Abstract:
An energy-saving optimizing program works closely with conventional process simulation programs by applying energy saving paradigms embodied in script files that may review data inherent in the simulation program to identify possible energy-saving opportunities. When the script files identify a possible energy savings, they may interact with the simulation program to evaluate the savings potential and present the same to a user. In this way opportunistic energy savings may be provided even for processes that resist close form global optimization.

Description:
BACKGROUND OF THE INVENTION 
     The present invention relates to computerized analysis of control processes and in particular to a program working with computerized process simulations to identify energy savings. 
     The manufacture of many products requires the execution of complex processes typically under automated control. Such processes, including diverse processes such as oil refining, paper manufacture, synthesis of pharmaceuticals, electrical energy generation and the like, may be defined by a set of input and output material streams and input and output energy flows into and out of the process. The process may include multiple unit operations each with corresponding material streams and energy flows. 
     The complexity of many commercially important processes has led to the development of sophisticated simulation tools in which the streams and flows are characterized numerically and the operations on the streams modeled mathematically so that the proper operation of the process may be verified or modified before actual construction or modification. Commercial products for such simulation include, for example, AspenPlus, a process simulation software package commercially available from AspenTech of Burlington, Mass. and a similar product line commercially available from Intelligen Inc. of Scotch Plains N.J. as well as products manufactured by Pavilion Technologies of Austin, Tex. 
     While complex processes may be accurately simulated, optimization of the process for particular goals, for example, energy savings and cost is not inherent in the ability to simulate the process. Even when a simulation can reveal how a cost and energy savings may change with changes in the defined streams and flows, particularly for complex processes, the ability to simulate the process alone does not necessarily indicate the type or amount of modifications necessary to optimize an arbitrary parameter. For example, an accurate simulation of a process combining two chemicals in chemical reaction may indicate how the resulting product will change with changes in the input streams of the chemicals but will not necessarily suggest, for example, the introduction of an enzyme that may improve the reaction efficiency or how to change input streams to reduce energy usage. Even trial and error changes to one stream or flow to indicate how it changes energy may not reveal the correct setting for the stream or flow for global energy reduction in the process because of the problem of local minima. 
     Experts in process control can often identify improvements in a process&#39;s efficiency on a case-by-case basis, but software tools to assist non-experts in process optimization or to augment the abilities of experts remain elusive because of the complexity of the problem and the case-by-case nature of the solutions. 
     SUMMARY OF THE INVENTION 
     The present inventor has recognized that although complex processes often resist optimization by comprehensive automatic procedures, they may nevertheless be improved by applying expert-known patterns of optimization that tend to be applicable to a wide range of processes. The inventor has further recognized that these patterns may be automatically identified based on information generally held in the data tables of process simulation tools. Using existing or supplemental rules on changing process variables in the data of the process simulation tool, the identified patterns may be used to guide changes in the process variables to effect significant improvements in energy usage of a process. 
     In one embodiment, the patterns of optimization may be divided into the categories of transformative, reflexive, integrative, or cyclic, related generally to the scope of the energy-saving pattern with respect to the process. By sequentially applying the patterns in the order of these categories, increased energy improvement may be obtained. 
     Specifically then, in one embodiment, the invention provides a method for reducing energy consumption in manufacturing processes comprising the steps of generating a computer simulation of the manufacturing process defining material input and output streams and energy input and output flows and providing computer readable rules associated with the computer simulation defining constraints on changes in at least one of the material input and output streams and energy input and output flows. An optimizing program is executed on electronic computer to apply a series of scripts to data of the material input and output streams to identify at least one predefined pattern of energy savings applicable to the manufacturing process. Based on the identified predefined pattern of energy savings, the computer program provides variations to at least one of the input and output streams and energy input and output flows, as constrained by the computer readable rules, to the computer simulation to provide a simulation output quantifying a change in energy usage. 
     It is thus one object of at least one embodiment of the invention to provide a software tool for helping identify energy efficiencies in complex processes that are resistant to purely mathematical global optimization. 
     The manufacturing process may include multiple stages and the scripts may be organized with respect to whether the predetermined pattern of energy savings is transformative, reflexive, integrative, or cyclic, in which transformative patterns of energy savings change proportions of mass or energy used in a stage; reflexive patterns of energy savings change reuse of mass or energy in a stage; integrative patterns of energy savings change reuse of mass or energy between different stages; and cyclic patterns of energy savings change amounts of mass or energy that have been transformed or rejuvenated. 
     It is thus one object of at least one embodiment of the invention to provide a methodology for identifying patterns of energy savings that may be locally applied. 
     The method sequentially applies, first, scripts related to transformative patterns of energy savings, second, scripts related to reflexive patterns of energy savings, third, scripts related to integrative patterns of energy savings, and fourth, scripts related to cyclic patterns of energy savings. 
     It is thus one object of at least one embodiment of the invention to develop an order of applying local energy-saving patterns in a way that will best approximate optimized global energy savings. 
     The method may provide multiple simulated outputs for different scripts to a user for selection by the user of variations in material input and output streams or energy input and output flows related to a subset of the scripts before repeating step (c) with those variations selected. 
     It is thus one object of at least one embodiment of the invention to accept user input for improved optimization wherein the user may provide for insight not fully captured by the data of the simulation program. 
     The defined material input and output streams may include material identifications and characterizations of a role of the identified materials and the scripts may identify applicable patterns of energy savings based on material identifications and characterizations of the role of the materials. For example, the role of the materials may include materials identified as components of an end product and materials identified as incidental to the end product. More specifically, for example, some materials may be identified as raw materials and some identified as solvents. 
     It is thus one object of at least one embodiment of the invention to provide a method of identifying patterns for energy savings by automatic or semiautomatic review of the data in a pre-existing process simulation. 
     It is thus one object of at least one embodiment of the invention to 
     At least one predefined pattern of energy savings may be selected from the group consisting of dilution reduction, catalyst introduction, heat recovery, membrane separation, and material reuse; material transformation. 
     It is thus one object of at least one embodiment of the invention to provide compact and easily understood patterns of energy savings that may be reviewed and accepted by the user 
     The method may further include the step of providing a simulation output quantifying a change in cost. 
     It is thus an object of at least one embodiment of the invention to constrain energy savings optimization to situations having economic reality. 
     These particular features and advantages may apply to only some embodiments falling within the claims and thus do not define the scope of the invention. 
    
    
     
       BRIEF DESCRIPTION OF THE FIGURES 
         FIG. 1  is a simplified diagram of a unit operation (possibly a portion of a multi-step process) that may be optimized by the present invention, showing input and output material streams and energy flows; 
         FIG. 2  is a block diagram of an electronic computer suitable for execution of an optimizing program implementing the present invention and a simulation program from the prior art; 
         FIG. 3  is a representation of an optimizing and simulation program held in the computer of  FIG. 2  and their related data structures for implementing the present invention; 
         FIG. 4  is a simplified representation of the data table of  FIG. 3  used to hold process variables for a the simulation program; 
         FIG. 5  is a data flow diagram showing application of savings-pattern scripts of the present invention on the data table of  FIG. 4  to identify and propose patterns of energy savings and to modify the process variables of the data table to provide comparative energy savings data; 
         FIG. 6  is a hierarchical diagram showing grouping of the savings-pattern scripts of  FIG. 5  into categories of transformative, reflexive, integrative, or cyclic for sequential consideration; 
         FIG. 7  is a diagram showing the process of  FIG. 1  in the context of a larger process with an example transformative change; 
         FIG. 8  is a figure similar to that of  FIG. 7  showing example reflexive changes; 
         FIG. 9  is a figure similar to  FIGS. 7 and 8  showing example integrative changes; 
         FIG. 10  is a figure similar to  FIGS. 7-9  showing example cyclic changes; and 
         FIG. 11  is a simplified screen diagram showing a mechanism by which a user may select proposed optimizations from the present invention in between each group of changes per the hierarchy of  FIG. 6  and the display of absolute or differential energy and dollar costs. 
     
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT 
     Referring now to  FIG. 1 , an example unit operation  10  of an industrial process may receive inputs  12  comprised of input materials  14  being, for example, feedstock chemicals A and B that will be consumed in the unit operation  10  and a solvent S serving as an intermediary material. The unit operation  10  may also receive input energy  16  typically in the form of heat, for example, for an endothermic reaction. 
     Likewise, the unit operation  10  may produce outputs  20 , comprised of output materials  22  including: by-product D, unused feedstock chemicals A and B, solvent S and the desired product C. Output energy  18 , typically in the form of waste heat, is also generated. 
     Referring to  FIG. 2 , a process including the unit operation  10  may be simulated on a computer system  30  including a processor  32  communicating with the memory  34 , for example, via a bus structure  36 . The memory  34  may hold a simulation program  38  of the type generally known in the art (and cited above) having associated data files  40  as will be described below. The memory  34  may also hold an optimizing program  42  of the present invention together with its associated data files  44 . 
     The bus structure  36  of the computer system  30  may also allow the processor  32  to communicate with an interface  46  for communicating with human machine interface elements  48  including, for example, a computer monitor  50  and input device  52  providing input and output to a human operator. 
     It will be understood that the computer system  30  may be realized in the components of an industrial control system having, for example, interconnected components of a power supply, controller, I/O modules, and network interface cards, as modules that plug into a common high speed backplane in a rack structure. Such industrial controller are known in the art and include devices manufactured by Rockwell Automation, Inc. for example under the Logix tradename. In this case, either or both of the simulation program  38  and optimizing program  42  of the present invention together with the associated data files may be held and executed by the controller module or another specialized module. 
     Referring now to  FIG. 3 , the data files  40  of the simulation program  38  will generally include a set of models  54  describing physical processes that may be implemented by the unit operation  10 , for example, functions describing the operation chemical reactions, thermodynamic processes, and mechanical actions in processing of the inputs  12  to manufacture the outputs  20 . The models  54  may work closely in conjunction with a stream table  56  describing the above described inputs  12  and outputs  20  together with their initial states, time rates (e.g. flow), costs, etc. The stream table  56  also inferentially describes the interaction of materials and energy in the unit operation  10  through description of streams combining other streams. 
     Generally, the stream table  56  will hold information entered by the user for the purpose of process simulation, the user having knowledge of the unit operation  10 . The stream table  56  will thus capture process data related to a desired operating point for the process which may or may not be optimized for a particular parameter such as energy. The data files  40  may also include a rules table  58  describing rules with respect to the possible changes in the data of the stream table  56 . For example, the rules table  58  may describe ranges of purity or temperature required of materials of the streams or the possible substitution of different materials for materials of the streams. In cases where the simulation program  38  does not explicitly provide for rules table  58 , a comments field of the stream table  56  may be used. Generally the rules of the rules table  58  will be written in a script that may be interpreted by the optimizing program  42 . 
     Referring still to  FIG. 3 , the optimizing program  42  may communicate with the simulation program  38  by reading the rules table  58  reading and writing to the stream table  56  (either directly or through the agency of the simulation program  38 ) and invoking commands to cause simulations in various experimental scenarios using the simulation program  38 . 
     The data files  44  of the optimizing program  42  may include a script file  60  holding energy-saving pattern scripts  76  describing common energy-saving paradigms (as will be discussed below) and scenario file  62  recording changes in the stream table  56  for various simulations that may be run on the simulation program  38  by the optimizing program  42 . 
     Referring now to  FIG. 4 , the stream table  56  may generally define a series of material streams  64  and energy flows  66  in different rows of the stream table  56 . Each stream or flow may be given an identifier  67  and a full description  71 . In the case of material streams  64  the description  71  may include, for example, chemical composition purity and the like. The role of stream or flow is also given a role description  72  deriving from the purpose of the material of the stream or flow in the unit operation  10 . Thus, for example, a material such as ethanol could have the role of “raw material” when used in a chemical reaction to produce a product or the role of a “solvent” when used for holding reactants that produce the product, depending on its intended use. Likewise energy, for example, electrical energy, could have a role of “electroplating” or “heating”, a distinction which will be important with respect possible substitutions of other energy sources. Other additional information  74  related to the streams may be provided including flow rate, initial temperature, price, molecular weight, viscosity, density and the like. The particular information will vary according to the simulation program  38 . 
     Referring now to  FIG. 5 , the optimizing program  42  may sequentially execute a series of savings-pattern scripts  76  held in the script file  60 , each savings-pattern scripts  76  embodying an empirically derived paradigm for energy savings, for example, changing dilution ratios to reduce solvent costs in heat and material. Each savings-pattern script  76 , when executed, causes the optimizing program  42  to scan through the stream table  56  to identify streams and their relationships that match the paradigm of the energy savings. Thus, for example, if the script  76  relates to changing dilution ratios, the script  76  will look for streams in the stream table  56  related to solvents and their solutes. 
     The savings-pattern scripts  76  will generally be prepared on an ad hoc basis and will not include every possible optimization of all possible processes. Using savings-pattern scripts  76  avoids the problems of attempting to construct a global optimization process that requires consideration of every process variable. 
     When each savings-pattern script  76  has been scanned, only a subset  78  of scripts  76  will be identified as applicable to the unit operation  10 . 
     Each of the selected subset  78  of savings-pattern scripts  76  will then generate a new set of input stream data  80  that will be substituted for existing stream data  82  from the stream table  56  and applied to a simulation engine  84 , being part of the simulation program  38 , to produce new output stream values  86 . The new set of input stream data  80  and new output stream values  86  will be stored in the scenario file  62  for later consideration by the user. Thus, for example, if the savings-pattern scripts  76  relates to changing dilution values, new dilution values that may form a new set of input stream data  82  to be substituted for the existing stream data  82  will be run on the simulation program  38 , and the new output stream value provided by that simulation stored in the scenario file  62 . 
     The data of the scenario file  62  may be provided to an output formatter  68  that may also review the stream table  56  to collect additional data used to prepare an output table  70  displaying data from the scenario file  62  together with a column indicating changes in energy or dollars caused by application of the different savings-pattern scripts  76  and thus the relative improvements in the unit operation  10  attributable to each savings-pattern scripts  76 . 
     Referring now to  FIG. 6 , each of the savings-pattern scripts  76  may be classified according to the scope of its changes to the unit operation  10  and the associated operations that comprise the process. A first categorization is that of transformative paradigms  90 . Generally transformative paradigms for energy savings change proportions of mass or energy used in a single given unit operation of the process. A second categorization is that of reflexive paradigms  92 . Generally, reflexive paradigms of energy savings change reuse of mass or energy in a single given unit operation  10 . A third categorization is that of integrative paradigms  94 . Integrative paradigms of energy savings change reuse of mass or energy between different unit operations  10 , being part of a larger process. Finally, a fourth categorization is that of cyclic paradigms  96 . Cyclic paradigms of energy savings change amounts of mass or energy that have been transformed or rejuvenated in some manner. 
     The optimizing program  42 , in applying the savings-pattern scripts  76 , applies them in this order of: (1) transformative, (2) reflexive, (3) integrative, and (4) cyclic repeating the steps of reviewing the stream table  56  to find potential energy-saving paradigms that match savings-pattern scripts  76  for that category as indicated by process block  100  and then for those applicable savings-pattern scripts  76 , simulating an alternative scenario for improved energy usage as indicated by process block  102 , and finally, allowing the user or automated program to select among proposed energy-saving paradigms as indicated by process block  104 . 
     Only after all of the savings-pattern scripts  76  of a single grouping (e.g. transitive, reflexive, integrative, and cyclic) have been applied, per process box  100 - 104 , are the steps repeated for the next grouping. By dividing the savings-pattern scripts  76  thusly and applying them sequentially, problems of conflicting savings-pattern scripts  76  are reduced, for example, where one paradigm undoes the benefits of other paradigms or blocks the use of superior paradigms. 
     Referring now to  FIGS. 1 and 7 , an example of this process may be illustrated in an industrial process  110  comprised of three unit processes  10   a - 10   c  including unit operation  10   a  (described above) which combines chemicals A and B in order to react to produce compound C. The reaction takes place in a solvent S, and reaction of A and B to produce C is endothermic, which means that heat in the form of energy input E must be input for the reaction to occur. The reaction is not 100% efficient, so there is some residual A and B left in solution. Also, an unwanted byproduct D is produced. 
     The stream table  56  of the process simulation program  38  for the unit operation  10   a , as simplified, may be represented by the following Table I: 
     
       
         
               
               
               
             
               
               
               
             
           
               
                 TABLE I 
               
               
                   
               
               
                 Item 
                 Input 
                 Output 
               
               
                   
               
             
             
               
                   
               
             
          
           
               
                 A 
                 100 
                 8 
               
               
                 B 
                 100 
                 8 
               
               
                 C 
                 0 
                 160 
               
               
                 D 
                 0 
                 24 
               
               
                 S 
                 1000 
                 1000 
               
               
                 E 
                 100 
                 92 
               
               
                   
               
             
          
         
       
     
     Using this and other data in the stream table  56  the output formatter  68  may calculate the mass and energy efficiency and overall process efficiency (OPE). 
     
       
         
           
             
                 
             
             ⁢ 
             
               
                 Mass 
                 ⁢ 
                 
                     
                 
                 ⁢ 
                 Efficiency 
                 ⁢ 
                 
                   : 
                 
                 ⁢ 
                 
                     
                 
                 ⁢ 
                 
                   
                     Mass 
                     ⁢ 
                     
                         
                     
                     ⁢ 
                     of 
                     ⁢ 
                     
                         
                     
                     ⁢ 
                     C 
                   
                   
                     MassofA 
                     + 
                     B 
                     + 
                     C 
                   
                 
               
               = 
               
                 
                   160 
                   
                     100 
                     + 
                     100 
                     + 
                     1000 
                   
                 
                 = 
                 
                   13 
                   ⁢ 
                   % 
                 
               
             
           
         
       
       
         
           
             
                 
             
             ⁢ 
             
               
                 Energy 
                 ⁢ 
                 
                     
                 
                 ⁢ 
                 Efficiency 
                 ⁢ 
                 
                   : 
                 
                 ⁢ 
                 
                     
                 
                 ⁢ 
                 
                   
                     Change 
                     ⁢ 
                     
                         
                     
                     ⁢ 
                     in 
                     ⁢ 
                     
                         
                     
                     ⁢ 
                     Gibbs 
                     ⁢ 
                     
                         
                     
                     ⁢ 
                     Free 
                     ⁢ 
                     
                         
                     
                     ⁢ 
                     Energy 
                     ⁢ 
                     
                         
                     
                     ⁢ 
                     of 
                     ⁢ 
                     
                         
                     
                     ⁢ 
                     C 
                   
                   
                     Total 
                     ⁢ 
                     
                         
                     
                     ⁢ 
                     Input 
                     ⁢ 
                     
                         
                     
                     ⁢ 
                     Energy 
                   
                 
               
               = 
               
                 
                   3 
                   10 
                 
                 = 
                 
                   3 
                   ⁢ 
                   % 
                 
               
             
           
         
       
       
         
           
             
               Overall 
               ⁢ 
               
                   
               
               ⁢ 
               Process 
               ⁢ 
               
                   
               
               ⁢ 
               Efficiency 
               ⁢ 
               
                 : 
               
               ⁢ 
               
                   
               
               ⁢ 
               Mass 
               ⁢ 
               
                   
               
               ⁢ 
               Efficiency 
               × 
               Energy 
               ⁢ 
               
                   
               
               ⁢ 
               Efficiency 
             
             = 
             
               
                 13 
                 ⁢ 
                 % 
                 × 
                 3 
                 ⁢ 
                 % 
               
               = 
               
                 0.39 
                 ⁢ 
                 % 
               
             
           
         
       
     
     In this example, the savings-pattern scripts  76  identified two possible paths of improved energy efficiency: adding a catalyst to react products A and B and changing the dilution of the products A and B in solvent S. The script provides a simple hill climb optimization for each of these energy-saving paradigms based on the identified materials of the stream tables as described above. The hill climb is effected by trying different inputs and running the simulation to provide different outputs. The output formatter  68  then analyzes the mass balance from the stream tables to recalculate the energy efficiency. The models have estimates of the cost of implements these methods, so an automated ROI calculation can be made. 
     A simplified output table  70  from the output formatter  68  thus has the following form: 
     
       
         
               
               
               
               
               
               
               
             
               
               
               
               
               
               
               
             
           
               
                 TABLE II 
               
               
                   
               
               
                   
                 Original 
                 Original 
                   
                 Revised 
                 Revised 
                 Est. Energy 
               
               
                 Item 
                 Input 
                 Output 
                 Paradigm 
                 Input 
                 Output 
                 Savings ROI 
               
               
                   
               
             
             
               
                   
               
             
          
           
               
                 A 
                 100 
                 8 
                 Enzyme 
                 100 
                 1 
                 −5% 
               
               
                   
                   
                   
                 Catalysis 
               
               
                 B 
                 100 
                 8 
                 Enzyme 
                 100 
                 1 
                 −5% 
               
               
                   
                   
                   
                 Catalysis 
               
               
                 C 
                 0 
                 160 
                 Enzyme 
                 0 
                 180 
                 −5% 
               
               
                   
                   
                   
                 Catalysis 
               
               
                 D 
                 0 
                 24 
                 Enzyme 
                 0 
                 4 
                 −5% 
               
               
                   
                   
                   
                 Catalysis 
               
               
                 S 
                 1000 
                 1000 
                 Dilution 
                 800 
                 800 
                 300%  
               
               
                   
                   
                   
                 Reduction 
               
               
                 E 
                 100 
                 92 
                 Dilution 
                 80 
                 73 
                 200%  
               
               
                   
                   
                   
                 Reduction 
               
               
                   
               
             
          
         
       
     
     Referring now momentarily to  FIG. 11 , the output table  70  may include voting buttons  112  allowing the user to select which particular ones (or all) of these paradigms to implement. In this case, the user would likely select the dilution reduction and not the enzyme catalysts, as the latter produces a negative return on investment (for example as may it result from a high expense of the catalyst and its relative low effectiveness). Generally, by decreasing the dilution of the materials A and B in solvent S, solvent is saved as well as the cost of heating the solvent. This is largely a rule of thumb improvement that has been embodied in a savings-pattern script  76 . In addition, the output table  70  may be associated with a display  73  indicating cumulative energy savings, cost savings or return on investment. In this respect, the present program may also be used to optimize costs that are separate from energy, for example savings in material costs which may be aggregated with energy savings costs or treated individually. 
     Alternatively the particular paradigms to implement may be selected automatically based on ROI. 
     Once the transformative savings are calculated and selected, they are assumed as a starting condition for the application of the reflexive paradigms. As noted above, reflexive savings will be those that reuse a waste stream from the unit operation  10  back into the unit operation  10 . For batch operations, this means reusing something from the prior batch into the current batch. 
     In this case, the savings-pattern scripts  76  may identify the possibility of membrane separation of output streams A and B for reuse and solvent reuse (where output solvent S is returned for use as input solvent S), and heat recovery from the solvent. Solvent reuse is blocked by the rules of the rules table  58  indicating a particular purity of solvent is required or information characterizing the solvent in the stream table  56  or by the user manually vetoing by the operator as indicated in the following Table III: 
     
       
         
               
               
               
               
               
               
               
             
               
               
               
               
               
               
               
             
           
               
                 TABLE III 
               
               
                   
               
               
                   
                   
                   
                   
                   
                   
                 Est. 
               
               
                   
                   
                   
                   
                   
                   
                 Energy 
               
               
                   
                 Original 
                 Original 
                   
                 Revised 
                 Revised 
                 Savings 
               
               
                 Item 
                 Input 
                 Output 
                 Model 
                 Input 
                 Output 
                 ROI 
               
               
                   
               
             
             
               
                   
               
             
          
           
               
                 A 
                 100 
                 8 
                 Membrane 
                 94 
                 6 
                 30% 
               
               
                   
                   
                   
                 Separation 
               
               
                 B 
                 100 
                 8 
                 Membrane 
                 94 
                 6 
                 30% 
               
               
                   
                   
                   
                 Separation 
               
               
                 C 
                 0 
                 160 
                 No Action 
                 0 
                 160 
                 NA 
               
               
                 D 
                 0 
                 24 
                 No Action 
                 0 
                 24 
                 NA 
               
               
                 S 
                 800 
                 800 
                 No Action, 
                 800 
                 800 
                 NA 
               
               
                   
                   
                   
                 Solvent 
               
               
                   
                   
                   
                 Contaminated. 
               
               
                 E 
                 80 
                 73 
                 Heat 
                 10 
                 65 
                 200%  
               
               
                   
                   
                   
                 Recovery 
               
               
                   
                   
                   
                 from Solvent 
               
               
                   
               
             
          
         
       
     
     Again, the user may select particular paradigms to proceed with. The optimizing program  42  then considers the savings-pattern scripts  76  associated with integrative savings. These savings-pattern scripts  76  may compare the waste streams with resource input requirements of other unit operations in the process. In this case, the savings-pattern scripts  76  may identify the reuse of solvent in later unit operations  10   b - c  and additional energy reuse; however the latter is precluded by the earlier application of the reflexive savings. Generally, the ordering of the application of the savings-pattern scripts  76  according to  FIG. 6  is believed to ensure that this blockage between the applications of different paradigms only occurs when a superior paradigm blocks and inferior paradigm from the point of view of global energy reduction. 
     At the conclusion of the application of the integrative paradigms, the following output table  70  may be produced per Table IV: 
     
       
         
               
               
               
               
               
               
               
             
               
               
               
               
               
               
               
             
           
               
                 TABLE IV 
               
               
                   
               
               
                   
                   
                   
                   
                   
                   
                 Est. 
               
               
                   
                   
                   
                   
                   
                   
                 energy 
               
               
                   
                 Original 
                 Original 
                   
                 Revised 
                 Revised 
                 savings 
               
               
                 Item 
                 Input 
                 Output 
                 Model 
                 Input 
                 Output 
                 ROI 
               
               
                   
               
             
             
               
                   
               
             
          
           
               
                 A 
                 94 
                 6 
                 No Action 
                 94 
                 6 
                 NA 
               
               
                 B 
                 94 
                 6 
                 No Action 
                 94 
                 6 
                 NA 
               
               
                 C 
                 0 
                 160 
                 No Action 
                 0 
                 160 
                 NA 
               
               
                 D 
                 0 
                 24 
                 No Action. 
                 0 
                 24 
                 NA 
               
               
                   
                   
                   
                 No 
               
               
                   
                   
                   
                 other process 
               
               
                   
                   
                   
                 can utilize D 
               
               
                 S 
                 800 
                 800 
                 Reuse 
                 800 
                 800 now 
                 400% 
               
               
                   
                   
                   
                 solvent 
                   
                 categorized 
               
               
                   
                   
                   
                 in other 
                   
                 as 
               
               
                   
                   
                   
                 process 
                   
                 product 
               
               
                   
                   
                   
                   
                   
                 not 
               
               
                   
                   
                   
                   
                   
                 waste 
               
               
                 E 
                 10 
                 65 
                 No Action. 
                 10 
                 65 
                 NA 
               
               
                   
                   
                   
                 Heat already 
               
               
                   
                   
                   
                 recovered 
               
               
                   
               
             
          
         
       
     
     Note that by reusing the solvent, the solvent is characterized differently thus affecting the energy savings ROI computed by the output formatter  68 . 
     The optimizing program  42  analyzes the stream table  56  and determined that the waste solvent could be used in another unit operation where the contamination of the solvent by D is not of a concern according to the rule table  58 , so the solvent is not wasted any longer in the unit operation  10   a , but represents a product, so it is re-categorized. At this point in the process there is no reuse for byproduct D. 
     The optimizing program  42  then proceeds to the final step of cyclic savings-pattern scripts  76 . In this case, two savings-pattern scripts  76  identify the ability to sell product D (thus re-characterizing it) or separate and reverse react D to create source materials A and B. The following final output table  70  is generated as Table V: 
     
       
         
               
               
               
               
               
               
               
             
               
               
               
               
               
               
               
             
           
               
                 TABLE V 
               
               
                   
               
               
                   
                   
                   
                   
                   
                   
                 Est. 
               
               
                   
                   
                   
                   
                   
                   
                 Energy 
               
               
                   
                 Original 
                 Original 
                   
                 Revised 
                   
                 Savings 
               
               
                 Item 
                 Input 
                 Output 
                 Model 
                 Input 
                 Revised Output 
                 ROI 
               
               
                   
               
             
             
               
                   
               
             
          
           
               
                 A 
                 94 
                 6 
                 No Action 
                 94 
                 6 
                 NA 
               
               
                 B 
                 94 
                 6 
                 No Action 
                 94 
                 6 
                 NA 
               
               
                 C 
                 0 
                 160 
                 No Action 
                 0 
                 160 
                 NA 
               
               
                 D 
                 0 
                 24 
                 Membrane 
                 0 
                 24: Now 
                 −20% 
               
               
                   
                   
                   
                 Separation 
                   
                 categorized as 
               
               
                   
                   
                   
                 and 
                   
                 product 
               
               
                   
                   
                   
                 Sell 
               
               
                 D 
                 0 
                 24 
                 Membrane 
                 0 
                 6. Incomplete 
                   35% 
               
               
                   
                   
                   
                 Separate 
                   
                 reversal. 9A 
               
               
                   
                   
                   
                 reverse 
                   
                 and 9B 
               
               
                   
                   
                   
                 reaction 
                   
                 recovered 
               
               
                   
                   
                   
                 creating 
               
               
                   
                   
                   
                 A &amp; B 
               
               
                 S 
                 800 
                 800 
                 No Action 
                 800 
                 800 now 
                 NA 
               
               
                   
                   
                   
                   
                   
                 categorized as 
               
               
                   
                   
                   
                   
                   
                 product not 
               
               
                   
                   
                   
                   
                   
                 waste 
               
               
                 E 
                 10 
                 65 
                 No 
                 10 
                 65 
                 NA 
               
               
                   
                   
                   
                 Action. 
               
               
                   
               
             
          
         
       
     
     This now completes the application of the savings-pattern scripts  76  and the output formatter  68  may again compute various energy efficiencies to compare the new Overall Process Efficiency with the beginning process. 
     
       
         
           
             
               Mass 
               ⁢ 
               
                   
               
               ⁢ 
               Efficiency 
               ⁢ 
               
                 : 
               
               ⁢ 
               
                   
               
               ⁢ 
               
                 
                   C 
                   + 
                   S 
                 
                 
                   A 
                   + 
                   B 
                   + 
                   S 
                 
               
             
             = 
             
               
                 
                   160 
                   + 
                   800 
                 
                 
                   
                     85 
                     * 
                   
                   + 
                   
                     85 
                     * 
                   
                   + 
                   800 
                 
               
               = 
               
                 98.9 
                 ⁢ 
                 % 
                 ⁢ 
                 
                     
                 
                 ⁢ 
                 
                   ( 
                   
                     as 
                     ⁢ 
                     
                         
                     
                     ⁢ 
                     compared 
                     ⁢ 
                     
                         
                     
                     ⁢ 
                     to 
                     ⁢ 
                     
                         
                     
                     ⁢ 
                     13 
                     ⁢ 
                     % 
                   
                   ) 
                 
               
             
           
         
       
     
     The 85 represents the input now required after recovering unused material and reversing D to yield A and B. 
     
       
         
           
             
               Energy 
               ⁢ 
               
                   
               
               ⁢ 
               Efficiency 
               ⁢ 
               
                 : 
               
               ⁢ 
               
                   
               
               ⁢ 
               
                 
                   Change 
                   ⁢ 
                   
                       
                   
                   ⁢ 
                   in 
                   ⁢ 
                   
                       
                   
                   ⁢ 
                   Gibbs 
                   ⁢ 
                   
                       
                   
                   ⁢ 
                   Free 
                   ⁢ 
                   
                       
                   
                   ⁢ 
                   Energy 
                   ⁢ 
                   
                       
                   
                   ⁢ 
                   of 
                   ⁢ 
                   
                       
                   
                   ⁢ 
                   C 
                 
                 
                   Total 
                   ⁢ 
                   
                       
                   
                   ⁢ 
                   Input 
                   ⁢ 
                   
                       
                   
                   ⁢ 
                   Energy 
                 
               
             
             = 
             
               
                 3 
                 
                   10 
                   * 
                 
               
               = 
               
                 30 
                 ⁢ 
                 % 
                 ⁢ 
                 
                   ( 
                   
                     compared 
                     ⁢ 
                     
                         
                     
                     ⁢ 
                     to 
                     ⁢ 
                     
                         
                     
                     ⁢ 
                     3 
                     ⁢ 
                     % 
                   
                   ) 
                 
               
             
           
         
       
     
     This energy input reflects a steady state situation. There will be an additional loss of 80 over the entire run. This is the amount of energy required to do the first batch. It will not be recovered on the last batch. If 10 batches are planned, then allocating this loss over the 10 batches increases the average input energy to 18, reflecting a Energy Efficiency of 17% which will be used in the final OPE calculation.
 
Overall Process Efficiency=Mass Efficiency×Energy Efficiency=98.9%×17%=16.8% (as compared to 0.39%)
 
     In this simplified example, the optimizing program  42  improves the efficiency of this unit operation by 16.8/0.39=43 times. 
     The above description begins with an arbitrary operational unit  10  and proceeds generally in a direction of evident material flow, however, such an ordering is not always implicit in a complex process or desirable for optimization. In complex processes that involve multiple interrelated process steps, additional attention may be given to the problem of identifying the sequence in which unit operations are analyzed for savings, because changing a mass or energy balance in one unit operation may have effects on linked processes. 
     In an additional embodiment of the invention, a sequence of optimization may be adopted by analyzing energy usage of each of the operational units  10  according to the following categories: 
     Direct Energy 
     This is the energy directly required to perform the chemical or biological transformation of the unit operation  10 . This is typically described as the change in the Gibbs Free Energy of the reaction, or in the case of biological systems, the metabolic balance. It is specific to the reaction. 
     Indirect Energy 
     This is the energy that is required to facilitate the reaction but is not directly involved in the reaction. It can be thought of as amount of energy required to transfer the direct energy to the reaction. For example, one must heat all of the solvent in an endothermic reaction in order to transfer the requisite direct energy to the reacting species. The heating of the solvent is indirect energy because it just facilitates the reaction but does not participate in the reaction. 
     Environmental Energy. 
     Associated with containment, control and regulation. It is the energy of the surroundings, for example lighting, air conditioning, etc. 
     In optimizing a process comprised of multiple unit operations  10  the energy flows  66  may be characterized manually or automatically (in the latter case by a script system similar to scripts  76  described above), and the OPE calculated for each unit operation  10 . The optimization may start with the unit operation  10  having the lowest energy efficiency. In the case of a tie, the unit operation  10  with the worst Mass Efficiency takes precedent. This is because mass efficiency typically provides increased savings, since it reduces both energy usage and material consumption. 
     Next, when performing the analysis process described above with respect to transformative, reflexive, integrative, and cyclic paradigms, these optimizations are applied with respect to energy savings in the following sequence. 
     Indirect Energy 
     Environmental Energy 
     Direct Energy. 
     Thus, the energy-saving paradigms are applied first to Indirect Energy. This is because Direct Energy processes are determined by the reaction itself, which one cannot change. Environmental Energy is analyzed after Indirect Energy because Environmental Energy is a function of Indirect Energy. For example, if one can reduce the amount of solvent, then one doesn&#39;t need as large a vessel, floor space and hence heating and air conditioning and the like. 
     Certain terminology is used herein for purposes of reference only, and thus is not intended to be limiting. For example, terms such as “upper”, “lower”, “above”, and “below” refer to directions in the drawings to which reference is made. Terms such as “front”, “back”, “rear”, “bottom” and “side”, describe the orientation of portions of the component within a consistent but arbitrary frame of reference which is made clear by reference to the text and the associated drawings describing the component under discussion. Such terminology may include the words specifically mentioned above, derivatives thereof, and words of similar import. Similarly, the terms “first”, “second” and other such numerical terms referring to structures do not imply a sequence or order unless clearly indicated by the context. 
     When introducing elements or features of the present disclosure and the exemplary embodiments, the articles “a”, “an”, “the” and “said” are intended to mean that there are one or more of such elements or features. The terms “comprising”, “including” and “having” are intended to be inclusive and mean that there may be additional elements or features other than those specifically noted. It is further to be understood that the method steps, processes, and operations described herein are not to be construed as necessarily requiring their performance in the particular order discussed or illustrated, unless specifically identified as an order of performance. It is also to be understood that additional or alternative steps may be employed. 
     References to “a controller” and “a processor” can be understood to include one or more controllers or processors that can communicate in a stand-alone and/or a distributed environment(s), and can thus be configured to communicate via wired or wireless communications with other processors, where such one or more processor can be configured to operate on one or more processor-controlled devices that can be similar or different devices. Furthermore, references to memory, unless otherwise specified, can include one or more processor-readable and accessible memory elements and/or components that can be internal to the processor-controlled device, external to the processor-controlled device, and can be accessed via a wired or wireless network. 
     The term script refers simply to a short computer program that can be executed by another computer program and is not intended to suggest or imply an interpreted language or program that coordinates different application programs. 
     It is specifically intended that the present invention not be limited to the embodiments and illustrations contained herein and the claims should be understood to include modified forms of those embodiments including portions of the embodiments and combinations of elements of different embodiments as come within the scope of the following claims. All of the publications described herein, including patents and non-patent publications, are hereby incorporated herein by reference in their entireties.