Patent Publication Number: US-2004049369-A1

Title: System and method for facilities management

Description:
BACKGROUND OF THE INVENTION  
       [0001] The present invention relates generally to systems and methods for facilities management. More specifically, the present invention relates to systems and methods for managing and analyzing production and operations data for facilities such as mills, plants, production facilities, factories, manufacturing facilities, production plants, etc.  
       [0002] The production and management of facilities, such as mills, is becoming increasingly more complicated. The number of systems and processes involved with producing product (such as a feed product) can pose challenges for management including optimizing operational efficiency, production efficiency, costs, budgeting, etc.  
       [0003] Accordingly, it would be advantageous to provide a system and method that may be used to determine a number of personnel at a plant to meet a sales or production level. It would also be advantageous to provide a system and method that may be used to manage production costs of product (such as animal feed, etc.). It would further be advantageous to provide a system and method that may be used to identify inefficiencies and “bottlenecks” in a production process. It would further be advantageous to provide a system and method that may be used to provide modeling of process changes (such as “what-if-modeling”) and to determine the cost effect of any changes. It would further be advantageous to provide a system and method that may be used to assist in the preparation of a budget for a mill. It would further be advantageous to provide a system and method that may be used to allocate costs by process, variable costs, and fixed costs, and to determine incremental costs of production (such as marginal costs).  
       [0004] It would be advantageous to provide a system and method for facilities management of a type disclosed in the present application that includes any one or more of these or other advantageous features.  
       SUMMARY OF THE INVENTION  
       [0005] One embodiment of the invention relates to a system for modeling a production plant. The system includes a processing unit and a memory portion in communication with the processing unit having information stored to configure the processing unit to receive model data for the production plant, receive operational data for the production plant, compare the operational plant data to the model plant data, and generate a report at least daily containing the comparison between the operational plant data and the model plant data.  
       [0006] Another embodiment of the invention relates to a method of managing a transfer of material within a plant. The method includes receiving model bin storage data, receiving model flat storage data, generating model data from the model bin storage data and the model flat storage data, receiving actual transfer data, and comparing the model data with the actual transfer data.  
       [0007] Another embodiment of the invention relates to a method of managing physical maintenance of a plant. The method includes receiving model maintenance data, generating model data from the model maintenance data, receiving actual maintenance data, and comparing the model data with the actual maintenance data. The model maintenance data includes data relating to at least one of a Mezzannine area, and a sweeping time based on empirical data.  
       [0008] Another embodiment of the invention relates to a method of managing personnel time for a recurring meeting in a plant. The method includes receiving model data relating to a number of employees for the recurring meeting, receiving model data relating to a time per employee for the recurring meeting, generating model data relating to a total number of hours required for the recurring meeting, receiving actual data relating to a total number of hours for the recurring meeting, and comparing the model data relating to the total number of hours required for the recurring meeting with the actual data relating to the total number of hours for the recurring meeting.  
       [0009] Another embodiment of the invention relates to a method of managing a bag material receiving process in a plant. The method includes receiving model bag receiving data, generating model data from the model bag receiving data, receiving actual bag receiving data, and comparing the model data with the actual bag receiving data. The model bag receiving data further includes data relating to at least one of amount of bag material received with a forklift, and a capacity of the forklift.  
       [0010] Another embodiment of the invention relates to a method of managing a bulk material receiving process in a plant. The method includes receiving model dumping data, generating model data from the model dumping data, receiving actual dumping data, and comparing the model data with the actual dumping data.  
       [0011] Another embodiment of the invention relates to a method of managing a mixing process in a plant. The method includes receiving model mixing data, generating model data from the model mixing data, receiving actual mixing data, and comparing the model data with the actual mixing data. The model mixing data further comprises data relating to at least one of a best practice time for mixing, and a batches per hour.  
       [0012] Another embodiment of the invention relates to a method of managing a packing process in a plant. The method includes receiving model dry packing data, receiving actual dry packing data, and comparing the model dry packing data with the actual dry packing data. The method further includes receiving model wet packing data, receiving actual wet packing data, and comparing the model wet packing data with the actual wet packing data.  
       [0013] Another embodiment of the invention relates to a method of managing a shipping process in a plant. The method includes receiving model shipping data, generating model data from the model shipping data, receiving actual shipping data, and comparing the model data with the actual shipping data. The model shipping data includes data relating to one of a set time for a rail car, a clean time for a rail car, a sample time for a rail car, a weigh time for a rail car, an operator rate for a rail car, a load rate for a rail car, a wet clean rate, a wet load rate, a wet average tons per item, and a resacking rate.  
       [0014] Another embodiment of the invention relates to a method of managing a pelleting process in a plant. The method includes receiving model pelleting data, generating model data from the model pelleting data, receiving actual pelleting data, and comparing the model data with the actual pelleting data. The model pelleting data includes data relating to one of die friction, throughput of a pelleting machine, energy cost of the pelleting machine, and a time required to change a die of a pelleting machine.  
       [0015] Another embodiment of the invention relates to a method of managing a maintenance process in a plant. The method includes receiving model maintenance data, generating model data from the model maintenance data, receiving actual maintenance data, and comparing the model data with the actual maintenance data. The model maintenance data further comprises data relating to one of a number of extruders, and a number of dryers.  
       [0016] Another embodiment of the invention relates to a method of managing an energy consumption process in a plant. The method includes receiving model energy consumption data, generating model data from the model energy consumption data, receiving actual energy consumption data, and comparing the model data with the actual energy consumption data. The model energy consumption data include data relating to one of an energy amount associated with an extruding process, an energy amount associated with an extrusion screen, an additional amount of steam, an additional BTU usage, and wet packing amps.  
       [0017] Another embodiment of the invention relates to method of managing operations processes in a plant. The method includes receiving model operations processes data, generating model data from the model operations processes data, receiving actual operations processes data, and comparing the model data with the actual operations processes data. The model operations processes data further comprises data relating to one of a cost associated with a security guard and a currency conversion.  
       [0018] Another embodiment of the invention relates to a method of managing contract labor in a plant. The method includes receiving model contract labor data, receiving actual contract labor data, and comparing the model contract labor data with the actual contract labor data. The model contract labor data and the actual contract labor data include data relating to a cost associated with contracting one of interplant transfer, bag receiving, bulk receiving, mixing, packing, wet packing, bulk warehouse, bag warehouse, pelleting, grinding, second mixing, rolling, flaking, grain processing, block pressing, and extruding.  
       [0019] Another embodiment of the invention relates to a method of managing an extruding process in a plant. The method includes receiving model extruding data, generating model data from the model extruding data, receiving actual extruding data, and comparing the model data with the actual extruding data. The model extruding data includes data relating to a cost associated with one of an energy cost associated with the extruding process and a labor cost associated with the extruding process.  
       [0020] Another embodiment of the invention relates to a method of managing a facility having at least one process, the at least one process having a plurality of steps. The method includes receiving model data relating to the plurality of steps of the at least one process, receiving actual data relating to the plurality of steps of the at least one process, and comparing the model data to the actual data.  
       [0021] Another embodiment of the invention relates to a method of providing consulting services. The method includes receiving, by a consulting servicer, operational data from a production plant, generating model data for the production plant, generating comparison data from the operational data and the model data, by the consulting servicer. The method further includes generating, by the consulting servicer, a report analyzing the operational data, the model data and the comparison data.  
       [0022] Another embodiment of the invention relates to a method of providing management reports for a production plant. The method includes receiving operational data at least partially automatically from machines in the production plant, by a data processing device, generating model data for the production plant using a production plant modeling program running on the data processing device, and generating a report based on the operational data and the model data. 
     
    
    
     BRIEF DESCRIPTION OF THE DRAWINGS  
     [0023]FIG. 1 is a schematic view of a facilities management system according to an exemplary embodiment.  
     [0024]FIG. 2 is a schematic view of a facilities management system according to an exemplary embodiment.  
     [0025]FIG. 3 is a schematic view of a process for managing a facility according to an exemplary embodiment.  
     [0026]FIG. 4 is a schematic view of a facilities management system according to an exemplary embodiment applied to various process.  
     [0027]FIG. 5 is a portion of a user interface for a facilities management system according to an exemplary embodiment.  
     [0028]FIG. 6 is a portion of a user interface for a model process according to an exemplary embodiment.  
     [0029]FIG. 7 is a portion of a user interface for a model process according to an exemplary embodiment.  
     [0030]FIG. 8 is a portion of a user interface for a model process according to an exemplary embodiment.  
     [0031]FIG. 9 is a portion of a user interface for a model process according to an exemplary embodiment.  
     [0032]FIG. 10 is a portion of a user interface for a model process according to an exemplary embodiment.  
     [0033]FIG. 11 is a portion of a user interface for a model process according to an exemplary embodiment.  
     [0034]FIG. 12 is a portion of a user interface for a model process according to an exemplary embodiment.  
     [0035]FIG. 13 is a portion of a user interface for a model process according to an exemplary embodiment.  
     [0036]FIG. 14 is a portion of a user interface for a model process according to an exemplary embodiment.  
     [0037]FIG. 15 is a portion of a user interface for a model process according to an exemplary embodiment.  
     [0038]FIG. 16 is a portion of a user interface for a model process according to an exemplary embodiment.  
     [0039]FIG. 17 is a portion of a user interface for a model process according to an exemplary embodiment.  
     [0040]FIG. 18 is a portion of a user interface for a model process according to an exemplary embodiment.  
     [0041]FIG. 19 is a portion of a user interface for a model process according to an exemplary embodiment.  
     [0042]FIG. 20 is a portion of a user interface for a model process according to an exemplary embodiment.  
     [0043]FIG. 21 is a portion of a user interface for a model process according to an exemplary embodiment.  
     [0044]FIG. 22 is a portion of a user interface for a model process according to an exemplary embodiment.  
     [0045]FIG. 23 is a portion of a user interface for entry of actual data according to an exemplary embodiment.  
     [0046]FIG. 24 is a portion of a user interface for entry of actual data according to an exemplary embodiment.  
     [0047]FIG. 25 is a portion of a user interface for entry of actual data according to an exemplary embodiment.  
     [0048]FIG. 26 is a portion of a user interface for generating of summary data according to an exemplary embodiment.  
     [0049]FIG. 27 is a schematic view of a facilities management system according to an alternative embodiment.  
     [0050]FIG. 28 is a portion of a user interface for a model process according to an alternative embodiment.  
     [0051]FIG. 29 is a portion of a user interface for a model process according to an alternative embodiment.  
     [0052]FIG. 30 is a portion of a user interface for a model process according to an alternative embodiment.  
     [0053]FIG. 31 is a portion of a user interface for a model process according to an alternative embodiment.  
     [0054]FIG. 32 is a portion of a user interface for a model process according to an alternative sembodiment. 
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS  
     [0055] Systems and methods for facilities management are disclosed. The systems and methods disclosed assist management of one or more mills (e.g. facilities, plants, production facilities, factories, production plants, manufacturing facilities, etc.). The systems and methods disclosed provide and allow comparison of criteria by which one or more mills may be managed, modeled, budgeted, compared and/or otherwise analyzed. The systems and methods disclosed provide comparison of production data of an actual facility with a “model” facility (e.g., data representative of a facility, similar to the actual facility, operating according to predetermined, idealized, optimized, or preset production/operation data).  
     [0056] 1. Facilities Management System  
     [0057] In one embodiment, a computer system is used which has a central processing unit (CPU) that executes sequences of instructions contained in a memory. More specifically, execution of the sequences of instructions causes the CPU to perform steps, which are described below. The instructions may be loaded into a random access memory (RAM) for execution by the CPU from a read-only memory (ROM), a mass storage device, or some other persistent storage. In other embodiments, hardwired circuitry may be used in place of, or in combination with, software instructions to implement the functions described. Thus, the embodiments described herein are not limited to any specific combination of hardware circuitry and software, nor to any particular source for the instructions executed by the computer system.  
     [0058]FIG. 1 shows a facilities management system  10 . Facilities management system  10  may, in an exemplary embodiment, comprise a server  12 , a network  20  and one or more remote computer systems  30 . Network  20  connects server  12  and one or more computer systems  30 . In an exemplary embodiment, network  20  is the Internet, a worldwide network of computer networks that use various protocols to facilitate data transmission and exchange. Network  20  can use a protocol, such as, but not limited to, the TCP/IP network protocol or the DECnet, X.25, and UDP protocols. In alternative embodiments, network  20  is any type of network, such as, but not limited to, a virtual private network (VPN), an Ethernet, or a Netware network. Further, network  20  may comprise a configuration, such as but not limited to, a wide area network (WAN) or a local area network (LAN). Network  20  preferably provides communication via a CITRIX server or other server platform. Alternatively, Hypertext Markup Language (HTML), extensible markup language (XML) web pages, or other communications protocols and communications interfaces may be used.  
     [0059] Generally, system  10  can be implemented using computer server  12  configured by software  14  running on server  12 . According to various alternative embodiments, software may be run on a number of different locations, including on the remote computer system, one or more servers in communication with each other, etc.  
     [0060] Server  12  may have a central processing unit (CPU  16 ) that executes sequences of instructions (e.g., software) contained in a memory to perform steps which are described below. Preferably, server  12  includes read/write memory, such as, disc drives and other storage.  
     [0061] A user (e.g., manager, system administrator, personnel, etc.) may access system  10  via a CITRIX platform, web pages having secure, time restricted access, etc.  
     [0062] As shown in FIG. 1, a database  15  may be provided on server  12 . Database  15  may be used to store data relating to one or more models, actual data, reports, etc. According to one exemplary embodiment, two separate databases may be provided on server  12 . One data base (i.e., database  15 ) may serve internal plants or facilities, the other data base (i.e., database  25 ) may serve outside customers for consulting purposes, etc.  
     [0063] Computer system  30  may be any type of computing device, including work stations, laptop computers, notebooks, computers, handheld computers, personal digital assistants (PDAs), mobile phones, beepers, or other equipment capable of communication with network  20 . In another embodiment, system  10  can be accessed via telephones, such as, a mobile phone or a standard telephone. Other user interface platforms may also be provided for accessing system  10 . Such user interface platforms include, but are not limited to, for example, WAP (wireless application protocol) and web browser interfaces.  
     [0064] According to an alternative embodiment, software and databases may be provided on remote computer systems at the facility. The remote computer systems may be configured to autonomously run the software, store inputted data, generate reports and/or analysis, and store generated data. The remote computer systems may be configured to be in selective communication with a central server (i.e., data may be selectively uploaded to the server).  
     [0065] 2. Facilities  
     [0066] As shown in FIG. 2, system  10  may be used by a user  17  (e.g., a plant manager, process engineer, supervisor, employee, contractor, consultant, etc.) to provide analysis (e.g., management, modeling, budgeting, comparison, etc.) of a facility  18  (shown as a mill).  
     [0067] System  10  may be configured to analyze one or more facilities. According to a particularly preferred embodiment shown in FIG. 1, system  10  may be used on any number of facilities. The facilities may be organized or grouped for analysis according to various criteria such as geographic location, facility type, capacity, size, division, individually, etc.  
     [0068] 3. Models and Model Data  
     [0069] According to an exemplary embodiment, user  17  may include a plant manager and a production manager in charge of a region, district, selected plants, etc. who may be jointly responsible for analysis of the facility.  
     [0070] As shown in FIG. 3, model(s)  40  of facility  18  will typically include model data relating to processes (e.g. work-flows, production steps, management steps, work processes) occurring in or associated with the facility. Model(s)  40  may be based on theoretical data, production capacities, time studies, operational capacities, estimates, ideal costs, etc.  
     [0071] As shown in FIG. 3, one or more models for a facility may be created. Models  40  may be created to allow analysis of the facility, to compare a variety of different models having different data, etc. Multiple models also allows a user to review a number of scenarios for changing the operation of the facility (e.g., to see effects from changing one or more operational parameters).  
     [0072] 4. Facilites and Actual Data  
     [0073] As the facility operates, actual data  50  (e.g., operational data, production data, actual costs, actual labor times, etc.) is entered or received into system  10  (see FIG. 3). According to a particularly preferred embodiment, actual data may be obtained from employee time sheets, timing the processes, actual costs, completing forms, data entry, data entry terminals provided at or near the processes, etc. According to alternative embodiments, data may be received from a direct link to the process (e.g., time to pack product received from automated packing equipment, monitoring systems to track employee locations, etc.).  
     [0074] 5. Example Analysis  
     [0075] System  10  may make comparisons between the model data and the actual data, project costs, identify discrepancies, bottlenecks, etc. (see operation  52  in FIG. 3). Analysis of a facility may include analysis and/or comparison of model data with actual data. Analysis of a facility may include analysis and/or comparison of one or more model data sets.  
     [0076] By way of a simplified example shown in FIG. 4, facility  18  may be a feed mill. Facility  18  may produce products  60  (such as animal feed). In order to produce products  60 , facility  18  may utilize various processes. For example, a receiving process  62 , a mixing process  64 , and a shipping process  66  may be used. Receiving process  62  may be a process in which materials for production of products  60  are received within facility  18 . Mixing process  64  may be a process in which materials are mixed together to form products  60 . Shipping process  66  may be a process in which products  60  are shipped or sent to customers, distributors, etc.  
     [0077] In this simplified example, model data may be generated and/or used for the three processes. The model data may be derived from time studies, theoretical operational capacities, estimates, ideal costs, etc.  
     [0078] For example, model data for the receiving process (e.g., model receiving data  70 ) may include a model time needed to weigh materials, a model time to sample materials, a model time to unload the materials from the transport, and a model time to place the materials into storage. Model data may be calculated from one or more of these processes or steps.  
     [0079] Model data for the mixing process (e.g., model mixing data  72 ) may include a model capacity of a mixing machine (e.g., tons/hour, line speed), a model time to mix the materials and a model time to empty the mixing machine. Model data may be calculated from one or more of these processes or steps.  
     [0080] Model data for the shipping process (e.g., model shipping data  74 ) may include a model time to fill a bag of product, a model distance from a bagging area to a shipment area, a model cost of running loading equipment, and a model rate of shipment capacity (e.g., tons per hour, etc.). Model data may be calculated from one or more of these processes or steps.  
     [0081] In this simplified example, actual data may also be generated for all three processes (e.g., actual receiving data  82 , actual mixing data  84 , and actual shipping data  86 ). The actual data will reflect actual operating values for the various processes. The actual data may be obtained from employee time sheets, timing the processes, actual costs, etc.  
     [0082] In this simplified example, model data may then be compared to actual (collected, sensed, and/or recorded) data for analysis. Analysis may be done on factors or data which may have an effect on the operation of the facility (e.g., cost, production, efficiency, volume, etc.).  
     [0083] According to various exemplary embodiments, a wide variety or types of analysis may be done on the model data and/or actual data. For example, model receiving data  70  may be compared to actual receiving data  82 . If actual receiving data  82  is greater than model receiving data  70  (e.g., actual time for the receiving process is longer than the model time for receiving), a manager may further review the process in order to find out the cause of the delay.  
     [0084] The receiving data (both model and actual) may include a break-down of all steps or sub-processes that comprise receiving process  62 . This information may provide a manager with a way to localize a problem point in the process by comparing a model step (or process) with an actual step (or process). Alternatively, if actual receiving data  82  is less than model receiving data  70 , a manager may use this information to award employees for productivity, etc.  
     [0085] Model data, actual data, comparative information, calculated efficiencies, etc. may be provided using system  10 . Data may be provided at a number of levels, including at a process level (e.g., time for receiving process), at a step level (e.g., time for unloading a truck) at a facility level (e.g., time from receiving to shipment) or analysis of a group or all facilities (e.g., average time for receiving process). Any and all data may be provided in a variety of formats, including reports, charts, graphs, tables, etc.  
     [0086] 6. Facility Processes—Model Data  
     [0087] The analysis of a facility largely depends on the various processes being used or employed in the facility. System  10  may model or receive model data relating to one or more processes  90  occurring in the facility (see FIG. 5). The one or more processes  90  may comprise one or more steps (e.g., sub-processes, components, etc.).  
     [0088] According to a particularly preferred embodiment shown in FIG. 5, processes  90  include processes relating to interplant transfer, housekeeping, general plant processes, bag receiving, bulk receiving, mixing, dry packing, wet packing, bulk loadout, bag loadout, pelleting, maintenance, grinding, second mixing, rolling/flaking, user defined processes (shown as Proc  16  and Proc  17 ), gas/oil, electrical energy, supplies, miscellaneous, contract labor, and extruding. According to an alternative embodiment, the processes used for analysis may include processes used in food business, milling, grain mills, food production, etc., including processing, screening, sifting, sorting, etc.  
     [0089] According to one exemplary embodiment shown in FIGS.  6  to  22 , model data (for use with a process) may be inputted into fields having a “window” or field allowing changes. Other non-windowed fields may be calculated model values. According to a particularly preferred embodiment, calculated model values are comparable data types to actual data. Calculated model values may be based on one or more inputted data fields in the one or more processes.  
     [0090] a. Interplant Transfer Process  
     [0091] As shown in FIG. 6, interplant transfer process data  100  may include steps and model data associated with transferring or moving product within a facility, such as model data relating to bin and flat storage processes (e.g., time for bin cleaning, rate for bin cleaning, leg capacity, ingredient density, operator time for equipment, set time, clean time, average run length, tons per month, other user defined parameters, etc.). Data  100  may include bin cleaning, ingredient transfer from temporary storage (i.e. totes to bulk or outside bulk storage to mill), and set/clean time. Set/clean time will include any set up time involved in transfers and cleaning areas that are directly effected by the transfer.  
                                   Data   Description                  Bin Cleaning (Hrs/Mo)   Time for cleaning various bins.       Bin Leg Capacity   The leg capacity for bin transfer system.       Bin Ingred Dens   The average density of the material being           transferred in the units indicated by the field           label.       Bin Set/Clean Time (Min)   May includes time to:           1) Set distribution           2) Start equipment           3) Check flow           4) Travel time           5) Shutdown equipment           6) Clean up       Bin Oper Time (Min/Hr)   May be based on a time study. May include           time to:           1) Monitor equipment           2) Check heights of material in bin being           filled           3) Travel time           4) Operator equipment       Bin Avg Run Leng (Ton)   The average run length for bin transfer           system.       Bin Tons/Month (Ton)   The amount of bulk ingredients that are           transferred during an average month.       Other(Hrs/Mo)   May include the hours per month used to           transfer other products, i.e: ingredients           stored at another warehouse/facility and           moved to facility.       Flat Leg Capacity   The leg capacity for flat transfer system.       Flat Practical Leg Capacity   The value may be a predetermined operating           factor multiplied by the flat leg capacity.       Flat Ingred Dens   The average density of the material being           transferred.       Flat Set/Clean Time (Min)   May be based on a time study. May           includes time to:           1) Set distribution           2) Start equipment           3) Check flow           4) Travel time           5) Shutdown equipment           6) Clean up       Flat Oper Time (Min/Hr)   May be based on a time study. May include           time to:           1) Monitor equipment           2) Check heights of material in bin being           filled           3) Travel time           4) Operator equipment       Flat Avg Run Leng (Ton)   The average run length for flat transfer           system.       Flat Tons/Month (Ton)   The amount of bulk ingredients that are           transferred during an average month.       Bin Clean (Hrs/Day)   This field is computed from user inputs.           (Bins required cleaning or the average bins           cleaned × hours per bin × number of times           cleaned per year)/12 = hours per month.       Ingred Trans (Hrs/Day)   This field is computed from user inputs           including leg capacity, ingredient density and           tons/month.       Other (Hrs/Day)   This field is computed from user inputs           including hours per day to transfer other           products.       InterPlant (Hrs/Day)   This field is computed from user inputs           including bin clean, ingredient transfer and           other.       Wages/Hr $   Wages per hour of employees involved with           the process.       Cost/Day $   Cost per ton that the process adds to the           product.       Tot MIg Cost $   Overall cost of milling                  
 
     [0092] Bin storage data and flat storage data are preferably separate. The cost and/or time associated with transferring or moving product within a facility may vary depending on whether the product is stored in a bin or stored in “flat storage.” Bin storage generally refers to product that is stored in bins, containers, etc. Flat storage generally refers to product that is stored in flat storage areas or sections such as pallets, shelving, stacked, etc. Other transfer process data may be included depending on the facility and types of materials being handled, among other factors.  
     [0093] Model data may be provided for comparison to actual data for the process. The model data provided for comparison may be one or more inputted values, or one or more calculated values. According to a particularly preferred embodiment, the model data compared to the actual data may be a calculated value, based on inputted data, that is comparable to the actual data. For example, a model time, tons or run length may be provided that will be compared to the actual time, tons or run length.  
     [0094] b. Housekeeping Process  
     [0095] As shown in FIG. 7, housekeeping process data  110  may include steps and model data associated with cleaning and/or upkeep of a facility. The plant may be divided into various sections. The employee may record their time spent cleaning in each area. Examples of sections include: storage roof, shop, compressor room, boiler room, panel room, finished feed bag warehouse, warehouse dock, ingredient bag warehouse, drug room, packer area, table area, main floor, hand add area, pellet mill area, outside bins, basement, floor  1 A, floor old  2 , floor old  3 , floor new  2 , floor new  3 , floor new  4 , floor new  5 , bin tops, plant roofs, bulk receiving area, bulk loadout area, plant yard, as well as other areas which may be a part of the facility.  
                                   Data   Description                  Bin Deck Area   The area of the bin deck.       Bin Deck Hskpng Freq   The frequency of housekeeping per month           for the bin deck.       Mill Floor A Area   The area of the mill floor A.       Mill Floor A Hskpng Freq   The frequency of housekeeping per month           for mill floor A.       Mill Floor B Area   The area of mill floor B.       Mill Floor B Hskpng Freq   The frequency of housekeeping per month           for mill floor B.       Mill Floor C Area   The area of Mill Floor C.       Mill Floor C Hskpng Freq   The frequency of housekeeping per month           for mill floor C.       Basement A Area   The area of Mill Basement A,       Basement A Hskpg Freq   The frequency of housekeeping per month           for basement A.       Basement B Area   The area of Mill Basement B.       Basement B Hskpng Freq   The frequency of housekeeping per month           for the basement B.       Warehouse A Area   The area of Warehouse A.       Warehouse A Hskpng Freq   The frequency of housekeeping per month           for warehouse A.       Autosweep   Autosweep rate.       Warehouse B Area   The area of Warehouse B.       Warehouse B Hskpng Freq   The frequency of housekeeping per month           for warehouse B.       Truck Receiving Area   The area of the truck receiving area.       Truck Receiving Hskpng Freq   The frequency of housekeeping per month           for truck receiving.       Truck Receiving   This field is computed from user inputs.       Rail Receiving Area   The area of the rail receiving area.       Rail Receiving Hskpng Freq   The frequency of housekeeping per month           for rail receiving.       Rail Receiving   This field is computed from user inputs.       Truck Loadout Area   The area for the truck loadout area.       Truck Loadout Hskpng Freq   The frequency of housekeeping per month           for truck loadout.       Truck Loadout   This field is computed from user inputs.       Rail Loadout Area   Enter the area for the rail loadout area.       Rail Loadout Hskpng Freq   The frequency of housekeeping per month           for rail loadout.       Rail Loadout   This field is computed from user inputs.       Boil/PMP/Elect Area   The size of the boiler/power area.       Boil/PMP/Elect Hskpng Freq   The frequency of housekeeping per month           for the boiler/power area.       Boil/PMP/Elect   This field is computed from user inputs.       Truck Tunnel Area   The area of the truck terminal.       Truck Tunnel Hskpng Freq   The frequency of housekeeping per month           for the truck tunnel.       Truck Tunnel   This field is computed from user inputs.       Rail Tunnel Area   The area of the rail terminal.       Rail Tunnel Hskpng Freq   The frequency of housekeeping per month           for the rail tunnel.       Rail Tunnel   This field is computed from user inputs.       Maint Shop Area   The size of the maintenance shop.       Maint Shop Hskpng Freq   The frequency of housekeeping per month           for the maintenance shop.       Maint Shop   This field is computed from user inputs.       Office/Employ Area   The area of the office/employee area.       Office/Employ Hskpng Freq   The frequency of housekeeping per month           for the office/employee area.       Office/Employ   This field is computed from user inputs.       Parking Lot (Hrs/Mo)   The hours per month for cleaning the           parking lot.       Mow/Snow Rmv (Hrs/Mo)   The hours per month for mowing/snow           removal.       Mill   This field may be a constant rate.       Warehouse   This field may be a constant rate.       Blowdown   This field may be a constant rate.       Mezzanine area   The area of the mezzanine.       Mezzanine Hskpng Freq   Enter the frequency of housekeeping per           month for the mezzanine area.       Mezzanine   This field is computed from user inputs.       Total Hrs/Day   This field is computed from user inputs.       Wages/Hr $   Wages per hour of employees involved           with the process.       Cost/Day $   Cost per ton that the process adds to the           product       Tot MIg Cost $   Overall cost of milling       Autosweep (% UM)   This field may be a constant rate.       Other   The area for the user entered area.       Other Hskpng Freq   The frequency of housekeeping per month           for the user entered area.       Other Area   The area for the user entered area.                  
 
     [0096] Housekeeping process data  110  may be based on areas or spaces within the facility (shown as “Bin Deck,” “Mill Floor A,” “Mill Floor B,”“Mezannine Area,” etc.), on the size of those spaces (e.g., square footage, etc.), and/or on the frequency that housekeeping processes should be conducted (e.g., frequency, occurrences, daily, monthly, number of days per month, etc.). Housekeeping process data may also be based on an estimated number of hours required to complete a task (e.g., mowing, snow removal, etc.). System  10  may calculate time required to complete the housekeeping processes (e.g., based on a given space size and cleaning rate) and the cost associated with the housekeeping processes. As well, other housekeeping data may be included depending on the facility, processes, and employees involved, among other factors.  
     [0097] Model data may be provided for comparison to actual data for the process. The model data provided for comparison may be one or more inputted values, or one or more calculated values. According to a particularly preferred embodiment, the model data compared to the actual data may be a calculated value, based on inputted data, that is comparable to the actual data. For example, a model time, tons or run length may be provided that will be compared to the actual time, tons or run length.  
     [0098] c. General Plant  
     [0099] As shown in FIG. 8, general plant processes data  120  may include steps and model data associated with personnel time, hours associated with general plant or facilities operations, meetings, etc. General plant process data may include the time needed for the purposes of conducting month end inventories, to inventory both finished bagged products and bulk products, to inventory both bagged and bulk ingredients, to inventory empty bags for finished feed bagged production, to inventory feed tags, for formally held safety meetings, for quality work group meetings, for formally held shift meetings, for changes of grinder screens for the purpose of a grind size change, the time required of employees for the purpose of directing others or production process coordination, or other purposes. According to a particularly preferred embodiment, general plant processes data  120  comprises model data relating to a recurring meeting in facility including the number of employees needed/required for the recurring meeting, and an amount of time needed per employee for the recurring meeting. A total number of hours required for the recurring meeting may then be generated by multiplying the number of employees needed by the amount of time needed per employee. Other general plant data may be included, depending on the facility, processes, and employees involved, among other factors.  
     [0100] Model data may be provided for comparison to actual data for the process. The model data provided for comparison may be one or more inputted values, or one or more calculated values. According to a particularly preferred embodiment, the model data compared to the actual data may be a calculated value, based on inputted data, that is comparable to the actual data. For example, a model time, tons or run length may be provided that will be compared to the actual time, tons or run length.  
                                   Data   Description                  Inventory Month-end   The hours required by hourly paid employees           for the purposes of month end inventories.           Typically these inventories are done by           teams of 2 employees.       Inventory Finish Fd   The time required to inventory both finished           bagged products and bulk products.       Inventory Ingred   The time required to inventory both bagged           and bulk ingredients.       Inventory Q C   The time required daily to inventory both           drugs and premixes.       Inventory Empty Bag   The time required to inventory empty bags           for finished feed bagged production.       Inventory Tags   The time required to inventory feed tags.       Meetings Safety   This field is computed from user inputs.           The time established for formally held safety           meetings.       QWG Meetings   This field is computed from user inputs.           The time established for formally held quality           work group meetings.       Shift Meetings   This field is computed from user inputs.           The time established for formally held shift           meetings.       Grind Scr Chg(Hrs/Mo)   Any changes of hammermill screen for the           purpose of a grind size changed.       Lead People   The time required of hourly paid employees           for the purpose of directing others or           production process coordination.       Inv [2 + 3 + 4] Hrs/Day   This field is computed from user inputs.       Lead People Hrs/Day   This field is computed from user inputs.       Tot Gen Plt Hrs/Day   This field is computed from user inputs.       Wages/Hr $   Wages per hour of employees involved with           the process.       Cost/Day $   Cost per ton that the process adds to the           product       Tot Mlg Cost $   Overall cost of milling       # of Empl in QW Group   The number of employees in the Quality           Work Group.       QWG Hrs/Mth per Psn   The hours per month per person in the           Quality Work Group.                  
 
     [0101] d. Bag Receiving Process  
     [0102] As shown in FIG. 9, bag receiving process data  130  may include steps and model data associated with receiving materials in a bag form. For example, in a facility producing feed products (such as animal feed products) or other food products, materials which are constituents or make up the feed product may be shipped in bags, containers, bins, etc. At the facility, the materials may be received and moved within the facility by hand, carts, pallet jacks, forklifts, conveyor belts, etc.  
                                   Data   Description                  Set/Clean Time (Min)   May be based on a time study,           including time to:           Set dock plate           Check and handle paperwork           Clean/arrange product bays       Stack Time (Min/Ton)   May be based on a time study of how           long it takes to stack one ton of bags.           (Min.), from the floor of the truck           onto a handtruck or pallet       Avg Ship Size (Ton)   Divide the receiving tons by the total           number of bag shipments received.             Bag In (Tons)             Shipments       Avg # Items/Ship   The number of items received and           divided by the number of bag           shipments received.             Items Received             Shipments       Recd on Pallets (Ton/Percentage)   Tons or percentage of materials           received on pallets.       Label: Recd on Floor   Tons or percentage of materials       (Ton/Percentage)   received on floor.       Label: Restack in Whse (Ton)   Amount to be restacked on pallets.       Recd-Hand Eqp (Ton)   Amount received with hand           equipment       Recd-In Sax Fd (Ton)   Amount received in sacks       Storage Dist (% UM)   The distance from receiving dock to           weighted center (roughly weigh the           effect of ingredient usage vs.           distance) of ingredient storage           (Ft or Meters)       Hand Equipment (Ton)   The average handtruck load (ton).       Trip Time (Min)   This field is computed from user           inputs.       Trips/Load   This field is computed from user           inputs.       Tons/Psn Hour   This field is computed from user           inputs.       Wages/Hr $   Wages per hour of employees           involved with the process.       Cost/Ton $   Cost per ton that the process adds to           the product.       Tot Mlg Cost $   Overall cost of milling.       % Rcvd by Forklift   This field is from user inputs           The percent received by forklift.                  
 
     [0103] Bag receiving process data  130  may include time taken to unload trucks, handling of paperwork (shipping orders, receipts, loading orders, etc.), set/clean time (setting up and cleaning the area directly effected by bag receiving), and re-stacking time.  
     [0104] Bag receiving process data may include Set/Clean Time (Min) (e.g., an estimate of time needed to set the dock plate, Check and handle paperwork, and Clean/arrange product bays), Stack Time (Min/Ton) (e.g. an estimate of time needed to stack one ton of bags (Min.), from the floor of the truck onto a handtruck or pallet), Avg Ship Size (Ton) (e.g., the tons received divided by the total number of bag shipments received), Avg # Items/Ship (e.g, the number of items received divided by the number of bag shipments received), Recd on Pallets (e.g, tons of product received on pallets, percentage of tons of product received on pallets, etc.), Recd on Floor (e.g, tons of product received on the floor, percentage of tons of product received on floor, etc.), Restack in Whse (e.g., changing pallets), Recd-Hand Eqp (Ton) (may be expresses as tons or as a percentage of received bags, Recd-In Sax Fd, Storage Dist (% UM), Hand Equipment (Ton)(the average handtruck load (ton)), Forklift (the average forklift load (ton)), Trip Time (Min), Trips/Load, Tons/Psn Hour (e.g., tons per person hour), Wages/Hr $, Cost/Ton $, Tot Mlg Cost $, % Rcvd by Forklift, etc.  
     [0105] According to a particularly preferred embodiment, bag receiving process data  130  comprises model bag receiving data, data relating to an amount or percentage of bag material received with a forklift, and data relating to a capacity of the forklift. The percentage of bag material received with a forklift may be calculated by ((FIELD 5+FIELD 6)−FIELD 8)/(FIELD 5+FIELD 6)*100. As well, other calculations may be used depending on the desired results and the available inputs. Also, other bag receiving data may be included depending on the facility and processes involved, among other factors.  
     [0106] Model data may be provided for comparison to actual data for the process. The model data provided for comparison may be one or more inputted values, or one or more calculated values. According to a particularly preferred embodiment, the model data compared to the actual data may be a calculated value, based on inputted data, that is comparable to the actual data. For example, a model time, tons or run length may be provided that will be compared to the actual time, tons or run length.  
     [0107] e. Bulk Receiving Process  
     [0108] As shown in FIG. 10, bulk receiving process data  140  may include steps and model data associated with receiving material in bulk form (such as from rail cars and trucks). Bulk receiving process data  140  may include set/clean time (setting up and cleaning the area directly effected by bulk receiving), handling of paperwork, weight time, sample time, and testing time (for trucks and rail cars)  
     [0109] Bulk receiving process data may include the following data:  
                                   Data   Description                  Truck Set/Clean Time (Min)   May be based on a time study.           Includes time to:           Set Distribution           Check/Handle paperwork           Cleanup           Travel time           Open-Close car       Truck Weigh Time (Min)   This is the time required to weigh the           unit in and out for receiving.       Truck Sample Time (Min)   This is the time required to sample the           ingredient before unloading.       Truck Testing Time (Min)   This is the time required to conduct           quality control tests on incoming           ingredients.       Truck Oper Time (Min/Truck)   May be based on a time study.           Includes time to:           Check ingredient quality           Monitor the progress on unload       Truck Avg Load Size (Ton)   Average amount of material received           per truck load (e.g., total tons of           material received per month divided           by number of trucks per month.       Truck Hopper/Dump Trk   Amount or percentage of material       (Ton/Percentage)   received by truck hopper and dump           truck.       Truck Liquid/Air Truck   Amount or percentage of liquid or gas       (Ton/Percentage)   material received by truck.       Truck Hoist Dumper (Ton/   Amount or percentage of material       Percentage)   received by trucks which are unloaded           by a hydraulically operated dumper           unit or scale.       Truck Mineral (Ton/Percentage)   Amount or percentage of mineral           material received by truck hopper and           dump truck.       Truck Leg Cap   Capacity of leg(s) operating on truck           bulk receiving process.       Truck Avg Density   Average density of material received           in trucks.       Truck Leg Cap (Tons/Hr)   This field is computed from user           inputs.       Truck Tons/Psn Hour   This field is computed from user           inputs.       Truck Total Tons/Psn Hour   This field is computed from user           inputs.       Railcars Set/Clean Time (Min)   May be based on a time study.           Includes time to:           Set distribution           Check/Handle paperwork           Cleanup           Set and move car (one or more           times)           Travel Time           Open-Close car       Railcars Weigh Time (Min)   This is the time required to weigh the           unit in and out for receiving.       Railcars Sample Time (Min)   This is the time required to sample           the ingredient before unloading.       Railcars Testing Time (Min)   This is the time required to conduct           quality control tests on incoming           ingredients.       Railcars Avg Load Size (Ton)   Average amount of material received           per railcar load (e.g., total tons of           material received per month divided           by number of railcars per month.       Railcars Boxcar (Ton/   Amount or percentage of material       Percentage)   received by boxcar.       Railcars Hop Car (Soft-Tn/   Amount or percentage of material       Percentage)   received by hop cars.       Railcars Hop Car (Grain-Tn/   Amount or percentage of material       Percentage)   received by hop cars.       Railcars Mineral (Ton)   Amount or percentage of mineral           material received.       Railcars Leg Cap (% UM)   Capacity of leg(s) operating on truck           bulk receiving process.       Railcars Avg Density (% UM)   Average density of material received           in trucks.       Railcars Leg Cap (Tons/Hr/   This field is computed from user       Percentage)   inputs.       Railcars Rail Tons/Psn Hour   This field is computed from user           inputs.       Wages/Hr $   Wages per hour of employees           involved with the process.       Cost/Ton $   Cost per ton that the process adds to           the product       Tot Mlg Cost $   Overall cost of milling                  
 
     [0110] According to a particularly preferred embodiment, bulk receiving process data  140  comprises model dumping data. For example, as shown in FIG. 11, model dumping data  150  may comprise data related to transferring material received in bags (such as large “one-ton-totes”) into a bulk storage area. For example, the process may involve emptying material from these bags into holding areas. As shown in FIG. 11, model dumping data may relate to the size of one or more bags, bag tons per month, dumped tons (tons/hour), operator time, set times, clean times, weigh times, sample times, testing times, and average load size.  
     [0111] Model data may be provided for comparison to actual data for the process. The model data provided for comparison may be one or more inputted values, or one or more calculated values. According to a particularly preferred embodiment, the model data compared to the actual data may be a calculated value, based on inputted data, that is comparable to the actual data. For example, a model time, tons or run length may be provided that will be compared to the actual time, tons or run length.  
     [0112] f. Mixing Process Data  
     [0113] As shown in FIG. 12, mixing process data  160  may include steps and model data associated with mixing various materials and products together to form products. Mixing process data may include changeover time, mixing time, short mixing (getting ingredients, and weighing), recording drug and premix usage, and completing mixing process improvement sheets.  
     [0114] Mixing process data may include the following data:  
                                   Data   Description                  Changeover Time (Min)   May be based on a time study. This is the           time between stopping one run and starting           another: Includes time to:           Get formula           Get shortmix items           Cleanup per run           Set distribution           Paperwork       Best Practice Time   This field is computed from user inputs.       Mixing Time (Min)   May be based on a mixer efficiency study to           find the minimum mixing time (Min.).       Scale Mty Time (Min)   Timed value of how long it takes to empty a           scale (Min.).       Mixer Mty Time (Min)   Timed value of how long it takes to empty a           mixer (Min.).       Avg Run Length (Ton)   The mixing tons divided by the runs during           the same period (Tons).       Mixer Size (Ton)   The size or capacity of a mixer (Tons).       Line Speed (Tons/Hr)   The tons per hour of continuous mix           operations.       Avg Shortmix Items   Average-weight of shortmix items (e.g.,           typically small, hand-added ingredients).       Ton Mix w/Man   Manual shortmix tons are the shortmix items       Shortmix/Percentage   that are weighed by an operator and           manually dumped. Includes the tons           weighed/dumped manually.       Ton Mix w/Auto   Automatic shortmix tons includes the       Shortmix/Percentage   shortmix that is added to product mix           automatically by machine. Includes the tons           added automatically.       Avg Shortmix (% UM)   The bag ingredients divided by the tons           mixed then multiply by mixer size (Pounds or           Kilograms per Batch.       Manual (Production %)   The percent of production that is mixed with           a manual system.       Line (Production %)   The percent of production that is mixed with           a line system.       Line (Automation %)   The percent of automation of production for           the line system.       Batching   The percent of production that is mixed with       (Automation %)   a batching system.       Avg Shortmix Time   Average shortmix time       (Percentage)       Mixing Tons/Hr   Mixing tons per hour       (Percentage)       Tons/Psn Hour   Tons per person hour       (Percentage)       Wages/Hr $   Wages per hour of employees involved with           the process.       Cost/Ton $   Cost per ton that the process adds to the           product.       Tot Mlg Cost $   Overall cost of milling.       Batches/Hr (BP = 10+)   This field is computed from user inputs.                  
 
     [0115] According to a particularly preferred embodiment, mixing process data  160  comprises best practice time (e.g., mixing time plus scale emptying time plus mixer empty time) and batches/hour (e.g., mixing tons/hour divided by mixer size). As well, other mixing process data may be included depending on the facility and the processes involved, among other factors.  
     [0116] Model data may be provided for comparison to actual data for the process. The model data provided for comparison may be one or more inputted values, or one or more calculated values. According to a particularly preferred embodiment, the model data compared to the actual data may be a calculated value, based on inputted data, that is comparable to the actual data. For example, a model time, tons or run length may be provided that will be compared to the actual time, tons or run length.  
     [0117] g. Dry Packing Process And Wet Packing Process  
     [0118] As shown in FIGS. 13 and 14, dry packing process data  170  and wet packing process data  180  may include steps and model data associated with packing both wet and dry products into containers, bags, bulk containers, etc. Dry packing process data  170  may include bagging, storage distribution, sampling, changeover time, getting bags and tags, and completing packing process control sheets  
     [0119] Dry packing and wet packing process data may include the following data:  
                                   Data   Description                                    DRY PACKING PROCESS:                     Changeover Time (Min)   May be based on a time study (Min.).           This is the time between stopping one           run and starting another run. Time may           be multiplied by two to calculate the           labor time needed. (Multiplying by two           is for purposes of including both the           packing and table employees). Includes           time to:           Open/Close and vibrate bin           Get tag/bag supply           Paperwork           Cleanup           Bay time       Bag/tag/smp/wgh ea 2 ton   May be based on a time study (Min.).           This is the time required to reload           empty bags, reload tags, sample run, or           test weigh bags once per every two           ton. Includes time to:           Restock bags (80 bags)           Restock tags (80 tags)           Sample feed           Check weigh bag           Adjust scale       Avg Run Length (Ton)   The packing tons divided by the number           of runs packed during that period           (Tons).       Pel/Ml/Other (Ton/Percentage)   The total tons of all dry feeds packed.           (Pellet, meal and other).       Storage Dist (% UM)   Average distance operators need to           travel (one way) to get to a warehouse           bay.       Avg Actual (Bags/Min)   This field is computed from user inputs.       Avg Achieve Rate(%)   This field is computed from user inputs.       Stor Equip Cap (Ton)   Equipment capacity of forklifts, hand           trucks, etc. Forklifts may be one ton           and hand trucks may be 1/4 ton.       Auto Stacker (%)   The percent of product that is handled           with an auto stacker.       Auto Hanging (%)   The percent of product that is handled           with an auto hanger.       Auto Closer (%)   The percent of product that is handled           with an auto closer.       Run Speed (Tons/Hr)   This field is computed from user inputs.       Pack-Whse Time (Min)   This field is computed from user inputs.       Pack-Table Time (Min)   This field is computed from user inputs.       Wages/Hr $   Wages per hour of employees involved           with the process.       Tons/Psn Hour   Cost per ton that the process adds to           the product       Cost/Ton $   Overall cost of milling.       Tot Mlg Cost $   This field is computed from user inputs.                 WET PACKING PROCESS:                     Changeover Time (Min)   May be based on a time study (Min.).           This is the time between stopping one           run and starting another run. Time may           be multiplied by two to calculate the           labor time needed. (Multiplying by two           is for purposes of including both the           packing and table employees). Includes           time to:           Open/Close and vibrate bin           Get tag/bag supply           Paperwork           Cleanup           Bay time       Bag/tag/smp/wgh ea 2 ton   May be based on a time study (Min.).           This is the time required to reload           empty bags, reload tags, sample run, or           test weigh bags once per every two           ton. Includes time to:           Restock bags (80 bags)           Restock tags (80 tags)           Sample feed           Check weigh bag           Adjust scale       Wet Clean (Min/Run)   Clean scale and miscellaneous           equipment after running wet feed           (Min.). This is the time required to           clean the scale and work area after a           wet feed run.       Avg Run Length (Ton)   The packing wet tons divided by the           number of runs packed during that           period (Tons).       Wet Feed (Ton) Percentage   The total tons (or percentage) of all. wet           feeds.       Storage Dist (% UM)   Average distance operators need to           travel (one way) to get to a warehouse           bay.       Avg Actual (Bags/Min)       Avg Achieve Rate(%)       Stor Equip Cap (Ton)   Equipment capacity of forklifts, hand           trucks, etc. Forklifts may be one ton           and hand trucks may be 1/4 ton.       Auto Stacker (%)   The percent of product that is handled           with an auto stacker.       Auto Hanging (%)   The percent of product that is handled           with an auto hanger.       Auto Closer (%)   The percent of product that is handled           with an auto closer.       Run Speed (Tons/Hr)   This field is computed from user inputs.       Pack-Whse Time (Min)   This field is computed from user inputs.       Pack-Table Time (Min)   This field is computed from user inputs.       Tons/Psn Hour   This field is computed from user inputs.       Wages/Hr $   Wages per hour of employees involved           with the process.       Cost/Ton $   Cost per ton that the process adds to           the product.       Tot Mlg Cost $   Overall cost of milling.                  
 
     [0120] According to a particularly preferred embodiment, dry packing process data and wet packing process data  170  and  180  comprise model dry packing data, model wet packing data, wet and dry packing efficiency, bag size data (e.g., one or two or more bag sizes), average bag weight, scale rate of number of bags per time, scale rate of number of bags per minute, actual rate of bags per time, actual rate of bags per minute, bag tons per month, a manufacturer specification for at least one piece of packing equipment (such as automated packing equipment), liquid addition time, setup time and clean up time. As well, other information relating to the dry packing processes and the wet packing processes may be included depending on the facility and the processes involved, among other factors.  
     [0121] Model data may be provided for comparison to actual data for the process. The model data provided for comparison may be one or more inputted values, or one or more calculated values. According to a particularly preferred embodiment, the model data compared to the actual data may be a calculated value, based on inputted data, that is comparable to the actual data. For example, a model time, tons or run length may be provided that will be compared to the actual time, tons or run length.  
     [0122] h. Bulk Load Out Process and Bag Load Out Process  
     [0123] As shown in FIG. 15, bulk load out process data  190  and bag load out process data  200  may include steps and model data associated with loading trucks, railcars and other transports with product, or other steps involved with shipping product. Bag load out may include set/clean time (setting up and cleaning areas directly effected by bag loading), truck loading time, handling paperwork, resacking and handling broken bags. Bulk load out may include set/clean time (setting up and cleaning areas directly effected by bulk loading), truck loading time, sample time, weigh time, and handling paperwork for trucks and rail cars.  
     [0124] Bulk load out and bag load out process data may include the following data:  
                                   Data   Description                                    BULK LOADOUT PROCESS:                     Dry Set/Clean (Min)   May be based on a time study. Time           required to set up, complete paperwork,           and cleanup after loading one feed.           Includes:           Time to position unit for loading           Paperwork           Travel time       Sample Time   Time it takes to sample each single feed           after loading (Min.).       Weigh Time (Min)   Time it takes to weigh a truck both in and           out for each single feed or obtain rail           weight for each feed.       Urea Hang Time (Min)   Time during which an operator needs to           vibrate a bin to release a hang for urea           feeds.       Dry Avg Tons/Item(Ton)   Bulk warehousing tons divided by the           difference in the “Scale Ticket” numbers           during this period.           Bulk Warehouse Tons (Truck only)/           (Ending Scale Ticket Number - Beginning           Scale Ticket Number)       Wet Feed (Ton) (Percentage)   Average wet feed bulk tons.       Urea Feed (Ton) (Percentage)   Average urea feed bulk tons.       Pel/Ml/Other (Ton)   Bulk warehouse tons and subtract wet and       Percentage   urea feed tons.       Dry Load Rate(Tons/Hr)   Time of loading rate per ton once the           product is free flowing.       Set/Clean (Min)   May be based on a time study (Min.).           Time required to set up, complete           paperwork, and cleanup after loading one           feed. Includes:           Time to position unit for loading           Paperwork           Travel time       Sample Time (Min)   Time to sample each single feed after           loading (Min.).       Weigh Time (Min)   Time to weigh a truck both in and out for           each single feed or obtain rail weight for           each feed.       Oper Time (Min)   May be based on a time study (Min.). This           is the time required for an operator to load           out feed. Includes time to:           Check finish feed quality           Monitor the progress of loading           Automatic Loading: (Rail)           No time allowed           Truck Loading: (Given)           Time to load at loading rate.       Avg Tons/Item (Ton)   Bulk tons of feed loaded into railcars           divided by the number of different items           shipped by rail.           Bulk Warehouse Tons (Rail only)/           Number of items shipped       Pel/Ml/Other (Ton)   Bulk warehouse tons and subtract wet and       Percentage   urea feed tons.       Load Rate (Tons/Hr)   Time of loading rate per ton once the           product is free flowing.       Avg Loading (Tons/Hr)   This field is computed from user inputs.       Truck Tons/Psn Hour   This field is computed from user inputs.       Total Tons/Psn Hour   This field is computed from user inputs.       Avg Loading (Tons/Hr)   This field is computed from user inputs.       Tons/Psn Hr   This field is computed from user inputs.       Wages/Hr $   Wages per hour of employees involved           with the process.       Cost/Ton $   Cost per ton that the process adds to the           product.       Tot Mlg Cost $   Overall cost per ton of product.       Wet Avg Tons/ltem(Ton)   Divide the wet bulk warehousing tons by           the difference in the “Scale Ticket”           numbers during this period.           Bulk Warehouse Tons (Truck only)/           (Ending Scale Ticket Number - Beginning           Scale Ticket Number)           NOTE: Railcar loading needs to be backed           out of the bulk warehouse tons to make           this calculation.       Wet Set/Clean (Min)   May be based on a time study. Time           required to set up, complete paperwork,           and cleanup after loading one feed.           Includes:           Time to position unit for loading           Paperwork           Travel time       Wet Load Rate(Tons/Hr)   Time of loading rate per ton once the           product is free flowing.                 BAG LOADOUT PROCESS:                     Set/Clean Time (Min)   Time required to set up, to load a           customer and cleanup afterward. May           be based on a time study (Min.).           May include time to:           Set dock plate           Check and handle paperwork           Travel time           Set chocks       Avg Load Size (Ton)   Average load size       % Loaded &lt; Pallet   Capacity of a forklift or handtruck       Avg # Items/Shipped   Average the number of items per load.       Avg # Items/Shipped   Average the number of items per load.       Cargill Hand Ld (Ton/   The tons of product loaded by Cargill.       Percentage)       Cust Hand Ld (Ton/   The tons of product loaded by the       Percentage)   customer.       Pallet Loaded (Ton/   The tons of product loaded by pallet.       Percentage)       Table Loaded (Ton/   The tons of product TABLE LOADED.       Percentage)       Hand Eqp (Ton/Percentage)   The tons of product loaded with hand           equipment.       Storage Dist (% UM)   The average length the operators need to           travel (one way) to get to a warehouse           bay.       Resacking (Hrs/Day)   Time required to re-sack broken bags.       Tons per Pallet   The tons loaded per pallet.       Wages/Hr $   Wages per hour of employees involved           with the process.       Cost/Ton $   Cost per ton that the process adds to the           product.       Tot Mlg Cost $   Overall cost of milling.                  
 
     [0125] According to a particularly preferred embodiment, bulk load out and bag load out process data  190  and  200  comprise model load out data, data relating to a set time for a rail car, a clean time for a rail car, a sample time for a rail car, a weigh time for a rail car, an OPER rate for a rail car, a load rate for a rail car, wet clean rate, wet load rate, wet average tons per item, and a resacking rate. Bulk load out and bag load out may include other data depending on the facility and materials being handled, among other factors. Model data may be provided for comparison to actual data for the process. The model data provided for comparison may be one or more inputted values, or one or more calculated values. According to a particularly preferred embodiment, the model data compared to the actual data may be a calculated value, based on inputted data, that is comparable to the actual data. For example, a model time, tons or run length may be provided that will be compared to the actual time, tons or run length.  
     [0126] i. Pelleting Process  
     [0127] As shown in FIG. 16, pelleting process data  210  may include steps and model data associated with producing products in pellet form. Pelleting process data may include changeover time, pelleting, PDI testing, die changes, pellet dusting, daily maintenance, and pelleting process control sheets.  
     [0128] Pelleting process data may include:  
                                      Changeover Time (Min)   Time between stopping one run and           starting another run. May be based on a           time study (Min.). Time may include:           Travel time           Set distribution           Startup           Sample and check quality           Fill in records           Shut down           Run fines           Cleanup floor       PDI Test Time (Min)   Time to get a sample and run a PDI test           (pellet density index). Time may not           include when the sample is unsupervised           while in the tumbling chamber.       Daily Maint (Min)   Daily maintenance time in minutes/pellet           mill/shift. This time may be deducted           from time available to pelleting. This may           be the sum total of daily maintenance for           all mills.       Oper Time/Hr (Min)   Time the operator spends monitoring a           single unit. May be based on a time study           (Min.). Time may include:           Travel time           Check amps, feeder, feed quality, and           adjust mill as needed           Inspect cooler           Discuss operation with others       Avg Run Length (Ton)   Divide the actual pellet tons by the runs           during the same period (Tons).       40+   The tons pelleted using a 40+ mm die           size.       Cubes   The tons pelleted into cubes.       30 +   The tons pelleted using a 30+ mm die           size.       20+   The tons pelleted using a 20+ mm die           size.       10+   The tons pelleted using a 10+ mm die           size.       Tot Pellet Mill HP   The pellet mill horsepower available at           facility. This is maindrive motors only.       No. of Pellet Mills   The number of pellet mills available at           facility.       Pel Dust (Tons/Mo)   Pellet dusting time       % Fd PDI Tested   The percent of feeds requiring PDI testing.       % UM   An entry here will override the computed           value shown for field       Daily Die Chg (Min)   This field is computed from user inputs.       % UM   This field is computed from user inputs.       Avg Pel Rate (Tons/Hr)   This field is computed from user inputs.       Tons/Psn Hour   This field is computed from user inputs.       Wages/Hr $   Wages per hour of employees involved           with the process.       Cost/Ton $   Cost per ton that the process adds to the           product..       Tot Mlg Cost $   Overall cost of milling.       % UM   This field is computed from user inputs.                  
 
     [0129] According to a particularly preferred embodiment, pelleting process data  190  comprises model pelleting data, pelleting data relating to die friction, throughput of a pelleting machine, energy cost of the pelleting machine, or a time required to change a die of a pelleting machine. Other pelleting process data may also be included depending on the facility and the materials being handled, among other factors. Model data may be provided for comparison to actual data for the process. The model data provided for comparison may be one or more inputted values, or one or more calculated values. According to a particularly preferred embodiment, the model data compared to the actual data may be a calculated value, based on inputted data, that is comparable to the actual data. For example, a model time, tons or run length may be provided that will be compared to the actual time, tons or run length.  
     [0130] j. Maintenance Process  
     [0131] As shown in FIG. 17, maintenance process data  220  may include steps and model data associated with maintenance of facility equipment. Maintenance process data may include lubes, inspections, repairs (planned and unexpected), parts ordering, equipment history, and file maintenance.  
     [0132] Maintenance process data may include  
                                   DATA   DESCRIPTION                  No. of Legs   Number of Legs actively used and           maintained.       No. of Mixers   Number of Mixers actively used and           maintained.       No. of Pkg Scales   Number of Package Scales actively used           and maintained.       No. of Bag Hangers   Number of Bag Hangers actively used and           maintained.       No. of Screws   Number of Screws actively used and           maintained.       No. of Drags   Number of Drags actively used and           maintained.       No. of Boilers   Number of Boilers actively used and           maintained.       No. of Air Comp   Number of Air Compressors actively used           and maintained.       No. of Distributors   Number of Distributors actively used and           maintained.       No. of Vert/Cflw Coolers   Number of Vertical/Counterflow Coolers           actively used and maintained.       No. of Horiz Coolers   Number of Horizontal Coolers actively used           and maintained.       No. of Pellet Scrs   Number of Pellet screeners actively used           and maintained.       No. of Ingrd Cleanrs   Number of Ingredient Cleaners actively           used and maintained.       No. of Grinders   Number of Grinders actively used and           maintained.       No. of Air Cond   Number of Air Conditioners actively used           and maintained.       No. of Mol Mixers   Number of Molasses Mixers actively used           and maintained.       No. of Belt Conv   Number of Belt Conveyors actively used           and maintained.       No. of Car Pul   Number of Car Pul actively used and           maintained.       No. of Forklift   Number of Forklifts actively used and           maintained.       No. of Pel Mills   Number of Pellet Mills actively used and           maintained.       No. of Roller Mills   Number of Roller Mills actively used and           maintained.       No. of Stm Chambers   Number of Steam Chambers actively used           and maintained.       No. of Grain Dryers   Number of Grain Dryers actively used and           maintained.       No. of Spr Systems   Number of Sprinkler Systems actively used           and maintained.       Plant Index (1,2,3)   Number which best represents the           mechanical complexity of the plant as           follows:           1 - small plant           2 - medium plant           3 - large plant       Misc maint (Hrs/Mo)       Inspect/Lube (Hrs/Day)   This field is computed from user inputs.       Repairs (Hrs/Day)   This field is computed from user inputs.       Total Hrs/Day   This field is computed from user inputs.       Wages/Hr $   Wages per hour of employees involved           with the process.       Cost/Day $   Cost per ton that the process adds to the           product.       Tot Mlg Cost $   Overall cost of milling.       No. of Extruders   Number of Extruders actively used and           maintained.       No. of Dryers   Number of Dryers actively used and           maintained.                  
 
     [0133] According to a particularly preferred embodiment, maintenance process data  220  comprises model maintenance data, data relating to one of a number of extruders, and a number of dryers. As well, other maintenance data may be included depending on the facility and machinery being used, among other factors.  
     [0134] Model data may be provided for comparison to actual data for the process. The model data provided for comparison may be one or more inputted values, or one or more calculated values. According to a particularly preferred embodiment, the model data compared to the actual data may be a calculated value, based on inputted data, that is comparable to the actual data. For example, a model time, tons or run length may be provided that will be compared to the actual time, tons or run length.  
     [0135] k. Energy Process  
     [0136] As shown in FIGS. 18 and 19, energy process data  230  may include steps and model data associated with gas/oil consumption and/or electrical consumption at a facility.  
     [0137] Energy process data may include data relating to electrical, gas and oil use such as:  
                                   DATA   DESCRIPTION                  Sys Voltage   Plant is typically on a 230, 460, or 575           voltage system. Electrical usage may be           calculated for 3 phase equipment, or other           configurations.       InterPlt Xfer Amps   Amperage of each motor (AMPS).       Bag In Amps   Amperage of each motor (AMPS).       Bulk In-Truck Amps   Amperage of each motor (AMPS).       Bulk In-Rail Amps   Amperage of each motor (AMPS).       Mixing Amps   Amperage of each motor (AMPS).       Packing Amps   Amperage of each motor (AMPS).       Bulk Wh-Truck Amps   Amperage of each motor (AMPS).       Bulk Wh-Rail Amps   Amperage of each motor (AMPS).       Bag Whse Amps   Amperage of each motor (AMPS).       Pelleting Amps   Amperage of each motor used for pelleting           (AMPS).       Grinding Amps   Amperage of each motor (AMPS) used for           grinding.       Amps   Amperage of each motor (AMPS).       Roll/Flake Amps   Amperage of each motor used for           rolling/flaking (AMPS).       Amps   Amperage of each motor (AMPS).       Amps   Amperage of each motor (AMPS).       Gen Plant Amps   Amperage of each motor (AMPS).       Lighting Kw/Hr   The number of fixtures, kilowatts (KW)           and percent usage during production           hours. Total the weighted KW usage per           hour.       Electrical $/Kw   Estimate or determination of the % of full           amp load that plant typically electrically           operate.       Adjustment %       Extr/Dryer Amps   The amperage of each extruder/dryer           motor (AMPS).       BTUs/Ton   This field is computed from user inputs.       Cost/Ton $   This field is computed from user inputs.       Tot Mlg Cost $   This field is computed from user inputs.       Boiler Horsepower   The total horsepower available (H.P.).       Steam (% UM)   NOTE: Use gage pressure values.       Feedwater Temp (% UM)   The temperature of feedwater coming into           the makeup tank.           This may be city or well water           temperature.       Pellet Steam Add %   The percent of steam added at the pellet           mill.       Str Fat-Ml-Wax % UM   The average gallons of liquid ingredients           which are heated with water or steam           (Gallons/Liters).       HExcg Ft-Ml-Wx % UM   The average gallons of liquid ingredients           that pass through a heat exchanger.       Flake Steam Add %   May be from moisture tests to determine           how much steam is being added to grain in           the steam chamber (%).       Steam Htr + Furn. (BTU)   The connected BTU of steam heaters that           are needed in the plant (BTU).       Grain Moist Remov %   May be from moisture tests to determine           how much moisture is being removed           during the grain drying process.       Grain &gt; 18% Moist(0-1)   May be from moisture tests to determine           the average moisture content of the           incoming grain. If it is over 18% enter “1”           may tell the computer to use the high           moisture calculation. If the average           moisture content is 18%, “0” may be           entered.       Prod Moist Add (%)   May be from moisture tests to determine           how much moisture is added during this           process. Process 16 can be used for a           moisture adding process as well as for           grain drying.       Deg Days Dec-Jan-Feb       Deg Days Nov-Mar-Apr       BTUs per Fuel Unit   The BTU&#39;s per fuel unit of fuel for a boiler.       Energy ($/Unit)   The cost per unit for energy source.       Heater Avg BTU (Y/N)   Enter “Y” to calculate average Gas/Oil           usage. This means that space heater fuel           usage would be equally distributed over a           12 month calendar period. Enter “N” to           calculate seasonal Gas/Oil usage for the           current time frame utilizing the date typed           at the start of program.       Extr Steam Add %       % Adj Ext BTU Usage       BTUs/Ton   BTUs required/estimated per ton of           product.       Cost/Ton $   Cost per ton that the process adds to the           product       Tot Mlg Cost $   Overall cost of milling                  
 
     [0138] According to a particularly preferred embodiment, energy process data  230  comprises model energy consumption data, gas consumption data, oil consumption data, electrical consumption data, energy amount associated with an extruding process, an energy amount associated with an extrusion screen, an additional amount of steam, an additional BTU usage, and wet packing amps. As well, other energy data may be used depending on the facility and the types of energy available, among other factors.  
     [0139] Model data may be provided for comparison to actual data for the process. The model data provided for comparison may be one or more inputted values, or one or more calculated values. According to a particularly preferred embodiment, the model data compared to the actual data may be a calculated value, based on inputted data, that is comparable to the actual data. For example, a model time, tons or run length may be provided that will be compared to the actual time, tons or run length.  
     [0140] l. Miscellaneous Process  
     [0141] As shown in FIG. 20, miscellaneous process data  240  may include steps and model data associated with miscellaneous processes at a facility.  
     [0142] Miscellaneous process data may include  
                                   DATA   DESCRIPTION                  Work Days   The AVERAGE number of work days per           month. Days that feed is PRODUCED.           Maintenance days are not included.       Overtime (%)   Percent overtime.       Health Ins (%)   The cost of health insurance, as a           PERCENTAGE of hourly wages.       Workers Comp (%)   The cost of Workers&#39; Comp Insurance as a           PERCENTAGE of hourly wages.       Pension (%)   Pension cost, expressed as a PERCENT of           hourly wages.       Payroll Taxes (%)   The percent of total hourly wages paid to           PAYROLL TAXES.       Supv Sal + Frg ($/Mo)   Monthly cost of supervisor salaries, plus           some fringe benefits.       Supervisory (Hr/Yr)   Supervisor Hours per year.       Vac/Hol (Hr/Yr)   Annual vacation and holiday hours for           hourly employees.       Demurrage ($/Mo)   Cost associated with delaying the           unloading or loading or a transport such as           a truck or a rail car.       Depr ($/Mo)   Depreciation expressed as dollars per           month.       Ins-Prop/Stk ($/Mo)       Rent ($/Mo)       Taxes ($/Mo)       Break Time (Min)   The time for A SINGLE BREAK at this           facility, e.g. 15 minutes. The model will           assume 2 breaks per day.       Production Hrs/Day   The NUMBER OF HOURS plant is running           on an average production day.       Security Guards ($/Mo)   Cost per month for security guards.       Process 13 Name   The Operation synonymous with PROCESS           13 in the Model Mill.       Process 16 Name   The Operation synonymous with PROCESS           16 in the Model Mill.       Process 17 Name   The Operation synonymous with PROCESS           17 in the Model Mill.       Repr($/Ton)   Repair cost per ton to maintain this           equipment.       Flake Repairs ($/Ton)   Dollars per ton required to maintain flake           equipment.       Repr($/Ton)   Cost per ton required to repair/maintain           Operaton 16 equipment.       Repr($/Ton)   Cost per ton for maintenance/repair of           equipment used in Operation 17.       % Pellet in Txt Feed   If plant uses PREMIX PELLETS, the           WEIGHTED AVERAGE of premix pellets           used in textured feed.       Shifts/Day   The number of shifts per day.       Tot Mlg Cost $   Total Milling Cost.                  
 
     [0143] According to a particularly preferred embodiment, miscellaneous process data  240  comprises model operations processes data, actual operations processes data, data relating to a cost associated with a security guard, or currency conversions to allow the system to convert various costs between different currencies. Further, other miscellaneous data may be included depending on the availability and desirability of such data, among other factors.  
     [0144] Model data may be provided for comparison to actual data for the process. The model data provided for comparison may be one or more inputted values, or one or more calculated values. According to a particularly preferred embodiment, the model data compared to the actual data may be a calculated value, based on inputted data, that is comparable to the actual data. For example, a model time, tons or run length may be provided that will be compared to the actual time, tons or run length.  
     [0145] m. Contract Labor Process  
     [0146] As shown in FIG. 21, contract labor process data  250  may include steps and model data associated with costs and amounts of materials handled by contract laborers or contract vendors.  
     [0147] Contract labor process data may include  
                                                   DATA   DESCRIPTION                          Interplant Transfer   Data includes the contract-processed               number of tons. The tons are included in               the process tons entered on the               corresponding process screen, not an               addition to the process tons. Data also               includes the cost per ton for the               contracted process.           Bag Receiving   Data includes the contract-processed               number of tons. The tons are included in               the process tons entered on the               corresponding process screen, not an               addition to the process tons. Data also               includes the cost per ton for the               contracted process.           Bulk Receiving   Data includes the contract-processed               number of tons. The tons are included in               the process tons entered on the               corresponding process screen, not an               addition to the process tons. Data also               includes the cost per ton for the               contracted process.           Mixing   Data includes the contract-processed               number of tons. The tons are included in               the process tons entered on the               corresponding process screen, not an               addition to the process tons. Data also               includes the cost per ton for the               contracted process.           Packing   Data includes the contract-processed               number of tons. The tons are included in               the process tons entered on the               corresponding process screen, not an               addition to the process tons. Data also               includes the cost per ton for the               contracted process.           Bulk Warehouse   Data includes the contract-processed               number of tons. The tons are included in               the process tons entered on the               corresponding process screen, not an               addition to the process tons. Data also               includes the cost per ton for the               contracted process.           Bag Warehouse   Data includes the contract-processed               number of tons. The tons are included in               the process tons entered on the               corresponding process screen, not an               addition to the process tons. Data also               includes the cost per ton for the               contracted process.           Pelleting   Data includes the contract-processed               number of tons. The tons are included in               the process tons entered on the               corresponding process screen, not an               addition to the process tons. Data also               includes the cost per ton for the               contracted process.           Grinding   Data includes the contract-processed               number of tons. The tons are included in               the process tons entered on the               corresponding process screen, not an               addition to the process tons. Data also               includes the cost per ton for the               contracted process.           Secondary Mixing   Data includes the contract-processed               number of tons. The tons are included in               the process tons entered on the               corresponding process screen, not an               addition to the process tons. Data also               includes the cost per ton for the               contracted process.           Rolling/Flaking   Data includes the contract-processed               number of tons. The tons are included in               the process tons entered on the               corresponding process screen, not an               addition to the process tons. Data also               includes the cost per ton for the               contracted process.           Process 16   Data includes the contract-processed               number of tons. The tons are included in               the process tons entered on the               corresponding process screen, not an               addition to the process tons. Data also               includes the cost per ton for the               contracted process.           Process 17   Data includes the contract-processed               number of tons. The tons are included in               the process tons entered on the               corresponding process screen, not an               addition to the process tons. Data also               includes the cost per ton for the               contracted process.           Extruder   Data includes the contract-processed               number of tons. The tons are included in               the process tons entered on the               corresponding process screen, not an               addition to the process tons. Data also               includes the cost per ton for the               contracted process.           Wet Packing   Data includes the contract-processed               number of tons. The tons are included in               the process tons entered on the               corresponding process screen, not an               addition to the process tons. Data also               includes the cost per ton for the               contracted process.                      
 
     [0148] According to a particularly preferred embodiment, contract labor process data  250  comprises model contract labor data (e.g., data relating to a cost or amount associated with contracting any one or more of the following: an interplant transfer, bag receiving, bulk receiving, mixing, packing, wet packing, bulk warehouse, bag warehouse, pelleting, grinding, second mixing, rolling, flaking, grain processing, block pressing, and extruding. Other contract labor data may be included depending on the labor arrangements for the facility, among other factors.  
     [0149] Model data may be provided for comparison to actual data for the process. The model data provided for comparison may be one or more inputted values, or one or more calculated values. According to a particularly preferred embodiment, the model data compared to the actual data may be a calculated value, based on inputted data, that is comparable to the actual data. For example, a model time, tons or run length may be provided that will be compared to the actual time, tons or run length.  
     [0150] n. Extruding Process  
     [0151] As shown in FIG. 22, extruding process data  260  may include steps and model data associated with producing products in extruded form.  
                                   DATA   DESCRIPTION                  Changeover Time (Min)   May be based on a time study (Min.).           Includes time to:           Travel time           Set distribution           Startup           Sample and check quality           Fill in records           Shut down           Run fines           Cleanup floor       Daily Maint (Min)   This field is computed from user inputs.       Oper/Test Time (Min)   This field is computed from user inputs.       Avg Run Length (Ton)   Divide the extruder tons by the runs during           the same period (Tons).        2 mm &gt; Die(Tons/Mo)   The tons extruded using a 2 mm &gt; die           size.       2-3 mm Die(Tons/Mo)   The tons extruded using a 2-3 mm die           size.       3-4 mm Die(Tons/Mo)   The tons extruded using a 3-4 mm die           size.        4 mm &lt; Die(Tons/Mo)   The tons extruded using a 4 mm &lt; die           size.       Total Extruder HP   The extruder horsepower available at the           facility.       No. of Extruders   The number of extruders available at           facility.       Fuel Type   The extruder&#39;s necessary fuel type.       BTUs per Fuel Unit   If “Other” is selected for mm 23_19, enter           the BTUs per fuel unit for the fuel used by           the extruder.       Energy ($/Unit)   The cost per unit for energy source.       Avg Moisture IN (%)   Average moisture percentage of product           sample in.       Avg Moisture OUT (%)   Average moisture percentage of product           sample out.       No. of Extruding Dryers   The number of extruding dryers available           at facility.       % UM   This field is computed from user inputs.       Tons/Hr   This field is computed from user inputs.       Wages/Hr $   Wages per hour of employees involved           with the process.       Cost/Ton $   Cost per ton that the process adds to the           product       Tot Mlg Cost $   Overall cost of milling                  
 
     [0152] According to a particularly preferred embodiment, extruding process data  260  comprises model extruding data (e.g., data relating to any one or more of the following: an energy cost associated with the extruding process, and a labor cost associated with the extruding process). As well, other extruding data may be used depending on the facility and extruding processes used, among other factors.  
     [0153] Model data may be provided for comparison to actual data for the process. The model data provided for comparison may be one or more inputted values, or one or more calculated values. According to a particularly preferred embodiment, the model data compared to the actual data may be a calculated value, based on inputted data, that is comparable to the actual data. For example, a model time, tons or run length may be provided that will be compared to the actual time, tons or run length.  
     [0154] According to various alternative embodiments, other processes or data may be provided, including user defined processes, grinding processes, second mixing processes, rolling processes, flaking processes, etc. (e.g., see FIGS.  28  to  32 ).  
     [0155] 7. Actual Data  
     [0156] According to one exemplary embodiment, the actual data for the processes may be recorded manually throughout the process. For example, a worker conducting a housekeeping process or portion of a process (e.g., sweeping an area) may provide a start time for sweeping an area, and an end time for sweeping the area. Alternatively, the worker may provide an elapsed time. According to one exemplary embodiment, actual data may be recorded manually (e.g., on paper records, spreadsheets, etc.) and then later entered into system  10 . Shown in FIG. 25 is a particularly preferred embodiment of a form which may be provided to employees in order to record and/or track times, costs, etc. with the various processes.  
     [0157] In a particularly preferred embodiment, actual data is entered after each production day. In an alternative embodiment, actual data may be entered directly into the system by the worker at a variety of locations such as terminals in communication with the system. In another alternative embodiment, the system may be coupled to equipment in the production facility via direct connections, wireless connections, and/or a communications network. The equipment may supply actual data about the process from the machines to the system, so that no (or less) manual entry of data would have to occur.  
     [0158] According to a particularly preferred embodiment shown in FIGS. 23 and 24, actual data may be entered or provided in a “Production Data” screen  270 . Actual data relevant to various processes may be provided via an interface having actual process data fields. For example, FIELD 1 in FIG. 1 allows for entry of the actual tons of product that have been processed in the interplant process. Furthermore, FIELD 1 allows for entry of a run length for the interplant process. Furthermore, FIELD 1 allows for entry of time associated with the interplant process. Additional fields for actual data are provided for various process and data fields (see FIG. 23). As shown, actual data is entered at a process level (e.g., time, tons and run-length). Alternatively, actual data may be provided for each step or sub-process of the process (e.g., mirroring the model data fields provided for each process). Shown in FIG. 24 is a particularly preferred embodiment of an interface  280  which allows for the entry of data relating to contract labor processes, or processes which have utilized a contract vendor.  
     [0159] 8. Analysis—Comparison of Model Data and Actual Data  
     [0160] According to various exemplary embodiments, various types, levels and quality of analysis may be conducted on the model data and the actual data.  
     [0161] Analysis may be done in order to optimize operational efficiency, production efficiency, costs, etc.  
     [0162] Shown in FIG. 3 is an exemplary process of analyzing model data  40  and/or actual data  50 . Actual data  50  and model data  40  for various processes, facilities, etc. may be compared. Model data  40  may present a base line or metric to measure, analyze or assess actual data  50 . According to the particularly preferred embodiment comparing actual data  50  and model data  40  comprises identifying and/or calculating a difference (e.g., subtraction, comparison, etc.) between actual data  50  and model data  40 .  
     [0163] According to another particularly preferred embodiment an efficiency may be calculated based on actual data  50  and model data  40 . For example, an efficiency may be actual data  50  divided by model data  40  or vice versa. Efficiencies be calculated on a cost per ton, amount of excess cost, time efficiency, etc.  
     [0164] According to a particularly preferred embodiment, the model data fields which allow for user entry are manipulated and calculated into model values that may be compared to the actual data fields. For example, in a housekeeping process, model housekeeping data may be generated from the data entry fields provided for comparison to the actual data. The model housekeeping data may be in a form that allows for direct comparison to the actual data. For example, one or more or all of the data entry fields may be used to create an overall model housekeeping value (e.g., a sum of the hours needed to complete all housekeeping processes or steps shown in FIG. 7). The overall model housekeeping value may then be directly compared with the actual data. Similar overall model values for the various processes may be generated for comparison to the actual data shown in FIG. 23 (e.g., hours, tons involved in process, run length, etc).  
     [0165] System  10  advantageously provides information regarding the operation and production of a facility which may be used to improve aspects of operation. For example, system  10  may provide reports summarizing various actual processes and how they compare to model processes. These reports may be provided at any level of detail (e.g., at a housekeeping process level, at a certain sweeping process level, etc. at a plant level, region level). The reports may be used to identify areas which may not be operating as expected, bottlenecks, problem areas, areas which need improvement, that are below a predetermined level or that are above a predetermined level. The reports assist in comparing model or ideal values to actual values in areas relating to productivity, maintenance, supplies, energy, labor, consumption, etc.  
     [0166] Efficiency may be reviewed daily, weekly, monthly, etc. Trends may be identified in various processes. For example, if efficiency trends downward, that process may be investigated to identify a problem. The problem may be equipment (e.g., improper design, not used to full capacity, etc.), personnel (e.g. too many people for a production run, process, etc.), procedures or process (e.g., late orders, wait on formulas, changes in schedule, flushing, etc.) or other factors.  
     [0167] Reports provide information to identify a problem or to localize an area of improvement, and also allows for corrective action to be taken. Alternatively, system  10  may be configured to respond based on the comparison of the actual data to the model data. Reports may also provide productivity measurement (i.e., a measurement of the labor and process efficiency of total plant and/or by process).  
     [0168] System  10  advantageously allows for “what-if” modeling of the facility, providing expected results or changes when altering the operating parameters without having to actually alter the operating parameters. For example, data can be changed “on-the-screen” and the results of those changes can be presented for consideration and/or implementation. For example, the average run length for mixing from first weight to a second weight and the results of this change (e.g. a cost savings, a cost increase, etc.) will be presented. Such results may then be useful for scheduling (i.e. if increasing the average run length results in a cost savings) more personnel, more runs of longer length, etc. may be scheduled.  
     [0169] Additionally, the incremental cost to produce additional product may be determined. For example, by increasing production of bulk pellets by 1000 tons, only variable costs may change. The reports (e.g., MM1, MM2, MM3 reports) provide data which illustrates the differences between before and after changes.  
     [0170] Additionally, cost effects of various labor and wages cost may be varied to illustrate the financial impact over a period of time, and showing the overall cost of product produced. For example, consideration may be given to buying new equipment (e.g. a new packer machine). A scale rate may be 10 bags/min.; a new packer machine may have a scale rate of 20 bags/min. The machine may cost $50,000. Scale rates may be adjusted and the report shows that the effect as being a lower cost per ton. Based on output, a return-on-investment may then be calculated.  
     [0171] System  10  also advantageously allows for budgeting and cost allocation. For example, historical data may be analyzed to predict future expenditures. System  10  may also allow for cost monitoring, including cost monitoring to be done at relatively high intervals, including daily and/or monthly. Cost monitoring may be conducted at the facility level, process level, sub-process level, etc.  
     [0172] System  10  also advantageously provides for capacity determination to assist with present and future planning, utility needs and individual process capacities. Appropriate staffing or crewing may also be determined using system  10 . A project may be properly staffed based on various production amounts, product mix changes, etc.  
     [0173] For example, an estimate of tons of product will be produced in the next month may be provided. (The estimate may be from a budget for the present year and adjusted for other factors, such as marketing, manager predictions, etc. The estimated tons of product for each operation at the plant may be adjusted. Estimating production for each operation may then be done. For example, if pelleting comprises 50% our production, and assuming the estimated tons of product for the next month is known, the amount of pelleting tons will be estimated. The number of hours to produce may then be calculated (e.g. estimated tons divided by adjusted tons/man-hour). Using the hours required, the number of employees needed for a production may be calculated (e.g., employees required=Total hours/8 hr per worker per day/work days to complete operation).  
     [0174] 9. Reporting  
     [0175] According to an exemplary embodiment, system  10  may generate one or more reports containing analysis, summaries, data, etc. which may be used in reviewing facility  18 .  
     [0176] As shown in FIG. 26, a reporting feature may be accessed through a menu item  326  and/or by other operations and/or commands.  
     [0177] In a particularly preferred embodiment, a variety of reports may be provided which contain summary statistics for actual mill, production mix and labor hours, various types of product as a percent of sales (e.g., bulk sales as a percent of total sales, etc.). Further, reports summarizing costs per day for a particular facility may be generated. A report summarizing model facts and parameters may also be generated.  
     [0178] In an exemplary embodiment, any of a variety of reports may be generated, including but not limited to production summary reports, model summary reports, estimated actual plant expenses and estimated model expenses. An exemplary production summary report may provide information relating to actual production statistics. The production statistics may be presented on a daily basis or on a monthly (cumulative) basis or alternatively may be provided on other desired intervals. The model summary report may include information, assumptions, and/or parameters relating to the model and on which the model is based. Further, the model summary report may alternatively include a report on different models, and/or include details of multiple models. The estimate of actual and model plant expenses report may be used to detail estimated actual expenses based on data that is input from the production process during a given period of time (e.g., one day, 30 days, etc.) as well as estimated adjusted model expenses which are representative of the expenses for the operation of the model production facility. Further still, a history report may be accessed to provide historical data and trends for the facility. In an exemplary embodiment, such information may be communicated by tables, charts, graphs, numerical listings, etc.  
     [0179] Other reports which may be accessed in the systems described above include but are not limited to reports providing information from different plants at different locations. Such reports provide simplified comparison of the performance of various plants at different locales. Also, a year-to-date report may be accessed and/or generated at anytime providing up to date information of the facility and up to date comparisons of the facility with the model from a year-to-date perspective. Reports such as this include a world class standing report, which may include information relating to management criteria and goals compared with actual facility numbers. A plant operations report may also be provided for detailing plant and model comparison in various geographic categories. Further still, reports for any particular facility and/or for all facilities may be generated, including but not limited to monthly productivity summaries, year-to-date productivity summaries, cost structure summaries, and the like.  
     [0180] Reports representative of some of the above are provided in Appendices A to O. The appendices provided are representative of those possible and/or available and should not be seen as limiting. The reports provided include a null data set, as information in the reports is dependent entirely on the facility and therefore would not serve to provide instructive information relating to the systems and methods described.  
     [0181] In an exemplary embodiment, the reports may be accessed and/or generated from a server that is coupled to a communications network. Such functionality allows management at any location to access reports needed to make managing decisions about the facilities. Also, such a reporting system allows management at a centralized location to access reports relating to facilities that may be located worldwide. Reports may also be generated which include data from various divisions even if the division of interest has multiple production facilities.  
     [0182] 10. Consulting Services  
     [0183] According to one exemplary embodiment shown in FIG. 1, system  10  comprises a server  12  containing a database  15  which may store model data, actual data, programs, etc. One or more facilities may access database  15 . According to a particularly preferred embodiment, the one or more facilities may be related (e.g., operate under the management and control of a single entity such as a corporation, subsidiaries, parent companies, etc.).  
     [0184] According to an alternative embodiment, system  10  may be used to provide consulting services to facilities not associated or affiliated with itself.  
     [0185] For example, companies which desire to improve operations, production, cost, and other parameters may use, hire, retain or otherwise utilize consulting services. According to a particularly preferred embodiment, actual data may be provided to the consultant and then analyzed by the systems and methods described. Alternatively, the consultant may install a system for use by the unrelated company.  
     [0186] As shown in FIG. 1, system  10  may comprise a server  12  containing a first database  15  and a second database  25 . First database  15  may be used for model data, actual data, program data, etc. of facilities operating within the company. Second database  25  may be used for model data, actual data, program data, etc. of facilities outside independent of the company (e.g., companies which have hired or retained the company for consulting services.).  
     [0187] This configuration advantageously separates the consulting data and the company data, providing an additional level of security, etc. However, other configurations may be used to similarly provide consulting services using the system described.  
     [0188] 11. Alternative Embodiments  
     [0189] In an alternative embodiment, the systems and methods may be used to streamline and/or enhance the budgeting process. For example, in conventional systems, future cost projections may not be automated but are based on historical information contained in the system database. However, providing suitable software code that provides access to the system database and uses information that would typically appear on multiple screens, would enable the information to be automatically accessed and an algorithm applied to make budget projections including extrapolated information and projections, such as for energy costs and the like.  
     [0190] In another alternative embodiment, the systems and methods may include screens including alternative equipment (e.g. robotic stackers, fat coaters, etc.) and/or may be reformatted for data relating to other equipment, including but not limited to robotic equipment like stackers, stacking bags, etc.  
     [0191] In yet another alternative embodiment, the system may be coupled to the equipment in the production facility via direct connections and/or a communications network. The equipment would supply data about the production process directly from the machines to the system, so that no (or less) manual entry of data would have to occur. In yet still another alternative embodiment, a system that is in communication with the equipment, may also include an expert system, or other type of controls and/or intelligence to make decisions that are based on comparisons made using the system and are then fed back to the plant itself to make adjustments to machine and/or human parameters. Further, data collection may occur in real-time and it may then be possible to view plant efficiencies in real-time or near real-time. Data links may also be provided to logistics systems such as real time logistics systems, ingredient inventory and shipment systems, etc. for receiving, shipping, and production data inputs. Also, the database accessed by the system may include a database of equipment capacities and may be used to analyze equipment utilization.  
     [0192] In yet still other alternative embodiments, the system may be adapted to display graphs and charts of certain and/or specified parameters. Further still, the system may be configured to adapt to other industries so that it may be used for consulting and/or in different production contexts including, but not limited to food production facilities. Such adaptations include providing new fields and the renaming of certain fields within the program as well as providing customized reports for the particular facility. Yet further still, an alternative embodiment may include product quality factor information as well as information relating to other specialized processes.  
     [0193] And yet still further, alternative embodiments may apply to numerous enhancements which utilize a variety of defined inputs and/or input screens, such as but not limited to ingredient and/or feed processing screens, sanitized feed processing inputs, rationing system information used at the bulk load out area, micro auto batching system information (e.g., direct link information from the processing facility), post grind system after batching information (e.g., information gathered after the feed has been mixed and ground), aqua processing information (e.g., information relating to processes involving the introduction of liquids), as well as other information.  
     [0194] In yet still further alternative embodiments, the systems and methods may be used to compare information relating to the quality of the product when compared with an idealized or target quality. Further, the systems and methods may be applied to applications in other industries, including but not limited to the food processing industry and flour milling operations. Additionally, connection to electricity or other energy software which estimates cost and usage may be used to determine usage patterns and control savings. It may also be beneficial to provide reports that may be separated for different divisions and geographic locations. Further, alternative embodiments may include functionality which allows a variety of types of structured reporting that may be simply customized by a user without program modification.  
     [0195] And yet still further, another alternative embodiment is shown in FIG. 27. Facilities management system  410  may analyze or assess data at a process level (e.g., multiple steps of a process are converted into data that can be compared to typical, measured production data (e.g., tons, time, run-length, etc. of the process as a whole). Alternatively, model data for the various steps of the process (e.g., data fields shown in FIGS.  6  to  22 ) may be compared to actual data for the various steps of the process (e.g., the actual steps of the process may be measured and compared to the model data).  
     [0196] While the embodiments illustrated in the figures and described above are presently preferred, it should be understood that these embodiments are offered by way of example only. While exemplary embodiments describe the invention in the context of facilities management, the invention may extend to other areas of production. The invention is not limited to a particular embodiment, but extends to various modifications, combinations, and permutations that nevertheless fall within the scope and spirit of the appended claims.