Method and apparatus for improving efficiency of a food production plant
By creating digital models and factory auxiliary libraries, artificial intelligence was used to optimize the equipment layout and operation of food production plants, solving the problem of low equipment layout and operation efficiency, achieving efficient and energy-saving production optimization, and reducing improvement costs.
Patent Information
- Application Number
- CN202180041639.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Priority Date
- 2020-06-12
- Filing Date
- 2021-05-28
- Publication Date
- 2026-02-17
- Estimated Expiration
- 2041-05-28
AI Technical Summary
Existing food production plants suffer from inefficiencies in equipment layout and operation optimization, which are difficult to improve, and the improvement process may lead to unnecessary side effects and production impacts.
By creating digital models and factory auxiliary libraries, improvements to production scenarios are identified and recommended, including optimization of equipment layout and operation methods. These improvements are matched and updated using artificial intelligence software, and are optimized independently of the control system.
It enables improvements in the efficiency and energy-saving effects of food production plants without affecting production, allows for the sharing of optimization knowledge among different control systems, and reduces improvement costs.
Smart Images
Figure CN115698883B_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present invention relates to software technology in food production. More particularly, it relates to a method and an arrangement for improving the efficiency of a food production plant, a server configured to improve the efficiency of a food production plant, and a method of creating a plant assistance library to be used for improving the efficiency of a food production plant. BACKGROUND
[0002] Today's food production plants are complex. One reason is that the food production units, such as heat exchangers, separators, homogenizers and fillers, that form part of the food production plant can be arranged differently, and the setup of one food production unit can not only affect the food production unit itself, but also other food production units placed downstream. Furthermore, the food production units can be placed in different orders. In addition, the food production plant can also be arranged with parallel production units, e.g. tanks, so that one tank can be used for production while another tank is cleaned. Thus, designing a food production plant requires both knowledge of the individual food production units, in the way these units can influence each other, and knowledge of the possible ways of operation of the food production plant on an overall level.
[0003] In addition to specifying that the food production plant is arranged in a way that enables production of food, it is most often also required that the equipment is arranged in a way that enables efficient production in terms of product waste, energy and time. Thus, in the food production industry today, new methods of improving the efficiency of the plant are constantly sought. Savings achieved in this way in terms of product, processing medium or energy can both save costs and the environment.
[0004] One way of improving the efficiency is to optimize the food production units. In order to improve on a line level or a plant level, changes can be made to the control system. However, it is not an easy task to identify possible improvements, and there is a risk that these changes result in unwanted side effects. Thus, testing possible improvements of a production plant can be a difficult and time-consuming process, and there is a risk of affecting ongoing production.
[0005] Based on the above, there is a need for a method or a tool for optimizing a production plant, so that more efficient production can be achieved. SUMMARY
[0006] It is an object of the present invention to at least partly overcome one or more of the above-mentioned limitations of the prior art. In particular, it is an object of the present invention to provide a method of improving the efficiency of a food production plant by providing a plant assistance library comprising production scenarios.
[0007] It has been recognized that knowledge gained in setting up or running a production plant can be efficiently shared by creating a digital model (sometimes referred to as a data model) of the production plant, and subsequently identifying possible improvements in the form of production scenarios (referred to as initial production scenarios), and how to change these scenarios (referred to as recommended production scenarios) to improve efficiency, with the help of a so-called plant assistance library. The plant assistance library can comprise the initial production scenarios as well as the recommended production scenarios. Both can comprise information about how the equipment (i.e. food production units) is arranged (referred to as initial equipment object arrangement and recommended equipment object arrangement, respectively) and how to use these arrangements (referred to as initial series of actions and recommended series of actions, respectively). By having these plant assistance objects and having a digital model for the production plant, it is thus possible to identify possible improvements, and suggest how to rearrange the food production units (this can be done by redirecting product flow using valves) and how to set up the food production units.
[0008] According to a first aspect, there is provided a method for improving efficiency of a food production plant, the method can comprise:
[0009] extracting plant data from a control system of the food production plant, wherein the control system can be communicatively connected to control units placed in food production units in the food production plant,
[0010] generating a digital model of the food production plant based on the plant data extracted from the control system, wherein the digital model can comprise equipment objects with actions linked thereto, connections between the equipment objects, and a series of actions linked to an equipment object arrangement,
[0011] downloading a plant assistance library that can comprise a plurality of assistance objects, each assistance object can comprise:
[0012] an initial production scenario comprising an initial series of actions linked to an initial equipment object arrangement, and
[0013] a recommended production scenario comprising a recommended series of actions linked to a recommended equipment object arrangement, wherein the recommended production scenario can result in an improved efficiency of the food production plant compared to the initial production scenario,
[0014] identifying a current equipment object arrangement in the digital model that can correspond to the initial equipment object arrangement of the matching assistance object’s initial production scenario,
[0015] replacing the current equipment object arrangement and the current series of activities linked to the current equipment object arrangement with the matching assistance object’s recommended equipment object arrangement and recommended series in the digital model,
[0016] transmitting update data to the control system, the update data can correspond to the recommended equipment object arrangement and the recommended series in the digital model,
[0017] updating the food production plant based on the update data.
[0018] The advantages of having a digital model for improving efficiency as described above is that the method can be independent of the control system. In other words, possible shortcomings in the control system do not hinder the digital model, because if it is not possible or convenient to retrieve plant data via the control system, the digital model can retrieve this data directly from sensors or control units in the food production unit. A further advantage related to this control system independence is that knowledge can be shared between food production plants using different types of control systems. Having a large number of food production plants makes it possible to implement a more comprehensive plant assistance library.
[0019] A further advantage is that it can be added to an existing food production plant. This is advantageous because it can be added to an installed and running food production plant at low cost, because the plant can continue to run at least to a large extent when the additional functionality is added.
[0020] The plant assistance library can be retrieved from a central server connected to a plurality of food production plants having a digital model, the central server can be configured to continuously record data from the digital models and create assistance objects based on the data.
[0021] The digital model can be independent of the control system type.
[0022] In order to enable efficient management of different types of control systems, it has been recognized that the digital model can be formed based on characteristics of the food production plant retrieved via the control system. In order to avoid control system type dependency, the characteristics can be converted to data model characteristics based on which the data model is built. Thus, if a central server is used to host the data model, the software in the central server for converting the characteristics to data model characteristics is sufficient to support different types of control systems.
[0023] The initial production scenario and the recommended production scenario can comprise a food product being produced, and food product characteristics associated with the food product being produced.
[0024] The advantage of having a food product as part of the initial production scenario and the recommended production scenario is that different food products can require different handling. For example, an orange juice product containing pulp can result in the use of a tubular heat exchanger without baffles to avoid fibers being stuck in the baffles, while a juice product without pulp can be used in a tubular heat exchanger with baffles.
[0025] The method can further comprise determining a current food conversion of the current equipment object arrangement and the current series of activities, and a recommended food conversion of the recommended series of actions linked to the recommended equipment object arrangement.
[0026] As different treatments (also referred to as processes) can result in different impacts on the properties of the food product, information about this can be added in the factory assistant object. An advantage of this is that a higher control over the food production factory can be provided.
[0027] The method can further comprise determining a current energy use of the current arrangement of equipment objects and the current series of activities, and a recommended energy use of the recommended series of actions linked to the recommended arrangement of equipment objects.
[0028] An advantage of this is that energy savings can easily be taken into account, which is advantageous as for example a trade-off between small differences in food product quality and energy savings can be made. In other words, this enables the food production factory to be optimized taking a broad range of aspects into account.
[0029] The method can further comprise determining a current production time of the current arrangement of equipment objects and the current series of activities, and a recommended production time of the recommended series of actions linked to the recommended arrangement of equipment objects.
[0030] As mentioned above, this enables a broad range of aspects to be taken into account when optimizing the food production factory.
[0031] The initial order in which the food production units are used in the initial production scenario can be different from the recommended order in which the food production units are used in the recommended production scenario.
[0032] The step of identifying the current arrangement of equipment objects in the digital model that corresponds to the initial arrangement of equipment objects of the initial production scenario of the matching assistant object can be performed by artificial intelligence (AI) based software, wherein the AI based software is trained on an approved digital model of the food production factory.
[0033] Identifying the corresponding arrangement of equipment objects can be a so-called one-to-one match, that is, the same equipment arrangement is required for the arrangements to be considered a match, but it can also not be required that they are exactly the same, but essentially the same. To be able to handle this situation, AI based software can come in handy. In case the recommended production scenario is considered successful, or in other words approved and introduced in the food production factory, the software can be trained on the digital model before and after the updating step.
[0034] According to a second aspect, a server configured to improve the efficiency of a food production factory is provided, the server comprising:
[0035] a transceiver configured to:
[0036] transmit, to the control system, update data corresponding to the recommended arrangement of equipment objects and the recommended series in the digital model,
[0037] a control circuit configured to perform:
[0038] an extraction function configured to extract plant data from a control system of a food production plant, wherein the control system is communicatively connected to control units placed in food production units in the food production plant,
[0039] a generation function configured to generate a digital model of the food production plant based on the plant data extracted from the control system, wherein the digital model comprises device objects with actions linked thereto, connections between the device objects, and a series of actions linked to a device object arrangement,
[0040] a download function configured to download a plant library comprising a plurality of helper objects, each helper object comprising:
[0041] an initial production scenario comprising an initial series of actions linked to an initial device object arrangement, and
[0042] a recommended production scenario comprising a recommended series of actions linked to a recommended device object arrangement, wherein the recommended production scenario results in an improved efficiency of the food production plant compared to the initial production scenario,
[0043] an identification function configured to identify a current device object arrangement in the digital model corresponding to the initial device object arrangement of the initial production scenario of the matching helper object,
[0044] a replacement function configured to replace the current device object arrangement and the current series of activities linked to the current equipment object arrangement with the recommended device object arrangement and the recommended series of the matching helper object in the digital model,
[0045] an update function configured to update the food production plant based on update data.
[0046] The control circuit can further be configured to perform:
[0047] a first determination function configured to determine a current food conversion of the current device object arrangement and the current series of activities, and a recommended food conversion of the recommended series of actions linked to the recommended device object arrangement.
[0048] The control circuit can further be configured to perform:
[0049] a second determination function configured to determine a current energy use of the current device object arrangement and the current series of actions, and a recommended energy use of the recommended series of actions linked to the recommended device object arrangement.
[0050] The control circuit can further be configured to perform:
[0051] a third determining function configured to determine a current production time for the current arrangement of equipment objects and the current series of activities, and a recommended production time for a recommended series of actions linked to a recommended arrangement of equipment objects.
[0052] According to a third aspect, there is provided a method of creating a factory assistance library to be used for improving the efficiency of a food production plant (100) according to the first aspect, wherein the method comprises:
[0053] receiving a digital model of a food production plant,
[0054] identifying corresponding production scenarios in the digital model,
[0055] selecting an initial production scenario in the corresponding production scenarios based on a first set of requirements, and
[0056] selecting a recommended production scenario in the corresponding scenarios based on a second set of requirements.
[0057] It is an advantage with having a first set of requirements for the initial production scenario and a second set of requirements for the recommended production scenario that these can be set such that only changes that will provide an improvement in efficiency above a certain threshold are suggested. The first set of requirements and the second set of requirements can partly correspond to each other.
[0058] According to a fourth aspect, there is provided a computer program comprising instructions for implementing the method of the first aspect.
[0059] Other objects, features, aspects and advantages of the present application will appear from the following detailed description, as well as from the drawings. The same features and advantages described in relation to one aspect apply to the other aspects, unless explicitly stated otherwise. BRIEF DESCRIPTION OF DRAWINGS
[0060] Embodiments of the present application will now be described, by way of example, with reference to the accompanying drawings, in which:
[0061] Figure 1 is a schematic illustration of a food production plant;
[0062] Figure 2 illustrates a server configured to improve the efficiency of a food production plant;
[0063] Figure 3 is a flow chart illustrating steps of a method of improving the efficiency of a food production plant;
[0064] Figure 4 is a flow chart illustrating steps of a method of creating a factory assistance library to be used for improving the efficiency of a food production plant. DETAILED DESCRIPTION
[0065] Figure 1An overview of a food production plant 100 is shown by way of example. The food production plant 100 can be described by plant data 102 which can be provided via a control system 104. The control system 104 can be connected to control units 105a-e placed in food production units 106a-e. The control units 105a-e can be programmable logic controllers (PLCs) or other similar types of devices which can be used for control in a food production plant. The food production units 106a-e can be food processing equipment such as heat exchangers, separators, homogenizers but also pipes, valves and pumps which do not directly participate in food processing. Further, the food production units 106a-e can be packaging equipment such as fillers but also so-called downstream equipment such as lidding machines, straw applicators and palletizers.
[0066] As shown, the food production units 106a-e can be arranged such that different food production lines can be implemented. In other words, the food production units 106a-e can be arranged such that food can be fed through different subgroups of the food production units 106a-e and also in different orders. In order to enable food to be fed through the food production units 106a-e in different ways, valve arrangements can be used.
[0067] The plant data 102 which can be extracted from the control system 104 can be fed to a server 107. In the server 107, a digital model 108 of the food production plant 100 can be generated. The digital model 108 can comprise device objects A-E corresponding to the food production units 106a-e. The device objects A-E can have linked actions i-xii. In case the device objects are tanks, the actions i-xii can for example be filling the tank, stirring the food in the tank with a stirrer at a first speed, stirring the food in the tank with the stirrer at a second speed, emptying the tank, etc. Connections I-V between different device objects A-E can be provided to reflect how food can be fed through the food production plant 100.
[0068] In order to improve the efficiency of the food production plant 100, a plant assistant library 110 can be downloaded. If only a part of the plant assistant library 110 is considered relevant, only this part of the plant assistant library 110 can be downloaded.
[0069] The plant assistant library 110 can comprise a plurality of different plant assistant objects comprising initial production scenarios linked to recommended production scenarios. Each of the initial production scenarios can comprise an initial series of actions linked to an initial device object arrangement and each of the recommended production scenarios can comprise a recommended series of actions linked to a recommended device object arrangement.
[0070] The current object arrangement, i.e. the currently used food production units 106a-e and their order of use, can be compared to different initial device object arrangements, whereby an initial production scenario 112 can be identified in which there is an initial device object arrangement that corresponds to the current object arrangement. Linked to the initial production scenario 112, a recommended production scenario 114 is provided and it can be said that these two form a matching auxiliary object 116, i.e. a plant auxiliary object that matches the current use of the food production units 106a-e.
[0071] After the matching auxiliary object 116 has been identified, the recommended production scenario 114 can be provided to the server 107, which in turn can provide information relating to the recommended production scenario 114 of the matching auxiliary object 116 to the control system 104 in the form of update data 118. The update data 118 can be information that can cause the food production to be changed to be performed in accordance with the recommended production scenario 114.
[0072] As Figure 1 As is provided by way of example in the
[0073] The plant auxiliary library 110 can be saved in a central server 120. The advantage of saving the plant auxiliary library 120 in this way is that this can be shared by different food production plants, which makes it possible for successful optimisations made in one food production plant to be easily shared with other plants.
[0074] Figure 2 A schematic diagram of the server 107 is shown. The server 107 can be configured to improve the efficiency of the food production plant 100. The server 107 can comprise a transceiver 202, a control circuit 204 and a memory 208.
[0075] The transceiver 202 can be configured to enable the server 107 to communicate with other devices, such as the control system of the food production plant 100. The transceiver 202 can be configured to transmit update data 118 corresponding to the recommended device object arrangement and the recommended series in the digital model 108 to the control system 104.
[0076] The control circuit 204 can be configured to perform control of the functions and operations of the server 107. The control circuit 204 can comprise a processor 206, e.g. a central processing unit (CPU). The processor 206 can be configured to execute program code stored in a memory 208 in order to perform the functions and operations of the server 107.
[0077] The control circuit 204 can perform an extraction function 210. The extraction function 210 can be configured to extract plant data 102 from a control system 104 of a food production plant 100, wherein the control system 104 can be communicatively connected to control units 105a-e placed in food production units 106a-e in the food production plant 100.
[0078] The control circuit 204 can perform a generation function 212. The generation function 212 can be configured to generate a digital model 108 of the food production plant 100 based on the plant data 102 extracted from the control system 104, wherein the digital model 108 can comprise equipment objects A-E with actions i-xii linked thereto, connections I-V between the equipment objects A-E, and a series of actions linked to the equipment object arrangement.
[0079] The control circuit 204 can perform a download function 214. The download function 214 can be configured to download a plant library 110 of auxiliary objects, each auxiliary object comprising:
[0080] an initial production scenario 112 comprising an initial series of actions linked to an initial equipment object arrangement, and
[0081] a recommended production scenario 114 comprising a recommended series of actions linked to a recommended equipment object arrangement, wherein the recommended production scenario 114 results in an improved efficiency of the food production plant 100 compared to the initial production scenario 112.
[0082] The control circuit 204 can perform an identification function 216. The identification function 216 can be configured to identify a current equipment object arrangement in the digital model 108 corresponding to the initial equipment object arrangement of the initial production scenario 112 of the matching auxiliary object 116.
[0083] The control circuit 204 can perform a replacement function 218. The replacement function 218 can be configured to replace the current equipment object arrangement and the current series of activities linked to the current equipment object arrangement with the recommended equipment object arrangement and the recommended series of actions of the matching auxiliary object in the digital model 108.
[0084] The control circuit 204 can perform an update function 220. The update function 220 can be configured to update the food production plant 100 based on the update data 118.
[0085] Optionally, the control circuit 204 can execute a first determining function 222. The first determining function 222 can be configured to determine a current food conversion of the current device object arrangement and the current series of activities, and a recommended food conversion of the recommended series of actions linked to the recommended device object arrangement.
[0086] Optionally, the control circuit 204 can execute a second determining function 224. The second determining function 224 can be configured to determine a current energy use of the current device object arrangement and the current series of activities, and a recommended energy use of the recommended series of actions linked to the recommended device object arrangement.
[0087] Optionally, the control circuit 204 can execute a third determining function 226. The third determining function 226 can be configured to determine a current production time of the current device object arrangement and the current series of activities, and a recommended production time of the recommended series of actions linked to the recommended device object arrangement.
[0088] Figure 3 is a flowchart showing steps of a method 300 for improving the efficiency of a food production plant.
[0089] In a first step 302, plant data can be extracted from a control system of the food production plant, wherein the control system can be communicatively connected to control units placed in food production units in the food production plant.
[0090] In a second step 304, a digital model of the food production plant can be generated based on the plant data extracted from the control system, wherein the digital model can comprise device objects with actions linked thereto, connections between the device objects, and a series of actions linked to a device object arrangement.
[0091] In a third step 306, a plant assistant library can be downloaded, which comprises a plurality of assistant objects, each comprising:
[0092] an initial production scenario comprising an initial series of actions linked to an initial device object arrangement, and
[0093] a recommended production scenario comprising a recommended series of actions linked to a recommended device object arrangement, wherein the recommended production scenario can result in an improved efficiency of the food production plant compared to the initial production scenario.
[0094] In a fourth step 308, a current device object arrangement in the digital model 108 corresponding to the initial device object arrangement of the initial production scenario 112 of the matching assistant object 116 can be identified.
[0095] In a fifth step 310, the current device object arrangement and the current series activities linked with the current device object arrangement can be replaced with the recommended device object arrangement of the matching auxiliary object in the digital model 108 and the recommended series of the recommended device object arrangement.
[0096] In a sixth step 312, update data 118 corresponding to the recommended device object arrangement and the recommended series in the digital model 108 can be transmitted to the control system 104.
[0097] In a seventh step 314, the food production plant 100 can be updated based on the update data 118.
[0098] Optionally, in an eighth step 316, a current food conversion of the current device object arrangement and the current series activities, and a recommended food conversion of the recommended series actions linked with the recommended device object arrangement can be determined.
[0099] Optionally, in a ninth step 318, a current energy usage of the current device object arrangement and the current series activities, and a recommended energy usage of the recommended series actions linked with the recommended device object arrangement can be determined.
[0100] Optionally, in a tenth step 320, a current production time of the current device object arrangement and the current series activities, and a recommended production time of the recommended series actions linked with the recommended device object arrangement can be determined.
[0101] Even if described in a particular order, the steps can be performed in other orders.
[0102] Figure 4 is a flowchart showing steps of a method 400 for creating a plant auxiliary library 110 to be used for improving the efficiency of a food production plant 100 as described above.
[0103] In a first step 402, a digital model of a food production plant can be received.
[0104] In a second step 404, a corresponding production scenario in the digital model can be identified.
[0105] In a third step 406, an initial production scenario 112 can be selected in the corresponding production scenario based on the first set of requirements.
[0106] In a fourth step 408, a recommended production scenario 114 can be selected in the corresponding scenario based on the second set of requirements.
[0107] As can be seen from the above description, although various embodiments of the application have been described and shown, the application is not limited thereto, but can also be implemented in other ways within the scope of the subject matter defined in the following claims.
Claims
1. A method (300) for improving the efficiency of a food production plant (100), the method comprising: Factory data (102) is extracted from the control system (104) of the food production plant (100), wherein the control system (104) is communicatively connected to a control unit (105a-e) located in a food production unit (106a-e) within the food production plant (100), the food production unit including a heat exchanger, separator, homogenizer, or filling machine. A digital model (108) of the food production plant (100) is generated based on the factory data (102) extracted from the control system (104), wherein the digital model (108) includes equipment objects (AEs) with actions (i-xii) linked to them, connections (IVs) between the equipment objects (AEs), and a series of actions linked to the arrangement of the equipment objects. Download the factory helper library (110) which includes multiple helper objects, each of which includes: The initial production scenario (112) includes the initial series of actions linked to the initial equipment object arrangement, and The recommended production scenario (114) includes a series of recommended actions linked to the placement of recommended equipment objects, wherein the recommended production scenario (114) improves the efficiency of the food production plant (100) compared to the initial production scenario (112), wherein the initial production scenario (112) and the recommended production scenario (114) include the food being produced and the food characteristics associated with the food being produced, and the auxiliary objects include different processing requirements for different foods. Identify the current equipment object arrangement in the digital model (108) that corresponds to the initial equipment object arrangement of the initial production scenario (112) of the matching auxiliary object (116). Replace the current device object arrangement and the current series of activities linked to the current device object arrangement with the recommended device object arrangement and the recommended series of actions of the matching auxiliary object in the digital model (108). Update data (118) is transmitted to the control system (104), the update data (118) corresponding to the recommended equipment object arrangement and the recommended series of actions in the digital model (108). The food production plant (100) is updated based on the updated data (118).
2. The method of claim 1, wherein the plant auxiliary library (110) is retrieved from a central server (120) connected to a plurality of food production plants having digital models, the central server (120) being configured to continuously record data from the digital models and create auxiliary objects based on the data.
3. The method according to claim 1 or 2, wherein the digital model (108) is independent of the control system type.
4. The method according to claim 1, further comprising: Determine the current food transition of the current device object layout and the current series of activities, as well as the recommended food transition of the recommended series of actions linked to the recommended device object layout.
5. The method according to claim 1, 2, or 4, further comprising: Determine the current energy usage of the current device object layout and the current series of activities, as well as the recommended energy usage of the recommended series of actions linked to the recommended device object layout.
6. The method according to claim 1, 2, or 4, further comprising: Determine the current production time of the current equipment object layout and the current series of activities, as well as the recommended production time of the recommended series of actions linked to the recommended equipment object layout.
7. The method according to claim 1, 2 or 4, wherein the initial order of using the food production units (106a-e) in the initial production scenario (112) is different from the recommended order of using the food production units (106a-e) in the recommended production scenario (114).
8. The method according to claim 1, 2 or 4, wherein the step of identifying the current equipment object arrangement in the digital model (108) corresponding to the initial equipment object arrangement of the initial production scenario (112) of the matching auxiliary object (116) is performed by artificial intelligence (AI) based software, wherein the AI based software is trained on an approved digital model of a food production plant.
9. A server (107) configured to improve the efficiency of a food production plant (100), said server (107) comprising: Transceiver (202), which is configured as follows: The updated data (118) corresponding to the recommended equipment object layout and recommended series of actions in the digital model (108) is transmitted to the control system (104). Control circuit (204), which is configured to execute: An extraction function (210) is configured to extract plant data (102) from a control system (104) of the food production plant (100), wherein the control system (104) is communicatively connected to a control unit (105a-e) located in a food production unit (106a-e) within the food production plant (100), the food production unit including a heat exchanger, separator, homogenizer, or filling machine. A generation function (212) is configured to generate a digital model (108) of the food production plant (100) based on the plant data (102) extracted from the control system (104), wherein the digital model (108) includes equipment objects (AEs) with actions (i-xii) linked to them, connections (IVs) between the equipment objects (AEs), and a series of actions linked to the arrangement of the equipment objects. A download function (214) is configured to download a factory auxiliary library (110) comprising multiple auxiliary objects, each auxiliary object including: The initial production scenario (112) includes the initial series of actions linked to the initial equipment object arrangement, and The recommended production scenario (114) includes a series of recommended actions linked to the placement of recommended equipment objects, wherein the recommended production scenario (114) improves the efficiency of the food production plant (100) compared to the initial production scenario (112), wherein the initial production scenario (112) and the recommended production scenario (114) include the food being produced and the food characteristics associated with the food being produced, and the auxiliary objects include different processing requirements for different foods. The identification function (216) is configured to identify the current device object arrangement in the digital model (108) that corresponds to the initial device object arrangement of the initial production scenario (112) of the matching auxiliary object (116). The replacement function (218) is configured to replace the current device object arrangement and the current series of activities linked to the current device object arrangement with the recommended device object arrangement and the recommended series of actions of the matching auxiliary object in the digital model (108). An update function (220) is configured to update the food production plant (100) based on the update data (118).
10. The server (107) according to claim 9, wherein the control circuit (204) is further configured to perform: A first determining function (222) is configured to determine the current food transition of the current device object arrangement and the current series of activities, as well as the recommended food transition of the recommended series of actions linked to the recommended device object arrangement.
11. The server (107) according to claim 9 or 10, wherein the control circuit (204) is further configured to perform: The second determination function (224) is configured to determine the current energy usage of the current device object arrangement and the current series of activities, as well as the recommended energy usage of the recommended series of actions linked to the recommended device object arrangement.
12. The server (107) according to claim 9 or 10, wherein the control circuit (204) is further configured to perform: A third determination function (226) is configured to determine the current production time of the current device object arrangement and the current series of activities, as well as the recommended production time of the recommended series of actions linked to the recommended device object arrangement.
13. A method (400) for creating a factory auxiliary library (110), said factory auxiliary library (110) being used to improve the efficiency of a food production factory (100) according to any one of claims 1 to 8, said method comprising: Receive digital models of food production plants. Identify the corresponding production scenario in the digital model. Based on the first demand set, the initial production scenario (112) is selected in the corresponding production scenario, and Based on the second set of requirements, the recommended production scenario (114) is selected in the corresponding scenario.
14. A computer program comprising instructions for implementing the method according to any one of claims 1 to 8.
Citation Information
Patent Citations
Industrial machine diagnosis and maintenance using a cloud platform
US20170351226A1