A comprehensive management device and method for multiple types of food processing machinery

Abstract

The present invention provides a comprehensive management device and method for multiple types of food processing machines, wherein the device includes: an identification module for continuously identifying whether multiple types of food processing machines have triggered an optimization management opportunity; a decision module for starting to make a decision on an optimization management strategy based on the processing operation information of each food processing machine in a first time period whenever it is identified as a trigger to enter the optimization management opportunity; wherein the first time period is a preset first time period before and after the moment when the optimization management opportunity is identified; a first management module for optimizing and managing each food processing machine in a second time period based on the optimization management strategy when the decision is completed; wherein the second time period is a preset second time period after the moment when the decision is completed. The global optimization of multiple food processing machines in the entire production line greatly improves the production efficiency of the food processing production line.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent mechanical management, and in particular to a comprehensive management device and method for multiple types of food processing machinery. Background Art

[0002] In the modern food processing industry, with the continuous expansion of production scale and the increasing diversification of equipment types, various types of food processing machinery are playing an increasingly important role in the process.

[0003] However, with the increase in the number and complexity of equipment, there are many challenges in optimizing the performance of different equipment and improving overall production efficiency. Especially in an environment where multiple types of equipment work together, how to maximize production efficiency through scientific and effective management and scheduling has become an urgent problem to be solved.

[0004] Traditional equipment management methods often focus on the monitoring and scheduling of a single device, lacking the global optimization of multiple food processing machines in the entire production line. How to monitor the operating status of each device in real time, discover potential optimization opportunities in a timely manner, and adopt precise management strategies based on specific working conditions and needs has become the key to improving production efficiency. However, most current technologies rely on manual intervention or simple time scheduling methods, and cannot achieve intelligent optimization decisions.

[0005] Therefore, a practical solution is urgently needed. Summary of the invention

[0006] The present invention provides a comprehensive management device and method for multiple types of food processing machines, which continuously identify whether each type of food processing machine has triggered an optimization management opportunity, so as to timely discover potential optimization opportunities. When the optimization management opportunity is identified and triggered, an optimization management strategy is decided based on the processing operation information of each food processing machine in a first time period. When the decision is made, each food processing machine is optimized and managed in a second time period based on the optimization management strategy, so as to adopt precise management strategies according to specific working conditions and needs, and globally optimize multiple food processing machines in the entire production line, thereby greatly improving the production efficiency of the food processing production line.

[0007] The present invention provides a comprehensive management device for multiple types of food processing machines, comprising:

[0008] Identification module, used to continuously identify whether various types of food processing machinery have triggered the opportunity to enter optimization management;

[0009] A decision-making module, for starting to decide on an optimization management strategy based on processing operation information of each food processing machine in a first time period whenever it is identified as a triggering time to enter optimization management; wherein the first time period is a preset first time period before and after the moment when it is identified as a triggering time to enter optimization management;

[0010] The first management module is used to optimize the management of each food processing machine within a second time period based on the optimization management strategy when the decision is completed; wherein the second time period is a second time period preset after the moment when the decision is completed.

[0011] Optionally, the identification module continuously identifies whether each type of food processing machine triggers an optimization management opportunity, including:

[0012] Whenever each food processing machine generates incremental dynamics, if the incremental dynamics correspond to a leaf node in the situation graph, an attempt is made to trace the history of multiple target nodes for each food processing machine; wherein the multiple target nodes include: non-leaf nodes and leaf nodes on other paths connected to the root node of the path where the leaf node is located in the situation graph;

[0013] When the proportion of successful tracing attempts exceeds the threshold of the successful tracing ratio, it is determined that each food processing machine is triggered to enter the optimization management time; wherein the proportion of successful tracing attempts is the ratio of the number of target leaf nodes that have been successfully traced to the total number of target leaf nodes; the threshold of the successful tracing ratio is greater than the total number of other paths connected to the root node;

[0014] and / or,

[0015] Continuously determining the trigger detection angle of view and the trigger detection mechanism from the panoramic monitoring map of each food processing machine; wherein the first monitoring element set that has fallen into the trigger detection angle of view and the second monitoring element set that is about to fall into the trigger detection angle of view respectively meet the first element set condition and the second element set condition in the same standard condition combination, and the trigger detection mechanism is the standard mechanism corresponding to the same standard condition combination;

[0016] Based on the trigger detection mechanism, trigger detection is performed according to the trigger detection perspective;

[0017] When the trigger detects the corresponding content, it determines the timing for each food processing machine to be triggered to enter optimized management.

[0018] Optionally, the decision module starts to make decisions on the optimization management strategy based on the processing operation information of each food processing machine in the first period, including:

[0019] Analyze processing operation information, determine the problems to be optimized and the applicable evaluation basis;

[0020] Based on the applicable evaluation basis, multiple optimization management knowledge for the optimization problem are evaluated for their applicability respectively, and the knowledge evaluation value ranking is obtained;

[0021] Performing feature description on the knowledge evaluation value ranking to obtain feature descriptors;

[0022] Based on the knowledge indication rules corresponding to the feature descriptors, the knowledge indicated is determined from each optimization management knowledge;

[0023] When the knowledge indicated by the indication is unique, the decision-making optimization management strategy begins based on the knowledge indicated by the indication; otherwise, the interactively assisted decision makers begin to decide on the optimization management strategy based on the knowledge indicated by the indication.

[0024] Optionally, the decision module interactively assists the decision maker to start making a decision on the optimization management strategy based on the knowledge indicated by the instruction, including:

[0025] Expand the knowledge referred to by the indication through management stages and obtain multiple management stage sequences;

[0026] Based on the display content determination rule, the display content is determined according to the target knowledge set; wherein the target knowledge set includes: the stage knowledge of the i-th management stage of each management stage sequence;

[0027] Whenever the determination is completed, the presentation content is presented to the decision maker, and the decision maker receives the stage strategy determined from the presentation content or formulated based on the presentation content;

[0028] When no longer starting to determine new display content, integrate phase strategies to obtain optimized management strategies;

[0029] The display content determination rules include:

[0030] Each time i changes from 1 to N1, when the stage knowledge in the target knowledge set is different from each other, the stage strategy most relevant to the formulated strategy library is determined from the target knowledge set as the display content; otherwise, the stage strategy most relevant to the formulated strategy library and / or the determined strategy library is determined from the target knowledge set as the display content;

[0031] Each time i changes from N1+1 to N2, when the larger of the relevance between the stage knowledge in the target knowledge set and the formulated strategy library and the determined strategy library exceeds the relevance threshold, all the stage knowledge in the target knowledge set is used as the display content; otherwise, the display content is set as blank;

[0032] Among them, N1 is the minimum number of management stages in each management stage sequence, and N2 is the maximum number of management stages in each management stage sequence.

[0033] Optional, integrated management device for multiple types of food processing machinery, including:

[0034] The second management module is used for:

[0035] In the second period, based on the optimization management feedback of each food processing machine, the optimization management strategy is adjusted, and based on the adjusted optimization management strategy, each food processing machine is optimized and managed in a relay manner.

[0036] The present invention provides a comprehensive management method for multiple types of food processing machinery, comprising:

[0037] Continuously identify whether various types of food processing machinery have triggered the opportunity to enter optimized management;

[0038] Whenever it is identified as a trigger to enter the optimization management opportunity, the optimization management strategy is decided based on the processing operation information of each food processing machine in the first time period; wherein the first time period is a preset first time period before and after the moment when it is identified as a trigger to enter the optimization management opportunity;

[0039] When the decision is made, each food processing machine is optimally managed within a second time period based on the optimization management strategy; wherein the second time period is a second time period preset after the moment when the decision is made.

[0040] Optionally, the continuously identifying whether each type of food processing machinery triggers an opportunity to enter optimization management includes:

[0041] Whenever each food processing machine generates incremental dynamics, if the incremental dynamics correspond to a leaf node in the situation graph, an attempt is made to trace the history of multiple target nodes for each food processing machine; wherein the multiple target nodes include: non-leaf nodes and leaf nodes on other paths connected to the root node of the path where the leaf node is located in the situation graph;

[0042] When the proportion of successful tracing attempts exceeds the threshold of the successful tracing ratio, it is determined that each food processing machine is triggered to enter the optimization management time; wherein the proportion of successful tracing attempts is the ratio of the number of target leaf nodes that have been successfully traced to the total number of target leaf nodes; the threshold of the successful tracing ratio is greater than the total number of other paths connected to the root node;

[0043] and / or,

[0044] Continuously determining the trigger detection angle of view and the trigger detection mechanism from the panoramic monitoring map of each food processing machine; wherein the first monitoring element set that has fallen into the trigger detection angle of view and the second monitoring element set that is about to fall into the trigger detection angle of view respectively meet the first element set condition and the second element set condition in the same standard condition combination, and the trigger detection mechanism is the standard mechanism corresponding to the same standard condition combination;

[0045] Based on the trigger detection mechanism, trigger detection is performed according to the trigger detection perspective;

[0046] When the trigger detects the corresponding content, it determines the timing for each food processing machine to be triggered to enter optimized management.

[0047] Optionally, starting to make decisions on the optimization management strategy based on the processing operation information of each food processing machine in the first period includes:

[0048] Analyze processing operation information, determine the problems to be optimized and the applicable evaluation basis;

[0049] Based on the applicable evaluation basis, multiple optimization management knowledge for the optimization problem are evaluated for their applicability respectively, and the knowledge evaluation value ranking is obtained;

[0050] Performing feature description on the knowledge evaluation value ranking to obtain feature descriptors;

[0051] Based on the knowledge indication rules corresponding to the feature descriptors, the knowledge indicated is determined from each optimization management knowledge;

[0052] When the knowledge indicated by the indication is unique, the decision-making optimization management strategy begins based on the knowledge indicated by the indication; otherwise, the interactively assisted decision makers begin to decide on the optimization management strategy based on the knowledge indicated by the indication.

[0053] Optionally, the interactive auxiliary decision-maker starts to make a decision on the optimization management strategy based on the knowledge indicated by the instruction, including:

[0054] Expand the knowledge referred to by the indication through management stages and obtain multiple management stage sequences;

[0055] Based on the display content determination rule, the display content is determined according to the target knowledge set; wherein the target knowledge set includes: the stage knowledge of the i-th management stage of each management stage sequence;

[0056] Whenever the determination is completed, the presentation content is presented to the decision maker, and the decision maker receives the stage strategy determined from the presentation content or formulated based on the presentation content;

[0057] When no longer starting to determine new display content, integrate phase strategies to obtain optimized management strategies;

[0058] The display content determination rules include:

[0059] Each time i changes from 1 to N1, when the stage knowledge in the target knowledge set is different from each other, the stage strategy most relevant to the formulated strategy library is determined from the target knowledge set as the display content; otherwise, the stage strategy most relevant to the formulated strategy library and / or the determined strategy library is determined from the target knowledge set as the display content;

[0060] Each time i changes from N1+1 to N2, when the larger of the relevance between the stage knowledge in the target knowledge set and the formulated strategy library and the determined strategy library exceeds the relevance threshold, all the stage knowledge in the target knowledge set is used as the display content; otherwise, the display content is set as blank;

[0061] Among them, N1 is the minimum number of management stages in each management stage sequence, and N2 is the maximum number of management stages in each management stage sequence.

[0062] Optional, integrated management approach for multiple types of food processing machinery, also includes:

[0063] In the second period, based on the optimization management feedback of each food processing machine, the optimization management strategy is adjusted, and based on the adjusted optimization management strategy, each food processing machine is optimized and managed in a relay manner.

[0064] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0065] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0067] Figure 1 is a schematic diagram of a comprehensive management device for multiple types of food processing machines in an embodiment of the present invention;

[0068] Figure 2 The present invention is a flowchart of a comprehensive management method for multiple types of food processing machines in an embodiment of the present invention. DETAILED DESCRIPTION

[0069] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0070] The present invention provides a comprehensive management device for various types of food processing machinery, such as Figure 1 As shown, including:

[0071] Identification module 1, used to continuously identify whether various types of food processing machines have triggered the opportunity to enter optimization management;

[0072] Decision module 2, used for starting to decide on the optimization management strategy based on the processing operation information of each food processing machine in a first time period whenever it is identified as a triggering time to enter the optimization management; wherein the first time period is a preset first time period before and after the moment when it is identified as a triggering time to enter the optimization management;

[0073] The first management module 3 is used to optimize the management of each food processing machine within a second time period based on the optimization management strategy when the decision is completed; wherein the second time period is a preset second time period after the moment when the decision is completed.

[0074] Multi-type food processing machinery refers to different types of food processing machinery in the food processing site. Taking the pepper processing site as an example, there are pepper grinding equipment, pepper pigment production equipment, pepper powder mixing equipment, pepper drying equipment, pepper selection equipment, etc.; the optimization management opportunity refers to the opportunity to optimize the management of each food processing machinery; the processing operation information includes: equipment status, operating parameters, operators, processing rate, yield rate, waste and loss, energy usage, etc.; when the identification triggers the optimization management opportunity, it means that each food processing machinery can be optimized, and it is necessary to make decisions on the optimization management strategy based on the historical and future processing operations of each food processing machinery. Therefore, the first time period is set to be within the first preset time length before and after the moment identified as the trigger to enter the optimization management opportunity; the first time length can be, for example, 10 minutes; when the optimization management strategy decision is completed, the food processing machinery is optimized and managed based on the optimization management strategy; the second time length can be, for example, 20 minutes, when a new optimization management opportunity is triggered, a new optimization management strategy decision and execution can be made again; the second time length can also be instructed by the optimization management strategy, that is, how long the optimization management strategy needs to be executed is how long the second time length is set; optimization management refers to the global optimization of various types of food processing machinery to improve the efficiency of their collaborative work, thereby improving production efficiency.

[0075] The present application continuously identifies whether various types of food processing machinery have triggered the opportunity to enter optimized management, so as to timely discover potential optimization opportunities. When the opportunity to enter optimized management is triggered, the optimization management strategy is decided based on the processing operation information of each food processing machinery in the first time period. When the decision is made, the optimization management of each food processing machinery is performed in the second time period based on the optimization management strategy, so as to adopt precise management strategies according to specific working conditions and needs, and globally optimize various food processing machinery in the entire production line, thereby greatly improving the production efficiency of the food processing production line.

[0076] In one embodiment, the identification module continuously identifies whether each of the multiple types of food processing machines triggers an optimization management opportunity, including:

[0077] S111. Whenever each food processing machine generates incremental dynamics, if the incremental dynamics correspond to a leaf node in the situation graph, try to trace the history of multiple target nodes for each food processing machine; wherein the multiple target nodes include: non-leaf nodes and leaf nodes on other paths connected to the root node of the path where the leaf node is located in the situation graph; wherein, in step S111, there are multiple tree structures in the situation graph, each tree structure includes a root node, multiple paths connected to the root node, non-leaf nodes in the middle of each path connected in sequence on each path, and leaf nodes at the end of the path, the root node represents a situation that requires optimized management of each food processing machine, the non-leaf nodes and leaf nodes connected in sequence on a path represent the development and change of a situation element in the situation, and the leaf node is the final change state of the situation element, for example: The root node represents the situation where the raw materials for pepper grinding equipment are insufficient. The non-leaf nodes and leaf nodes connected in sequence on a path represent the development and change of the remaining proportion of raw materials for pepper grinding equipment in this situation from 20% to 18% and then to 15%; the incremental dynamics refer to the latest changes in the dynamics of each food processing machinery, for example: the newly updated remaining raw materials of pepper grinding equipment; when the incremental dynamics correspond to leaf nodes in the situation map, it means that each food processing machinery has already experienced a situation in which a situation element in the situation represented by the root node of the path where the leaf node is located has changed to the final state, and the situation represented by the root node of the path where the leaf node is located may appear, and the history of multiple target nodes of each food processing machinery is traced back; historical tracing refers to searching whether each food processing machinery has produced the state represented by the target node in history;

[0078] S112, when the proportion of successful tracing attempts exceeds the threshold of the proportion of successful tracing attempts, determine the timing for each food processing machine to trigger the optimization management; wherein the proportion of successful tracing attempts is the ratio of the number of target leaf nodes that have been successfully traced to the total number of target leaf nodes; the threshold of the proportion of successful tracing attempts is greater than the total number of other paths connected to the root node; wherein, in step S112, when the proportion of successful tracing attempts exceeds the threshold of the proportion of successful tracing attempts, it indicates that the probability that the situation represented by the root node of the path where the leaf node is located is relatively high for each food processing machine at present, and then determine the timing for each food processing machine to trigger the optimization management; the change of the situation element represented by the path where the leaf node is located has ended, and the other paths connected to the root node represent the change state of the remaining situation elements in the situation represented by the root node, ensuring that the threshold of the proportion of successful tracing attempts is greater than the total number of other paths connected to the root node, so that when the proportion of successful tracing attempts exceeds the threshold of the proportion of successful tracing attempts, it is sufficient to indicate that the probability that the situation represented by the root node of the path where the leaf node is located is relatively high for each food processing machine at present;

[0079] and / or,

[0080] S121. Continuously determine the trigger detection perspective and trigger detection mechanism from the panoramic monitoring map of each food processing machine; wherein, the first monitoring element set that has fallen into the trigger detection perspective and the second monitoring element set that is about to fall into the trigger detection perspective each respectively meet the first element set condition and the second element set condition in the same standard condition combination, and the trigger detection mechanism is the standard mechanism corresponding to the same standard condition combination; wherein, in step S121, the panoramic monitoring map is a three-dimensional map of the three-dimensional restoration of the food processing site, on which there are three-dimensional models corresponding to each food processing machine, and the working status of the corresponding food processing machine is also marked next to the three-dimensional model; the trigger detection perspective and the trigger detection mechanism correspond one-to-one, the trigger detection perspective is a virtual perspective set in the panoramic monitoring map, and the trigger detection mechanism indicates how to perform trigger detection within the virtual perspective; different standard condition combinations are pre-set, each standard condition combination contains the first element set condition and the second element set condition, When the first monitoring element set entering the trigger detection perspective meets the first element set conditions and the second monitoring element set that is about to fall into the trigger detection perspective meets the second element set conditions, the corresponding trigger detection perspective can be effective. The standard condition combination pre-sets the standard mechanism, and the corresponding standard mechanism can be used as the trigger detection mechanism. For example: the first element set conditions and the second element set conditions in the same standard condition combination are respectively the required processing raw material quantity of the chili grinding equipment contained in the set and the cargo capacity of the Agv trolley that delivers goods to the chili grinding equipment. When the first monitoring element set and the second monitoring element set meet the first element set conditions and the second element set conditions respectively, the trigger detection perspective only needs to remain unchanged, and the Agv trolley is about to enter the trigger detection perspective. The corresponding standard mechanism is set to detect whether the cargo capacity of the Agv trolley that delivers goods to the chili grinding equipment is lower than the required processing raw material quantity of the chili grinding equipment. When detected, it means that the supply is insufficient, and it is determined to enter the trigger to enter the optimization management timing;

[0081] S122, performing trigger detection based on a trigger detection mechanism and a trigger detection perspective;

[0082] S123. When the trigger detects the corresponding content, determine the timing for each food processing machine to be triggered to enter optimization management.

[0083] The above technical scheme of the embodiment of the present invention determines whether each food processing machine triggers the optimization management opportunity through the situation map, thereby improving the determination efficiency; secondly, if the incremental dynamics correspond to a leaf node in the situation map and then start historical tracing, the historical tracing resources are reduced and the historical tracing efficiency is improved; when the proportion of successful tracing attempts exceeds the threshold of the successful tracing proportion, it is determined that each food processing machine triggers the optimization management opportunity, thereby improving the accuracy and comprehensiveness of the optimization management opportunity triggering determination.

[0084] The above-mentioned other technical scheme of the embodiment of the present invention determines the trigger detection angle of view and the trigger detection mechanism in the panoramic monitoring map, and performs trigger detection based on the trigger detection mechanism and the trigger detection angle of view, so as to determine whether each food processing machine is triggered to enter the optimization management opportunity, thereby improving the accuracy and comprehensiveness of the determination of the trigger entry of the optimization management opportunity.

[0085] In one embodiment, the decision module starts to make decisions on the optimization management strategy based on the processing operation information of each food processing machine in the first period, including:

[0086] S21, analyzing the processing operation information, determining the problem to be optimized and the applicable evaluation basis; wherein, in step S21, the problem to be optimized is the problem that each food processing machine needs to be optimized and managed as reflected in the processing operation information, and the applicable evaluation basis is the basis for evaluating the degree to which the optimization management knowledge is applicable to the problem, for example, if the problem to be optimized is the insufficient supply of raw materials for pepper grinding equipment, then the applicable evaluation basis is the type of raw materials, the agreed time of the order of pepper powder, etc.;

[0087] S22, based on the applicable evaluation basis, respectively perform applicable evaluation on multiple optimization management knowledge of the optimization problem to be optimized, and obtain the knowledge evaluation value ranking; wherein, in step S22, multiple optimization management knowledge are pre-set for the problem to be optimized, and the optimization management knowledge is the expert experience indicating how to deal with the problem to be optimized; when performing the applicable evaluation, based on the applicable evaluation basis, the degree to which the optimization management knowledge is applicable to the problem to be optimized is evaluated, that is, the knowledge evaluation value, for example: the type of processing raw materials applicable in the optimization management knowledge and the agreed order time of the chili powder are consistent with the applicable evaluation basis, then the knowledge evaluation value of the optimization management knowledge is 10, and finally, the knowledge evaluation values ​​of each optimization management knowledge are ranked from large to small to obtain the knowledge evaluation value ranking; specifically, the rules for performing the applicable evaluation can also be set in advance by technical personnel according to actual needs;

[0088] S23, performing feature description on the knowledge evaluation value ranking to obtain a feature descriptor; wherein, in step S23, when performing feature description, the knowledge evaluation value ranking may be represented by a vector, and the represented vector is used as the feature descriptor;

[0089] S24, based on the knowledge indication rule corresponding to the feature descriptor, determine the indicated knowledge from each optimization management knowledge; wherein, in step S24, the feature descriptor pre-sets the knowledge indication rule, and the knowledge indication rule indicates how to make a decision on the optimization management strategy based on each optimization management knowledge, for example: the maximum knowledge evaluation value in the knowledge evaluation value ranking is 10, which is the full quota, and the remaining knowledge evaluation values ​​are smaller, such as 3 and 2, which means that the optimization management knowledge corresponding to the maximum knowledge evaluation value is the most applicable, and it is used as the indicated knowledge, and the indicated knowledge is unique. For another example: the knowledge evaluation values ​​of the first three optimization management knowledge in the knowledge evaluation value ranking are 8, 7, and 6, which means that the applicability level of the optimization management knowledge is equivalent, but has not reached the full quota, and can be used together as the indicated knowledge to assist decision makers, and the indicated knowledge is not unique;

[0090] S25. When the knowledge indicated by the indication is unique, the decision-making optimization management strategy is started based on the knowledge indicated by the indication; otherwise, the interactive auxiliary decision-maker starts the decision-making optimization management strategy based on the knowledge indicated by the indication.

[0091] The above-mentioned technical scheme of the embodiment of the present invention, when starting to decide on the optimization management strategy based on the processing operation information of each food processing machine in the first time period, performs applicable evaluation on multiple optimization management knowledge of the optimization problem based on the applicable evaluation basis, and performs feature description on the ranking of the knowledge evaluation values ​​obtained by the evaluation. Based on the knowledge indication rule corresponding to the feature descriptor obtained by the feature description, the knowledge indicated by the indication is determined from each optimization management knowledge, and the method of optimizing the management strategy decision is comprehensively determined according to whether the knowledge indicated by the indication is unique. This greatly improves the accuracy and comprehensiveness of the optimization management strategy decision, avoids decision-making obstacles caused by insufficient optimization management knowledge, and greatly improves the applicability of the system. At the same time, it is also more intelligent.

[0092] In one embodiment, the decision module interactively assists the decision maker to start making decisions on the optimization management strategy based on the knowledge indicated by the instruction, including:

[0093] S251, expand the management stage of the knowledge indicated by the indication to obtain multiple management stage sequences; wherein, in step S251, when expanding the management stage, the sequential management stages of optimizing management of each food processing machine indicated by the knowledge indicated by the indication and the corresponding stage knowledge of each management stage are analyzed to form a management stage sequence; the stage knowledge indicates how to optimize management of the food processing machine in a single management stage; in addition, when expanding the management stage, it is ensured that the first N1 management stages in each management stage sequence are the same;

[0094] S252, based on the display content determination rule, starting to determine the display content according to the target knowledge set; wherein the target knowledge set includes: the stage knowledge of the i-th management stage of each management stage sequence;

[0095] S253, whenever the determination is completed, the display content is displayed to the decision-maker, and the stage strategy determined by the decision-maker from the display content or formulated based on the display content is received; wherein, in step S253, when the display content is displayed to the decision-maker, the decision-maker will receive the best assistance, so as to determine the stage strategy from the display content or formulate the stage strategy based on the display content, and the stage strategy can be used as the strategy implemented in the corresponding management stage in the optimization management strategy of the final decision;

[0096] S254, when no new display content is determined, the stage strategies are integrated to obtain an optimized management strategy; wherein, in step S253, when no new display content is determined, it means that the interactive assistance is ended, the decision maker has also made a decision, and the stage strategies are integrated to obtain an optimized management strategy;

[0097] The display content determination rules include:

[0098] Rule A1, each time i changes from 1 to N1, when the stage knowledge in the target knowledge set is different, the stage strategy most relevant to the formulated strategy library is determined from the target knowledge set as the display content; otherwise, the stage strategy most relevant to the formulated strategy library and / or the determined strategy library is determined from the target knowledge set as the display content; wherein, in Rule A1, the formulated strategy library contains stage strategies that have been formulated by decision makers in the history of this decision, and also stage strategies formulated by decision makers when making optimization decisions on other problems to be optimized that are the same as the problem to be optimized; the determined strategy library contains stage strategies that have been determined from the display content by decision makers in the history of this decision; when the target knowledge set When the stage knowledge in the target knowledge set is different from each other, it means that the stage knowledge is quite different. If all the stage knowledge in the target knowledge set is directly output, it will interfere with the decision-making of the decision-makers and make it difficult for them to make a decision. However, the established strategy library represents the subjective decision-making intention of the decision-makers. If the displayed content is most relevant to the established strategy library, it can avoid interfering with the decision-making of the decision-makers and facilitate their decision-making. Otherwise, that is, when the stage knowledge in the target knowledge set is not different from each other, the output of more stage knowledge in the target knowledge set will have little interference with the decision-making of the decision-makers. In this case, it is ensured that the displayed content is most relevant to the established strategy library and / or the determined strategy library, and the output is provided for the common reference of the decision-makers.

[0099] Rule A2, each time i changes from N1+1 to N2, when the larger one of the correlations between the stage knowledge in the target knowledge set and the formulated strategy library and the determined strategy library exceeds the correlation threshold, all the stage knowledge in the target knowledge set will be used as the display content; otherwise, the display content will be set as blank; where, in Rule A1, the correlation threshold can be 90%; each time i changes from N1+1 to N2, it means that the decision-making process is approaching the end, and the decision-maker needs to pay attention to the extra management stages in the individual management stage sequence. When the larger one of the correlations between the stage knowledge in the target knowledge set and the formulated strategy library and the determined strategy library exceeds the correlation threshold, it means that it is necessary for the decision-maker to view all the stage knowledge in the target knowledge set and display it as the display content, otherwise, it means that it is not necessary for the decision-maker to view all the stage knowledge in the target knowledge set, and the display content will be set as blank.

[0100] Among them, N1 is the minimum number of management stages in each management stage sequence, and N2 is the maximum number of management stages in each management stage sequence.

[0101] The above-mentioned technical scheme of the embodiment of the present invention interactively assists decision makers to start making decisions on optimizing management strategies based on the knowledge indicated by the instructions, accurately sets the display content determination rules, and starts to determine the display content based on the display content determination rules and the target knowledge set. Whenever the determination is completed, the display content is displayed to the decision makers, and the stage strategies determined by the decision makers from the display content to be displayed or formulated based on the display content are received. Finally, the stage strategies are integrated, which can ensure that the decision makers can view the best display content and get the best assistance at different stages, thereby improving their efficiency in optimizing management strategies. It is very user-friendly and further improves the applicability of the system.

[0102] In one embodiment, the integrated management device for multiple types of food processing machines further includes:

[0103] The second management module is used for:

[0104] In the second period, based on the optimization management feedback of each food processing machine, the optimization management strategy is adjusted, and based on the adjusted optimization management strategy, each food processing machine is optimized and managed in a relay manner.

[0105] The optimization management feedback includes: the relevant status information of each food processing machine after the optimization management; the optimization management strategy can be adjusted based on the optimization management feedback, and after the adjustment, the optimization management of each food processing machine is carried out in relay based on the adjusted optimization management strategy, which improves the effect of the optimization management of each food processing machine.

[0106] The present invention provides a comprehensive management method for various types of food processing machinery, such as Figure 2 As shown, including:

[0107] S1. Continuously identify whether various types of food processing machinery have triggered the opportunity to enter optimized management;

[0108] S2. Whenever it is identified as a triggering time for entering the optimization management, based on the processing operation information of each food processing machine in the first time period, start to decide on the optimization management strategy; wherein the first time period is a preset first time period before and after the moment when it is identified as a triggering time for entering the optimization management;

[0109] S3. When the decision is made, based on the optimization management strategy, each food processing machine is optimized and managed within a second time period; wherein the second time period is a second time period preset after the moment when the decision is made.

[0110] The continuous identification of whether each type of food processing machinery triggers the opportunity to enter optimization management includes:

[0111] Whenever each food processing machine generates incremental dynamics, if the incremental dynamics correspond to a leaf node in the situation graph, an attempt is made to trace the history of multiple target nodes for each food processing machine; wherein the multiple target nodes include: non-leaf nodes and leaf nodes on other paths connected to the root node of the path where the leaf node is located in the situation graph;

[0112] When the proportion of successful tracing attempts exceeds the threshold of the successful tracing ratio, it is determined that each food processing machine is triggered to enter the optimization management time; wherein the proportion of successful tracing attempts is the ratio of the number of target leaf nodes that have been successfully traced to the total number of target leaf nodes; the threshold of the successful tracing ratio is greater than the total number of other paths connected to the root node;

[0113] and / or,

[0114] Continuously determining the trigger detection angle of view and the trigger detection mechanism from the panoramic monitoring map of each food processing machine; wherein the first monitoring element set that has fallen into the trigger detection angle of view and the second monitoring element set that is about to fall into the trigger detection angle of view respectively meet the first element set condition and the second element set condition in the same standard condition combination, and the trigger detection mechanism is the standard mechanism corresponding to the same standard condition combination;

[0115] Based on the trigger detection mechanism, trigger detection is performed according to the trigger detection perspective;

[0116] When the trigger detects the corresponding content, it determines the timing for each food processing machine to be triggered to enter optimized management.

[0117] The process of starting to make a decision on the optimization management strategy based on the processing operation information of each food processing machine in the first period includes:

[0118] Analyze processing operation information, determine the problems to be optimized and the applicable evaluation basis;

[0119] Based on the applicable evaluation basis, multiple optimization management knowledge for the optimization problem are evaluated for their applicability respectively, and the knowledge evaluation value ranking is obtained;

[0120] Performing feature description on the knowledge evaluation value ranking to obtain feature descriptors;

[0121] Based on the knowledge indication rules corresponding to the feature descriptors, the knowledge indicated is determined from each optimization management knowledge;

[0122] When the knowledge indicated by the indication is unique, the decision-making optimization management strategy begins based on the knowledge indicated by the indication; otherwise, the interactively assisted decision makers begin to decide on the optimization management strategy based on the knowledge indicated by the indication.

[0123] The interactive assistant decision maker starts to make decisions on the optimization management strategy based on the knowledge indicated by the instructions, including:

[0124] Expand the knowledge referred to by the indication through management stages and obtain multiple management stage sequences;

[0125] Based on the display content determination rule, the display content is determined according to the target knowledge set; wherein the target knowledge set includes: the stage knowledge of the i-th management stage of each management stage sequence;

[0126] Whenever the determination is completed, the presentation content is presented to the decision maker, and the decision maker receives the stage strategy determined from the presentation content or formulated based on the presentation content;

[0127] When no longer starting to determine new display content, integrate phase strategies to obtain optimized management strategies;

[0128] The display content determination rules include:

[0129] Each time i changes from 1 to N1, when the stage knowledge in the target knowledge set is different from each other, the stage strategy most relevant to the formulated strategy library is determined from the target knowledge set as the display content; otherwise, the stage strategy most relevant to the formulated strategy library and / or the determined strategy library is determined from the target knowledge set as the display content;

[0130] Each time i changes from N1+1 to N2, when the larger of the relevance between the stage knowledge in the target knowledge set and the formulated strategy library and the determined strategy library exceeds the relevance threshold, all the stage knowledge in the target knowledge set is used as the display content; otherwise, the display content is set as blank;

[0131] Among them, N1 is the minimum number of management stages in each management stage sequence, and N2 is the maximum number of management stages in each management stage sequence.

[0132] A comprehensive management approach for multiple types of food processing machinery, also including:

[0133] In the second period, based on the optimization management feedback of each food processing machine, the optimization management strategy is adjusted, and based on the adjusted optimization management strategy, each food processing machine is optimized and managed in a relay manner.

[0134] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A comprehensive management device for multiple types of food processing machinery, characterized in that: include: Identification module, used to continuously identify whether various types of food processing machinery have triggered the opportunity to enter optimization management; A decision-making module, for starting to decide on an optimization management strategy based on processing operation information of each food processing machine in a first time period whenever it is identified as a triggering time to enter optimization management; wherein the first time period is a preset first time period before and after the moment when it is identified as a triggering time to enter optimization management; A first management module is used to optimize the management of each food processing machine within a second time period based on the optimization management strategy when the decision is made; wherein the second time period is a preset second time period after the moment when the decision is made; The identification module continuously identifies whether each type of food processing machine triggers an optimization management opportunity, including: Whenever each food processing machine generates incremental dynamics, if the incremental dynamics correspond to a leaf node in the situation graph, an attempt is made to trace the history of multiple target nodes for each food processing machine; wherein the multiple target nodes include: non-leaf nodes and leaf nodes on other paths connected to the root node of the path where the leaf node is located in the situation graph; When the proportion of successful tracing attempts exceeds the threshold of the successful tracing ratio, it is determined that each food processing machine is triggered to enter the optimization management time; wherein the proportion of successful tracing attempts is the ratio of the number of target leaf nodes that have been successfully traced to the total number of target leaf nodes; the threshold of the successful tracing ratio is greater than the total number of other paths connected to the root node; and, Continuously determining the trigger detection angle of view and the trigger detection mechanism from the panoramic monitoring map of each food processing machine; wherein the first monitoring element set that has fallen into the trigger detection angle of view and the second monitoring element set that is about to fall into the trigger detection angle of view respectively meet the first element set condition and the second element set condition in the same standard condition combination, and the trigger detection mechanism is the standard mechanism corresponding to the same standard condition combination; Based on the trigger detection mechanism, trigger detection is performed according to the trigger detection perspective; When the trigger detects the corresponding content, it determines the timing for each food processing machine to be triggered to enter optimized management.

2. The integrated management device for multiple types of food processing machines according to claim 1, characterized in that: The decision module starts to make decisions on the optimization management strategy based on the processing operation information of each food processing machine in the first period, including: Analyze processing operation information, determine the problems to be optimized and the applicable evaluation basis; Based on the applicable evaluation basis, multiple optimization management knowledge for the optimization problem are evaluated for their applicability respectively, and the knowledge evaluation value ranking is obtained; Performing feature description on the knowledge evaluation value ranking to obtain feature descriptors; Based on the knowledge indication rules corresponding to the feature descriptors, the knowledge indicated is determined from each optimization management knowledge; When the knowledge indicated by the indication is unique, the decision-making optimization management strategy is started based on the knowledge indicated by the indication; otherwise, the interactive auxiliary decision maker starts the decision-making optimization management strategy based on the knowledge indicated by the indication.

3. The integrated management device for multiple types of food processing machines according to claim 2, characterized in that: The decision module interactively assists decision makers to start making decisions on optimizing management strategies based on the knowledge indicated by the instructions, including: Expand the knowledge referred to by the indication through management stages and obtain multiple management stage sequences; Based on the display content determination rule, the display content is determined according to the target knowledge set; wherein the target knowledge set includes: the stage knowledge of the i-th management stage of each management stage sequence; Whenever the determination is completed, the presentation content is presented to the decision maker, and the decision maker receives the stage strategy determined from the presentation content or formulated based on the presentation content; When no longer starting to determine new display content, integrate phase strategies to obtain optimized management strategies; The display content determination rules include: Each time i changes from 1 to N1, when the stage knowledge in the target knowledge set is different from each other, the stage strategy most relevant to the formulated strategy library is determined from the target knowledge set as the display content; otherwise, the stage strategy most relevant to the formulated strategy library and / or the determined strategy library is determined from the target knowledge set as the display content; Each time i changes from N1+1 to N2, when the larger of the relevance between the stage knowledge in the target knowledge set and the formulated strategy library and the determined strategy library exceeds the relevance threshold, all the stage knowledge in the target knowledge set is used as the display content; otherwise, the display content is set as blank; Among them, N1 is the minimum number of management stages in each management stage sequence, and N2 is the maximum number of management stages in each management stage sequence.

4. The integrated management device for multiple types of food processing machines according to claim 1, characterized in that: Also includes: The second management module is used for: In the second period, based on the optimization management feedback of each food processing machine, the optimization management strategy is adjusted, and based on the adjusted optimization management strategy, each food processing machine is optimized and managed in a relay manner.

5. A comprehensive management method for multiple types of food processing machinery, characterized in that: include: Continuously identify whether various types of food processing machinery have triggered the opportunity to enter optimized management; Whenever it is identified as a trigger to enter the optimization management opportunity, the optimization management strategy is decided based on the processing operation information of each food processing machine in the first time period; wherein the first time period is a preset first time period before and after the moment when it is identified as a trigger to enter the optimization management opportunity; When the decision is made, each food processing machine is optimally managed within a second period based on the optimization management strategy; wherein the second period is a preset second time period after the moment when the decision is made; The continuous identification of whether each type of food processing machinery triggers the opportunity to enter optimization management includes: Whenever each food processing machine generates incremental dynamics, if the incremental dynamics correspond to a leaf node in the situation graph, an attempt is made to trace the history of multiple target nodes for each food processing machine; wherein the multiple target nodes include: non-leaf nodes and leaf nodes on other paths connected to the root node of the path where the leaf node is located in the situation graph; When the proportion of successful tracing attempts exceeds the threshold of the successful tracing ratio, it is determined that each food processing machine is triggered to enter the optimization management time; wherein the proportion of successful tracing attempts is the ratio of the number of target leaf nodes that have been successfully traced to the total number of target leaf nodes; the threshold of the successful tracing ratio is greater than the total number of other paths connected to the root node; and, Continuously determining the trigger detection angle of view and the trigger detection mechanism from the panoramic monitoring map of each food processing machine; wherein the first monitoring element set that has fallen into the trigger detection angle of view and the second monitoring element set that is about to fall into the trigger detection angle of view respectively meet the first element set condition and the second element set condition in the same standard condition combination, and the trigger detection mechanism is the standard mechanism corresponding to the same standard condition combination; Based on the trigger detection mechanism, trigger detection is performed according to the trigger detection perspective; When the trigger detects the corresponding content, it determines the timing for each food processing machine to be triggered to enter optimized management.

6. The integrated management method for multiple types of food processing machines according to claim 5, characterized in that: The process of starting to make a decision on the optimization management strategy based on the processing operation information of each food processing machine in the first period includes: Analyze processing operation information, determine the problems to be optimized and the applicable evaluation basis; Based on the applicable evaluation basis, multiple optimization management knowledge for the optimization problem are evaluated for their applicability respectively, and the knowledge evaluation value ranking is obtained; Performing feature description on the knowledge evaluation value ranking to obtain feature descriptors; Based on the knowledge indication rules corresponding to the feature descriptors, the knowledge indicated is determined from each optimization management knowledge; When the knowledge indicated by the indication is unique, the decision-making optimization management strategy is started based on the knowledge indicated by the indication; otherwise, the interactive auxiliary decision maker starts the decision-making optimization management strategy based on the knowledge indicated by the indication.

7. The integrated management method for multiple types of food processing machines according to claim 6, characterized in that: The interactive assistant decision maker starts to make decisions on the optimization management strategy based on the knowledge indicated by the instructions, including: Expand the knowledge referred to by the indication through management stages and obtain multiple management stage sequences; Based on the display content determination rule, the display content is determined according to the target knowledge set; wherein the target knowledge set includes: the stage knowledge of the i-th management stage of each management stage sequence; Whenever the determination is completed, the presentation content is presented to the decision maker, and the decision maker receives the stage strategy determined from the presentation content or formulated based on the presentation content; When no longer starting to determine new display content, integrate phase strategies to obtain optimized management strategies; The display content determination rules include: Each time i changes from 1 to N1, when the stage knowledge in the target knowledge set is different from each other, the stage strategy most relevant to the formulated strategy library is determined from the target knowledge set as the display content; otherwise, the stage strategy most relevant to the formulated strategy library and / or the determined strategy library is determined from the target knowledge set as the display content; Each time i changes from N1+1 to N2, when the larger of the relevance between the stage knowledge in the target knowledge set and the formulated strategy library and the determined strategy library exceeds the relevance threshold, all the stage knowledge in the target knowledge set is used as the display content; otherwise, the display content is set as blank; Among them, N1 is the minimum number of management stages in each management stage sequence, and N2 is the maximum number of management stages in each management stage sequence.

8. The integrated management method for multiple types of food processing machines according to claim 5, characterized in that: Also includes: In the second period, based on the optimization management feedback of each food processing machine, the optimization management strategy is adjusted, and based on the adjusted optimization management strategy, each food processing machine is optimized and managed in a relay manner.

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