mixture. The information concerning the transport can include changes which are made to the mixture during transport (e.g., addition of water or other chemicals), the length of travel, temperatures during transport, or other events that occur during transport. For example, in the ready mix concrete industry it is common for a truck transporting the mixture from the production facility to a delivery site to add water and/or chemicals during the transport process. Information indicating such addition of chemicals or water is transmitted to master database module  11  by communication line  24 . Furthermore, in the ready mix concrete industry, measuring and recording the temperature of the concrete during transport is advantageous for several reasons: (a) such data can be used to determine a maturity value per ASTM c1074; (b) such data, in combination with reference heat of hydration data may be used to determine degree of hydration attained during transport; (c) the data, in combination with reference strength and heat of hydration data may be used to determine pre-placement strength loss due to pre-hydration prior to discharge of the concrete at project site. 
     The transport-related information is transmitted by transport module  15  to master database module  11 . For example, such information may be transmitted in the form of an alert. The information is analyzed by master database module  11  to determine whether the changes that are made are within acceptable tolerances.  FIG. 6  is a flowchart of a method of managing transport-related data in accordance with an embodiment. 
     At step  610 , information indicating changes to a mixture during transport is received from a transport module. For example, master database module  11  may receive an alert from transport module  15  indicating that changes occurred to a mixture during transport of the mixture. Referring to block  620 , a determination is made whether the changes are within acceptable tolerances. If the changes are within acceptable tolerances, the method proceeds to step  630 . At step  630 , the product/mixture is delivered to the customer&#39;s site. If the changes are not within acceptable tolerances, the method proceeds to step  640 . At step  640 , an alert is transmitted to the customer and the product/mixture is delivered. Alerts to the customer may be issued by alert module  17 , or by master database module  11 . At step  650 , the information concerning changes occurring during transport is saved at master database module  11 . In other embodiments, the information concerning changes is not stored. 
     In the illustrative embodiment, the customer&#39;s site or location is equipped with site module  16 , which transmits to master database module  11 , by communication line  25 , information about the mixture of product that is delivered to the site. Such information may include, for example, information indicating the actual performance of the product/mixture as delivered. Master database module  11  stores the actual performance data. Master database module  11  may provide to the customer a report concerning various aspects of the actual product delivered. 
     Site module  16  may also receive alerts from alert module  17  by communication line  35 . In the illustrative embodiment, alert module  17  is a module separate from master database module  11 . However, in other embodiments, the functions of alert module  17  may be performed by master database module  11 . 
     Alert module  17  may also transmit final reports concerning the products to site module  16 , thereby enabling the seller and the customer a way of managing the product. Feedback provided throughout the production process, as illustrated above, advantageously allows the customer and the manufacturer to manage costs and quality of the products. 
     The alert functions described above facilitate the process of managing production and costs. In response to any alert, the customer or the manufacturer has the ability to make a decision not to continue the production or delivery of the product because the product has fallen outside of acceptable tolerances. 
     While the illustrative embodiment of  FIG. 1A  includes only one production module, one transport module, one site module, one alert module, one purchase module, one input module, and one sales module, in other embodiments, a system may include a plurality of production modules, a plurality of transport modules, a plurality of site modules, a plurality of alert modules, a plurality of purchase modules, a plurality of input modules, and/or a plurality of sales modules. For example, in an illustrative embodiment, suppose that a system used by a company in the ready mix concrete industry includes a master database module  11  residing and operating on a server computer located in Pittsburgh, Pa. The company&#39;s sales force may be located in Los Angeles, Calif., where the sales module  13  resides and operates (on a computer). Suppose that a sale is made in Los Angeles, and the purchase order specifies a site in San Francisco, Calif. Thus, master database module  11  may output an order to a production module  14  which is located at a ready mix production facility in the vicinity of San Francisco, Calif. Suppose further that a single production facility in the vicinity of San Francisco cannot handle the volume of the concrete that is needed for the job site in San Francisco. In such a case, master database module  11  may output to a plurality of production facilities, each having a production module  14 , the necessary orders for fulfillment. Thus, the system includes a plurality of production modules, one in each of the various production facilities. The production facilities produce the specified mixture and transport the ready mix concrete in a plurality of trucks to the customer site in San Francisco. Each truck has a transport module associated therewith. Suppose that one or more of the production modules does not have the specific components that were specified in the purchase order for the concrete. Thus, adjustments may be made at the production facility to the concrete mixes, and information concerning such adjustments are transmitted back to the master data base module  11 . Such adjustment information may be processed in accordance with the steps illustrated in  FIGS. 3 and/or 4 . 
     During the transport of the ready mix concrete from the various production facilities, the transport modules  15  in each of the trucks transmit to the master database module  11  any changes made to the mixture. The master database module  11  may then perform the method described  FIG. 6 . In a similar manner, master database module  11  is informed of any changes occurring during production and, as a result, master database module  11  may perform the method described in  FIG. 5 . 
     Finally, the concrete is delivered to the customer site in San Francisco and information concerning the delivered concrete may be transmitted to the master database module  11 . The site module  16  may also be used to provide the master database module  11  with information relating to one or more of the following: measurements of the actual heat of hydration taken from the fresh state through the hardening process, strength characteristics of the concrete after it is hardened, etc. Advantageously, the feedback provided in this manner to master database module  11  from the various modules enables the customer of the concrete in Los Angeles to monitor, on a real time basis, the concrete poured at the customer&#39;s construction site in San Francisco, without having to physically be in San Francisco. 
     Furthermore, the customer in Los Angeles may monitor, on a real time basis, costs associated with the concrete which is delivered to the site in San Francisco. 
     Furthermore, the ready mix concrete producer may associate, in real time, variances in one or more parameters relating to the concrete&#39;s performance from specified expectations, and correlate such variances to actual batched versus the expected specified recipe. These capabilities advantageously allow the maintenance of consistent, low standard deviation production batching from a mixture recipe baseline, and production of concrete that has a consistent strength performance with a low standard deviation. 
     Changes in materials may impact a producer&#39;s cost of materials (COM). An increase in COM can in turn impact the producer&#39;s profitability. In many instances, any increase (in percentage terms) in the COM results in a much greater impact on profitability (in percentage terms). For example, it has been observed that, using ACI 318 statistical quality criteria, it can be demonstrated that each 1% cement or water variance from the mix design theoretical recipe value can result in a cost impact of around $0.2 to $0.4 per cubic yard. Since such variances can typically range from 2% to 10%, the cost impact may range from $0.4 to $10 per cubic yard annually. This cost impact is a very large percentage of the average profit of a producer in the ready mix concrete industry, which is on the order of $1/cubic yard. 
     Advantageously, the integrated production management system and method described herein enables a producer to manage the overall production system for ready mix concrete, and allows greater control over changes that may impact the producer&#39;s costs (and profits). The integrated production management system and method described herein also provides a customer increased control over the customer&#39;s construction site. 
     For convenience, several examples relating to the ready mix concrete industry are described below. 
     Concrete Construction &amp; Manufacturing/Production Examples 
     Examples are provided for three different market segments: 
     A. Ready Mix Concrete 
     B. Contractors 
     C. State Authorities 
     Closed Loop Solutions (CLS) Overview 
     Set forth below is a discussion of a closed loop solution (CLS) in accordance with an embodiment. Each operation has a set of theoretical goals and obtained physical or actual results. 
     Practically all operational IT architectures include a collection of disparate information systems that need to work together. 
     CLS is an information technology solution that enforces: 
     Data Integrity across linked or associated disparate information systems (Ready Mix Example: Mix costs &amp; formulae to have data integrity or be the same across mix management, sales, dispatch, batch panels, and business systems) 
     Closed Loop Data Integrity, meaning that the operations&#39; goals and its actual physical results match within tolerances (concrete batch &amp; mix BOMs (Bill of Materials) closely match) 
     Four Types of CLS for Different Market Segments 
     
         
         
           
             I. Ready Mix Producers: Closed Loop Integration (CLI):
           1) CLI has been implemented as a CLS application for many Ready Mix Producers in the US and Canada.   2) CLI applications are real-time, two-way interfaces with production systems   3) One of the main purposes of CLI is to enforce data integrity between batches in trucks and parent mix designs; CLI closes the loop between the mix management and production cycles.   
         
             II. Ready Mix Producers: Closed Loop Sales Management (CLSM):
           1) CLSM is a CLS application for Ready Mix Producers in the US and Internationally.   2) One of the main purposes of Closed Loop Sales Management is a project-based workflow for the industry sales process, tracking actual versus target profitability, This application closes the loop between actual and target profitability factors. One benefit is maximization of profitability.   
         
             III. Contractors: Closed Loop Quality &amp; Cost:
           1) The solution for the Contractor market segment is similar to the Closed Loop Quality application, except that it also includes concrete delivered cost management   2) One of the main purposes of Closed Loop Quality &amp; Cost is a real time enforcement of placed concrete obtained specs and performance to the applicable project specs, plus monitoring placed versus as-purchased cost—This application closes the loop between both the delivered versus specified project concrete performance and cost.   
         
             IV. State Authorities: Closed Loop Quality:
           1) This solution is intended for the Authorities market segment as a modification of the CLI production driven Ready Mix application   2) One of the main purposes of Closed Loop Quality is a real time enforcement of placed concrete obtained specs and performance to the applicable project specs. This application closes the loop between the delivered versus specified project concrete performance.   Set forth below are several application examples.
 
[A] Ready Mix Concrete Producers—CLS TYPE: Closed Loop Integration for Real Time, Production Level, Consolidated Mix Management
   
         
             I. Ready Mix Needs Include:
           1) Consolidate critical mix, cost, and quality data in a single database   2) Minimize quality issues   3) Utilize materials efficiently   4) Real time information visibility—customized by user profile   
         
             II. Ready Mix Economics &amp; its Management:
           1) 50% to 70% of cost of business (COB) is cost of materials (COM)   2) A 1% increase in COM can translate to more than a 10% profitability drop   3) Thus, production level materials management is important to profitability.   
         
           
         
       
    
     
       
         
           
               
               
               
             
               
                 TABLE 1 
               
               
                   
               
               
                   
                 Item 
                 per Cyd 
               
               
                   
               
             
            
               
                   
                 Net Profit % 
                    5.0% 
               
               
                   
                 Price 
                 $85.00 
               
               
                   
                 Cost of Business (COB) 
                 $80.75 
               
               
                   
                 Net Profit 
                  $4.25 
               
               
                   
                 Cost of materials (COM) as % of 
                   55.0% 
               
               
                   
                 COB 
                   
               
               
                   
                 COM 
                 $44.41 
               
               
                   
                 1% increase in COM 
                  $0.44 
               
               
                   
                 Change in COB 
                  $0.44 
               
               
                   
                 Change in Net profit 
                 ($0.44) 
               
               
                   
                 % change in net profits per % COM 
                 −10.5% 
               
               
                   
               
            
           
         
       
         
         
           
             
               
                 Table 1 shows the relationship between COM and profitability. 
               
             
             III. To Meet Quality, Materials Utilization, and Information Visibility Needs:
           1) Optimize mixes to performance and cost goals in a consolidated database using mix optimization tools.   2) Implement closed loop integration (CLI) for the production level management of optimized mixes; may use alerts application for alert notification of out-of-tolerance batches.   3) Use CLI to ship concrete to mix baselines for implementing production level, real time cost and quality management. The CLI system in effect uses mixes as a budgetary tool for both quality and cost control.
 
[B] Contractors—CLS Type: Closed Loop Cost &amp; Quality
 
Table 2 illustrates advantages of real time, consolidated costs and quality management.
   
         
           
         
       
    
     
       
         
           
               
             
               
                 TABLE 2 
               
               
                   
               
             
            
               
                 
                   
                     
                     
                         
                         
                     
                   
                 
               
               
                   
               
            
           
         
       
         
         
           
             I. Contractor Concrete Related Needs:
           1) Consolidate aspects of concrete related data across all projects in a single database.   2) Ensure obtained quality meets specifications in order to minimize quality issues and avoid project delays   3) Track &amp; match up contracted volume &amp; cost versus actual delivered volumes &amp; costs   4. Real time information visibility—customized by user profile   
         
             II. Basic Contractor Economics:
           1) Concrete cost and quality related schedule delay can amount to around 16% in profit loss.   2) Thus, production level concrete quality and cost management are important to contractor profitability   
         
             III. Closed Loop Solution to Meet Quality, Cost Management, and Information Visibility Needs:
           1) Implement Closed Loop Cost &amp; Quality (CLCQ) for the real time management of obtained versus a) specified performance and recipe factors, b) Actual versus budgeted cost and volume factors; use an alert system for alert reporting &amp; notification of out-of-tolerance monitored variables.   2) For each project, consolidate quality &amp; engineering team, tests, concrete deliveries &amp; poured volumes, cost, project mix designs and specs, project documents, in a single unified database; do this across all of the contractor&#39;s projects in one or more countries—makes possible sharing and learning cross project experience   3) Use CLCQ to maintain quality, enforce meeting specs in real time, enforce budgetary cost &amp; volume goals, and create real time, production level visibility including alerting reports.
 
Contractor Concrete Economics
   
         
             1. 10% to 20% of a project cost is concrete cost; in some regions/countries this number may be close to 20% 
             2. Since contractor margin is on the order of 1% to 5%, a 1% change in concrete cost may result on average in about a 8% profitability drop 
             3. Additionally, it is import to avoid schedule slippage due to quality issues:
           1. Each delay day may represent roughly 0.2% to 1% of total project cost—assume 0.2%   2. Each delay day due to concrete quality for a $100 mil project may cost $200,000, or roughly an 8% drop in profitability   
         
             4. Concrete cost and quality schedule delay may total to around 16% in profit loss. 
             5. Thus, production level quality and cost management are important to contractor profitability, and the related cost factors can be managed by a closed loop production system
 
[C] State Authorities—CLS TYPE: Closed Loop Quality
 
For Real Time, Consolidated Concrete Quality Management
 
             I. State Authority Key Concrete Related Needs:
           1) Consolidate all aspects of concrete related data across all projects in a single database including mix specifications and designs, batch data, and test data, as well as the required QC/QA plan   2) Make possible data access, input, and sharing cross projects, and by project-based entities   3) Ensure obtained quality and performance meet specifications in order to minimize quality issues and avoid project delays   4) Track &amp; match up contracted costs &amp; volumes versus actual values   5) Real time information visibility—customized by project &amp; user profile   
         
             II. State Authority Economics—Costs of poor quality and reduced longevity:
           1) Assume: $100 mil structure; 30,000 m3 concrete @ $100/m3 delivered   2) Concrete quality related schedule delay costs may amount to $70,000/delay day   3) Poor quality future repair costs may amount to $120,000 per 1% increase in strength CV   4) If the building service life is reduced by one year due to poor quality, then a revenue loss of around $1.25 mil. may result   5) Thus, production level, real time quality and cost management is important to the owner economics   6) These significant cost factors may be managed by the closed loop system   
         
             III. To meet quality, cost management, and information visibility needs:
           1) For each project, consolidate concrete production volumes, project mix designs and specifications, and tests in a single database. Also, include the QA/QC plan   2) Make possible data access, input, and sharing across projects. Restrict access by project and user profile. Include: State officials, Engineers/Architects, Contractors, Test Labs, and Ready Mix Producers   3) Implement Closed Loop Quality (CLQ) for the real time management of obtained versus specified performance and recipe factors; use an alert system for alert notification of out-of-tolerance batches. Reconcile tests against QC/QA plan.   4) Create real time, production level visibility including alerting reports.
 
State Authority Concrete Economics
 
Assume a $100 Mil Structure Requiring 30,000 m3 Concrete @ an Average of $100/m3 Delivered.
   
         
             1. Suppose that:
           1) The owner wishes to amortize the $100 mil cost during a 10-year period, which amounts to a monthly rate of $833,333, and wishes to lease the building for the same amount   2) The owner takes a 30 year mortgage @ 5% interest amounting to a monthly payment of $535 k.   3) This leaves a monthly cash flow of around $300 k, or $3.6 mil/yr   
         
             2. Poor Quality Cost Factors include:
           1) Each delay day may result in an opportunity cost of roughly $70,000, or around 2% of annual cash flow   2) If poor quality goes unnoticed, and is repaired at a later date, each 1% increase in the 28-day strength coefficient of variation from its ACI 318 design base may result in future repair costs of $120 k, or around 7% of the annual cash flow   3) If poor quality goes unnoticed, and is not treated, each one year reduction in the service life may amount to $3.6 in lost revenues. Annualized over the first 10 years, this changes the monthly cash flow to around a loss of ($60,000)   
         
             3. Concrete poor quality costs without a reduction in the service life can amount to around 9% of cash flow; with service life reduction, the cash flow can turn negative. 
             4. Thus, production level quality management is important to the owner economics, and the related cost factors can be managed by the closed loop system 
           
         
       
    
     In accordance with another embodiment, a mixture formulation is maintained by master database module  11 . Localized versions of the mixture formulation intended for use at respective production facilities are generated, stored, and provided to the respective production facilities, as necessary. At a respective production facility, the mixture is produced based on the localized version of the mixture formulation. 
       FIG. 7A  shows a production management system  700  in accordance with another embodiment. Similar to product management system  10  of  FIG. 1A , product management system  700  includes a master database module  11 , an input module  12 , a sales module  13 , a production module  14 , a transport module  15 , a site module  16 , an alert module  17 , and a purchase module  18 . 
     A localization module  19  resides and operates in master database module  11 . For example, master database module  11  and localization module  19  may comprise software that resides and operates on a computer. 
     Localization module  19  generates one or more localized versions of a mixture formulation for use at respective production facilities where a mixture may be produced. Localization module  19  may, for example, access a mixture formulation maintained at master database module  11 , analyze one or more local parameters pertaining to a selected production facility, and generate a modified version of the mixture formulation for use at the selected production facility. Localization module  19  may generate localized versions of a particular mixture formulation for one production facility or for a plurality of production facilities. For example, master database module  11  may generate localized versions of a mixture formulation for every production facility owned or managed by a producer. Likewise, localization module  19  may generate localized versions of selected mixture formulations maintained by master database module  11 , or may generate localized versions for all mixture formulations maintained by master database module  11 . 
       FIG. 7B  shows a production management system  702  in accordance with another embodiment. Similar to product management system  10  of  FIG. 1A , product management system  702  includes a master database module  11 , an input module  12 , a sales module  13 , a production module  14 , a transport module  15 , a site module  16 , an alert module  17 , and a purchase module  18 . In the embodiment of  FIG. 7B , localization module  19  is separate from master database module  11  and is connected to master database module  11  by a link  41 . For example, master database module  11  may reside and operate on a first computer and localization module  19  may reside and operate on a second computer remote from master database module  11 . For example, localization module  19  may reside and operate on a second computer located at a production facility. Localization module  19  may communicate with master database module  11  via a network such as the Internet, or via another type of network, or may communicate via a direct communication link. 
       FIG. 7C  shows a production management system  703  in accordance with another embodiment. Product management system  703  includes a master database module  11 , an input module  12 , a sales module  13 , a production module  14 , a transport module  15 , a site module  16 , an alert module  17 , a purchase module  18 , and a localization module  19 . Modules  11 - 19  are connected to a network  775 . Modules  11 - 19  communicate with each other via network  775 . For example, various modules may transmit information to master database  11  via network  775 . 
     Network  775  may comprise the Internet, for example. In other embodiments, network  775  may comprise one or more of a number of different types of networks, such as, for example, an intranet, a local area network (LAN), a wide area network (WAN), a wireless network, a Fibre Channel-based storage area network (SAN), or Ethernet. Other networks may be used. Alternatively, network  775  may comprise a combination of different types of networks. 
       FIG. 8  illustrates a system for the management of localized versions of a mixture formulation in accordance with an embodiment. In the illustrative embodiment of  FIG. 8 , master database module  11  comprises localization module  19 , a mixture database  801 , a local factors database  802 , a components database  803 , and a tolerances database  804 . A mixture formulation  810  associated with a particular mixture is maintained in mixture database  801 . While only one mixture formulation is shown in  FIG. 8 , it is to be understood that more than one mixture formulation (each associated with a respective mixture) may be stored by master database module  11 . 
     Master database module  11  is linked to several production facilities, as shown in  FIG. 8 . In the illustrative embodiment, master database module  11  is in communication with Production Facility A ( 841 ), located in Locality A, Production Facility B ( 842 ) located in Locality B, and Production Facility C ( 843 ), located in Locality C. While three production facilities (and three localities) are shown in  FIG. 8 , in other embodiments more or fewer than three production facilities (and more or fewer than three localities) may be used. 
     In the embodiment of  FIG. 8 , local factors database  802  stores local factor data relating to various production facilities, including, for example, local availability information, local cost information, local market condition information, etc. Localization module  19  may obtain local factor data based on the information in local factors database  802 . Components database stores information pertaining to various components of product mixtures, such as, for example, technical information concerning various components, costs of various components, etc. Tolerances database  804  stores information defining tolerances related to various components and mixtures. 
     In the illustrative embodiment, localization module  19  accesses mixture formulation  810  and generates a localized version for Production Facility A ( 841 ), shown in  FIG. 8  as Mixture Formulation A ( 810 -A). Localization module  19  generates a localized version for Production Facility B ( 842 ), shown in  FIG. 8  as Mixture Formulation B ( 810 -B). Localization module  19  also generates a localized version for Production Facility C ( 843 ), shown in  FIG. 8  as Mixture Formulation C ( 810 -C). Mixture Formulation A ( 810 -A), Mixture Formulation B ( 810 -B), and Mixture Formulation C ( 810 -C) are stored at master database module  11 . 
     In order to generate a localized version of a mixture formulation for a particular production facility, localization module  19  accesses local factors database  802  and analyzes one or more local factors pertaining to the particular production facility. For example, localization module  19  may analyze one or more local availability factors representing local availability of components in the mixture formulation, one or more local market condition factors representing characteristics of the local market, one or more local cost factors representing the cost of obtaining various components in the local market, etc. 
     Localization module  19  may modify a mixture formulation based on a local factor. For example, if a local market factor indicates a strong preference for a product having a particular feature (or a strong bias against a certain feature), localization module  19  may alter the mixture formulation based on such local market conditions. If a particular component is not available in a local market, localization module  19  may alter the mixture formulation by substituting an equivalent component that is locally available. Similarly, if a particular component is prohibitively expensive in a particular locality, localization module  19  may reduce the amount of such component in the mixture formulation and/or replace the component with a substitute, equivalent component. 
     It is to be understood that  FIG. 8  is illustrative. In other embodiments, master database module  11  may include components different from those shown in  FIG. 8 . Mixtures and local factors may be stored in a different manner than that shown in  FIG. 8 . 
       FIG. 9  is a flowchart of a method of generating localized versions of a mixture formulation in accordance with an embodiment. The method presented in  FIG. 9  is discussed with reference to  FIG. 10 .  FIG. 10  shows mixture formulation  810  and several corresponding localized versions of the mixture formulation in accordance with an embodiment. 
     At step  910 , a formulation of a product is stored, the formulation specifying a plurality of components and respective quantities. As discussed above, mixture formulation  810  is stored at master database module  11 . Referring to  FIG. 10 , mixture formulation  810  specifies the following components and quantities: C-1, Q-1; C-2, Q-2; C-3, Q-3; C-4, Q-4; and C-5, Q-5. Thus, for example, mixture formulation  810  requires quantity Q-1 of component C-1, quantity Q-2 of component C-2, etc. Mixture formulation  810  may also specify other information, including a method to be used to manufacture the mixture. 
     At step  920 , a plurality of production facilities capable of producing the product are identified, each production facility being associated with a respective locality. In the illustrative embodiment, localization module  19  identifies Production Facility A ( 841 ) in Locality A, Production Facility B ( 842 ) in Locality B, and Production Facility C ( 843 ) in Locality C. 
     Referring to block  930 , for each respective one of the identified production facilities, a series of steps is performed. At step  940 , a local factor that is specific to the corresponding locality and that relates to a particular one of the plurality of components is identified. Localization module  19  first accesses local factors database  802  and examines local factors relating to Locality A and Production Facility A ( 841 ). Suppose, for example, that localization module  19  determines that in Locality A, component C-1 is not readily available. 
     At step  950 , the formulation is modified, based on the local factor, to generate a localized version of the formulation for use at the respective production facility. In the illustrative embodiment of  FIG. 10 , localization module  19  substitutes an equivalent component SUB-1 for component C-1 to generate a localized version  810 -A of mixture  810 . Localized version  810 -A is intended for use at Production Facility A ( 841 ). 
     At step  960 , the localized version of the formulation is stored in association with the formulation. In the illustrative embodiment, localized version  810 -A is stored at master database module  11  in association with mixture formulation  810 . 
     Referring to  FIG. 9 , the routine may return to step  930  and repeat steps  930 ,  940 ,  950 , and  960  for another production facility, as necessary. Suppose, for example that localization module  19  determines that in Locality B (associated with Production Facility B ( 842 )), local purchasers prefer a product with less of component C-2. Localization module  19  thus reduces the quantity of component C-2 in the respective localized version  810 -B of mixture  810 , as shown in  FIG. 10 . In particular, the amount of component C-2 in localized version  810 -B is (0.5)*(Q-2). Localized version  810 -B is intended for use at Production Facility B ( 842 ). Localized version  810 -B is stored at master database module  11  in association with mixture formulation  810 , as shown in  FIG. 8 . 
     Suppose that localization module  19  also determines that in Locality C (associated with Production Facility C ( 843 )), local purchasers prefer a product with an additional component C-6. Localization module  19  further determines that component C-6 is an equivalent of component C-5, but is of lower quality. To accommodate local market conditions, localization module  19  reduces the quantity of component C-5 to (0.7)*(C-5) and also adds a quantity Q-6 of component C-6 to generate a localized version  810 -C of mixture  810 , as shown in  FIG. 10 . Localized version  810 -C is intended for use at Production Facility C ( 843 ). Localized version  810 -C is stored at master database module  11  in association with mixture formulation  810 , as shown in  FIG. 8 . 
     Master database module  11  may subsequently transmit one or more of the localized versions  810 -A,  810 -B,  810 -C to Production Facilities A, B, and/or C, as necessary. For example, suppose that an order is received for Mixture Formulation  810 . Suppose further that Production Facility A and Production Facility B are selected to produce the mixture. Master database module  11  accordingly transmits the localized version Mixture Formulation A ( 810 -A) to Production Facility A ( 841 ). Mixture Formulation A ( 810 -A) is stored at Production Module  14 . Master database module  11  also transmits the localized version Mixture Formulation B ( 810 -B) to Production Facility B ( 842 ). Mixture Formulation B ( 810 -B) is stored at a respective production module (not shown) operating at Production Facility B ( 842 ). 
     The mixture is then produced at each designated production facility based on the respective localized version of the mixture formulation. In the illustrative embodiment, the mixture is produced at Production Facility A ( 841 ) in accordance with the localized version Mixture Formulation A ( 810 -A)). The mixture is produced at Production Facility B ( 842 ) in accordance with the localized version Mixture Formulation B ( 810 -B). 
     In accordance with another embodiment, master database module  11  from time to time updates the master version of a mixture formulation (stored at master database module  11 ). Master database module  11  also monitors versions of the mixture formulation maintained at various production facilities. If it is determined that a version of the mixture formulation stored at a particular production facility is not the same as the master version of the mixture formulation, an alert is issued and the local version is synchronized with the master version. For purposes of the discussion set forth below, any version of a mixture formulation that is stored at master database module  11  may be considered a “master version” of the mixture formulation. 
     In an illustrative embodiment, suppose that master database module  11  updates Mixture Formulation  810 . This may occur for any of a variety of reasons. For example, the cost of one of the components in Mixture Formulation  810  may increase substantially, and the particular component may be replaced by an equivalent component. Referring to  FIG. 11A , the updated formulation is stored at master database module  11  as Updated Mixture Formulation  810 U. 
     Master database module  11  also generates localized versions of the updated mixture formulation. Thus, for example, master database module  11  generates an updated localized version of Mixture Formulation  810 U for Production Facility  841  (in Locality A). The updated localized version of is stored at master database module  11  as Updated Mixture Formulation A ( 810 U-A), as shown in  FIG. 11A . 
     Master database module  11  identifies one or more production facilities that store a localized version of Mixture Formulation  810 , and notifies each such production module that Mixture Formulation  810  has been updated. If a production module does not have the correct updated version of the mixture formulation, the localized version must be synchronized with the updated master version stored at master database module  11 .  FIG. 12  is a flowchart of a method of synchronizing a localized version of a mixture formulation with a master version of the mixture formulation in accordance with an embodiment. 
     In the illustrative embodiment, certain aspects of production at Production Facility A ( 841 ) are managed by production module  14 . For example, production module  14  may operate on a computer or other processing device located on the premises of Production Facility A ( 841 ). At step  1210 , a determination is made that a mixture formulation stored at a particular production facility is different from the mixture formulation stored by the master database module. For example, master database module may communicate to production module  14  (operating at Production Facility A ( 841 )) that Mixture Formulation A ( 810 -A) has been updated. Production module  14  determines that its current localized version of the mixture formulation is not the same as Updated Mixture Formulation A ( 810 U-A). 
     At step  1220 , an alert is transmitted indicating that the version of the mixture formulation stored at the particular production facility is different from the mixture formulation stored by master database module  11 . Accordingly, production module  14  transmits an alert to master database module  11  indicating that its local version of the mixture formulation is not the same as the updated version stored at master database module  11 . 
     At step  1230 , the version of the mixture formulation stored at the particular production facility is synchronized with the mixture formulation stored at the master database module  11 . In response to the alert, master database module  11  provides production module  14  with a copy of Updated Mixture Formulation A ( 810 U-A). Production module  14  stores Updated Mixture Formulation A ( 810 U-A), as shown in  FIG. 11B . 
     Various methods and system described above may be used in an integrated closed-loop production system to manage a production system. In accordance with an embodiment, a method of managing a closed-loop production system is provided. Master database module  11  provides to sales module  13  descriptions, prices, and other information relating to a plurality of available mixtures, enabling sales module  13  to offer several options to potential customers. Specifically, master database module  11  provides information relating to a plurality of concrete mixtures. Sales module  13  may present the information to a customer in the form of a menu, as discussed above with reference to  FIG. 1B . 
     Suppose now that a customer considers the available mixtures and selects one of the plurality of concrete mixtures. Suppose further that the customer submits an order for the selected mixture, specifying parameters such as quantity, date and place of delivery, etc. For illustrative purposes, suppose that the customer selects the mixture associated with mixture formulation  810  (shown in  FIG. 8 ) and specifies a delivery site located in or near Locality A (also shown in  FIG. 8 ). Master database module  11  utilizes a closed-loop production system such as that illustrated in  FIG. 1A  to manage the sale, production and delivery of the selected mixture to the customer. 
       FIGS. 13A-13B  comprise a flowchart of a method of managing a closed-loop production system in accordance with an embodiment. At step  1310 , an order for a mixture selected from among the plurality of mixtures is received, by a processor, from a sales module operating on a first device different from the processor, the order being associated with a purchase of the mixture by a customer. In the illustrative embodiment, sales module  13  transmits the order for the selected concrete mixture to master database module  11 . The order specifies the selected mixture and other information including quantity, date and place of delivery, etc. Master database module  11  receives the order for the selected concrete mixture from sales module  13 . 
     At step  1310 , a mixture formulation defining a plurality of components and respective quantities required to produce the selected mixture is provided, by the processor, to a production module operating on a second device located at a production facility capable of producing the mixture. Accordingly, master database module  11  identifies one or more production facilities capable of producing the selected mixture. Production facilities may be selected based on a variety of factors. For example, master database module  11  may select one or more production facilities that are located near the delivery site specified in the order. In the illustrative embodiment, master database module  11  selects Production Facility A ( 841 ) due to the fact that the customer&#39;s delivery site is located in or near Locality A. It is to be understood that more than one production facility may be selected and used to produce a mixture to meet a particular order. 
     Master database module  11  transmits Mixture Formulation A ( 810 -A) (or any updated version thereof) to Production Facility A ( 841 ). Production module  14  manages and monitors the production process. In the illustrative embodiment, production module  14  determines that a particular component of mixture formulation A ( 810 -A) is currently unavailable and replaces the component with a known equivalent. Production module  14  accordingly transmits an alert to master database module  11  indicating that the component has been replaced. An alert may then be provided to the customer, as well. Production of the selected mixture proceeds. In one embodiment, the alert may be transmitted in real time (e.g., within a specified time period after production module  14  receives the information). 
     At step  1315 , first information identifying a modification made to the mixture formulation is received, by the processor, from the production module, prior to production of the mixture. Master database module  11  receives the alert from production module  14 . 
     At step  1320 , an alert is transmitted if the first information does not meet a first predetermined criterion. If the modification does not meet specified requirements, master database module  11  transmits an alert to the customer. In one embodiment, the alert is transmitted in real time. 
     In the illustrative embodiment, a quantity of the mixture actually produced at Production Facility A ( 841 ) differs from the quantity specified in the order. Production module  14  transmits an alert to master database module  11  and to alert module  17  indicating that the quantity actually produced differs from the quantity ordered. The alert may be transmitted in real time. At step  1325 , second information indicating an actual quantity of the mixture produced is received, from the production module, prior to delivery of the mixture. Master database module  11  receives the alert and stores the information specifying the actual quantity produced. 
     At step  1330 , an alert is transmitted if the second information does not meet a second predetermined criterion. If the quantity of concrete mixture actually produced does not meet specified requirements, master database module  11  transmits an alert to the customer. In one embodiment, the alert is transmitted in real time. 
     In another embodiment, production module  14  may inform master database module  11  if the method of manufacture specified in the mixture formulation is changed. For example, a step of the method may be modified or eliminated, or a new step may be added. 
     The method now proceeds to step  1335  of  FIG. 13B . 
     The mixture is now placed on a transport vehicle, such as a truck, and transported to the delivery site specified in the order. The vehicle includes transport module  15 , which may be a software application operating on a processing device, for example. The vehicle may have one or more sensors to obtain data such as temperature of the mixture, water content of the mixture, etc. During transport, transport module  15  monitors the condition of the mixture and detects changes made to the mixture. 
     At step  1335 , third information identifying a change made to the mixture produced during transport of the mixture is received, from a transport module operating on a third device located on a vehicle transporting the mixture produced from the production facility to a delivery site. In the illustrative embodiment, the driver of the truck makes a change to the mixture during transport to the delivery site. For example, the driver may add additional water to the mixture while the mixture is in the truck. Transport module  15  transmits an alert to master database module  11  and to alert module  17  indicating the change that was made. In one embodiment, the alert is transmitted in real time. 
     At step  1340 , an alert is transmitted if the third information does not meet a third predetermined criterion. If the third information is not within pre-established tolerances, an alert is issued to the customer. In one embodiment, the alert is transmitted in real time. 
     In the illustrative embodiment, the mixture is delivered to the customer&#39;s construction site. At the customer&#39;s site, site module  16  monitors delivery of the mixture and performance of the mixture after delivery. At step  1345 , fourth information relating to delivery of the mixture produced is received, from a site module operating on a fourth device associated with the delivery site. When the mixture is delivered to the specified delivery site, site module  16  transmits an alert to master database module indicating that the mixture has been delivered. In one embodiment, the alert is transmitted in real time. 
     At step  1350 , an alert is transmitted if it is determined that the fourth information does not meet a fourth predetermined criterion. For example, if the delivery of the mixture occurs outside of a specified delivery time frame (e.g., if the delivery is late), master database module  11  (or alert module  17 ) may transmit an alert to the customer. In one embodiment, the alert is transmitted in real time. 
     The site module  16  may also monitor certain performance parameters of the mixture after it is delivered and used. At step  1355 , fifth information relating to a performance of the mixture is received, from the site module. After the mixture is used (e.g., when the concrete mixture is laid), site module  16  may transmit to master database module  11  information including performance data. In one embodiment, the information is transmitted in real time. 
     At step  1360 , an alert is transmitted if it is determined that the fifth information does not meet a fifth predetermined criterion. Thus, if the performance data does not meet specified requirements, master database module  11  (or alert module  17 ) transmits an alert to the customer. In one embodiment, the alert is transmitted in real time. 
     As described above, alerts are issued at various stages of the production process to inform master database module  11  of events and problems that occur during production, transport, and delivery of the mixture. Master database module  11  (or alert module  17 ) may then alert the customer if a parameter does not meet specified requirements. 
     Master database module  11  may collect information from various modules involved in the production of a mixture, in real time, and provide the information to the customer, in real time. For example, when master database module  11  receives from a respective module information pertaining to the production of a mixture, master database module  11  may transmit an alert to the customer in the form of an email, or in another format. 
     In one embodiment, master database module  11  maintains a web page associated with a customer&#39;s order and allows the producer (and/or the customer) to access the web page. Information received from various modules involved in the production of the mixture may be presented on the web page. In addition, information relating to cost analysis may be presented on the web page. For example, an analysis of the impact of a modification to the mixture formulation, a change to the mixture during production or transport, a delay in delivery, or any other event, on the cost of materials (COM) and/or on the producer&#39;s profitability may be provided on the web page. 
       FIG. 14  shows an exemplary web page that may be maintained in accordance with an embodiment. For example, access to the web page may be provided to a producer to enable the producer to manage the production system and to control costs and profitability. Web page  1400  includes a customer ID field  1411  showing the customer&#39;s name or other identifier, a mixture purchased field  1412  showing the mixture that the customer purchased, a quantity field  1413  showing the quantity of the mixture ordered, and a delivery location field  1414  showing the delivery location specified by the customer. 
     Web page  1400  also includes a Production-Related Events field  1420  that lists events that occur during production of the mixture. Master database module  11  may display in field  1420  information received from various modules during production of the mixture, including information indicating modifications made to the mixture formulation prior to production, changes made to the mixture during transport of the mixture, information related to delivery, etc. In the illustrative embodiment of  FIG. 14 , field  1420  includes a first listing  1421  indicating that component C-5 of the mixture formulation was replaced by an equivalent component EQU-1 at Production Facility A (prior to production). Field  1420  also includes a second listing  1422  indicating that delivery of the mixture was completed on 04-19-XXXX. 
     Web page  1400  also includes a Cost Impact Table  1431  showing the expected impact of certain events on cost and profitability. Table  1431  includes an event column  1441 , a cost impact column  1442 , and a profitability impact column  1443 . Master database module  11  accesses stored information concerning the costs of various components and calculates the expected impact of one or more selected events on the producer&#39;s costs. In the illustrative embodiment, row  1451  indicates that the replacement of C-5 by EQU-1 is expected to increase the cost of the mixture by +2.1%, and reduces the producer&#39;s profit by 6.5%. 
     In accordance with another embodiment, statistical measures of various aspects of the production process are generated for a plurality of production facilities and used to establish one or more benchmarks. 
     Concrete performance is generally specified and used on the basis of its 28 day compressive strength, or at times for pavement construction on the basis of its flexure strength at a specified age such as 7 or 28 days. The methods of measurement and reporting are generally specified by the American Society for Testing and Materials, or ASTM (such as ASTM C39 and C78) and the equivalent International standards such as applicable EN (European Norms). Additionally, concrete mix design and quality evaluation is guided by American Concrete Institute (ACI) 318 as a recommended procedure, which is almost always mandated by project specifications in the US, and also used in many countries worldwide. In ACI 318 a set of statistical criteria are established that relate concrete mix design strength, F′cr, to its structural grade strength, F′c, as used in the design process by the structural engineer. Thus the concrete producer designs his or her mixtures to meet certain F′cr values in order to meet certain desired F′c structural grades specified in the project specifications. A variable relating F′cr and F′c is the standard deviation of strength testing, SDT, as determined per prescribed ACI procedures. The ACI formulae include: 
     For F′c≦5,000 psi:
 
 F′cr=F′c+ 1.34 SDT  (ACI 1)
 
     (1% probability that the run average of 3 consecutive tests are below F′c)
 
 F′cr=F′c− 500+2.33 SDT  (ACI 2)
 
     (1% probability that a single test is 500 psi or more below F′c) 
     For F′c&gt;5,000 psi—[1] applies but[2] is replaced by [3] below:
 
 F′cr=F′c− 0.1 F′c+ 2.33 SDT  (ACI 3)
 
     (1% probability that a single test is 10% of F′c or more below F′c) 
     In general the above equations can be expressed in the following form:
 
Mix Design Strength ( F′cr )=Structural Grade Strength ( F′c )+An overdesign factor proportional to the Standard Deviation of testing, SDT.
 
     The factor SDT is a direct measure of concrete quality and reliability, and experience shows that it can range widely from an excellent level of on the order of 80 to 200 psi, to the very poor level of over 1,000 psi. Concrete mix design cost factor is directly proportional to SDT, which means that high quality concrete is also less expensive to produce since it would contain less cement (or cementitious materials, which include binders such as slag, fly ash, or silica fume in addition to cement). 
     Because of the above ACI approach now in practice for many decades, the industry (including ready mix producers, test labs, contractor, and specifying engineers) has paid significant attention to test results variability and the standard deviation of testing. 
       FIG. 15  shows a production management system  1500  in accordance with an embodiment. Product management system  1500  includes a master database module  11 , input module  12 , sales module  13 , production module  14 , transport module  15 , site module  16 , alert module  17 , purchase module  18 , and localization module  19 . Production management system  1500  also includes a comparison module  1520 , a network  1575  and a cloud database  1530 . Various components, such as master database module  11 , may from time to time store data in cloud database  1530 . Production management system  1500  also comprises a user device  1540 . 
     In another embodiment, the master database module  11 , the comparison module  1520 , and the alert module  17  are housed within a single module. 
     In one embodiment, a batch of a concrete mixture is produced at a production facility in accordance with a formulation. Certain aspects of the batch produced are measured and differences between the batch produced and the formulation requirements are identified. The differences are analyzed to determine if the differences fall within acceptable tolerances. 
       FIGS. 16A-16B  comprise a flowchart of a method of producing and analyzing a mixture in accordance with an embodiment. At step  1605 , a mixture formulation is input into a master database module. In the illustrative embodiment, input module  12  provides a formulation for a particular concrete mixture to master database module  11 . Master database module  11  stores the formulation. 
     In one embodiment, a plurality of mixture formulations is provided by input module  12  to master database module  11 . A master list of mixtures, comprising a plurality of mixture formulations, is maintained at master database module  11 . 
     As described above, master database module  11  may generate localized versions of a mixture formulation. Referring again to  FIG. 8 , localization module  19  generates localized mixture formulations for Production Facility A, Production Facility B, etc. 
     At step  1610 , data relating component types and costs are input into the master database module. Technical data for a variety of components used in the formulation (and in other formulations), as well as cost data for the components, is provided by input module  12  to master database module  11 . Technical data and cost data for various components may be stored in a components database  803 , shown in  FIG. 8 . 
     At step  1615 , first tolerance data and second tolerance data are input into the master database module. Input module  12  transmits to master database module  11  information defining a first tolerance and information defining the second tolerance. For example, tolerances may indicate that an amount of water in a batch of a concrete mixture must fall within a specified range, or that an amount of cementitious in the concrete mixture must fall within a specified range. Tolerance information is stored in tolerances database  804 . 
     At step  1620 , a formulation is provided to the production module. Master database module  11  transmits the mixture formulation to a selected production facility. For example, master database module  11  may provide a respective localized mixture formulation to Production Facility A ( 841 ). A different localized mixture formulation may be provided to Production Facility B ( 842 ), for example. 
     At step  1625 , the mixture is produced at the production facility. The production facility produces one or more batches of the mixture. For example, Production Facility A ( 841 ) may produce a batch of the mixture based on the mixture formulation. 
     At step  1630 , actual mixture data is provided to master database module. After a batch is made, production module  14  provides batch data indicating the actual quantity of the mixture produced, the components used to make the batch, the quantity of each component, etc., to master database module  11 . Production module  14  obtains batch data indicating the actual quantity of the mixture produced, which components were actually used, etc., and transmits the batch data to master database module  11 . Master database module  11  may store the batch data. The method now proceeds to step  1635  of  FIG. 16B . 
     At step  1635 , the comparison module compares the actual mixture data to the first tolerance. Comparison module  1520  accesses the stored batch data, and accesses tolerance information in tolerances database  804  (shown in  FIG. 8 ). Comparison module  1520  applies the first tolerance to the batch data to determine whether the batch data is acceptable. 
     At step  1640 , the comparison module compares the actual mixture data to the second tolerance. Comparison module  1520  accesses the stored batch data and applies the second tolerance to the batch data to determine whether the batch data is acceptable. 
     Referring to block  1645 , a determination is made whether the actual mixture data are within the first tolerance and the second tolerance. Comparison module  1520  determines whether the actual mixture data are within the specified tolerances. If the actual mixture data are within the first tolerance and the second tolerance, the method proceeds to step  1660 . If the actual mixture data are not within the first tolerance and the second tolerance, the method proceeds to step  1650 . 
     At step  1650 , an alert is transmitted to the master database module. Comparison module  1520  transmits to master database module  11  an alert indicating that the batch data are not within acceptable tolerances. 
     At step  1655 , an alert is transmitted to the customer. Alert module  17  transmits to the customer an alert indicating that the batch data are not within acceptable tolerances. 
     In another embodiment, a first alert is issued if the batch data is not within the first tolerance, and a second alert is issued if the batch data is not within the second tolerance. 
     At step  1660 , the mixture is delivered to the customer site. The mixture is placed on a transport vehicle and is delivered to the site specified by the customer in the order. 
     In accordance with another embodiment, comparison module  1520  monitors the quantity of one or more components in each batch actually produced, and compares the amounts to the amounts of such components as specified in the formulation. 
       FIG. 17  is a flowchart of a method of producing a formulation-based mixture in accordance with an embodiment. In another illustrative embodiment, suppose that another customer orders a desired quantity of the mixture defined by Mixture Formulation ( 810 ). Several production facilities may be selected to produce the mixture, including Production Facility C ( 841 ). Master database module  11  transmits localized Mixture Formulation C ( 810 -C) to production facility C ( 843 ). 
     At step  1710 , a batch of a mixture is produced based on a formulation. A batch of the mixture is produced at Production Facility C ( 843 ) based on localized Mixture Formulation A ( 810 -C). Referring to  FIG. 10 , localized Mixture Formulation ( 810 -C) specifies the following components and quantities: C-1, Q-1; C-2, Q-2; C-3, Q-3; C-4, Q-4; C-5, (0.7)*(Q-5); and C-6, Q-6. 
     Referring to block  1720 , for each component X in the batch, a series of step is performed. Thus, the steps described below are performed with respect to each of the components C-1, C-2, C-3, C-4, C-5, and C-6. For convenience, the method steps are described with respect to component C-1; however, the steps are also performed for each of the other components. 
     At step  1730 , the actual quantity of the component in the batched mixture, XB, is determined. Thus, the actual quantity of C-1 used in the batch produced at Production Facility C ( 843 ) is determined. Production module  14  obtains this information concerning the actual quantity of the component in the batched mixture, XB, and transmits the information to master database module  11 . 
     Now a measure of a difference between the batch and the formulation is determined based on a relationship between the quantity of the component in the batched mixture, XB, and the quantity of the component as specified by the formulation, XF. 
     Specifically, at step  1740 , a difference between the quantity of the component specified in the formulation and the actual quantity of the component in the batch produced is calculated. Specifically, the difference (XB−XF) is calculated, where XB is the amount of the component actually used in the batch produced and XF is the amount of the component as specified in the formulation. A percentage value representing the difference may then be computed using the following formula:
 
Δ X =( XB−XF )/ XF.  
 
     In the illustrative embodiment, comparison module  1520  calculates the quantity ΔX, and provides the information to master database module  11 . The quantity ΔX is stored at master database module  11 . 
     At step  1750 , a difference between the cost of the component as specified in the formulation and the cost of the component in the batch produced is calculated. Thus, the difference ($XB−$XF) is calculated, where $XB is the cost of the component actually used in the batch produced and $XF is the cost of the component as specified in the formulation. A percentage value representing the difference is then calculated using the following formula:
 
Δ$ X =($ XB −$ XF )/$ XF,  
 
     In the illustrative embodiment, comparison module  1520  calculates the quantity Δ$X and provides the information to master database module  11 . The quantity Δ$X is stored at master database module  11 . 
     In accordance with an embodiment, comparison module  1520  particularly monitors the quantity of cementitious and the quantity water in each batch. Systems and methods for monitoring and analyzing quantities of cementitious and water in batches produced are described below. 
     For convenience, the terms CMF, CMB, WF, and WB are defined as follows: 
     CM F =the amount of cementitious specified in the formulation, 
     CM B =the actual amount of cementitious in a batch produced, 
     W F =the amount of water specified in the formulation, 
     W B =the actual amount of water in a batch produced. 
     Then ΔCM and ΔW are defined as follows:
 
Δ CM=CM   B   −CM   F  
 
Δ W=W   B   −W   F  
 
     Using the terms defined above, set forth below is a method of computing a standard deviation of ΔCM/CM F  (referred to as SDrCM) and a standard deviation of ΔW/W F  (referred to as SDrW, for each production facility, across all its production batches and mixes. 
     In accordance with well-known principles of concrete technology, and since strength is proportional to CM/W ratio, it can be shown that for any given mix, a variance of the strength S of a given batch of concrete has the following relationship to CM and W:
 
Δ S/S =(Δ CM/CM )−(Δ W/W )
 
     Accordingly, relative strength increases as CM specified in the formulation increases. Likewise, relative strength increases as W specified in the formulation decreases. 
     In accordance with well-known statistical principles, the variance (VAR) of the strength measure can be expressed as follows: 
     
       
         
           
             
               VAR 
               ⁡ 
               
                 ( 
                 
                   Δ 
                   ⁢ 
                   
                       
                   
                   ⁢ 
                   
                     S 
                     / 
                     S 
                   
                 
                 ) 
               
             
             = 
             
               
                 
                   VAR 
                   ( 
                   
                       
                   
                   ⁢ 
                   
                     Δ 
                     ⁢ 
                     
                         
                     
                     ⁢ 
                     
                       CM 
                       / 
                       CM 
                     
                   
                   ) 
                 
                 + 
                 
                   VAR 
                   ⁡ 
                   
                     ( 
                     
                       Δ 
                       ⁢ 
                       
                           
                       
                       ⁢ 
                       
                         W 
                         / 
                         W 
                       
                     
                     ) 
                   
                 
               
               = 
               
                 
                   
                     ( 
                     SDrCM 
                     ) 
                   
                   2 
                 
                 + 
                 
                   
                     ( 
                     SDrW 
                     ) 
                   
                   2 
                 
               
             
           
         
       
     
     Now if SDrWCM is the standard deviation of the measured ratio W/CM in a batch actually produced relative to the value of W/CM specified in the formulation, the SDrWCM can be expressed as follows:
 
( SDrWCM )=[( SDrCM ) 2 +( SDrW )] 1/2  
 
Hence:
 
 SDrS =( SDrWCM ),
 
where SDrS is the standard deviation of relative strength resulting from the variability of the batching process. The term “relative strength” as used herein means the difference in strength in all batches actually produced at a given production facility relative to the strength baseline specified in the formulation, due to the batching variabilities of CM and W, expressed as a ratio with respect to the strength baseline specified in the formulation.
 
     It follows that:
 
 SD (Δ S )= S ×( SDrWCM )
 
     In accordance with an embodiment, the closed loop production management system described herein provides, in real time, to a producer and/or a customer, the statistical values SDrCM and SDrW, and SD(ΔS). SD(ΔS) is a direct measure of concrete strength performance quality related to the quality of the production batching process, both of which are characterized by the applicable SD values. Low batching quality is reflected by a high SD value; high batching quality is reflected by a low SD. Thus as the batching quality deteriorates, the strength quality also decreases proportionally. 
     Accordingly, when the batching quality decreases, it may be necessary to adjust the applicable formulation by using an extra batching driven increment in the SDT standard deviation factor. This is done using the ACI 318 Eqs.[1]-[3] and the equation above in the following form:
 
Δ F′cr= 1.34× S ×( SDrWCM )  [1a]
 
Δ F′cr= 2.33× S ×( SDrWCM )  [2a]
 
Δ F′cr= 2.33× S ×( SDrWCM )  [3a]
 
where ΔF′cr is an added mix design strength increment resulting from the batching variability SDrWCM, for each of the three ACI equations. Since Equations [2a] and [3a] are identical, the three ACI statistical criteria are in fact reduced to two for these batching increment cases.
 
     Because F′cr is the theoretical strength associated with the specified formulation, an increase in F′cr is associated with an increase in the CM content at constant W, resulting in an increase in the cost of the CM cost in the mixture. The cost of CM in a mixture can be expressed as follows:
 
Φ= CM  efficiency factor in  PSI /( LB·CYD )
 
 K=CM  cost per  LB  
 
$ CM=CM  cost per  cyd =( K /Φ)× F′cr  
 
     It follows from the equation above and Equations [1a-1b] that:
 
Δ$ CMB =increase in  CM  cost due to batching  SD  
 
Δ$ CMB= 1.34×( K /Φ)× S×SDrWCM  
 
Δ CSTB= 2.33×( K /Φ)× S×SDrWCM  
 
     Accordingly, in accordance with an embodiment, standard deviations are determined in according with the principles described above, and are used to determine a measure of concrete strength performance quality for a plurality of batches produced at a production facility.  FIG. 18  is a flowchart of a method of determining a measure of concrete strength performance quality for concrete produced at a production facility in accordance with an embodiment. 
     At step  1810 , a first difference between a measured quantity of cementitious and a first quantity specified in a formulation is determined, for each of a plurality of batches of concrete produced at a production facility. As described above, for each batch, the batched CM is measured, and information indicating the batched CM is provided to master database module  11 . Comparison module  1520  then determines the difference ΔCM between the batched CM and the CM amount specified in the formulation. 
     At step  1820 , a first standard deviation is determined based on the first differences. In the illustrative embodiment, comparison module  1520  calculates the Standard Deviation SDrCM of the difference of batched CM versus design specification (formulation) CM over all batches produced in the production facility. 
     At step  1830 , a second difference between a measured quantity of water and a second quantity specified in the formulation is determined for each of the plurality of batches. As described above, for each batch, the batched W is measured, and information indicating the batched W is provided to master database module  11 . Comparison module  1520  determines the difference ΔW between the batched W and the W amount in the formulation. 
     At step  1840 , a second standard deviation is determined based on the second differences. Comparison module  1520  calculates the Standard Deviation SDrW of the difference of batched W versus the design specification (formulation) W over all batches produced in the production facility. 
     At step  1850 , a measure of concrete strength performance quality is determined for the production facility based on the first standard deviation and the second standard deviation. In the manner described above, comparison module  1520  determines SD(ΔS) based on SDrCM and SDrW. 
     At step  1860 , a measure of a cost of adjusting the formulation is determined based on the measure of concrete strength performance quality. Comparison module  1520  calculates the potential impact on costs of adjusting the design specification (formulation). For example, as described above, increasing F′cr may result in an increase in costs due to an increase in the cost of CM in the mixture. The increase in CM cost Δ$CMB may be calculated using equations discussed above. 
     In accordance with another embodiment, statistical data is provided to a producer and/or a customer, for example, via a web page displayed on a user device. Suppose, for example, that a producer who owns and/or manages a plurality of production facilities wishes to compare the performance of the various production facilities. Statistical performance measures of the respective performance facilities are provided. For example, in the illustrative embodiment of  FIG. 15 , the producer may employ user device  1540  to access a web page and view the statistical data. 
       FIGS. 19A-19B  comprise a flowchart of a method of providing comparative statistical information relating to a plurality of production facilities in accordance with an embodiment. Referring to block  1910 , for each of a plurality of production facilities, a series of actions is performed as described below. 
     For a selected production facility (such as Production Facility A( 841 )), the following steps are performed. At step  1920 , a first standard deviation of a first difference between a measured quantity of cementitious and a first quantity specified in a design specification is determined. Comparison module  1520  computes the first standard deviation SDrCM of the difference of batched CM versus design specification (formulation) CM over all batches produced in the production facility, as described above in steps  1810 - 1820 . 
     At step  1930 , a second standard deviation of a second difference between a measured quantity of water and a second quantity specified in the design specification is determined. Comparison module  1520  computes the second standard deviation SDrW of the difference of batched W versus the design specification (formulation) W over all batches produced in the production facility, as described above in steps  1830 - 1840 . 
     At step  1940 , a measure of concrete strength performance quality for the production facility is determined based on the first standard deviation and the second standard deviation. Comparison module  1520  computes SD(ΔS) based on SDrCM and SDrW, as described above in step  1850 . 
     Referring to block  1950 , the method may return to step  1920  and statistics for another production facility may be generated in a similar manner. Preferably, statistical information is generated for a plurality of production facilities. Otherwise, the method proceeds to step  1960  of  FIG. 19B . 
     At step  1960 , information indicating each of the plurality of production facilities and, for each respective production facility, the corresponding first standard deviation, the corresponding second standard deviation, and the corresponding measure of concrete strength performance quality, is provided in a display. In one embodiment, the statistical information computed by comparison module  1520  may be displayed on a web page such as that shown in  FIG. 20 . Web page  2001  includes a statistics table  2010  which includes six columns  2011 ,  2012 ,  2013 ,  2014 ,  2015 , and  2016 . Production facility identifier column  2011  includes identifiers for a plurality of production facilities. Columns  2012 ,  2013 ,  2014 , and  2015  store values for SDrCM, SDrW, SDrWCM, and SD(ΔS), respectively, for each respective production facility listed. For example, referring to record  2021 , the production facility identified as PF-1 has the following statistics: sdrcm-1; sdrw-1; sdrwcm-1; sd-1. Column  2016  displays a potential cost savings for each production facility listed. 
     At step  1970 , a first benchmark is selected from among a first plurality of first standard deviations. For example, in the illustrative embodiment, comparison module  1520  may determine that the standard deviation associated with the best performance among those displayed in SDrCM column  2012  is sdrcm-2 (shown in record  2022 ). 
     At step  1980 , a second benchmark is selected from among a second plurality of second standard deviations. For example, comparison module  1520  may determine that the standard deviation associated with the best performance among those displayed in SDrW column  2013  is sdrw-4 (shown in record  2024 ). 
     At step  1990 , the first benchmark and the second benchmark are indicated in the display. In the illustrative embodiment, the benchmark standard deviations are displayed, respectively, in a Benchmark (SDrCM) field  2031  and a Benchmark (SDrW) field  2032 . The two benchmark values are also highlighted in columns  2012 ,  2013 . In other embodiments, the benchmark values may be indicated in a different manner. In another embodiment, a benchmark standard deviation of strength (PSI) is determined based on the benchmark values from fields  2031 ,  2032 , and/or values in column  2014 . Benchmark consistency values may also be determined. The benchmark standard deviation of strength and the benchmark consistency values may also be displayed on page  2001 . 
     At step  1995 , a potential cost savings value representing an amount that may be saved by improving production at the production facility to the benchmark is displayed in the display. For example, comparison module  1520  determines, for each production facility listed, how much savings may be achieved by improving the production process at the facility to meet the first and second benchmarks. In the illustrative embodiment of  FIG. 20 , the cost savings information is displayed in column  2016 . 
     In another embodiment, a single generalized benchmark is determined based on the first benchmark and the second benchmark. A potential cost savings value is determined based on the generalized benchmark. 
     These and other aspects of the present Invention may be more fully understood by the following Examples. 
     Example: Illustration of the Impact of Concrete SD on its CM Cost 
     As shown in Table 1, concrete variability impacts its CM (cementitious cost) cost very significantly. The analysis is performed for a concrete of structural grade 4,000 psi, and using the referenced equations previously derived in this document. The example analysis assumes a CM efficiency factor, Φ=8 psi/(LB·cyd), and a CM cost, K=$0.045/Lb. Starting at a SD of 200 psi, the SD is increased in 100 psi increments in column 2, the mix design strength computed in columns 3 &amp; 4 per two different ACI formulae, with the higher value always governing. The mix CM cost is computed in column 5. The cost of quality variability is well illustrated in columns 6 &amp; 7; column 6 shows that per each 100 psi increase in standard deviation of strength, the CM cost will increase between $0.75 to $1.31 per cyd. Column 7 shows that the CM cost relative to very high quality concrete (represented by row 1) can increase dramatically by more than $8/cyd. Noting that the concrete industry on average generates a net profit of on the order of $0.5 to $2 per cyd, this example (using realistic numbers) illustrates the tremendous importance of maintaining low variability. 
     An important factor for maintaining low strength performance variability is the consistency of the batching process. 
     
       
         
           
               
               
             
               
                   
                 TABLE 1 
               
             
            
               
                   
                   
               
               
                   
                 Ref# 
               
            
           
           
               
               
               
               
               
               
               
               
            
               
                   
                 1 
                 2 
                 3 
                 4 
                 5 
                 6 
                 7 
               
            
           
           
               
               
               
               
               
               
               
            
               
                   
                 Eng Design 
                   
                 Mix Design 
                   
                   
                 Relative cost of 
               
               
                   
                 Strength 
                   
                 Strength: F′cr, psi 
                 $CM/CYD 
                 $CM 
                 Variance 
               
            
           
           
               
               
               
               
               
               
               
               
            
               
                 Ref# 
                 F′c, psi 
                 SD, psi 
                 Eq [1] 
                 Eq [2] 
                 Eq [9] 
                 per 100 psi SD 
                 DEL_$CM/cyd 
               
               
                   
               
            
           
           
               
               
               
               
               
               
               
               
            
               
                 1 
                 4,000 
                 200 
                 4,268 
                 3,966 
                 $24.01 
                 $0.00 
                 $0.00 
               
               
                 2 
                 4,000 
                 300 
                 4,402 
                 4,199 
                 $24.76 
                 $0.75 
                 $0.75 
               
               
                 3 
                 4,000 
                 400 
                 4,536 
                 4,432 
                 $25.52 
                 $0.75 
                 $1.51 
               
               
                 4 
                 4,000 
                 500 
                 4,670 
                 4,665 
                 $26.27 
                 $0.75 
                 $2.26 
               
               
                 5 
                 4,000 
                 600 
                 4,804 
                 4,898 
                 $27.55 
                 $1.28 
                 $3.54 
               
               
                 6 
                 4,000 
                 700 
                 4,938 
                 5,131 
                 $28.86 
                 $1.31 
                 $4.85 
               
               
                 7 
                 4,000 
                 800 
                 5,072 
                 5,364 
                 $30.17 
                 $1.31 
                 $6.17 
               
               
                 8 
                 4,000 
                 900 
                 5,206 
                 5,597 
                 $31.48 
                 $1.31 
                 $7.48 
               
               
                 9 
                 4,000 
                 1,000 
                 5,340 
                 5,830 
                 $32.79 
                 $1.31 
                 $8.79 
               
               
                   
               
            
           
         
       
     
     Set forth below is a discussion of real-time batch data variability with respect to mixture design factors (as specified in a formulation, for example). Hypothetical data are used to illustrate a quantification of the cost of strength performance variably as driven by batching variability. 
     Example: Quantification of Batching Data Variability 
     Table 2 sets forth a set of real time data in columns 1-5. Column 6 shows the computed standard deviation W/CM using the raw data from columns 3 and 5. 
     In the example of Table 2, production facility (plant) #141, represented by row 9, is designated as the benchmark production facility (plant) because it shows the least variability. 
     
       
         
           
               
             
               
                 TABLE 2 
               
             
            
               
                   
               
               
                 Example Quantification of Strength Standard Deviation due to Batching 
               
               
                 Variability, and the Resulting Cost 
               
            
           
           
               
               
            
               
                   
                 Ref# 
               
            
           
           
               
               
               
               
               
               
               
            
               
                   
                 1 
                 2 
                 3 
                 4 
                 5 
                 6 
               
            
           
           
               
               
               
            
               
                   
                 Measured from CLI batch analysis 
                 Eq [6] - 
               
            
           
           
               
               
               
               
               
            
               
                   
                   
                 Del_CM % 
                 Del_WATER % 
                 data [A] &amp; [B] 
               
               
                   
                 Period 
                 FROM MIX 
                 FROM MIX 
                 STDEV W/CM 
               
            
           
           
               
               
               
               
               
               
               
            
               
                 Table [1] 
                 Volume, 
                   
                 [A] 
                   
                 [B] 
                 [C] 
               
            
           
           
               
               
               
               
               
               
               
               
            
               
                 Ref # 
                 PLANT 
                 cyds 
                 AVG DELTA 
                 SDrCM 
                 AVG DELTA 
                 SDrW 
                 SDrWCM 
               
               
                   
               
            
           
           
               
               
               
               
               
               
               
               
            
               
                 1 
                 121 
                 5,500 
                 0.10% 
                 0.50% 
                 −22.00% 
                 3.60% 
                 3.6% 
               
               
                 2 
                 122 
                 3,000 
                 0.11% 
                 0.68% 
                 −3.60% 
                 5.40% 
                 5.4% 
               
               
                 3 
                 124 
                 6,800 
                 −22.30% 
                 8.20% 
                 −14.00% 
                 8.00% 
                 11.5% 
               
               
                 4 
                 128 
                 2,000 
                 0.85% 
                 1.58% 
                 −10.00% 
                 4.50% 
                 4.8% 
               
               
                 5 
                 131 
                 8,990 
                 −0.49% 
                 0.33% 
                 −13.70% 
                 6.00% 
                 6.0% 
               
               
                 6 
                 135 
                 6,000 
                 −0.33% 
                 0.59% 
                 −7.40% 
                 2.10% 
                 2.2% 
               
               
                 7 
                 138 
                 2,500 
                 −0.08% 
                 0.56% 
                 −11.00% 
                 5.30% 
                 5.3% 
               
               
                 8 
                 140 
                 9,850 
                 −0.33% 
                 0.40% 
                 −8.70% 
                 11.60% 
                 11.6% 
               
               
                 9 
                 141 
                 6,780 
                 −0.16% 
                 0.70% 
                 −12.40% 
                 2.00% 
                 2.1% 
               
               
                 10 
                 142 
                 4,560 
                 −0.09% 
                 0.23% 
                 −9.60% 
                 3.60% 
                 3.6% 
               
               
                 11 
                 143 
                 7,860 
                 0.34% 
                 0.71% 
                 −20.20% 
                 6.00% 
                 6.0% 
               
               
                 12 
                 146 
                 3,450 
                 1.26% 
                 4.08% 
                 −13.80% 
                 6.60% 
                 7.8% 
               
               
                 13 
                 147 
                 5,450 
                 2.20% 
                 1.82% 
                 −14.60% 
                 2.10% 
                 2.8% 
               
               
                 14 
                 150 
                 9,540 
                 0.41% 
                 1.71% 
                 −11.00% 
                 9.20% 
                 9.4% 
               
               
                   
               
            
           
         
       
     
     Assuming an average concrete mix design strength of 4,000 psi, Table 3 shows the strength SD (Column 3) computed from the SD of W/Cm; the strength SD varies by more than a factor of 5 from 85 psi for the benchmark plant to 458 psi in plant #124 (row 3). If this batching strength SD were reduced to the benchmark value, then significant CM costs would be saved as shown in column 4; this cost factor varies from $0.02 per cyd to $2.85 due to the varying batching qualities of the production facilities. 
     Supposing that the mix designs (formulations) developed for the benchmark plant (production facility) are used across all the production facilities, this could lead to a very costly situation, since probability analysis shows that for each 100 psi increase in strength SD from its assumed mix design value, the failure rate will increase by more than 4%, which translates to a potential remedial cost of around $2/cyd per 100 psi of SD increase. 
     
       
         
           
               
             
               
                 TABLE 3 
               
             
            
               
                   
               
               
                 Closed Loop W/CM Ratio &amp; Batching Strength Standard 
               
               
                 Deviations From Real Time Data 
               
            
           
           
               
               
            
               
                   
                 Ref# 
               
            
           
           
               
               
               
               
               
            
               
                   
                 1 
                 2 
                 3 
                 4 
               
            
           
           
               
               
               
            
               
                   
                   
                 Computed from 
               
               
                   
                   
                 batch data for 
               
               
                   
                   
                 avg strength 
               
               
                   
                 Computed per 
                 of 4,000 psi 
               
            
           
           
               
               
               
               
               
            
               
                   
                   
                 Table [1] 
                 Batching 
                   
               
               
                   
                 Period 
                 STDEV W/CM 
                 Strength SD 
                 Bench Mark 
               
               
                 Table [2] 
                 Volume, 
                 [C] 
                 [D] 
                 Savings 
               
            
           
           
               
               
               
               
               
               
            
               
                 Ref # 
                 PLANT 
                 cyds 
                 SDrWCM 
                 SD(Del_S) 
                 [E] 
               
               
                   
               
            
           
           
               
               
               
               
               
               
            
               
                 1 
                 121 
                 5,500 
                 3.6% 
                 145 
                 $0.45 
               
               
                 2 
                 122 
                 3,000 
                 5.4% 
                 218 
                 $1.00 
               
               
                 3 
                 124 
                 6,800 
                 11.5% 
                 458 
                 $2.80 
               
               
                 4 
                 128 
                 2,000 
                 4.8% 
                 191 
                 $0.80 
               
               
                 5 
                 131 
                 8,990 
                 6.0% 
                 240 
                 $1.17 
               
               
                 6 
                 135 
                 6,000 
                 2.2% 
                 87 
                 $0.02 
               
               
                 7 
                 138 
                 2,500 
                 5.3% 
                 213 
                 $0.96 
               
               
                 8 
                 140 
                 9,850 
                 11.6% 
                 464 
                 $2.85 
               
               
                 9 
                 141 
                 6,780 
                 2.1% 
                 85 
                 $0.00 
               
               
                 10 
                 142 
                 4,560 
                 3.6% 
                 144 
                 $0.45 
               
               
                 11 
                 143 
                 7,860 
                 6.0% 
                 242 
                 $1.18 
               
               
                 12 
                 146 
                 3,450 
                 7.8% 
                 310 
                 $1.69 
               
               
                 13 
                 147 
                 5,450 
                 2.8% 
                 111 
                 $0.20 
               
               
                 14 
                 150 
                 9,540 
                 9.4% 
                 374 
                 $2.17 
               
               
                   
                   
                   
                   
                 AVG/YCD 
                 $1.21 
               
               
                   
               
            
           
         
       
     
     In various embodiments, the method steps described herein, including the method steps described in  FIGS. 2, 3, 4, 5, 6, 9, 12, 13A-13B, 16A-16B, 17, 18 , and/or  19 A- 19 B, may be performed in an order different from the particular order described or shown. In other embodiments, other steps may be provided, or steps may be eliminated, from the described methods. 
     Systems, apparatus, and methods described herein may be implemented using digital circuitry, or using one or more computers using well-known computer processors, memory units, storage devices, computer software, and other components. Typically, a computer includes a processor for executing instructions and one or more memories for storing instructions and data. A computer may also include, or be coupled to, one or more mass storage devices, such as one or more magnetic disks, internal hard disks and removable disks, magneto-optical disks, optical disks, etc. 
     Systems, apparatus, and methods described herein may be implemented using computers operating in a client-server relationship. Typically, in such a system, the client computers are located remotely from the server computer and interact via a network. The client-server relationship may be defined and controlled by computer programs running on the respective client and server computers. 
     Systems, apparatus, and methods described herein may be used within a network-based cloud computing system. In such a network-based cloud computing system, a server or another processor that is connected to a network communicates with one or more client computers via a network. A client computer may communicate with the server via a network browser application residing and operating on the client computer, for example. A client computer may store data on the server and access the data via the network. A client computer may transmit requests for data, or requests for online services, to the server via the network. The server may perform requested services and provide data to the client computer(s). The server may also transmit data adapted to cause a client computer to perform a specified function, e.g., to perform a calculation, to display specified data on a screen, etc. 
     Systems, apparatus, and methods described herein may be implemented using a computer program product tangibly embodied in an information carrier, e.g., in a non-transitory machine-readable storage device, for execution by a programmable processor; and the method steps described herein, including one or more of the steps of  FIGS. 2, 3, 4, 5, 6, 9, 12, 13A-13B, 16A-16B, 17, 18 , and/or  19 A- 19 B, may be implemented using one or more computer programs that are executable by such a processor. A computer program is a set of computer program instructions that can be used, directly or indirectly, in a computer to perform a certain activity or bring about a certain result. A computer program can be written in any form of programming language, including compiled or interpreted languages, and it can be deployed in any form, including as a stand-alone program or as a module, component, subroutine, or other unit suitable for use in a computing environment. 
     A high-level block diagram of an exemplary computer that may be used to implement systems, apparatus and methods described herein is illustrated in  FIG. 21 . Computer  2100  includes a processor  2101  operatively coupled to a data storage device  2102  and a memory  2103 . Processor  2101  controls the overall operation of computer  2100  by executing computer program instructions that define such operations. The computer program instructions may be stored in data storage device  2102 , or other computer readable medium, and loaded into memory  2103  when execution of the computer program instructions is desired. Thus, the method steps of  FIGS. 2, 3, 4, 5, 6, 9, 12, 13A-13B, 16A-16B, 17, 18 , and/or  19 A- 19 B can be defined by the computer program instructions stored in memory  2103  and/or data storage device  2102  and controlled by the processor  2101  executing the computer program instructions. For example, the computer program instructions can be implemented as computer executable code programmed by one skilled in the art to perform an algorithm defined by the method steps of  FIGS. 2, 3, 4, 5, 6, 9, 12, 13A-13B, 16A-16B, 17, 18 , and/or  19 A- 19 B. Accordingly, by executing the computer program instructions, the processor  2101  executes an algorithm defined by the method steps of  FIGS. 2, 3, 4, 5, 6, 9, 12, 13A-13B, 16A-16B, 17, 18 , and/or  19 A- 19 B. Computer  2100  also includes one or more network interfaces  2104  for communicating with other devices via a network. Computer  2100  also includes one or more input/output devices  2105  that enable user interaction with computer  2100  (e.g., display, keyboard, mouse, speakers, buttons, etc.). 
     Processor  2101  may include both general and special purpose microprocessors, and may be the sole processor or one of multiple processors of computer  2100 . Processor  2101  may include one or more central processing units (CPUs), for example. Processor  2101 , data storage device  2102 , and/or memory  2103  may include, be supplemented by, or incorporated in, one or more application-specific integrated circuits (ASICs) and/or one or more field programmable gate arrays (FPGAs). 
     Data storage device  2102  and memory  2103  each include a tangible non-transitory computer readable storage medium. Data storage device  2102 , and memory  2103 , may each include high-speed random access memory, such as dynamic random access memory (DRAM), static random access memory (SRAM), double data rate synchronous dynamic random access memory (DDR RAM), or other random access solid state memory devices, and may include non-volatile memory, such as one or more magnetic disk storage devices such as internal hard disks and removable disks, magneto-optical disk storage devices, optical disk storage devices, flash memory devices, semiconductor memory devices, such as erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM), digital versatile disc read-only memory (DVD-ROM) disks, or other non-volatile solid state storage devices. 
     Input/output devices  2105  may include peripherals, such as a printer, scanner, display screen, etc. For example, input/output devices  2105  may include a display device such as a cathode ray tube (CRT) or liquid crystal display (LCD) monitor for displaying information to the user, a keyboard, and a pointing device such as a mouse or a trackball by which the user can provide input to computer  2100 . 
     Any or all of the systems and apparatus discussed herein, including master database module  11 , input module  12 , sales module  13 , production module  14 , transport module  15 , site module  16 , alert module  17 , purchase module  18 , and localization module  19 , and components thereof, including mixture database  801  and local factors database  802 , may be implemented using a computer such as computer  2100 . 
     One skilled in the art will recognize that an implementation of an actual computer or computer system may have other structures and may contain other components as well, and that  FIG. 21  is a high level representation of some of the components of such a computer for illustrative purposes. 
     The foregoing Detailed Description is to be understood as being in every respect illustrative and exemplary, but not restrictive, and the scope of the invention disclosed herein is not to be determined from the Detailed Description, but rather from the claims as interpreted according to the full breadth permitted by the patent laws. It is to be understood that the embodiments shown and described herein are only illustrative of the principles of the present invention and that various modifications may be implemented by those skilled in the art without departing from the scope and spirit of the invention. Those skilled in the art could implement various other feature combinations without departing from the scope and spirit of the invention.