Production line capability evaluation method and device, electronic equipment and readable storage medium

Abstract

The invention relates to a production line capability assessment method and device, electronic equipment and a readable storage medium. The method comprises the following steps: acquiring a plurality of assessment indexes of a to-be-assessed production line and first weights of the plurality of assessment indexes; the first weight indicates the importance of the evaluation index; determining second weights of the plurality of evaluation indexes based on the plurality of groups of index data of the to-be-evaluated production line; each group of index data comprises index values of the plurality of evaluation indexes; the second weight indicates the amount of information reflected by the index value associated with the evaluation index; determining a target weight based on the first weight and the second weight; based on the target weight and the multiple groups of index data, determining a scoring result corresponding to each group of index data; the scoring result indicates the production line capability of the to-be-evaluated production line.

Description

Technical Field

[0001] The present disclosure relates to the field of intelligent manufacturing, and in particular to a method, device, electronic device and readable storage medium for evaluating production line capacity. Background Art

[0002] As manufacturing enterprises develop towards digitalization, intelligence, and automation, the amount of data generated by the manufacturing industry continues to increase, and the sources of data are becoming more diverse and complex.

[0003] In the related art, business personnel estimate the production capacity based on the indicator data corresponding to each indicator and rely on experience to grasp the production status. The obtained production status is not only biased towards the subjective judgment of business personnel, but also cannot have a general conclusion to reflect the overall manufacturing production status. Summary of the invention

[0004] In order to overcome the problems existing in the related art, the present disclosure provides a method, device, electronic device and readable storage medium for evaluating production line capacity.

[0005] In a first aspect of the present disclosure, a method for evaluating production line capability is provided, comprising:

[0006] Acquire multiple evaluation indicators of the production line to be evaluated and first weights of the multiple evaluation indicators; the first weight indicates the importance of the evaluation indicator;

[0007] Based on the multiple groups of indicator data of the production line to be evaluated, second weights of the multiple evaluation indicators are determined; each group of the indicator data includes: indicator values ​​of the multiple evaluation indicators; the second weight indicates the amount of information reflected by the indicator value associated with the evaluation indicator;

[0008] Determining a target weight based on the first weight and the second weight;

[0009] Based on the target weight and the multiple groups of indicator data, a scoring result corresponding to each group of the indicator data is determined; the scoring result indicates the production line capacity of the production line to be evaluated.

[0010] Optionally, determining the second weights of the plurality of evaluation indicators based on the plurality of groups of indicator data of the production line to be evaluated includes:

[0011] Based on the multiple groups of indicator data of the production line to be evaluated, determining the sum of multiple indicator values ​​corresponding to each evaluation indicator;

[0012] Determine the information entropy value and utility value of each evaluation indicator based on the ratio between each indicator value in the multiple groups of indicator data and the sum of the evaluation indicators associated with the indicator value;

[0013] Based on the information entropy values ​​and utility values ​​of the plurality of evaluation indicators, second weights of the plurality of evaluation indicators are determined.

[0014] Optionally, determining a scoring result corresponding to each group of the indicator data based on the target weight and the multiple groups of indicator data includes:

[0015] Based on the multiple groups of indicator data, determine the maximum indicator data set and the minimum indicator data set corresponding to the multiple groups of indicator data; wherein the maximum indicator data set includes: the maximum value of multiple indicator values ​​of each of the evaluation indicators; the minimum indicator data set includes: the minimum value of multiple indicator values ​​of each of the evaluation indicators;

[0016] Based on the target weight corresponding to each of the evaluation indicators and the maximum indicator data set, determining a first distance between each group of the indicator data and the maximum indicator data set;

[0017] Based on the target weight corresponding to each of the evaluation indicators and the minimum indicator data set, determining a second distance between each group of the indicator data and the minimum indicator data set;

[0018] A scoring result corresponding to each group of the indicator data is determined according to the first distance and the second distance of each group of the indicator data.

[0019] Optionally, determining the first distance between each group of the indicator data and the maximum indicator data set based on the target weight corresponding to each of the evaluation indicators and the maximum indicator data set includes:

[0020] Determine a first difference between each indicator value in each set of indicator data and a maximum value corresponding to an evaluation indicator associated with the indicator value;

[0021] Based on the target weight of each of the evaluation indicators, weighted processing is performed on the first difference corresponding to each set of indicator data;

[0022] Determine a first distance between the indicator data and the maximum indicator data set based on a first difference value after weighted processing of each group of the indicator data;

[0023] The determining, based on the target weight corresponding to each of the evaluation indicators and the minimum indicator data set, a second distance between each group of the indicator data and the minimum indicator data set comprises:

[0024] Determine a second difference between each indicator value in each set of indicator data and the minimum value corresponding to the evaluation indicator associated with the indicator value;

[0025] Based on the target weight of each of the evaluation indicators, weighted processing is performed on the second difference corresponding to each set of indicator data;

[0026] Based on the second difference value after weighted processing of each group of the indicator data, a second distance between the indicator data and the minimum indicator data set is determined.

[0027] Optionally, the obtaining of a plurality of evaluation indicators of the production line to be evaluated and first weights of the plurality of evaluation indicators includes:

[0028] Obtain multiple evaluation indicators of the production line to be evaluated;

[0029] Determine a target score corresponding to each evaluation indicator based on the order of importance between any two of the evaluation indicators among the plurality of evaluation indicators;

[0030] Based on the target scores of the plurality of evaluation indicators, first weights of the plurality of evaluation indicators are determined.

[0031] Optionally, determining a target score corresponding to each evaluation indicator based on the order of importance between any two of the multiple evaluation indicators includes:

[0032] Acquire multiple groups of importance scores for the multiple evaluation indicators; a group of the importance scores includes: multiple first score values ​​corresponding to the multiple evaluation indicators;

[0033] Based on the multiple first scoring values ​​corresponding to each of the evaluation indicators, determine an average scoring value corresponding to each of the evaluation indicators;

[0034] Based on the size relationship between the average score values ​​of any two evaluation indicators among the multiple evaluation indicators, determine multiple second score values ​​corresponding to each of the evaluation indicators; the second score value indicates the importance order between the corresponding two evaluation indicators;

[0035] According to the multiple second scoring values ​​corresponding to each of the evaluation indicators, a target score corresponding to each of the evaluation indicators is determined.

[0036] Optionally, after determining the second weights of the plurality of evaluation indicators based on the plurality of groups of indicator data of the production line to be evaluated, the method further includes:

[0037] Performing data preprocessing on the multiple groups of indicator data;

[0038] The plurality of groups of index data after preprocessing are subjected to positive processing; wherein the evaluation index associated with the index value in each group of index data after positive processing is a positive index.

[0039] A second aspect of the present disclosure provides a device for evaluating production line capacity, comprising:

[0040] An acquisition module, used to acquire a plurality of evaluation indicators of a production line to be evaluated and a first weight of the plurality of evaluation indicators; the first weight indicates the importance of the evaluation indicator;

[0041] A first determination module is used to determine the second weights of the multiple evaluation indicators based on multiple groups of indicator data of the production line to be evaluated; each group of the indicator data includes: indicator values ​​of the multiple evaluation indicators; the second weight indicates the amount of information reflected by the indicator value associated with the evaluation indicator;

[0042] A second determining module, configured to determine a target weight based on the first weight and the second weight;

[0043] The third determination module is used to determine the scoring result corresponding to each group of the data based on the target weight and the multiple groups of indicator data; the scoring result indicates the production line capacity of the production line to be evaluated.

[0044] Optionally, the first determining module is further used to:

[0045] Based on the multiple groups of indicator data of the production line to be evaluated, determining the sum of multiple indicator values ​​corresponding to each evaluation indicator;

[0046] Determine the information entropy value and utility value of each evaluation indicator based on the ratio between each indicator value in the multiple groups of indicator data and the sum of the evaluation indicators associated with the indicator value;

[0047] Based on the information entropy values ​​and utility values ​​of the plurality of evaluation indicators, second weights of the plurality of evaluation indicators are determined.

[0048] Optionally, the third determining module is further used to:

[0049] Based on the multiple groups of indicator data, determine the maximum indicator data set and the minimum indicator data set corresponding to the multiple groups of indicator data; wherein the maximum indicator data set includes: the maximum value of multiple indicator values ​​of each of the evaluation indicators; the minimum indicator data set includes: the minimum value of multiple indicator values ​​of each of the evaluation indicators;

[0050] Based on the target weight corresponding to each of the evaluation indicators and the maximum indicator data set, determining a first distance between each group of the indicator data and the maximum indicator data set;

[0051] Based on the target weight corresponding to each of the evaluation indicators and the minimum indicator data set, determining a second distance between each group of the indicator data and the minimum indicator data set;

[0052] A scoring result corresponding to each group of the indicator data is determined according to the first distance and the second distance of each group of the indicator data.

[0053] Optionally, the third determining module is further used to:

[0054] Determine a first difference between each indicator value in each set of indicator data and a maximum value corresponding to an evaluation indicator associated with the indicator value;

[0055] Based on the target weight of each of the evaluation indicators, weighted processing is performed on the first difference corresponding to each set of indicator data;

[0056] Determine a first distance between the indicator data and the maximum indicator data set based on a first difference value after weighted processing of each group of the indicator data;

[0057] The third determining module is further used for:

[0058] Determine a second difference between each indicator value in each set of indicator data and the minimum value corresponding to the evaluation indicator associated with the indicator value;

[0059] Based on the target weight of each of the evaluation indicators, weighted processing is performed on the second difference corresponding to each set of indicator data;

[0060] Based on the second difference value after weighted processing of each group of the indicator data, a second distance between the indicator data and the minimum indicator data set is determined.

[0061] Optionally, the acquisition module is further used to:

[0062] Obtain multiple evaluation indicators of the production line to be evaluated;

[0063] Determine a target score corresponding to each evaluation indicator based on the order of importance between any two of the evaluation indicators among the plurality of evaluation indicators;

[0064] Based on the target scores of the plurality of evaluation indicators, first weights of the plurality of evaluation indicators are determined.

[0065] Optionally, the acquisition module is further used to:

[0066] Acquire multiple groups of importance scores for the multiple evaluation indicators; a group of the importance scores includes: multiple first score values ​​corresponding to the multiple evaluation indicators;

[0067] Based on the multiple first scoring values ​​corresponding to each of the evaluation indicators, determine an average scoring value corresponding to each of the evaluation indicators;

[0068] Based on the size relationship between the average score values ​​of any two evaluation indicators among the multiple evaluation indicators, determine multiple second score values ​​corresponding to each of the evaluation indicators; the second score value indicates the importance order between the corresponding two evaluation indicators;

[0069] According to the multiple second scoring values ​​corresponding to each of the evaluation indicators, a target score corresponding to each of the evaluation indicators is determined.

[0070] Optionally, the first determining module is further used to:

[0071] Performing data preprocessing on the multiple groups of indicator data;

[0072] The plurality of groups of index data after preprocessing are subjected to positive processing; wherein the evaluation index associated with the index value in each group of index data after positive processing is a positive index.

[0073] According to a third aspect of the present disclosure, an electronic device is provided, including:

[0074] a memory for storing processor-executable instructions;

[0075] A processor connected to the memory;

[0076] Wherein, the processor is configured to execute the production line capacity evaluation method as described in any embodiment of the first aspect of the present disclosure.

[0077] A fourth aspect of the present disclosure provides a non-temporary computer-readable storage medium. When instructions in the storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute a method for evaluating production line capacity as described in any one of the embodiments of the first aspect of the present disclosure.

[0078] The technical solution provided by the embodiments of the present disclosure may have the following beneficial effects:

[0079] In the embodiment of the present disclosure, a first weight that can reflect the importance of multiple evaluation indicators can be determined by obtaining multiple evaluation indicators of the production line to be evaluated; through multiple groups of indicator data of the production line to be evaluated, and each group of indicator data includes: indicator values ​​of multiple evaluation indicators, so that a second weight that can reflect the amount of information of multiple indicator values ​​can be determined according to the multiple indicator values ​​corresponding to each evaluation indicator. Through the combination of the first weight and the second weight, a target weight that reflects both importance and amount of information can be determined for each evaluation indicator. Finally, based on the target weight of each evaluation indicator and multiple groups of indicator data, the scoring result corresponding to each group of indicator data can be determined, and the scoring result can directly indicate the production line capacity of the production line to be evaluated corresponding to each group of indicator data. The embodiment of the present disclosure can fully consider the importance of the evaluation indicator and the amount of information of the indicator values ​​associated with multiple evaluation indicators determined by the objective indicator data of multiple groups of production lines, and based on the importance and amount of information, give the target weight of each evaluation indicator, so as to more objectively reflect the comprehensive capacity of the production line to be evaluated under multiple indicators.

[0080] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0081] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0082] Figure 1 The following is a flow chart of a method for evaluating production line capacity according to an exemplary embodiment of the present disclosure. Figure 1 .

[0083] Figure 2 The following is a flow chart of a method for evaluating production line capacity according to an exemplary embodiment of the present disclosure. Figure 2 .

[0084] Figure 3 The following is a flow chart of a method for evaluating production line capacity according to an exemplary embodiment of the present disclosure. Figure 3 .

[0085] Figure 4 The following is a flow chart of a method for evaluating production line capacity according to an exemplary embodiment of the present disclosure. Figure 4 .

[0086] Figure 5 The following is a flow chart of a method for evaluating production line capacity according to an exemplary embodiment of the present disclosure. Figure 5 .

[0087] Figure 6It is a structural schematic diagram of a device for evaluating production line capacity according to an exemplary embodiment of the present disclosure.

[0088] Figure 7 It is a block diagram of an electronic device according to an exemplary embodiment of the present disclosure. DETAILED DESCRIPTION

[0089] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices consistent with some aspects of the present disclosure as detailed in the appended claims.

[0090] In the intelligent manufacturing industry, production lines have multiple indicator data, which can grasp the production status in multiple dimensions such as production efficiency, quality, cost, and supply chain.

[0091] However, the evaluation of multiple indicator data in related technologies relies too much on expert judgment, which makes it difficult to fully utilize the objective information of the data, resulting in strong subjectivity and randomness, inaccurate evaluation results, low efficiency and increased labor costs, and it is difficult to objectively and comprehensively reflect the comprehensive capabilities of multiple indicator data.

[0092] The present invention provides a method for evaluating production line capacity. Figure 1 The following is a flow chart of a method for evaluating production line capacity according to an exemplary embodiment of the present disclosure. Figure 1 ,like Figure 1 As shown, the production line capacity evaluation method includes:

[0093] Step S101, obtaining a plurality of evaluation indicators of a production line to be evaluated and a first weight of the plurality of evaluation indicators; the first weight indicates the importance of the evaluation indicator;

[0094] Step S102, based on multiple groups of indicator data of the production line to be evaluated, determining second weights of the multiple evaluation indicators; each group of the indicator data includes: indicator values ​​of the multiple evaluation indicators; the second weight indicates the amount of information reflected by the indicator value associated with the evaluation indicator;

[0095] Step S103, determining a target weight based on the first weight and the second weight;

[0096] Step S104, based on the target weight and the multiple groups of indicator data, determining a scoring result corresponding to each group of the indicator data; the scoring result indicates the production line capacity of the production line to be evaluated.

[0097] In the embodiment of the present disclosure, the multiple evaluation indicators of the production line to be evaluated include at least: indicators of multiple dimensions such as quality, output, yield rate, cost, etc., which can be respectively recorded as indicator one, indicator two,..., indicator n.

[0098] Each of the multiple evaluation indicators has a first weight, which may indicate the importance of the evaluation indicator.

[0099] Exemplarily, the first weight of indicator one may be 9, and the first weight of indicator two may be 8, thereby indicating that for production line A to be evaluated, the importance of indicator one is greater than that of indicator two.

[0100] The first weight may be a weight set based on subjective importance.

[0101] In some embodiments, the first weight may be set based on the experience of an expert or business person. For example, an expert may believe that the first weight corresponding to quality should be greater than the first weight corresponding to output.

[0102] In some embodiments, the first weight may be set based on the stage goal of the production line. For example, when the production line is in a rush stage, the first weight corresponding to the output may be appropriately increased.

[0103] In step S102, the multiple groups of indicator data of the production line to be evaluated may be indicator data corresponding to the same production line at multiple different time points. The scoring results corresponding to each group of indicator data finally obtained can characterize the production line capacity of the same production line at different time points, thereby realizing a longitudinal comparison of the production line capacity of the same production line based on different time points.

[0104] Exemplarily, each set of indicator data may be indicator data of the production line A to be evaluated when it is in production on a certain day, and multiple sets of indicator data may be indicator data of the production line A to be evaluated when it is in production on the first to seventh days respectively.

[0105] In one embodiment, the multiple groups of indicator data of the production line to be evaluated may also be the indicator data corresponding to multiple production lines at the same time point. The scoring results corresponding to each group of indicator data finally obtained can characterize the production line capacity of each production line at the same time point, thereby realizing a horizontal comparison of the production line capacities of multiple production lines.

[0106] Exemplarily, each set of indicator data may be the indicator data of a certain production line to be evaluated during production on a certain day, and multiple sets of indicator data may be multiple sets of indicator data of production line A to be evaluated, production line B to be evaluated, production line C to be evaluated, and other production lines to be evaluated during production on the same day.

[0107] It should be noted that the structures of multiple production lines should be the same so that they can be compared using the same evaluation indicators.

[0108] It should be noted that the multiple groups of indicator data of the production line to be evaluated can also be set in other ways according to the evaluation requirements. For example, the multiple groups of indicator data can be set as indicator data of multiple production lines at multiple time points. The embodiments of the present disclosure do not make specific limitations on this.

[0109] The electronic device can obtain multiple groups of indicator data of the production line to be evaluated, wherein each group of indicator data includes indicator values ​​of multiple evaluation indicators. In other words, each group of indicator data is composed of multiple indicator values ​​corresponding to the production line to be evaluated, and each indicator value corresponds to an evaluation indicator.

[0110] Based on the production data of the production line to be evaluated, the index value corresponding to each evaluation index can be obtained. For example, when the output of the production line to be evaluated on that day is 90, it can be determined that the index value corresponding to the output is 90.

[0111] Based on multiple groups of indicator data of the production line to be evaluated, multiple indicator values ​​corresponding to each evaluation indicator in the multiple groups of indicator data can be determined; based on the multiple indicator values ​​corresponding to each evaluation indicator, that is, the amount of information reflected by the multiple indicator values, the second weights of the multiple evaluation indicators can be determined.

[0112] The second weight is associated with the amount of information reflected by the index value. Furthermore, the index value is also related to the production data generated by the production line to be evaluated, so the second weight is a weight determined based on the production data (ie, objective facts).

[0113] In some embodiments, the second weight of each evaluation indicator is determined based on the data interval consisting of multiple indicator values ​​corresponding to each evaluation indicator. For example, when the data interval consisting of multiple indicator values ​​corresponding to an evaluation indicator is large, that is, when the indicator value corresponding to the evaluation indicator fluctuates greatly, the evaluation indicator can be determined as a secondary indicator, and the second weight of the evaluation indicator is confirmed to be small.

[0114] In step S103, after obtaining the first weights and the second weights of the plurality of evaluation indicators corresponding to the production line to be evaluated, the electronic device may determine a target weight of each evaluation indicator based on the first weight and the second weight.

[0115] Among them, the target weight can indicate the relative importance of each evaluation indicator in the overall evaluation of the production line.

[0116] It can be understood that the first weight can be a weight set based on subjective importance, and the second weight can be a weight determined based on objective facts. Therefore, combining the first weight with the second weight can realize the combination of the subjective importance corresponding to each evaluation indicator with the objective facts, and obtain a weight that better meets the evaluation needs, and subsequently realize accurate evaluation of the production line capacity.

[0117] In one embodiment, a target weight of each evaluation indicator is determined based on the first weight, the second weight, and the weight coefficient.

[0118] Exemplarily, the target weight of each evaluation indicator is determined by the following formula.

[0119] w final =t×w sub +(1-t)w obj (1)

[0120] Among them, w final represents the target weight of each evaluation indicator, t represents the weight coefficient, and w sub Represents the first weight of each evaluation indicator, w obj Represents the second weight of each evaluation indicator.

[0121] In step S104, based on the target weight determined in step S103 and the indicator values ​​of multiple evaluation indicators in each group of indicator data, the scoring result corresponding to each group of indicator data can be determined; based on the scoring result, the production line capacity of the production line to be evaluated can be characterized.

[0122] It can be understood that based on the weight of each evaluation indicator and the indicator value of each evaluation indicator, the scoring result corresponding to each evaluation indicator in each set of indicator data can be obtained; based on the scoring result corresponding to each evaluation indicator, the scoring results corresponding to all evaluation indicators in each set of indicator data can be determined. Based on the scoring results corresponding to all evaluation indicators in each set of indicator data, the production line capacity of the production line to be evaluated when each set of indicator data is obtained can be determined.

[0123] For example, assume that the score result corresponding to the first set of indicator data is 90, and the score result corresponding to the second set of indicator data is 60. The first set of indicator data is obtained from the production data on August 1, and the second set of indicator data is obtained from the production data on August 2. Then, the production capacity of the production line on August 1 is better than the production capacity on August 2.

[0124] It can be seen that the production line capacity evaluation method in the embodiment of the present disclosure can determine the production line capacity when the multiple sets of indicator data are acquired based on the acquired multiple sets of indicator data, so that the actual situation in the production line can be grasped in time, possible problems and shortcomings can be discovered in time, and data-level basis can be provided for the subsequent formulation of production line-related policies and measures.

[0125] In the embodiment of the present disclosure, by obtaining multiple evaluation indicators of the production line to be evaluated, a first weight that can reflect the importance of multiple evaluation indicators can be determined; through multiple groups of indicator data of the production line to be evaluated, and each group of indicator data includes: indicator values ​​of multiple evaluation indicators, so that according to the multiple indicator values ​​corresponding to each evaluation indicator, a second weight that can reflect the amount of information of multiple indicator values ​​can be determined. Through the combination of the first weight and the second weight, a target weight that reflects both importance and amount of information can be determined for each evaluation indicator. Finally, based on the target weight of each evaluation indicator and multiple groups of indicator data, a scoring result corresponding to each group of indicator data can be determined, and the scoring result can directly indicate the production line capacity of the production line to be evaluated corresponding to each group of indicator data. The embodiment of the present disclosure can fully consider the importance of the evaluation indicator and the amount of information of the indicator values ​​associated with multiple evaluation indicators determined by the objective indicator data of multiple groups of production lines, and based on the importance and amount of information, a target weight for each evaluation indicator is given, so that the comprehensive capacity of the production line to be evaluated under multiple indicators can be more objectively reflected.

[0126] Optional, Figure 2 The following is a flow chart of a method for evaluating production line capacity according to an exemplary embodiment of the present disclosure. Figure 2 ,like Figure 2 As shown, the step S102 of determining the second weights of the plurality of evaluation indicators based on the plurality of groups of indicator data of the production line to be evaluated includes:

[0127] Step S201, based on multiple groups of indicator data of the production line to be evaluated, determining the sum of multiple indicator values ​​corresponding to each evaluation indicator;

[0128] Step S202, determining an information entropy value and a utility value of each evaluation indicator based on a ratio between each indicator value in the multiple groups of indicator data and the sum of the evaluation indicators associated with the indicator value;

[0129] Step S203: determining second weights of the plurality of evaluation indicators based on the information entropy values ​​and utility values ​​of the plurality of evaluation indicators.

[0130] In the embodiment of the present disclosure, before the electronic device executes step S103, the electronic device may determine the second weights of the plurality of evaluation indicators by executing steps S201 to S203.

[0131] In step S201, firstly, based on multiple groups of indicator data of the production line to be evaluated, the sum of multiple indicator values ​​corresponding to each evaluation indicator can be determined.

[0132] Exemplarily, multiple groups of indicator data of the production line to be evaluated may be obtained, and the multiple groups of indicator data may be summarized into Table 1.

[0133] Table 1

[0134] Indicator 1 Indicator 2 ... Index 1 <![CDATA[x 11 ]]> <![CDATA[x 12 ]]> ... <![CDATA[x 1n ]]> 2 <![CDATA[x 21 ]]> <![CDATA[x 22 ]]> ... <![CDATA[x 2n ]]> ... ... ... ... m <![CDATA[x m1 ]]> <![CDATA[x m2 ]]> ... <![CDATA[x mn ]]>

[0135] The multiple evaluation indicators include: indicator 1, indicator 2, ..., indicator n. m represents the mth group of indicator data. 11 Indicates the index value of index one in the first set of index data, x 12 Indicates the index value of index 2 in the first set of index data, x 21 Represents the indicator value of indicator one in the second set of indicator data, and so on.

[0136] By obtaining multiple indicator values ​​corresponding to each evaluation indicator, for example: multiple indicator values ​​corresponding to indicator 1 (x 11 、x 21 , …, x m1 ), the sum of multiple indicator values ​​can be determined.

[0137] For example, the sum of multiple indicator values ​​can be expressed as Among them, i represents the i-th group of indicator data, and j represents the j-th indicator.

[0138] In step S202, based on the ratio between each indicator value and the sum of the evaluation indicators associated with the indicator value, the information entropy value and the utility value of each evaluation indicator are determined. The information entropy value can represent the uncertainty measure of the evaluation indicator. The utility value represents the value of the evaluation indicator for decision making.

[0139] Exemplarily, the information entropy value and utility value of each evaluation indicator are determined by the following formulas.

[0140]

[0141]

[0142] d j =1-e j (4)

[0143] Among them, p represents the ratio between the index value and the sum of the evaluation indicators associated with the index value, e represents the information entropy value of each evaluation indicator, and d represents the utility value of each evaluation indicator.

[0144] In step S203, based on the information entropy value and the utility value of each evaluation indicator, a second weight of each evaluation indicator may be determined.

[0145] It can be understood that the sum of the utility values ​​of all evaluation indicators can be determined based on the utility value of each evaluation indicator; and the second weight of each evaluation indicator can be determined based on the ratio of the utility value of one evaluation indicator to the sum of the utility values ​​of all evaluation indicators.

[0146] Exemplarily, the second weight of each evaluation indicator is determined by the following formula.

[0147]

[0148] Among them, w obj Represents the second weight of each evaluation indicator.

[0149] In the embodiment of the present disclosure, the second weight of each evaluation indicator can be determined based on the amount of information reflected by the multiple indicator values ​​corresponding to each evaluation indicator, so as to determine the second weight associated with each evaluation indicator and the objective data based on the objective data generated by the production line.

[0150] Optional, Figure 3 The following is a flow chart of a method for evaluating production line capacity according to an exemplary embodiment of the present disclosure. Figure 3 ,like Figure 3 As shown, the step S104, based on the target weight and the multiple groups of indicator data, determines the scoring result corresponding to each group of the indicator data, including:

[0151] Step S301, based on the multiple groups of indicator data, determine the maximum indicator data set and the minimum indicator data set corresponding to the multiple groups of indicator data; wherein the maximum indicator data set includes: the maximum value of multiple indicator values ​​of each of the evaluation indicators; the minimum indicator data set includes: the minimum value of multiple indicator values ​​of each of the evaluation indicators;

[0152] Step S302, determining a first distance between each group of the indicator data and the maximum indicator data set based on the target weight corresponding to each of the evaluation indicators and the maximum indicator data set;

[0153] Step S303, determining a second distance between each group of the indicator data and the minimum indicator data set based on the target weight corresponding to each of the evaluation indicators and the minimum indicator data set;

[0154] Step S304: determining a scoring result corresponding to each group of the indicator data according to the first distance and the second distance of each group of the indicator data.

[0155] In the disclosed embodiment, after executing step S103 to obtain the target weight corresponding to each evaluation indicator, the electronic device may execute steps S301 to S304 to determine the scoring result of each group of indicator data based on the target weight of each evaluation indicator.

[0156] In step S301, the maximum value and the minimum value corresponding to each evaluation indicator can be determined based on the multiple indicator values ​​corresponding to each evaluation indicator in the multiple indicator data sets, and then the maximum indicator data set and the minimum indicator data set can be constructed based on the maximum value and the minimum value corresponding to each evaluation indicator.

[0157] For example, the maximum indicator data set can be expressed as x + , the minimum indicator data set can be expressed as x - .

[0158]

[0159]

[0160] In step S302, after the electronic device executes step S301 to obtain the maximum indicator data set, it can determine the first distance between each group of indicator data and the maximum indicator data set based on the target weight corresponding to each evaluation indicator and the maximum indicator data set.

[0161] It can be understood that the first distance between each set of indicator data and the maximum indicator data set is determined at least based on the difference between each indicator value in each set of indicator data and the maximum value of the evaluation indicator corresponding to the indicator value, and the target weight of the evaluation indicator corresponding to the indicator value.

[0162] The first distance may represent the overall gap between each set of indicator data and the maximum indicator data set.

[0163] Optionally, the step of determining the first distance between each group of the indicator data and the maximum indicator data set based on the target weight corresponding to each of the evaluation indicators and the maximum indicator data set in step 302 includes:

[0164] Determine a first difference between each indicator value in each set of indicator data and a maximum value corresponding to an evaluation indicator associated with the indicator value;

[0165] Based on the target weight of each of the evaluation indicators, weighted processing is performed on the first difference corresponding to each set of indicator data;

[0166] Based on the first difference value after weighted processing of each group of the indicator data, a first distance between the indicator data and the maximum indicator data set is determined.

[0167] It is understandable that after the electronic device obtains the maximum indicator data set, it can subtract each indicator value in each set of indicator data from the maximum value corresponding to the evaluation indicator associated with the indicator value to obtain a first difference value. Then, based on the target weight corresponding to the evaluation indicator associated with the indicator value, the first difference value obtained by subtracting each indicator value in each set of indicator data from the maximum value is weighted to obtain the first difference value after weighted processing of each set of indicator data. Based on the first difference value after weighted processing of each set of indicator data, the first distance between the indicator data and the maximum indicator data can be determined.

[0168] Exemplarily, the first distance between the i-th group of indicator data and the maximum indicator data is determined by the following formula.

[0169]

[0170] Among them, D + Indicates the first distance between each group of indicator data and the maximum indicator data, x + Indicates the maximum value corresponding to each indicator in the maximum indicator data set.

[0171] In step S303, after the electronic device executes step S301 to obtain the maximum indicator data set, it can determine the second distance between each group of indicator data and the minimum indicator data set based on the target weight corresponding to each evaluation indicator and the minimum indicator data set.

[0172] It can be understood that the second distance between each set of indicator data and the maximum indicator data set is determined at least based on the difference between each indicator value in each set of indicator data and the minimum value of the evaluation indicator corresponding to the indicator value, and the target weight of the evaluation indicator corresponding to the indicator value.

[0173] The second distance may represent the overall gap between each set of indicator data and the minimum indicator data set.

[0174] Optionally, the step of determining the second distance between each group of the indicator data and the minimum indicator data set based on the target weight corresponding to each of the evaluation indicators and the minimum indicator data set in step 303 includes:

[0175] Determine a second difference between each indicator value in each set of indicator data and the minimum value corresponding to the evaluation indicator associated with the indicator value;

[0176] Based on the target weight of each of the evaluation indicators, weighted processing is performed on the second difference corresponding to each set of indicator data;

[0177] Based on the second difference value after weighted processing of each group of the indicator data, a second distance between the indicator data and the minimum indicator data set is determined.

[0178] It is understandable that after the electronic device obtains the minimum indicator data set, it can subtract each indicator value in each set of indicator data from the minimum value corresponding to the evaluation indicator associated with the indicator value to obtain a second difference. Then, based on the target weight corresponding to the evaluation indicator associated with the indicator value, the second difference obtained by subtracting each indicator value in each set of indicator data from the minimum value is weighted to obtain the second difference after weighted processing of each set of indicator data. Based on the second difference after weighted processing of each set of indicator data, the second distance between the indicator data and the minimum indicator data can be determined.

[0179] Exemplarily, the second distance between the i-th group of indicator data and the minimum indicator data is determined by the following formula.

[0180]

[0181] Among them, D - Represents the second distance between each set of indicator data and the minimum indicator data, x - Indicates the minimum value corresponding to each indicator in the minimum indicator data set.

[0182] In step S304, the electronic device may determine the scoring result of each set of indicator data based on the first distance between each set of indicator data obtained in step S302 and the maximum indicator data set, and the second distance between each set of indicator data obtained in step S303 and the minimum indicator data set.

[0183] It can be understood that after obtaining the first distance and the second distance corresponding to each set of indicator data, that is, after obtaining the overall gap between each set of indicator data and the maximum indicator data set and the minimum indicator data set, a comprehensive scoring result for each set of indicator data can be given based on the overall gap corresponding to each set of indicator data.

[0184] Exemplarily, the scoring result of each set of indicator data is determined by the following formula.

[0185]

[0186] Among them, S represents the scoring result of each set of indicator data.

[0187] In the embodiments of the present disclosure, by determining the proximity between each set of indicator data and the maximum indicator data set and the minimum indicator data set, the production status of the production line corresponding to each set of indicator data among all production lines can be determined, or the production status of the production node corresponding to each set of indicator data among all production nodes can be determined, and then based on the above production status, the most accurate scoring result is given for each set of indicator data, so as to accurately measure the production line capacity of the production line to be evaluated.

[0188] Optional, Figure 4 The following is a flow chart of a method for evaluating production line capacity according to an exemplary embodiment of the present disclosure. Figure 4 ,like Figure 4 As shown, the step S101 of obtaining multiple evaluation indicators of the production line to be evaluated and the first weights of the multiple evaluation indicators includes:

[0189] Step S401, obtaining multiple evaluation indicators of the production line to be evaluated;

[0190] Step S402, determining a target score corresponding to each evaluation indicator based on the order of importance between any two of the evaluation indicators among the plurality of evaluation indicators;

[0191] Step S403: determining first weights of the plurality of evaluation indicators based on target scores of the plurality of evaluation indicators.

[0192] In the embodiment of the present disclosure, the electronic device first needs to obtain multiple evaluation indicators of the production line to be evaluated, and determine multiple dimensions for evaluating the production line to be evaluated.

[0193] Then, the electronic device executes step S402 to determine a target score corresponding to each evaluation indicator based on the order of importance between any two evaluation indicators among the multiple evaluation indicators.

[0194] Among them, the target score corresponding to each evaluation indicator can indicate the order of importance of each evaluation indicator among multiple evaluation indicators.

[0195] In some embodiments, the electronic device may sort the multiple evaluation indicators by importance based on the importance order between any two evaluation indicators in the multiple evaluation indicators. Based on the result of the importance sorting, a corresponding target score is determined for each evaluation indicator in order from the most important to the least important.

[0196] In step S403, based on the relationship between the target score of each evaluation indicator and the target scores of multiple evaluation indicators, a first weight of each evaluation indicator may be determined.

[0197] Exemplarily, the first weight of each evaluation indicator is determined by the following formula.

[0198]

[0199] Among them, TTL represents the target score of each evaluation indicator, w sub Represents the first weight of each evaluation indicator.

[0200] In the disclosed embodiment, by obtaining multiple evaluation indicators and comparing the importance order between the evaluation indicators, a first weight can be obtained for any evaluation indicator. The first weight and the second weight are obtained in different ways, so that the evaluation indicator can be evaluated from different angles, and a more accurate target weight can be determined for the evaluation indicator.

[0201] Optionally, the step S402 of determining a target score corresponding to each evaluation indicator based on the order of importance between any two of the multiple evaluation indicators includes:

[0202] Acquire multiple groups of importance scores for the multiple evaluation indicators; a group of the importance scores includes: multiple first score values ​​corresponding to the multiple evaluation indicators;

[0203] Based on the multiple first scoring values ​​corresponding to each of the evaluation indicators, determine an average scoring value corresponding to each of the evaluation indicators;

[0204] Based on the size relationship between the average score values ​​of any two evaluation indicators among the multiple evaluation indicators, determine multiple second score values ​​corresponding to each of the evaluation indicators; the second score value indicates the importance order between the corresponding two evaluation indicators;

[0205] According to the multiple second scoring values ​​corresponding to each of the evaluation indicators, a target score corresponding to each of the evaluation indicators is determined.

[0206] In the disclosed embodiment, the electronic device first needs to obtain multiple groups of importance scores for multiple evaluation indicators. After obtaining the multiple groups of importance scores, the average score corresponding to each evaluation indicator can be determined based on multiple first score values ​​corresponding to the same evaluation indicator in the multiple groups of importance scores.

[0207] Each group of importance scores includes multiple first score values ​​corresponding to multiple evaluation indicators. That is, in one group of importance scores, each of the multiple evaluation indicators is scored, and each score directly represents the importance of the evaluation indicator.

[0208] In some embodiments, each set of importance scores may correspond to scores of a plurality of evaluation indicators by one expert. Multiple sets of importance scores may correspond to scores of a plurality of evaluation indicators by a plurality of experts.

[0209] For example, the scores of multiple experts can be obtained, and multiple groups of importance scores can be summarized as shown in Table 2

[0210] Table 2

[0211]

[0212] The multiple evaluation indicators include: indicator 1, indicator 2, ..., indicator n. The multiple experts include: expert 1, expert 2, ..., expert k. 11 represents the first expert's score on indicator 1, s 12 represents the first expert's score on indicator 2, s 21 It represents the score given by the second expert on indicator one, and so on.

[0213] Exemplarily, based on the multiple first scoring values ​​corresponding to each evaluation indicator, an average score as shown in Table 2 can be obtained, representing the average scoring value corresponding to each evaluation indicator.

[0214] Based on the magnitude relationship between the average score values ​​of any two evaluation indicators in the multiple evaluation indicators, the electronic device can also determine multiple second score values ​​corresponding to each evaluation indicator, wherein the second score value is used to indicate the importance order between the corresponding two evaluation indicators.

[0215] It can be understood that after comparing the average score values ​​of any two evaluation indicators, the second score values ​​of the any two evaluation indicators can be determined respectively, so that the importance of the any two evaluation indicators can be indicated based on the second score values.

[0216] For example, the electronic device may calculate the average score of indicator 1. and the average score of indicator 2 For comparison, if Greater than It can be determined that the second score value of indicator 1 is 1, and the second score value of indicator 2 is 0. equal It can be determined that the second scoring value of indicator one is 0.5.

[0217] After each evaluation indicator is compared with all other evaluation indicators, multiple second scoring values ​​corresponding to each evaluation indicator can be obtained. According to the multiple second scoring values ​​corresponding to each evaluation indicator, the target score corresponding to each evaluation indicator can be determined.

[0218] It can be understood that each second scoring value corresponding to an evaluation indicator can indicate the importance order between the evaluation indicator and another evaluation indicator, so according to all the second scoring values ​​corresponding to an evaluation indicator, the importance order between the evaluation indicator and all other evaluation indicators can be obtained. Then, based on the importance order between the evaluation indicator and all other evaluation indicators, the corresponding target score can be determined for the evaluation indicator.

[0219] Typically, a target score corresponding to an evaluation indicator may be obtained by adding all second score values ​​corresponding to the evaluation indicator.

[0220] In some embodiments, a priority diagram may be constructed to record the second score value of each evaluation indicator.

[0221] For example, the average score of each evaluation indicator can be used to construct a priority map matrix. Specifically, the evaluation indicators are compared in pairs, and a relatively larger average score value is recorded as 1 point, a relatively smaller average score value is recorded as 0 point, and an equal average score value is recorded as 0.5 point (the same evaluation indicator is also recorded as 0.5 point when compared), forming a priority map matrix, as shown in Table 3.

[0222] Table 3

[0223] Indicator 1 Indicator 2 ... Index Indicator 1 0.5 <![CDATA[v 12 ]]> ... <![CDATA[v 1n ]]> Indicator 2 <![CDATA[v 21 ]]> 0.5 ... <![CDATA[v 2n ]]> ... ... ... 0.5 ... Index <![CDATA[v n1 ]]> <![CDATA[v n2 ]]> ... 0.5

[0224] Where v represents the second score value of each evaluation indicator. 12 It represents the second score value of indicator 1 after comparing indicator 1 with indicator 2, v 1n It represents the second score value of indicator 1 after comparing indicator 1 and indicator n, v 21 It represents the second score value of indicator 2 after comparing indicator 2 with indicator 1, and so on.

[0225] It can be understood that Table 3 records multiple second scoring values ​​corresponding to each evaluation indicator. When determining the target score corresponding to each evaluation indicator, all second scoring values ​​corresponding to one evaluation indicator can be added together. Wherein, t represents the number of second rating values.

[0226] In the disclosed embodiment, the average score value of each evaluation indicator can be obtained based on multiple groups of importance scores, so that the importance of each evaluation indicator can be ranked based on the size relationship between the average score values ​​to determine the target score of each evaluation indicator.

[0227] Optionally, after determining the second weights of the plurality of evaluation indicators based on the plurality of groups of indicator data of the production line to be evaluated in step S102, the method further includes:

[0228] Performing data preprocessing on the multiple groups of indicator data;

[0229] The plurality of groups of index data after preprocessing are subjected to positive processing; wherein the evaluation index associated with the index value in each group of index data after positive processing is a positive index.

[0230] In the embodiment of the present disclosure, after determining the second weights of the multiple evaluation indicators, the electronic device may also perform data preprocessing on the multiple groups of indicator data.

[0231] Here, data preprocessing is used to eliminate the influence of different data indicator dimensions. The specific process can be set according to requirements, and the embodiment of the present disclosure does not make specific limitations on this.

[0232] Exemplarily, data preprocessing may include normalizing the index values ​​corresponding to the evaluation indexes in the multiple groups of index data. Specifically, the normalization calculation may be performed using the following formula.

[0233]

[0234] Among them, x represents multiple indicator values ​​corresponding to each evaluation indicator, and x represents an indicator value for each evaluation indicator.

[0235] After completing the preprocessing of the multiple groups of indicator data, the preprocessed multiple groups of indicator data can also be subjected to positive processing, so that the indicator types of the multiple evaluation indicators corresponding to the multiple groups of indicator data are converted into the same type. That is, all evaluation indicators associated with the indicator values ​​in each group of indicator data after the positive processing can be positive indicators.

[0236] By converting the indicator types of multiple evaluation indicators into the same type, the target scores corresponding to each evaluation indicator can be added together to obtain the comprehensive production line capacity of the production line to be evaluated.

[0237] Exemplarily, the indicator type of the evaluation indicator can be converted into an extreme type by the formula shown in Table 4.

[0238] Table 4

[0239]

[0240] In the embodiment of the present disclosure, by performing data preprocessing and forward processing on multiple groups of indicator data, the evaluation indicators corresponding to the processed multiple groups of indicator data can be made of the same type, so that a unified judgment standard can be used to evaluate each evaluation indicator, and the results of all evaluation indicators can be added together to obtain the comprehensive production line capacity of the production line.

[0241] The following is a specific example to illustrate the method for evaluating the production line capacity in the embodiment of the present disclosure.

[0242] Figure 5 The following is a flow chart of a method for evaluating production line capacity according to an exemplary embodiment of the present disclosure. Figure 5 , combined with Figures 1 to 5 As shown in the figure, the evaluation method of production line capacity includes:

[0243] Step S501, start.

[0244] Step S502, obtaining a first weight, and then executing step S506.

[0245] It is understandable that by obtaining multiple groups of importance scores of multiple evaluation indicators, a priority graph matrix can be constructed. According to the priority graph matrix, the first weights of the multiple evaluation indicators can be obtained.

[0246] Step S503, obtaining multiple groups of indicator data, and then executing steps S504 and S505.

[0247] Step S504, obtaining a second weight, and then executing step S506.

[0248] It can be understood that, based on multiple groups of indicator data, the information entropy value and utility value of each evaluation indicator can be determined to obtain the second weights of the multiple evaluation indicators.

[0249] Step S505, processing multiple groups of indicator data, and then executing step S507.

[0250] It is understandable that after data preprocessing and forward processing, multiple groups of processed indicator data can be obtained. Based on the multiple groups of processed indicator data, a maximum indicator data set and a minimum indicator data set can be obtained.

[0251] Step S506, calculate the target weight, and then execute step S507.

[0252] It can be understood that, based on the first weight and the second weight, the target weight of each evaluation indicator can be obtained.

[0253] Step S507, determining the distance between each group of indicator data and the maximum indicator data set and the minimum indicator data set, and then executing step S508.

[0254] It is understandable that based on the target weight and the maximum indicator data set and the minimum indicator data set, a first distance between each set of indicator data and the maximum indicator data set and a second distance between each set of indicator data and the minimum indicator data set can be determined.

[0255] Step S508, determine the scoring result, and then execute step S509.

[0256] Step S509, end.

[0257] Combining the above method steps, an example is given to illustrate the specific process of production line capacity assessment.

[0258] The first step is to select six representative indicators on the production line. A total of five experts participated in the scoring. The scoring results are shown in Table 5.

[0259] Table 5

[0260]

[0261]

[0262] The second step is to calculate the priority chart based on the scoring results, as shown in Table 6.

[0263] Table 6

[0264] Indicator 1 Indicator 2 Indicator 3 Indicator 4 Indicator 5 Indicator 6 Indicator 1 0.5 1 1 1 1 1 Indicator 2 0 0.5 0 1 1 1 Indicator 3 0 1 0.5 1 1 1 Indicator 4 0 0 0 0.5 0 0 Indicator 5 0 0 0 1 0.5 1 Indicator 6 0 0 0 1 0 0.5

[0265] Step 3: Calculate the first weight, as shown in Table 7.

[0266] Table 7

[0267] Evaluation Metrics Indicator 1 Indicator 2 Indicator 3 Indicator 4 Indicator 5 Indicator 6 First weight 31.43％ 20％ 25.71％ 2.86％ 11.43％ 8.57％

[0268] Step 4: Obtain the indicator value corresponding to each evaluation indicator of the production line to be evaluated within seven days, as shown in Table 8.

[0269] Table 8

[0270] Time Indicator 1 Indicator 2 Indicator 3 Indicator 4 Indicator 5 Indicator 6 1 0.950 260 500 0.0050 0.96 0.98 2 0.960 280 520 0.0040 0.95 0.91 3 0.942 290 560 0.0045 0.92 0.99 4 0.980 255 506 0.0060 0.97 0.90 5 0.963 264 530 0.0048 0.94 0.94 6 0.950 252 561 0.0050 0.93 0.98 7 0.961 291 494 0.0030 0.92 0.96

[0271] Step 5: Determine the combined target weight through the second weight and the first weight, as shown in Table 9.

[0272] Table 9

[0273] Evaluation Metrics Indicator 1 Indicator 2 Indicator 3 Indicator 4 Indicator 5 Indicator 6 Second weight 0.32％ 7.21％ 5.32％ 83.53％ 0.84％ 2.78％ First weight 31.43％ 20％ 25.71％ 2.86％ 11.43％ 8.57％ Target weight 15.875％ 13.605％ 15.515％ 43.195％ 6.135％ 5.675％

[0274] Step 6: Determine the scoring results, as shown in Table 10.

[0275] Table 10

[0276] time 1 2 3 4 5 6 7 Score 46 59 43 42 43 29 73

[0277] In the disclosed embodiment, through the combination of the first weight and the second weight, a target weight that reflects both the importance and the amount of information can be determined for each evaluation indicator. Finally, based on the target weight of each evaluation indicator and multiple groups of indicator data, the scoring result corresponding to each group of indicator data can be determined, and the scoring result can directly indicate the production line capacity of the production line to be evaluated corresponding to each group of indicator data. The disclosed embodiment can fully consider the importance of the evaluation indicators and the amount of information of the indicator values ​​associated with multiple evaluation indicators determined by the objective indicator data of multiple groups of production lines, and give a target weight for each evaluation indicator based on the importance and the amount of information, so as to more objectively reflect the comprehensive capabilities of the production line to be evaluated under multiple indicators.

[0278] The present disclosure provides a device for evaluating production line capacity. Figure 6 is a schematic diagram of a structure of a production line capacity evaluation device according to an exemplary embodiment of the present disclosure. Figure 6 As shown, the production line capacity assessment device 600 includes:

[0279] An acquisition module 601 is used to acquire multiple evaluation indicators of a production line to be evaluated and first weights of the multiple evaluation indicators; the first weight indicates the importance of the evaluation indicator;

[0280] A first determination module 602 is used to determine the second weights of the multiple evaluation indicators based on multiple groups of indicator data of the production line to be evaluated; each group of the indicator data includes: indicator values ​​of the multiple evaluation indicators; the second weight indicates the amount of information reflected by the indicator value associated with the evaluation indicator;

[0281] A second determination module 603, configured to determine a target weight based on the first weight and the second weight;

[0282] The third determination module 604 is used to determine the scoring result corresponding to each group of the data based on the target weight and the multiple groups of indicator data; the scoring result indicates the production line capacity of the production line to be evaluated.

[0283] Optionally, the first determining module 602 is further configured to:

[0284] Based on the multiple groups of indicator data of the production line to be evaluated, determining the sum of multiple indicator values ​​corresponding to each evaluation indicator;

[0285] Determine the information entropy value and utility value of each evaluation indicator based on the ratio between each indicator value in the multiple groups of indicator data and the sum of the evaluation indicators associated with the indicator value;

[0286] Based on the information entropy values ​​and utility values ​​of the plurality of evaluation indicators, second weights of the plurality of evaluation indicators are determined.

[0287] Optionally, the third determining module 604 is further configured to:

[0288] Based on the multiple groups of indicator data, determine the maximum indicator data set and the minimum indicator data set corresponding to the multiple groups of indicator data; wherein the maximum indicator data set includes: the maximum value of multiple indicator values ​​of each of the evaluation indicators; the minimum indicator data set includes: the minimum value of multiple indicator values ​​of each of the evaluation indicators;

[0289] Based on the target weight corresponding to each of the evaluation indicators and the maximum indicator data set, determining a first distance between each group of the indicator data and the maximum indicator data set;

[0290] Based on the target weight corresponding to each of the evaluation indicators and the minimum indicator data set, determining a second distance between each group of the indicator data and the minimum indicator data set;

[0291] A scoring result corresponding to each group of the indicator data is determined according to the first distance and the second distance of each group of the indicator data.

[0292] Optionally, the third determining module 604 is further configured to:

[0293] Determine a first difference between each indicator value in each set of indicator data and a maximum value corresponding to an evaluation indicator associated with the indicator value;

[0294] Based on the target weight of each of the evaluation indicators, weighted processing is performed on the first difference corresponding to each set of indicator data;

[0295] Determine a first distance between the indicator data and the maximum indicator data set based on a first difference value after weighted processing of each group of the indicator data;

[0296] The third determining module 604 is further configured to:

[0297] Determine a second difference between each indicator value in each set of indicator data and the minimum value corresponding to the evaluation indicator associated with the indicator value;

[0298] Based on the target weight of each of the evaluation indicators, weighted processing is performed on the second difference corresponding to each set of indicator data;

[0299] Based on the second difference value after weighted processing of each group of the indicator data, a second distance between the indicator data and the minimum indicator data set is determined.

[0300] Optionally, the acquisition module 601 is further used to:

[0301] Obtain multiple evaluation indicators of the production line to be evaluated;

[0302] Determine a target score corresponding to each evaluation indicator based on the order of importance between any two of the evaluation indicators among the plurality of evaluation indicators;

[0303] Based on the target scores of the plurality of evaluation indicators, first weights of the plurality of evaluation indicators are determined.

[0304] Optionally, the acquisition module 601 is further used to:

[0305] Acquire multiple groups of importance scores for the multiple evaluation indicators; a group of the importance scores includes: multiple first score values ​​corresponding to the multiple evaluation indicators;

[0306] Based on the multiple first scoring values ​​corresponding to each of the evaluation indicators, determine an average scoring value corresponding to each of the evaluation indicators;

[0307] Based on the size relationship between the average score values ​​of any two evaluation indicators among the multiple evaluation indicators, determine multiple second score values ​​corresponding to each of the evaluation indicators; the second score value indicates the importance order between the corresponding two evaluation indicators;

[0308] According to the multiple second scoring values ​​corresponding to each of the evaluation indicators, a target score corresponding to each of the evaluation indicators is determined.

[0309] Optionally, the first determining module 602 is further configured to:

[0310] Performing data preprocessing on the multiple groups of indicator data;

[0311] The plurality of groups of index data after preprocessing are subjected to positive processing; wherein the evaluation index associated with the index value in each group of index data after positive processing is a positive index.

[0312] Figure 7 1 is a block diagram of an electronic device according to an exemplary embodiment of the present disclosure. For example, the electronic device may be a server, a smart terminal, etc.

[0313] Reference Figure 7 The electronic device 80 may include one or more of the following components: a processing component 83, a memory 84, a power component 85, a multimedia component 86, an audio component 87, an input / output (I / O) interface 88, a sensor component 89, and a communication component 810.

[0314] The processing component 83 generally controls the overall operation of the electronic device 80, such as operations associated with display, phone calls, data communications, camera operations, and recording operations. The processing component 83 may include one or more processors 820 to execute instructions to complete all or part of the steps of the above-mentioned method. In addition, the processing component 83 may include one or more modules to facilitate the interaction between the processing component 83 and other components. For example, the processing component 83 may include a multimedia module to facilitate the interaction between the multimedia component 86 and the processing component 83.

[0315] The memory 84 is configured to store various types of data to support operations on the electronic device 80. Examples of such data include instructions for any application or method operating on the electronic device 80, contact data, phone book data, messages, pictures, videos, etc. The memory 84 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0316] The power supply assembly 85 provides power to the various components of the electronic device 80. The power supply assembly 85 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the electronic device 80.

[0317] The multimedia component 86 includes a screen that provides an output interface between the electronic device 80 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundaries of the touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 86 includes a front camera and / or a rear camera. When the electronic device 80 is in an operating mode, such as a shooting mode or a video mode, the front camera and / or the rear camera may receive external multimedia data. Each front camera and the rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.

[0318] The audio component 87 is configured to output and / or input audio signals. For example, the audio component 87 includes a microphone (MIC), and when the electronic device 80 is in an operating mode, such as a call mode, a recording mode, and a voice recognition mode, the microphone is configured to receive an external audio signal. The received audio signal can be further stored in the memory 84 or sent via the communication component 810. In some embodiments, the audio component 87 also includes a speaker for outputting audio signals.

[0319] I / O interface 88 provides an interface between processing component 83 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include but are not limited to: home button, volume button, start button and lock button.

[0320] The sensor assembly 89 includes one or more sensors for providing various aspects of status assessment for the electronic device 80. For example, the sensor assembly 89 can detect the open / closed state of the electronic device 80, the relative positioning of components, such as the display and keypad of the electronic device 80, and the sensor assembly 89 can also detect the position change of the electronic device 80 or a component of the electronic device 80, the presence or absence of user contact with the electronic device 80, the orientation or acceleration / deceleration of the electronic device 80, and the temperature change of the electronic device 80. The sensor assembly 89 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. The sensor assembly 89 may also include an optical sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 89 may also include an accelerometer, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

[0321] The communication component 810 is configured to facilitate wired or wireless communication between the electronic device 80 and other devices. The electronic device 80 can access a wireless network based on a communication standard, such as Wi-Fi, 4G or 5G, or a combination thereof. In an exemplary embodiment, the communication component 810 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 810 also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

[0322] In an exemplary embodiment, the electronic device 80 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors or other electronic components to perform the above methods.

[0323] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 84 including instructions, and the instructions can be executed by the processor 820 of the electronic device 80 to perform the above method. For example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0324] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. The present disclosure is intended to cover any variations, uses or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The description and examples are to be considered exemplary only, and the true scope and spirit of the present disclosure are indicated by the following claims.

[0325] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A method for evaluating production line capacity, characterized in that: include: Acquire a plurality of evaluation indicators of the production line to be evaluated and first weights of the plurality of evaluation indicators; The first weight indicates the importance of the evaluation indicator; Determining second weights of the plurality of evaluation indicators based on the plurality of groups of indicator data of the production line to be evaluated; Each group of the indicator data includes: the indicator values ​​of the multiple evaluation indicators; the second weight, indicating the amount of information reflected by the indicator value associated with the evaluation indicator; Determining a target weight based on the first weight and the second weight; Based on the target weight and the multiple groups of indicator data, a scoring result corresponding to each group of the indicator data is determined; the scoring result indicates the production line capacity of the production line to be evaluated.

2. The method according to claim 1, characterized in that The determining, based on the multiple groups of indicator data of the production line to be evaluated, second weights of the multiple evaluation indicators comprises: Based on the multiple groups of indicator data of the production line to be evaluated, determining the sum of multiple indicator values ​​corresponding to each evaluation indicator; Determine the information entropy value and utility value of each evaluation indicator based on the ratio between each indicator value in the multiple groups of indicator data and the sum of the evaluation indicators associated with the indicator value; Based on the information entropy values ​​and utility values ​​of the plurality of evaluation indicators, second weights of the plurality of evaluation indicators are determined.

3. The method according to claim 1, characterized in that The step of determining a scoring result corresponding to each group of the indicator data based on the target weight and the multiple groups of indicator data includes: Based on the multiple groups of indicator data, determine the maximum indicator data set and the minimum indicator data set corresponding to the multiple groups of indicator data; wherein the maximum indicator data set includes: the maximum value of multiple indicator values ​​of each of the evaluation indicators; the minimum indicator data set includes: the minimum value of multiple indicator values ​​of each of the evaluation indicators; Based on the target weight corresponding to each of the evaluation indicators and the maximum indicator data set, determining a first distance between each group of the indicator data and the maximum indicator data set; Based on the target weight corresponding to each of the evaluation indicators and the minimum indicator data set, determining a second distance between each group of the indicator data and the minimum indicator data set; A scoring result corresponding to each group of the indicator data is determined according to the first distance and the second distance of each group of the indicator data.

4. The method according to claim 3, characterized in that The determining, based on the target weight corresponding to each of the evaluation indicators and the maximum indicator data set, a first distance between each group of the indicator data and the maximum indicator data set comprises: Determine a first difference between each indicator value in each set of indicator data and a maximum value corresponding to an evaluation indicator associated with the indicator value; Based on the target weight of each of the evaluation indicators, weighted processing is performed on the first difference corresponding to each set of indicator data; Determine a first distance between the indicator data and the maximum indicator data set based on a first difference value after weighted processing of each group of the indicator data; The determining, based on the target weight corresponding to each of the evaluation indicators and the minimum indicator data set, a second distance between each group of the indicator data and the minimum indicator data set comprises: Determine a second difference between each indicator value in each set of indicator data and the minimum value corresponding to the evaluation indicator associated with the indicator value; Based on the target weight of each of the evaluation indicators, weighted processing is performed on the second difference corresponding to each set of indicator data; Based on the second difference value after weighted processing of each group of the indicator data, a second distance between the indicator data and the minimum indicator data set is determined.

5. The method according to claim 1, characterized in that: The step of obtaining a plurality of evaluation indicators of the production line to be evaluated and first weights of the plurality of evaluation indicators comprises: Obtain multiple evaluation indicators of the production line to be evaluated; Determine a target score corresponding to each evaluation indicator based on the order of importance between any two of the evaluation indicators among the plurality of evaluation indicators; Based on the target scores of the plurality of evaluation indicators, first weights of the plurality of evaluation indicators are determined.

6. The method according to claim 5, characterized in that The step of determining a target score corresponding to each evaluation indicator based on the order of importance between any two of the evaluation indicators among the plurality of evaluation indicators comprises: Acquire multiple groups of importance scores for the multiple evaluation indicators; a group of the importance scores includes: multiple first score values ​​corresponding to the multiple evaluation indicators; Based on the multiple first scoring values ​​corresponding to each of the evaluation indicators, determine an average scoring value corresponding to each of the evaluation indicators; Based on the size relationship between the average score values ​​of any two evaluation indicators among the multiple evaluation indicators, determine multiple second score values ​​corresponding to each of the evaluation indicators; the second score value indicates the importance order between the corresponding two evaluation indicators; According to the multiple second scoring values ​​corresponding to each of the evaluation indicators, a target score corresponding to each of the evaluation indicators is determined.

7. The method according to claim 1, characterized in that After determining the second weights of the plurality of evaluation indicators based on the plurality of groups of indicator data of the production line to be evaluated, the method further includes: Performing data preprocessing on the multiple groups of indicator data; The plurality of groups of index data after preprocessing are subjected to positive processing; wherein the evaluation index associated with the index value in each group of index data after positive processing is a positive index.

8. A production line capacity evaluation device, characterized in that: include: An acquisition module, used for acquiring a plurality of evaluation indicators of a production line to be evaluated and a first weight of the plurality of evaluation indicators; The first weight indicates the importance of the evaluation indicator; A first determination module, configured to determine second weights of the plurality of evaluation indicators based on the plurality of groups of indicator data of the production line to be evaluated; Each group of the indicator data includes: the indicator values ​​of the multiple evaluation indicators; the second weight, indicating the amount of information reflected by the indicator value associated with the evaluation indicator; A second determining module, configured to determine a target weight based on the first weight and the second weight; The third determination module is used to determine the scoring result corresponding to each group of the data based on the target weight and the multiple groups of indicator data; the scoring result indicates the production line capacity of the production line to be evaluated.

9. An electronic device, characterized in that: include: a memory for storing processor-executable instructions; A processor connected to the memory; The processor is configured to execute the production line capability evaluation method as described in any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium, characterized in that: When the instructions in the storage medium are executed by a processor of a computer, the electronic device is enabled to execute the method for evaluating the production line capability as described in any one of claims 1 to 7.

Images