Sizing of a new production plant for packaged dairy products using simulation

Abstract

A computer device implements a method (600) for sizing a new plant for producing packaged dairy products by simulation. The method operates by obtaining (601) a production target for a dairy product to be produced and packaged in the production plant, obtaining (602) a recipe for producing the packaged dairy product, wherein each recipe defines an ingredient and a recipe activity; and obtaining (603) production unit data that associates each of a plurality of optional production units with one or more unit activities and production capacity. The method also performs simulation by generating (604) a combination of optional production units based on the recipe and the production unit data, the optional production units being connected in fluid communication and operable to perform the recipe activities of the corresponding recipe to achieve the production target; and evaluating (605) the combinations to select at least one combination representing a plant configuration.

Description

Technical Field

[0001] The present invention relates generally to the production of dairy products and, in particular, to a simulation tool for dimensioning a new production plant for producing packaged dairy products. Background Art

[0002] The scale determination of a new plant for producing packaged dairy products is a complex task that usually relies on the inspiration, intuition and experience of a team of process engineers. As used herein, scale determination refers to the process of determining the production equipment to be included in the new plant and the material flow in the plant to achieve production goals. Generally, with respect to both the type of packaging and the type of dairy products, the plant for producing and packaging dairy products needs to be able to produce a large number of different types of packaged dairy products, and the type and / or volume of the packaged dairy products to be produced may vary over time. The factory can be designed with multiple production lines, and due to the changes in the capacity of the production line and the processing requirements, a large number of process constraints may exist. Some products may be produced on more than one production line, and some processes may need to share production equipment. Some products may have priority constraints, and products with similar production conditions may be produced continuously by scheduling. In addition, the production of packaged dairy products may involve batch production and continuous production, which makes scale determination more challenging.

[0003] Furthermore, when sizing a new plant for the production of packaged dairy products, different scenarios for future production targets may need to be considered, making sizing more complex and labor-intensive. For the same input data, sizing results often vary, depending on the experience of the team of process engineers. Given the economic consequences of potential undersizing of a production plant, there is a general tendency to oversize the production plant instead, leading to an overestimation of the required investment costs and ultimately unnecessary expenditures for building a new plant.

[0004] Additionally, there are production-related factors that process engineers do not consider when sizing a new plant. Summary of the invention

[0005] It is an object of the present invention to at least partially overcome one or more limitations of the prior art.

[0006] One such object is to improve and / or facilitate the dimensioning of plants for the production of packaged dairy products.

[0007] One or more of these objects, as well as other objects that will be apparent from the following description, are achieved at least in part by methods, computer readable media and devices according to the independent claims, embodiments of which are defined by the dependent claims.

[0008] A first aspect of the present invention is a computer-implemented method for sizing a factory for producing packaged dairy products by simulation. The method includes: obtaining target production data for a plurality of dairy products to be produced and packaged in a production factory to form the packaged dairy products; obtaining a recipe for producing a plurality of dairy products, wherein each recipe defines a set of ingredients and a series of recipe activities for producing a corresponding dairy product from the set of ingredients; obtaining production unit data for optional production units, the production unit data associating each optional production unit with one or more unit activities and production capacity; and simulating the production of the packaged dairy products in the factory to determine at least one combination of optional production units that achieve the target production data. The simulation includes: generating a combination of optional production units according to the recipe and the production unit data, the production units being connected for fluid communication and operable to perform the series of recipe activities of the corresponding recipe to achieve the target production data; evaluating the combinations to select at least one of the combinations; and outputting at least one of the combinations.

[0009] A second aspect of the present invention is a computer readable medium comprising computer instructions which, when executed by a processing device, cause the processing device to perform the method of the first aspect or any embodiment thereof.

[0010] A third aspect of the invention is an apparatus for dimensioning a plant for producing packaged dairy products, the apparatus being configured to carry out the method of the first aspect of any embodiment thereof.

[0011] Other objects, as well as features, aspects and advantages of the present invention will become apparent from the following detailed description and accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Embodiments of the invention will now be described, by way of example, with reference to the accompanying schematic drawings.

[0013] Figure 1 A method for producing a packaged dairy product from grouped ingredients in a production plant is schematically shown.

[0014] Figure 2 is a block diagram of a production plant for packaged dairy products.

[0015] Figures 3A-3C The process for producing three different dairy product packages is shown. Figure 2 Material flow in a factory.

[0016] Figure 4A is a summary of an embodiment of a method for sizing a plant for producing packaged dairy products, and Figure 4B It shows that it can be Figure 4A An example of a predefined functional group defined with input data in .

[0017] Figure 5 A series of activities corresponding to a recipe for producing yogurt is shown.

[0018] Fig. 6A is a flow chart of a sizing process according to one embodiment, and Figure 6B is a flow chart of a portion of a sizing process according to another embodiment.

[0019] Figure 7A-7B The variation of the time schedule depending on the sequence of material supply to the production units is shown.

[0020] Figures 8A-8C The variation of the time schedule depending on the production capacity and the number of production units is shown.

[0021] Fig. 9 Is for Figure 2 An example of a proposed time schedule generated by a production plant in .

[0022] Fig.10 is a block diagram of an apparatus for performing a sizing process according to an embodiment of the present invention. DETAILED DESCRIPTION

[0023] Embodiments of the present invention will now be described more fully hereinafter with reference to the accompanying drawings, in which some, but not all, embodiments of the invention are shown. Indeed, the invention may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure may satisfy applicable legal requirements.

[0024] In addition, it will be understood that, where possible, any advantages, features, functions, equipment and / or operational aspects of any embodiment of the present invention described and / or considered herein may be included in any other embodiment of the present invention described and / or considered herein, and / or vice versa. In addition, where possible, unless otherwise expressly stated, any term expressed in the singular herein is also intended to include the plural form and / or vice versa. As used herein, "at least one" should mean "one or more", and these phrases are intended to be interchangeable. Therefore, even if the phrases "one or more" or "at least one" are also used in this article, the terms "one" and / or "a kind of" should mean "at least one" or "one or more". As used herein, unless the context requires otherwise due to the expression language or necessary suggestion, the word "include" or a variation such as "contain" or "includes" is used with an inclusive meaning, that is, specifying the presence of the feature, but not excluding the presence or addition of other features in various embodiments of the present invention. As used herein, the term "and / or" includes any and all combinations of one or more associated listed items. As used herein, a "group" of items is intended to imply that one or more items are provided. Thus, a "group of ingredients" may specify a single ingredient or a plurality of ingredients. Likewise, a "group of production units" may specify a single production unit or a plurality of production units. As used herein, "dairy product" refers to a food product produced from a substance comprising the milk of a mammal (primarily but not exclusively a cow) or an emulsion from a plant source. The substance may be made from fresh milk and / or milk powder.

[0025] For brevity and / or clarity, well-known functions or constructions may not be described in detail. Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the invention belongs.

[0026] Like reference numerals refer to like elements throughout.

[0027] Figure 1It is a schematic diagram of a production plant 10, which is arranged to produce three different packaged dairy products 30A, 30B, 30C from ingredients I1, I2, I3 by using three production processes 20A, 20B, 20C performed by the production equipment in the plant 10. The production processes 20A, 20B, 20C and the ingredients I1, I2, I3 are defined by the recipes of the corresponding dairy products 30A-30C. In order to maximize the production throughput, it is desirable to perform the processes 20A-20C in parallel by using different production equipment. However, for economic reasons, it is usually impossible to determine the size of the plant for the parallel production of all possible types of packaged dairy products. Therefore, the processes 20A-20C usually have to share the production equipment in the plant at least in part. The task of allocating the activities of the corresponding processes 20A-20C to the production equipment in the plant 10 is called time scheduling.

[0028] Figure 2 A general example of a factory 10 for producing packaged dairy products is shown. Figure 2 In the figure, the hollow square represents a production unit, hereinafter referred to as a "production unit" or PU, and the solid line extending between the PUs represents a fluid conduit (fluid path). The fluid conduit can be permanently arranged to extend as shown, but it is also conceivable that the fluid conduit can be added and / or moved by manual operation by an operator of the factory 10. The fluid conduit is shown schematically, and each typically includes a plurality of fluid paths that allow one or more fluids to pass through simultaneously and separate from each other in opposite directions in the fluid conduit. In addition, the conventional pump symbol represents the setting of the fluid pump along the fluid conduit, and the hollow circle represents a flow control valve. The PU of the factory 10 shown includes milk receiving units R1-R3, each of which can include a tank and a device for further processing (such as preheating, degassing, homogenization, etc.). The pasteurizer PS1-PS3 is arranged for heat treatment. Tanks T1-T8 are distributed throughout the factory 10 for storing ingredients, intermediate products or final dairy products. Fermentation tanks ST1 and ST2 are provided to accommodate and distribute starter cultures for the production of fermented dairy products (such as yogurt). Mixing devices M1, M2 are provided to enable mixing of dry or liquid ingredients, and a heat exchanger C1 is provided for cooling or heating. Filling machines or packaging lines P1-P3 are provided to fill the dairy product into packages (e.g. packages made of cartons and / or plastic) which can be sealed for subsequent distribution. The plant 10 also includes an aseptic (sterilization) production area, which includes units UHT1, UHT2 for ultra-high temperature treatment (also known in the art as ultra-heat treatment or ultra-pasteurization), aseptic tanks AT1, AT2 for storing the sterilized dairy product, and aseptic filling machines or packaging lines AP1-AP4. Figure 2All PUs shown in are known to those skilled in the art, who will also appreciate that plant 10 may include additional PUs, including but not limited to separators, heaters, homogenizers, and packaging dispensing devices.

[0029] Figure 2 It is also shown that the plant 10 includes a cleaning unit CIP, such as a conventional cleaning-in-place system, which is connected to communicate with the fluid conduits and / or PU fluids in the plant 10 to enable the circulation of cleaning fluids. The ability to clean production equipment is a strict requirement in dairy production and is set by regulatory agencies. However, the need for cleaning may vary, depending on the dairy product being produced, the time since the last cleaning, etc. Typically, the plant 10 includes one or only a few CIPs, which usually need to be cleaned sequentially between the PU and the fluid conduits of the plant 10. Therefore, the scheduling of the CIPs may have a significant impact on the duration of the production processes 20A-20C in the plant 10 ( Figure 1 ).

[0030] Figure 2 The dotted lines in the figure indicate the affiliation of the corresponding PU with the functional group, as will be referred to below. Figure 5 and 6B Further described.

[0031] Figures 3A-3C shows how the material flows through Figure 2 0048] An example of a plant 10 in which thick arrow lines represent material flows and solid boxes represent PUs operating for processing.

[0032] Figure 3A The material flow for producing standard milk for packaging is shown. A delivery of raw milk is pumped into milk receiving units R1-R3 and then undergoes heat treatment as it is pumped through pasteurizer PS1 into storage tank T1. The treated milk is pumped from tank T1 to filling machine P1 which is operated to produce milk packaging. Figure 3A The combination of PUs indicated by solid boxes in FIG. 1 may be shown as performing Figure 1 The production process 20C is used to produce packaging of milk 30C based on raw milk I1.

[0033] Figure 3BThe material flow for producing packaged yogurt is shown. A delivery pump of raw milk is delivered to milk receiving units R1-R3, where the milk is then subjected to heat treatment as it is pumped through a pasteurizer PS1 into storage tank T2. The treated milk is pumped from tank T2 through a fermentation tank ST1, which is operated to add a starter culture to the milk. The mixture of milk and starter culture is pumped into tank T4 for fermentation (incubation) over a predetermined period of time, whereupon the resulting yogurt is cooled as it is pumped through a heat exchanger C1 into tank T6 for intermediate storage. The yogurt is pumped from tank T6 to a filling machine P3, which is operated to produce packages of yogurt. In Figure 3B The combination of PUs indicated by solid boxes in FIG. 1 is shown as performing Figure 1 The production process 20B is used to produce packaged yogurt 30B based on raw milk I1 and starter culture I2.

[0034] Figure 3C The material flow for producing chocolate milk in aseptic packaging is shown. A delivery of raw milk is pumped into milk receiving units R1-R3, where the milk is then subjected to heat treatment as it is pumped through a pasteurizer PS1 into a storage tank T1. The treated milk is pumped from tank T1 through a mixing unit M1, which is operated to mix chocolate powder and sugar into the milk. The resulting chocolate milk is pumped through an aseptic heat treatment unit UHT2 and into an aseptic tank AP2 for intermediate storage. The aseptic chocolate milk is pumped from the aseptic tank AP2 to aseptic filling machines AP3, AP4, which operate in parallel to produce aseptic packaging of the chocolate milk. In Figure 3C The combination of PUs indicated by solid boxes in FIG. 1 is shown as performing Figure 1 The production process 20A in the embodiment is to produce a package of chocolate milk 30A based on raw milk I1, chocolate powder I2 and sugar I3.

[0035] Figure 4A is used for new production plants (e.g. Figure 2 The plant 10 shown in FIG. 1 is a summary of an embodiment of the sizing process. As used herein, sizing refers to the process of determining the plant profile, the PUs included, and the available fluid paths between the PUs. The sizing process can also be expressed as an engineering design process, a simulation process, or a configuration process. Figure 4A It may be shown as representing input data 400 - 403 for sizing, blocks 410 , 420 configured to perform the sizing process, and output data 430 generated by the sizing process.

[0036] The input data includes target production data ("production target") 400 for the new factory. The production target 400 may specify the dairy product packages ("products") and production volumes ("volumes") to be produced in a specific time period (e.g., one or more days or weeks), where the respective dairy product packages may be defined by the type of dairy product and the type of packaging. Such production targets 400 are also known in the art as SKU lists (stock keeping units). Figure 4A As shown, the production objectives 400 may also include a production schedule ("schedule") for dairy product packaging, that is, the amount of a particular packaged dairy product to be produced as a function of time. The input data also includes a recipe 401 for the dairy product to be produced. Each recipe defines a series of recipe activities ("activities"), a set of ingredients ("ingredients"), and may also specify characteristics of one or more activities, such as minimum and / or maximum duration, time interval, pressure, pumping speed, etc. The input data also includes production unit data 402, which specifies optional PUs that may be included in the new plant. The production unit data 402 associates each optional PU with one or more unit activities ("activities") and one or more production capacities ("capacities"), for example, given as volume, volume flow rate, packaging production rate, etc. For example, a tank may be associated with one or more of a total capacity, a maximum filling rate, and a maximum emptying rate. Unit activities are defined to correspond to recipe activities, such that each recipe activity can be matched with one or more unit activities. As Figure 4AAs shown, the production unit data 402 may also associate one or more rules ("rules") with the optional PU. The rules may be directed to a cleaning process and, for example, specify one or more of the following: the duration of a short cleaning process ("short CIP"), the duration of an extended cleaning process ("full CIP"), the number of consecutive short CIPs allowed before a full CIP is required, a first time limit for not using the PU and not needing cleaning (i.e., if the PU is not used for a period of time exceeding the first time limit, a CIP is required), a second time limit for using the PU and not needing cleaning (i.e., a CIP is required as long as the second time limit is exceeded), and a CIP is required at the end of the use of the PU. Alternatively or additionally, the rules may be directed to other characteristics of the PU. For example, a rule for a tank may specify the volume or proportion of the tank that needs to be filled before it can begin to empty ("minimum volume before emptying"), a rule for a thermal processing unit may specify the maximum time that water may circulate in the unit ("circulation limit"), a rule for any PU may specify the nominal time required for an operator to set up the PU ("preparation event duration"), a rule for any PU may specify the nominal time required for daily care ("daily care duration"), etc. The input data may also include delivery data 403 for ingredients, including a delivery schedule for delivering one or more ingredients. Such a delivery schedule may specify the amount of a particular ingredient that is to be delivered and needs to be processed at the plant based on time.

[0037] like Figure 4A As shown, the combination block 410 is arranged to process the input data 400-403 to generate a combination of selectable PUs that are connected in fluid communication and operable to perform a series of recipe activities of the corresponding recipe 401. The evaluation block 420 is arranged to evaluate the combination generated by the block 410. Figure 4A As shown, the combination and evaluation blocks 410, 420 may implement an iterative optimization process, wherein the evaluation block 420 provides information about the evaluation results to the combination block 410, so that the combination block 410 can systematically generate combinations of optional PUs to achieve the purpose of reducing the time it takes for the evaluation block 420 to find one or more acceptable combinations. Such an iterative optimization process may be based on any suitable optimization model. Figure 6A-6B An example of the sizing process performed by blocks 410 , 420 is further provided.

[0038] The output data of the sizing process is one or more proposed combinations of optional PUs for the factory ("factory configuration"). As will be explained in further detail below, the output data may also include one or more proposed time schedules for the respective proposed combinations, wherein each proposed time schedule includes a time schedule of the optional PUs in the proposed combination, or a subset thereof, to implement the respective production process (see Figure 120A-20C in order to achieve the production target 400, wherein the production process is given by the recipe 401. The proposed combination and / or the proposed time schedule can be presented to a user, such as a process engineer, for further evaluation of relevance and feasibility. The output data may also include other data related to production, such as the investment cost of the proposed combination, the estimated time to achieve the production target for the corresponding time schedule, the production cost for the corresponding time schedule, and the consumption of one or more utilities such as water, energy, steam (for heat treatment and / or cleaning), detergents, coolants, etc. for the corresponding time schedule.

[0039] Figure 5 An exemplary recipe 500 for producing yogurt is shown in the form of a flow chart. The recipe 500 shown includes a series of processing steps 501-506 for producing a package containing yogurt. The recipe 500 also defines two ingredients: milk I1 and starter culture I2. Some processing steps are associated with specific characteristics, and some processing steps include a series of sub-steps, some of which are associated with specific characteristics. Specifically, the recipe 500 includes a milk processing step 501, in which milk I1 is received and processed including a series of sub-steps as follows: preheating, degassing, homogenization, heating, holding and cooling. The sub-steps preheating, heating and cooling are associated with corresponding characteristics TE1, TE2, TE3, which indicate the temperature to be used in the corresponding sub-steps. The milk processing step 501 is followed by an inoculation step 502, in which the starter culture I2 is added to the milk by online addition. Then an incubation step 503 is performed, in which the mixture of milk and starter culture is stirred, fermented and stirred. The fermentation sub-step is associated with a characteristic Δt1 indicating its duration. A subsequent cooling step 504 reduces the temperature of the fermented mixture to TE4 and the resulting yogurt is then buffered 505 for a period not exceeding Δt2. The recipe 500 is completed by a step 506 of filling the yogurt into packaging. Figure 5 As shown, recipe 500 can be summarized as a series of recipe activities, here A1, A6, A4, A2, A7, A2, A8, which are defined to correspond to activities that can be performed by an optional PU ("unit activities").

[0040] Thus, each recipe can be structured as a set of ingredients and a series of recipe activities, where any recipe activity can be associated with one or more properties.

[0041] Fig. 6A 6 is a flow chart of a sizing process 600 according to one embodiment. The process 600 includes a set of data collection steps 601-603 for obtaining input data. Step 601 obtains target production data ( Figure 4A), and step 602 obtains a dairy product formula ( Figure 4A Step 603 obtains the above production unit data ( Figure 4A Any of steps 601-603 may involve passing through a user interface (see Fig.10 1006 in the figure instructs the operator to manually input the input data and / or select the input data from the database. It is also conceivable that any of steps 601-603 automatically retrieves the input data from the database. For example, steps 602 and 603 can automatically retrieve the recipe 401 from the database based on the production target 400 input / selected by the operator, and automatically retrieve the production unit data 402 based on the recipe 401.

[0042] Process 600 also includes processing steps 604-605, which can be performed by Figure 4A Step 604 generates a candidate combination of selectable PUs based on the recipe 401 and the production unit data 402, the selectable PUs being connected in fluid communication and operable to perform a series of recipe activities of the corresponding recipe 401 to achieve the production target 400. Step 605 evaluates the candidate combinations to select at least one proposed combination ( Figure 4A Finally, step 606 outputs the proposed combination. Steps 604-606 may be illustrated as representing a simulation of the production of packaged dairy products in a production plant to determine at least one combination of selectable PUs that achieves the production target 400.

[0043] The sizing process 600, when implemented by a computer device, provides a simulation tool that enables a systematic analysis of various combinations of optional PUs with respect to meeting the production target 400 and outputs one or more proposed combinations 430 that can meet or sufficiently approach the production target 400. This tool will greatly facilitate the task of sizing a new production plant and may also enable significant improvements in time scheduling, for example, when steps 604-605 are implemented as an iterative optimization process that is configured to find a combination of optional PUs that results in an acceptable / optimal time schedule subject to one or more evaluation constraints.

[0044] In one embodiment, step 604 identifies a set of available optional PUs for performing the recipe activity by comparing the recipe activity of the recipe 401 with the unit activities of the optional PUs of the production unit data 402. Step 604 may thereby include any optional PU associated with a unit activity that matches a recipe activity in the available set. Step 604 may then allocate a combination of PUs based on the production capacities associated with the corresponding PUs in the available set. To perform the allocation, step 604 may reverse calculate the required production capacities of the corresponding PUs through mass balancing based on the products and volumes to be produced according to the production target 400, and the production schedule (if specified).

[0045] In one embodiment, step 605 generates one or more time schedules of recipe activities for each candidate combination based on recipe 401 and production unit data 402, the recipe activities being performed by the corresponding candidate combination to achieve production target 400. If production target 400 includes a production schedule, step 605 may also take the production schedule into account when generating the time schedule by ensuring that the corresponding dairy product packages are produced in accordance with the production schedule. In addition, process 600 may include the step of obtaining an ingredient delivery schedule ( Figure 4A 403 in ), and step 605 can take the ingredient delivery schedule 403 into account when generating the time schedule by adapting the timing of the recipe activities to the availability of the ingredients.

[0046] Step 605 may evaluate the candidate combinations based on the time schedule generated for the corresponding candidate combinations, thereby selecting the proposed combination 430 based at least in part on the evaluation of the time schedule. A more detailed example of the evaluation in step 605 is further given below.

[0047] Figure 6B According to another embodiment, Fig. 6A Flowchart of steps 604-605 in FIG. Steps 604A-604C correspond to Fig. 6A Step 604 in . Figure 6B The embodiment in assumes that the production unit data 402 obtained in step 603 associates each optional PU with one or more functional groups of PUs (hereinafter referred to as "functional groups"). Functional groups can be predefined to correspond to corresponding recipe activities. Specifically, all optional PUs in a certain functional group are associated with the same unit activity. Conceptually, functional groups can therefore be considered to be associated with corresponding unit activities.

[0048] exist Figure 4BA non-limiting example of production unit data 402 defining functional groups is shown in . In this example, the functional groups include milk receiving group A1, storage group A2, separation group A3, inoculation group A4, mixing group A5, heat treatment group A6, heat exchange group A7, and filling group A8. As indicated, each functional group A1-A8 can be associated with one or more optional PUs ("optional units"). For example, storage group A2 can be associated with different tanks, and filling group A8 can be associated with different filling machines or packaging lines. As shown in the figure, each optional PU can be associated with one or more capabilities ("capabilities"), a cost index ("cost"), and one or more rules ("rules"). It can be noted that Figure 5 The functional groups in correspond to Figure 4B To further illustrate, Figure 4B Function groups A1-A8 in have been mapped to Figure 2 10 in FIG. 4 , wherein the dotted lines surround the PUs associated with the respective functional groups.

[0049] Reference Figure 6B , step 604A generates a functional representation of recipe 401 by representing each recipe activity in the recipe by a functional group. Specifically, step 604 may represent the corresponding recipe activity by its corresponding functional group. Step 604B defines fluid paths between functional groups in the functional representation according to a series of recipe activities of the corresponding recipe. Step 604C selects one or more optional PUs associated with the functional group for the corresponding functional group in the functional representation, thereby generating a candidate combination of optional PUs that are connected to be fluidically connected and operable to perform a series of recipe activities of recipe 401 to achieve the production goal 400. Then, step 605 evaluates the candidate combination generated by step 604C. It is conceivable that step 604C generates several different candidate combinations to be subsequently evaluated by step 605. Alternatively, as Figure 6B As shown, steps 604C and 605 may be repeatedly performed to generate and evaluate different candidate combinations. Specifically, the process returns to step 604C to select a new candidate combination of selectable PUs based on the evaluation results in step 605. Therefore, step 604C may be adjusted based on the evaluation results of one or more of the previous candidate combinations. This iterative method allows the sizing process 600 to systematically search for acceptable / optimal combinations. Such an iterative method may also be used in Fig. 6A is implemented in the implementation scheme.

[0050] according to Figure 6BThe use of functional groups provides a structured way to select PUs for implementing multiple recipes and works particularly well in conjunction with the iterative approach described above. For example, step 604C may generate different candidate combinations by changing the selection of PUs for one or more functional groups in the functional representation (e.g., by changing the number of selected PUs and / or by replacing a previously selected PU with another PU having different production capabilities).

[0051] Figure 6A-6B The embodiments in can be modified to allow the user to review the production unit data 402 in step 603 (e.g., on a user interface) and remove one or more optional PUs before the method proceeds to step 604. In another variation, the sizing method 600 allows the user to pre-assign specific optional PUs to specific recipe activities in a specific recipe, or to limit the optional PUs that can be assigned to specific recipe activities in a specific recipe. In these variations, the user can therefore impose restrictions on the optional PUs that can be included in the combination generated by step 604. The sizing method 600 thus allows the user to test the impact of different modifications to gain a better understanding of how the new plant can be sized.

[0052] It is contemplated that the sizing process 600 may be further modified to account for the investment cost of a new plant. Figure 4A-4B As will be appreciated, the production unit data 402 may associate each optional PU with a cost index. The sizing process 600 may be modified to calculate an investment cost index for each candidate combination generated by step 604 / 604C based on the cost index of the optional PUs included in the corresponding candidate combination. In one embodiment, step 605 may generate candidate combinations such that their investment cost index is below a threshold value, which may be predefined or input by a user. The threshold value may thus be a constraint of step 604 / 604C (see the information provided to Figure 4A Alternatively, the threshold value may be a constraint of step 605 (see the constraint provided to Figure 4A For example, step 605 can evaluate candidate combinations based on their investment cost indexes and discard any candidate combinations with investment cost indexes exceeding a threshold. Typically, as described above, the investment cost index of the proposed combination 430 can be output by step 606.

[0053] As described above, step 605 may generate and evaluate one or more time schedules for the respective candidate combinations from step 604 / 604C. For example, step 605 may determine a plurality of candidate time schedules for each candidate combination, determine (if possible) an acceptable or optimal time schedule for each candidate combination (based on any criteria), and select the proposed combination 430 based on the acceptable / optimal time schedule so determined. It is also contemplated that step 605 may be performed in an iterative optimization process (compared to the one for the proposed combination 430). Figure 6B Thus, the evaluation result of one time schedule can be used to generate a subsequent time schedule, so that step 605 can systematically generate a time schedule to achieve the purpose of reducing the time to find an acceptable / optimal time schedule for each candidate combination.

[0054] In one embodiment, step 605 takes into account the need to clean the PU and / or fluid conduit when generating the candidate time schedule. As described above, in a plant for producing dairy products, intermittent cleaning is mandatory, and the use (access) of the cleaning unit (CIP) is usually the bottleneck of time scheduling. The scheduling process 600 may therefore include the following steps: defining the fluid path between at least one cleaning unit in the production plant and the optional PU in each candidate combination, and obtaining a rule for cleaning the corresponding optional PU, which rule is given, for example, by the production unit data 402 ( Figure 4A ). Therefore, step 605 can generate a time schedule according to the cleaning rules. Examples of such cleaning rules have been given above.

[0055] In one embodiment, step 605 may evaluate the time schedule to implement at least one evaluation constraint (see Figure 4A The evaluation constraints may be obtained as part of the data collection steps 601-603, or may be pre-defined and stored in memory (see Fig.10 1003 in). In one embodiment, the evaluation constraint defines at least one of the maximum production time, maximum production cost, and maximum labor cost required to achieve the production target. Therefore, step 605 can calculate a parameter value representing any evaluation constraint of the corresponding time schedule and compare the parameter value with the evaluation constraint. If the production time and / or production cost and / or labor cost exceed the evaluation constraint, step 605 can discard the time schedule. Labor costs can be calculated based on the amount of physical labor required to install the selected PU and / or rearrange the fluid conduit during the time schedule. The production cost can be calculated to represent the consumption of at least one utility (including one or more of water, energy, steam, coolant, and detergent) during the time schedule.

[0056] Step 605 may also forward compute the time schedule, or at least the time schedule found to satisfy the evaluation constraints, to verify whether the production target is indeed met given the batching and delivery schedules (if specified).

[0057] Typically, step 605 is performed to find one or more time schedules for each candidate combination that have high time utilization of PUs in the factory, few and / or short idle periods, few product changes, and few and / or short cleaning activities.

[0058] Acceptable / optimal time schedules for the proposed combinations 430 may be output via step 606. Additionally, step 606 may output other metrics calculated for each such time schedule, such as total production time, CIP utilization, graphical representation of bottlenecks, production costs, labor costs, etc.

[0059] Typically, step 605 may take into account the rules included in the production unit data 402 when generating the time schedule. For example, considering a cleaning rule that states that a PU must be cleaned after each processing of a certain dairy product or intermediate product, unless the same dairy product or intermediate product is to be processed next, the PU should be cleaned according to a default cleaning rule (e.g., "short CIP" and / or "full CIP" as described above). Figure 7A-7B The timing of recipe activities A10, A20, A30 for producing a first and a second (different) dairy product performed by three production units PU1, PU2, PU3 is shown. The recipe activities performed for producing the first and second dairy products are distinguished by subscripts 1 and 2, respectively. The first dairy product may be yogurt and the second dairy product may be standard milk. In the example shown, the production units PU2, PU3 are associated with a cleaning rule requiring cleaning after each completion of the recipe activities for producing the first dairy product, while no such cleaning rule is defined for the production of the second dairy product. Fig. 7A The sequence of recipe activities when processing a first dairy product before a second dairy product in the respective production units PU1-PU3 is shown. As shown, PU2 and PU3 require cleaning activities, indicated by CA. In addition, while waiting for the completion of the processing of the second dairy product in PU2, PU3 will have Fig. 8A The W in indicates an idle or waiting period. Figure 7B The timing of recipe activities is shown when a second dairy product is processed before a first dairy product. Clearly, the absence of cleaning activities enables better utilization of production units PU1-PU3 and also reduces the utilization of cleaning units in the plant.

[0060] from Figure 7A-7BIt can be understood that step 605 can generate different time schedules of candidate combinations by changing the order in which the dairy products or corresponding intermediate products are supplied to one or more PUs.

[0061] Fig. 8A The timing of recipe activities A10, A20, which are performed by two production units PU1, PU2 to produce a first and a second dairy product, is shown. As shown, PU2 will have an idle period, indicated by W, while waiting for the processing of the second dairy product in PU1 to complete. Figure 8B In , PU1 has been replaced by PU3, which is able to perform the same recipe activity (A10) as PU1, but with a higher production capacity. Thus, the idle period W is eliminated. Figure 8C middle, Fig. 8A PU1 is supplemented by PU4, which is able to perform the same recipe activity (A10) as PU1 and has the same production capacity as PU1. As shown, PU4 allows parallel processing of the first dairy product and the second dairy product, and eliminates the idle period W.

[0062] As per Figures 8A-8C It is understood that the acceptable / optimal time schedule determined by step 605 may vary significantly between candidate combinations. It is also recognized that Figure 6B The iterative method in can be very efficient because step 604 / 604C is controlled to selectively change the content of the aforementioned candidate combination, for example by changing the number of optional PUs associated with the unit activity and / or by replacing the optional PU associated with the unit activity with another optional PU associated with the same unit activity but with different production capabilities.

[0063] It is also conceivable that step 604 / 604C adds one or more optional PUs (tanks) for intermediate storage, even if such intermediate storage is not included in the recipe, for example to enable sequential processing in downstream PUs or sharing of fluid conduits and PUs between recipes. Figure 5 Yogurt formula 500 with Figure 3B For comparison, see an example in which the treated milk is temporarily stored in tank T2.

[0064] Fig. 9 A portion of a time schedule is shown in the form of a Gantt chart, which is generated and output by the sizing process 600 for the time corresponding to Figure 2 The proposed combination 430 of factory 10 produces packages containing standard milk, yogurt and chocolate milk (as well as other packaged dairy products). Figures 3A-3C The material flow in corresponds to Fig. 9The time schedule is shown in Figure 1. The thin lines represent the life span of the PUs, while the thick lines represent the cleaning activities. In addition, for the tanks, thin lines are drawn to represent the change in the volume of the fluid inside the corresponding tank over time. Only the dashed vertical lines corresponding to the time points t0-t20 are provided to facilitate the understanding of the Gantt chart by indicating the start and end of various activities. As shown in the figure, the time schedule is drawn up to synchronize the activities within the plant. It is also seen that the cleaning activities do not overlap because there is only one CIP in the plant. Fig. 9 The top of the time schedule, DEL, indicates the time period during which milk is delivered to the factory. Figure 3A and 3C production of standard milk and chocolate milk, although the filling and emptying of tank T2 is based on Figure 3B Part of yogurt production.

[0065] Fig.10 is a block diagram of an example structure of a computer device 1000 for performing a sizing process according to any of the embodiments and variations described above. In the example shown, the device 1000 includes a control circuit or control unit 1001 and a memory 1003. The control circuit 1001 is responsible for the overall operation of the device 1000 and may include any commercially available processing device 1002, such as a CPU ("central processing unit"), a DSP ("digital signal processor"), a microprocessor or other electronic programmable logic device, or a combination thereof. The control circuit 1001 may be implemented using instructions that enable hardware functions, such as executable computer program instructions 1004 that may be stored on the memory 1003. The processing device 1002 may be configured to read the instructions 1004 from the memory 1002 and execute these instructions to control the operation of the device 1000, for example to perform any of the methods described herein. Program instructions 1004 may be provided to device 1000 on a computer readable medium, which may be a tangible (non-transitory) product (eg, magnetic media, optical disk, read-only memory, flash memory, etc.) or a transitory product such as a propagated signal.

[0066] The memory 1003 may be, for example, one or more of a cache, a flash memory, a hard drive, a removable medium, a volatile memory, a non-volatile memory, a random access memory (RAM), or other suitable devices. In a typical arrangement, the memory 1003 includes a non-volatile memory for long-term data storage and a volatile memory used as a system memory for the control circuit 1001. Fig.10As shown, the memory 1003 may also store data 1005 used by the control circuit 1001 (e.g., recipe 401, production unit data 402, etc.). The memory 1003 may exchange data with the control circuit 1001 via a data bus. There may also be accompanying control lines and address buses between the memory 1003 and the control circuit 1001. In one variation, the memory 1003 is at least partially located within the control circuit 1001.

[0067] The device 1000 also includes a user interface (UI) 1006 for providing information or instructions to a user and / or receiving instructions from the user. For example, the device 1000 can present the proposed combination 430, the proposed time schedule of the proposed combination 430, and any associated metrics to the user via the UI 1006. The device 1000 can also obtain input data from the user via the UI 1006, for example as part of any of steps 601-603. The UI 1006 can include, for example, a display, a button, a keypad, a touch pad, a touch panel, an indicator light, a microphone, a speaker, etc., or any combination thereof.

[0068] In the example shown, the device 1000 also includes one or more communication interfaces 1007 for operably connecting the device 1000 to external devices by wired or wireless means (e.g., via a network). In one example, the device 1000 can retrieve data from the external device, such as the recipe 401, the production unit data 402, etc. In another example, the device 1000 can send the proposed combination 430 and other output data to the external device.

Claims

1. A computer-implemented method for sizing a plant (10) for producing packaged dairy products (30A, 30B, 30C) by simulation, the method comprising: obtaining (601) target production data (400) of a plurality of dairy products to be produced and packaged in the production plant to form the packaged dairy products (30A, 30B, 30C); Obtaining (602) recipes (401) for producing the plurality of dairy products, wherein each recipe (401) defines a set of ingredients (I1, I2, I3) and a series of recipe activities for producing a corresponding dairy product from the set of ingredients; obtaining (603) production unit data (402) for the selectable production units, the production unit data (402) associating each selectable production unit with one or more unit activities and production capabilities; as well as Simulating the production of the packaged dairy product (30A, 30B, 30C) in the factory (10) to determine at least one combination of optional production units for achieving the target production data (400), the simulation comprising: Generating (604) a combination of optional production units according to the recipe (401) and the production unit data (402), the optional production units being connected in fluid communication and operable to execute the series of recipe activities of the corresponding recipe (401) to achieve the target production data (400), wherein the generating (604) comprises: based on the target production data (400), reversely calculating the required production capacity of the optional production units by mass balance, and according to the required production capacity, allocating the combination of the optional production units based on the production capacity of each optional production unit; For each of the combinations, based on the recipe (401) and the production unit data (402), generating (605) a time schedule of recipe activities to be performed by the corresponding combination of the optional production units to achieve the target production data (400), wherein the combination is evaluated based on the time schedule generated for each of the combinations in an iterative optimization process, wherein the optimization process comprises: for the candidate combination, based on the recipe and the production unit data (402), repeatedly generating a time schedule (400) of recipe activities to be performed by the candidate combination to achieve the target production data (400), and evaluating the time schedule, wherein a result of the evaluation of the time schedule is used to generate a subsequent time schedule; evaluating (605) the combinations to select the at least one combination (430); and outputting (606) the at least one combination (430); As part of an optimization process, combinations of optional production units are iteratively generated and evaluated, wherein the optimization process includes: repeatedly selecting and evaluating candidate combinations among the combinations of optional production units, wherein the candidate combinations are selected based on evaluation results of one or more previous candidate combinations.

2. The computer-implemented method of claim 1 , wherein: Each optional production unit is associated with a cost index, wherein the method further comprises: for each of the combinations, calculating an investment cost index based on the cost index of the optional production unit contained in the respective combination.

3. The computer-implemented method of claim 2, wherein the combination is generated (604) such that the investment cost index is below a threshold.

4. The computer-implemented method of any one of claims 1 to 3, wherein said generating (604) comprises: comparing the recipe activity to the unit activity to identify a set of selectable production units for performing the recipe activity; Based on the production capabilities of the group of optional production units, a combination of optional production units is allocated in the group of optional production units to perform the series of recipe activities of the corresponding recipe to achieve the target production data (400).

5. The computer-implemented method of any of claims 1-3, wherein the production unit data (402) defines functional groups and associates each of the functional groups with a corresponding unit activity and a corresponding subset of the selectable production units, wherein the generating (604) comprises: A functional representation of the recipe (401) is generated (604A) by representing each recipe activity in the recipe (401) by a functional group (A1-A8); a fluid path is defined (604B) between the functional groups (A1-A8) in the functional representation according to the series of recipe activities of the corresponding recipe (401); and a combination is generated by selecting (604C) one or more of the optional production units associated with the corresponding functional group (A1-A8) for the corresponding functional group in the functional representation.

6. A computer-implemented method according to claim 5, wherein the difference between the combinations lies in at least one of the following: the production capacity of at least one optional production unit in at least one of the functional groups (A1-A8), and the count of the optional production units in at least one of the functional groups (A1-A8).

7. The computer-implemented method of claim 1 , further comprising: At least one evaluation constraint is obtained, wherein when evaluating (605) the combinations, the time schedule generated for each of the combinations is compared to the at least one evaluation constraint.

8. The computer-implemented method of claim 7, wherein the evaluation constraint defines at least one of: time, production cost, and labor cost required to achieve the target production data (400).

9. The computer-implemented method of claim 8, wherein the production cost is represented by consumption of at least one utility, the utility comprising one or more of water, energy, steam, coolant, and cleaning agent.

10. The computer-implemented method of claim 1 , further comprising: A delivery schedule (403) of the ingredients is obtained, wherein the time schedule is further generated (604) based on the delivery schedule (403) of the ingredients.

11. The computer-implemented method of claim 1 , further comprising: A production schedule for the packaged dairy product is obtained, wherein the time schedule is further generated (604) based on the production schedule for the packaged dairy product.

12. The computer-implemented method of claim 1 , further comprising: A fluid path between at least one cleaning unit (CIP) and the optional production unit in each combination is defined, and a rule for cleaning the corresponding optional production unit is obtained, wherein the time schedule is further generated according to the cleaning rule (604).

13. The computer-implemented method of any one of claims 1-3, wherein the optional production units include one or more of the following: a tank, a mixer, a filling machine, a packaging dispensing device, a packaging line, a separator, a homogenizer, and a thermal treatment unit.

14. The computer implemented method of claim 13, wherein the thermal processing unit is a heat exchanger.

15. A computer readable medium comprising computer instructions (1004) which, when executed by a processing device (1002), cause the processing device (1002) to perform the method according to any one of claims 1 to 14.

16. An apparatus (1000) for dimensioning a plant for producing packaged dairy products, the apparatus (1000) being configured to perform the method according to any one of claims 1 to 14.

Images