A quantitative evaluation method for adaptability of production lines

Abstract

The present invention belongs to the field of production line production technology, and specifically relates to a quantitative evaluation method for the adaptability of a production line, including: establishing a discrete event simulation model of the production line according to the production parameters of the production line to be evaluated and the statistical distribution information of various production parameters; performing multiple simulation experiments on the model according to each interference environment of the production line and its countermeasures, and obtaining multiple values ​​of each evaluation index under the interference environment; statistically analyzing the multiple values ​​of each evaluation index under each interference environment, and obtaining the adaptability value of the evaluation index under each interference environment; based on the weights of various evaluation indicators, weighted summing the adaptability values ​​of each evaluation index under each interference environment, and obtaining the total adaptability value of the production line under the interference environment; quantitatively determining the adaptability of the production line to be evaluated by the total adaptability value of each interference environment. The evaluation method of the present invention can be used in the design and operation stage, so that the production line has better adaptability in actual production and strong versatility.

Description

Technical Field

[0001] The present invention belongs to the technical field of production line production, and more specifically, relates to a quantitative evaluation method for the adaptability of a production line. Background Art

[0002] During the production process of the production line, it will inevitably be affected by various interferences, such as equipment failure, tool breakdown, operator error, supply chain failure resulting in delayed or uncertain material arrival time, etc. These interferences will have various impacts on the production line, and even these impacts will overlap with each other, causing damage to the production process, and ultimately reflected in production efficiency, production cost, and production quality.

[0003] In order to cope with these disturbances and reduce the impact of disturbances on production line production, it is necessary to improve the adaptability of the production line, that is, to change the system structure and functions to adapt to the characteristics and capabilities of new demands and new scenarios based on general adjustment strategies or manual intervention when unpredictable changes (interference) occur during the operation phase of the system. To improve the adaptability of the production line, the anti-interference ability, it is first necessary to quantify the adaptability. However, there is currently no unified indicator and method for quantitatively evaluating the adaptability of the production line. Summary of the invention

[0004] The present invention provides a quantitative evaluation method for the adaptability of a production line, which is used to solve the technical problem that there is no unified and effective quantitative evaluation method to quantify the adaptability of the production line to guide the improvement of the adaptability of the production line.

[0005] The technical solution of the present invention to solve the above technical problem is as follows: A quantitative evaluation method for adaptability of a production line, comprising:

[0006] According to the production parameters of the production line to be evaluated and the statistical distribution information of various production parameters, a discrete event simulation model of the production line is established;

[0007] According to each interference environment of the predetermined production line and its countermeasures, multiple simulation experiments are performed on the simulation model to obtain multiple values ​​of the adaptability evaluation index of each production line under the interference environment;

[0008] Performing statistical analysis on multiple values ​​of each adaptability evaluation index under each interference environment to obtain the adaptability value of the adaptability evaluation index under each interference environment;

[0009] Based on the weights of various adaptability evaluation indicators, the adaptability values ​​of each adaptability evaluation indicator under each interference environment are weighted and summed to obtain the total adaptability value of the production line under the interference environment;

[0010] The adaptability of the production line to be evaluated is quantitatively determined by the total adaptability value of each interference environment.

[0011] The beneficial effects of the present invention are as follows: the evaluation method of the present invention establishes a discrete event simulation model of the production line according to the relevant values ​​of the production parameters, and performs simulation experiments on various interference environments and corresponding countermeasures on the simulation model to record or count multiple values ​​corresponding to multiple experiments of each evaluation indicator under each interference environment, and obtains the adaptability value of the evaluation indicator under the interference environment by performing statistical analysis on the multiple values ​​of each evaluation indicator under each interference environment, and further quantifies the adaptability of the production line based on the fused values ​​corresponding to each interference environment. The evaluation method of the present invention can be used in the design stage and the operation stage. By applying the evaluation method of the present invention in the design stage, a general understanding of the adaptability of the production line can be obtained before the production line is established. According to the evaluation results of the adaptability, certain adjustments can be made to the design plan of the production line to make it have better adaptability; in the operation stage of the production line, the evaluation method of the present invention is applied to the production line to guide the adjustment of the production plan of the production line, so that the production line has better adaptability in actual production and strong versatility.

[0012] Based on the above technical solution, the present invention can also be improved as follows.

[0013] Furthermore, the adaptability evaluation index is selected from the following indexes:

[0014] Production efficiency indicators and production line buffer capacity indicators belonging to the dynamic performance of the production line;

[0015] Interference detection speed index, interference mean recovery time index, compensation capability index and maintenance cost index belonging to the maintainability of the production line; wherein the interference mean recovery time index includes the production line performance recovery time index, the compensation equipment conversion time index and the workstation function recovery time index.

[0016] A further beneficial effect of the present invention is that the dynamic performance index of the production line reflects the production line capacity of the production line. Through the changes in the index of this dimension, it can be seen that the production performance of the production line changes under the influence of the interference to the production line and the corresponding response measures taken. The smaller the change, that is, the larger the value of the index, the better the adaptability of the production line; the index of the maintainability dimension of the production line reflects the ability of the production line to respond to interference when it is disturbed. The stronger the ability to respond, the better the anti-interference ability of the production line is and the better the adaptability is. Specifically, production efficiency is the most common and most important indicator for evaluating the production capacity of a production line in actual production line production; the buffering capacity of the production line reflects the fault tolerance of the production line in the production process. When interference occurs, the buffering capacity decreases, the fault tolerance of the production line also decreases, and the ability to resist interference also decreases; the interference detection speed reflects the reaction speed of the production line to interference. The faster the reaction speed, the more likely the production line is to be maintained in time; the average recovery time of interference reflects the time from the production line taking corresponding countermeasures after being disturbed to the time of resuming normal production. The shorter the average recovery time, the better the production maintenance of the production line. According to the type and severity of the interference, it is divided into three specific indicators: production line performance recovery time indicator, compensation equipment conversion time indicator and workstation function recovery time indicator; compensation capacity is the higher production capacity of the production line with compensation equipment when using compensation equipment than when not using compensation equipment. This part of the capacity is the embodiment of its better maintainability under interference; maintenance cost is the converted cost corresponding to the countermeasures taken by the production line to various interferences. The higher the cost, the greater the maintenance resistance and the lower the maintainability. The above indicators can be used to comprehensively and effectively conduct quantitative evaluation of the adaptability of the production line.

[0017] Furthermore, the production line buffer capacity index represents the ratio of the total number of products that can be accommodated by the buffer zone in the production line to the average number of products in process in the buffer zone;

[0018] The interference detection speed index represents the average value of the detection speed of various types of interference detected by the production line;

[0019] The compensation capacity index is represented by the relative compensation difference of production efficiency, and the relative compensation difference of production efficiency represents the ratio of the difference in production efficiency of the same production line under the conditions of no compensation capacity and with compensation capacity to the production efficiency of the production line under the condition of no compensation capacity;

[0020] The maintenance cost represents the weighted cost of the production line's response measures to various types of disturbances;

[0021] The compensation device conversion time index represents the ratio of the total conversion time of all devices with compensation function to the total conversion times of the compensation devices;

[0022] The workstation function recovery time indicator indicates the time from when processing is stopped due to non-equipment failure to when processing is resumed.

[0023] Furthermore, when the production line to be evaluated is in the design stage, the adaptability evaluation indicators include:

[0024] Production efficiency indicators and production line buffer capacity indicators belonging to the dynamic performance of the production line;

[0025] It is a compensation capacity indicator of the maintainability of the production line.

[0026] A further beneficial effect of the present invention is that, since the production line has not yet been put into operation during the production line design phase, only indicators that can be obtained from simulation can be selected.

[0027] Furthermore, the adaptability of the production line to be evaluated is quantitatively determined as follows:

[0028] The maximum and minimum values ​​of the total adaptability values ​​of each interference environment are determined, and the interval formed by the maximum and minimum values ​​is used as the adaptability distribution range of the production line to complete the quantitative evaluation of the adaptability of the production line.

[0029] A further beneficial effect of the present invention is that the maximum and minimum values ​​of the adaptability value interval are the maximum and minimum values ​​of all adaptability evaluation results obtained by taking into account various possible interference situations that often occur. The adaptability of the production line will show different results in various indicators under different specific conditions and environments, resulting in the real-time adaptability evaluation value of the production line under different circumstances may be dynamically changing. In the form of an interval composed of the maximum and minimum values, the changes in the adaptability values ​​of the production line under various circumstances are included in this interval, so that the production line designer can grasp the overall adaptability changes of the production line.

[0030] Furthermore, when the production line to be evaluated is in operation, the adaptability evaluation index includes:

[0031] Production efficiency indicators and production line buffer capacity indicators belonging to the dynamic performance of the production line;

[0032] The indicators of interference detection speed, interference mean recovery time, compensation capacity and maintenance cost belong to the maintainability of the production line.

[0033] Furthermore, the adaptability of the production line to be evaluated is quantitatively determined as follows:

[0034] Determine the maximum and minimum values ​​of the total adaptability values ​​of each interference environment, use the interval formed by the maximum and minimum values ​​as the adaptability distribution range of the production line, and complete the quantitative evaluation of the adaptability of the production line; or,

[0035] The frequency of occurrence of each interference environment in the historical operation is counted, and a weight is assigned to each interference environment according to the frequency. The total adaptability value of each interference environment is weighted summed up as the adaptability of the production line to complete the quantitative evaluation of the adaptability of the production line.

[0036] A further beneficial effect of the present invention is that in the actual operation stage, the actual situation of various interference situations of the production line can be obtained by statistically analyzing the historical operation conditions, which cannot be accurately achieved in the design stage, and therefore this form is not adopted in the design stage; the frequency distribution obtained through the actual operation of the production line is relatively reliable, and interference situations with high frequency have a relatively large impact on the production line, so they are assigned relatively large weights. The production line fusion adaptability value obtained by weighting each interference situation in this way will more accurately reflect the overall adaptability of the production line.

[0037] Furthermore, a statistical analysis is performed on the multiple values ​​of each adaptability evaluation indicator under each interference environment, specifically, a risk value analysis is performed on the multiple values ​​of each adaptability evaluation indicator under each interference environment, and the risk value of the adaptability evaluation indicator under each interference environment is obtained as the adaptability value of the adaptability evaluation indicator under each interference environment.

[0038] A further beneficial effect of the present invention is that a confidence level, such as 95%, is required for the risk value analysis. Through this confidence level, an adaptability value corresponding to the confidence level can be obtained on the statistical distribution diagram of the adaptability value. The meaning of this value is that there is a 95% probability that the adaptability value will not be lower than this value. Therefore, this value can be considered to be a relatively safe value that is guaranteed not to be overestimated. Therefore, the use of risk value analysis can accurately perform quantitative assessment of adaptability.

[0039] The present invention also provides a computer-readable storage medium, which includes a stored computer program, wherein when the computer program is executed by a processor, the device where the storage medium is located is controlled to execute the above-mentioned method for quantitatively evaluating the adaptability of a production line. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 A flowchart of a method for quantitatively evaluating the adaptability of a production line provided by an embodiment of the present invention;

[0041] Figure 2 A schematic diagram of a framework of a method for quantitatively evaluating the adaptability of a production line provided by an embodiment of the present invention;

[0042] Figure 3 A schematic diagram of a method for integrating various indicators in a quantitative evaluation of production line adaptability in the design stage and the operation stage provided by an embodiment of the present invention;

[0043] Figure 4 A schematic diagram of a value-at-risk analysis provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0044] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0045] Embodiment 1

[0046] A quantitative evaluation method for the adaptability of a production line, such as Figure 1 As shown, including:

[0047] According to the production parameters of the production line to be evaluated and the statistical distribution information of various production parameters, a discrete event simulation model of the production line is established;

[0048] According to each interference environment of the production line and its countermeasures determined in advance, multiple simulation experiments are carried out on the simulation model to obtain multiple values ​​of the adaptability evaluation index of each production line under the interference environment;

[0049] Performing statistical analysis on multiple values ​​of each adaptability evaluation index under each interference environment to obtain the adaptability value of the adaptability evaluation index under each interference environment;

[0050] Based on the weights of various adaptability evaluation indicators, the adaptability values ​​of each adaptability evaluation indicator under each interference environment are weighted and summed to obtain the total adaptability value of the production line under the interference environment;

[0051] The adaptability of the production line to be evaluated is quantitatively determined by the total adaptability value of each interference environment. Based on the evaluation method of this embodiment, in actual implementation, the process may be as follows: according to the characteristics of the adaptability of the production line, an evaluation index (KPI, Key Point Indicators) of the adaptability of the production line is proposed; the production parameters of the production line (such as equipment preparation time, failure rate, failure time, processing time, replacement time of tools, brush wheels, etc., AGV number, AGV speed, AGV capacity, buffer capacity, production line shift, etc.) and their statistical distribution (the statistical distribution includes the statistical type of the determined parameters and their specific parameters, such as normal distribution, Erlang distribution, triangular distribution, uniform distribution, etc., and constants can also be used for those that cannot be determined. These distribution data will be used as input parameters when establishing the production line simulation model); establish different interference environments that often occur in the production line (interference refers to equipment failure, tool collapse, untimely supply of the supply chain, staff operation errors, etc., and different interference environments are constructed by changing the parameter settings in the established model), and their corresponding countermeasures (each interference has a corresponding countermeasure, such as the countermeasure for equipment failure is to send someone for repair, if there is a compensation device, it is converted to the compensation device for processing at the same time, and if the tool collapses, the tool is replaced); establish (for example, apply Plant A discrete event simulation model of the production line is established using the Simulation software (the previous production parameters and their statistical distribution, as well as the determination of the interference environment and its countermeasures are all preparations for this step of modeling). The model is used to perform repeated simulation experiments on each interference environment of the production line, and the experimental results are recorded (these results are evaluation index data that can be directly simulated in the software). For the evaluation index data that cannot be directly simulated in the software, the statistical data of this part of the evaluation index of the production line is obtained by recording the operation status of the production line after it is built; a unified statistical analysis is performed on the above-mentioned results obtained by simulation and the results obtained by statistics (it should be noted that the adaptability quantification process of the production line in the design stage only requires statistical analysis of the simulation results) to obtain the adaptability values ​​of each evaluation index under each interference environment; the hierarchical analysis method can be used to determine the weights of each indicator, and the obtained weights are used to perform weighted summation on the adaptability values ​​of each indicator under each interference environment to obtain a fused adaptability value under each interference environment; the overall adaptability of the production line is further determined based on the fused adaptability values ​​corresponding to each interference environment.

[0052] Preferably, the above-mentioned adaptability evaluation index is selected from the following indicators:

[0053] Indicators for the two dimensions of production line dynamic performance and production line maintainability; production line dynamic performance indicators include: production efficiency and production line buffer capacity. Production efficiency refers to the number of products produced per unit time of the production line. Production line buffer capacity refers to the ratio of the total number of products that can be accommodated in the buffer zone of the production line to the average number of work-in-progress of the production line. Production line maintainability indicators include: interference detection speed, average interference recovery time, compensation capability and maintenance cost. Interference detection speed refers to the speed at which the production line detects interference. Average interference recovery time refers to the time it takes for the production line to recover from interference. Compensation capability refers to the role of the compensation equipment of the production line in production. The specific indicator is the relative compensation difference of production efficiency. Maintenance cost refers to the cost incurred by the production line's response measures to interference. Specifically, average interference recovery time indicators include: production line performance recovery time, compensation equipment conversion time and workstation function recovery time.

[0054] Preferably, the production efficiency is the number of products leaving the production line per unit time, as shown in formula (1):

[0055] P=PN / T total (1)

[0056] Among them, PN represents the total number of products produced, T total Indicates production time.

[0057] The buffer capacity of the production line is the ratio of the total number of products that the buffer zone in the production line can accommodate to the average number of work-in-progress in the buffer zone in the production line. The formula is as follows:

[0058] W=N buffer / WIP buffer-mean (2)

[0059] Among them, N buffer Indicates the total number of products that the buffer can accommodate, WIP buffer-mean Indicates the average number of work-in-progress in the buffer zone within the production line.

[0060] The larger the capacity of the buffer zone, the better the buffering capacity of the production line; the smaller the average number of work-in-progress in the buffer zone within the production line, the less "crowded" the production line is, and the better the buffering capacity of the production line.

[0061] In the actual production of the production line, the processing equipment has a certain failure rate and repair rate. Production interruption or blockage caused by equipment failure or other reasons can be guaranteed to a certain extent by setting up a buffer between the processing equipment to store the intermediate work-in-progress.

[0062] The interference detection speed is the average value of the detection speed indicators of various types of interference. A detection time threshold is set for each type of interference. The detection time within the threshold can be regarded as normal. The ratio of the actual detection time to the threshold is used as the detection speed indicator of this type of interference. The formula is as follows:

[0063]

[0064] Where N is the total number of interference occurrences, V i Indicates the interference detection speed for each interference, as follows:

[0065] Among them, t i represents the detection time of each interference, t limit,i Indicates the detection time threshold corresponding to each interference.

[0066] The interference detection speed reflects the reaction speed of the production line to interference, the faster the better.

[0067] The production line performance recovery time indicates the average time it takes for the production line to recover when the equipment at the non-compensation station or all the equipment at the compensation equipment station fails and stops. The formula is as follows:

[0068]

[0069] in, It represents the total conversion time of all devices with compensation function, and N represents the number of conversion times of the compensation device.

[0070] Compensation equipment refers to the situation where there is more than one device at certain workstations on the production line. One of the devices is used for normal processing of the production line, while the other device is usually not in a processing state. When the processing equipment fails and cannot process, another device, namely the compensatory equipment, will take over the processing to prevent the production line from being interrupted for a long time.

[0071] The compensation equipment conversion time refers to the time it takes for a workstation with compensation function on the production line to use another compensation equipment to replace the original equipment when a working equipment fails and needs to be repaired. The formula is as follows:

[0072]

[0073] in, It represents the total conversion time of all devices with compensation function, and N represents the number of conversion times of the compensation device.

[0074] For the workstation function recovery time, if the workstation on the production line stops processing due to some reasons other than equipment failure (such as tool change, tool setting; brush wheel angle adjustment, brush wheel replacement, brush wheel test brushing; grinding wheel replacement; material replacement, etc.), in this case, only simple adjustment operations are needed to restore normal working conditions. The time from the occurrence of the situation to the resumption of processing is called the workstation function recovery time. The formula is as follows:

[0075]

[0076] in, It represents the total recovery time in the production process, and N represents the number of non-fault processing stops that occur in the production process.

[0077] The relative compensation difference of production efficiency refers to the difference in production efficiency of the same production line with and without compensation ability, and the ratio of the production efficiency of the production line without compensation ability. The formula is as follows:

[0078]

[0079] Among them, E1 represents the production efficiency of the production line without compensation ability, and E2 represents the production efficiency of the production line with compensation ability.

[0080] Maintenance cost refers to the maintenance measures taken for each interference situation. These measures will generate corresponding costs (such as labor costs, maintenance costs, etc.), which can be converted into corresponding monetary costs. The cost of corresponding measures for various types of interference that occur frequently is weighted, and the weight is the frequency of the corresponding interference. The resulting cost value is the maintenance cost of the production line.

[0081]

[0082] Among them, k i represents the weight, C i Indicates the cost corresponding to each maintenance measure.

[0083] It should be noted that the “production efficiency” in the relative compensation difference of production efficiency is the production efficiency defined in formula (1).

[0084] like Figure 2 and Figure 3 As shown in the figure, in order to meet the requirements for adaptability quantification in the two different stages of production line design and operation, the adaptability quantification method for production line design and the adaptability quantification method for production line operation are proposed respectively.

[0085] Preferably, when the production line to be evaluated is in the design stage, the evaluation method can be as follows:

[0086] S1, determine the evaluation indicators. According to the characteristics of the adaptive production of the production line, the evaluation indicators of the adaptability of the production line are proposed, and these indicators are selected according to the actual characteristics of the production line. Among them, the adaptability evaluation indicators include: indicators for the two dimensions of production line dynamic performance and production line maintainability; production line dynamic performance indicators include: production efficiency and production line buffering capacity; production line maintainability indicators include: interference detection speed, average interference recovery time, compensation ability and maintenance cost, among which the specific indicator of compensation ability is the relative compensation difference of production efficiency, and the average interference recovery time indicators include: production line performance recovery time, compensation equipment conversion time and workstation function recovery time.

[0087] Some of the above indicators can be obtained by simulation using Plant Simulation software, such as production efficiency, production line buffer capacity, compensation capacity, etc.; the other part can only be obtained by recording and counting the operation of the production line, such as interference detection speed, average interference recovery time, and maintenance cost. During the production line design phase, only data obtained by simulation can be obtained. Therefore, it is assumed that the production line selects the following indicators from the above adaptability indicators as its quantitative adaptability indicators:

[0088] Dynamic performance KPI 1: Production efficiency KPI 11 ,Production line buffer capacity KPI 12 ;

[0089] Maintainability KPI2: Compensation Ability KPI2.

[0090] S2, determine the relevant parameters of the production line and their statistical distribution. Since the parameters are set during the production line design phase, many parameters can only be roughly estimated. The statistical distribution (such as normal distribution, triangular distribution, etc.) of the startup time, processing time, failure rate, tool change time, etc. of each device can be estimated by comparing the equipment capacity parameters provided by the manufacturer of each device and the working conditions of similar production lines. For example, an automobile factory uses the historical production data of other existing production lines in the factory as a reference to derive the statistical distribution of various parameters of the new production line being designed.

[0091] S3, set up different interference environments and corresponding countermeasures. Assume that there are M kinds of interference environments that often occur, and take corresponding adjustment countermeasures for each interference situation. For example, if there is equipment failure, send repair workers to repair it, if the tool is broken or worn, replace the tool, if there is a station failure with compensation equipment, convert the compensation equipment, etc.

[0092] S4, establish a discrete event simulation model for the production line. Use Plant Simulation to establish a discrete event simulation model for the production line, input the required parameters for each device in the model, establish product transfer relationships and material supply settings between devices, etc. Conduct simulation experiments for each interference environment, and make corresponding countermeasures for the production line in each interference environment. Repeat the experiment N times in each interference environment and record the statistical results of each KPI.

[0093] S5, statistically analyzing the simulation results. Performing a value-at-risk analysis on the KPI values ​​obtained under each interference scenario (taking the confidence level as 95%, such as Figure 4 As shown in (Value at Risk analysis, Value at Risk), the value at risk of each KPI is obtained, which are: V 11 ,V 12 , V2 (corresponding to production efficiency KPI 11 , Production line buffer capacity KPI 12 and the value at risk of compensation capacity KPI2).

[0094] S6, determine the weight of each category of KPI. Use the analytic hierarchy process to determine the weight of each category of KPI: K1, K2. For the KPI of the same category, determine the weight of each KPI: K 11 ,K 12 .in:

[0095] K1+K2=1

[0096] K 11 +K 12 =1

[0097] S7, determine the KPI value in each interference environment. For each interference environment, normalize each KPI to obtain: 11 , v 12 , v2. Figure 3 , weight the normalized values, and get the KPI value of the same category as follows:

[0098] V1=K 11 v 11 +K 12 v 12

[0099] V2=v2

[0100] Then combine these two types of KPIs to obtain the final fusion performance indicator aKPI (aggregated KPI):

[0101] V=K1V1+K2V2

[0102] S8, determine the overall adaptability of the production line. Compare the values ​​of aKPI calculated under M different interference scenarios and obtain the maximum value V Max and minimum value V Min , the adaptability range of the production line is [V Min ,V Max ]. This adaptability interval represents the distribution range of the overall adaptability of the production line.

[0103] The above are the method steps for quantifying the adaptability of the production line during the design stage. The process of quantifying the adaptability of the production line during the operation stage is different from that during the design stage. This is mainly reflected in the fact that some of the indicators proposed above can only be obtained by recording and counting the actual operation conditions of the production line, and during operation, the production line parameters determined by methods such as equipment capacity parameters provided by the manufacturers of each equipment and comparison of the working conditions of similar production lines are bound to deviate from the actual conditions of the production line. During the operation stage, accurate parameter data can be obtained by recording and counting the actual operation conditions of the production line, so the quantification accuracy will also be improved compared to the design stage. Preferably, the following are the method steps for quantifying the adaptability of the production line during the operation stage:

[0104] S1, select the above indicators according to the actual characteristics of the production line. Assume that the production line selects the following indicators from the above adaptability indicators as its adaptability quantitative indicators:

[0105] Dynamic performance KPI 1: Production efficiency KPI 11 ,Production line buffer capacity KPI 12 ;

[0106] Maintainability KPI 2: Interference Detection Speed ​​KPI 21 , Interference Mean Recovery Time KPI 22 , relative compensation difference in production capacity KPI 23 , Maintenance Cost KPI 24 .

[0107] Among them, the interference average recovery time KPI 22 Determined by these three indicators: Production line performance recovery time KPI 221 , Compensation equipment conversion time KPI 222 , Workstation function automatic recovery time KPI 223 .

[0108] S2, determine the relevant parameters of the production line and their statistical distribution. By recording and counting the historical operation data of the production line for a period of time, the statistical distribution (such as normal distribution, triangular distribution, etc.) of the startup time, processing time, failure rate, tool change time, etc. of each device can be obtained.

[0109] S3, set up different interference environments and corresponding countermeasures. Assume that there are M kinds of interference environments that often occur, and take corresponding adjustment countermeasures for each interference situation. For example, if there is equipment failure, send repair workers to repair it, if the tool is broken or worn, replace the tool, if there is a station failure with compensation equipment, convert the compensation equipment, etc.

[0110] S4, establish a discrete event simulation model for the production line. Use Plant Simulation to establish a discrete event simulation model for the production line, input the required parameters for each device in the model, establish product transfer relationships between devices, material supply settings, etc. Conduct simulation experiments for each interference environment, and make corresponding countermeasures for the production line in each interference environment. Repeat the experiment N times in each interference environment and record KPIs 11 , KPI 12 , KPI 23 Statistical results.

[0111] S5, statistical analysis of simulation results and operation status. First, the KPIs obtained for each interference scenario are 11 , KPI 12 , KPI 23 The value of is analyzed at risk (with a confidence level of 95%) to obtain the KPI 11 , KPI 12 , KPI 23 The risk values ​​are: V 11 ,V 12 ,V 23 ;

[0112] Secondly, based on the statistical analysis of the historical operation data of the production line, we can get the KPI 21 , KPI 221 , KPI 222 , KPI 223 , KPI 24 The corresponding data distributions and the risk value analysis (taking the confidence level as 95%) are: V 21 , V 221 , V 222 , V 223 , V 24 .

[0113] S6, determine the weights of KPIs of each category. Use the analytic hierarchy process to determine the weights of KPIs of each category: K1, K2. For KPIs of the same category, determine the weights of each KPI: K 11 , K 12 , K 21 , K 22 , K 23 , K 24 Among them, K22 By K 221 , K 222 , K 223 Determined in the same way. The relationship between the weights is:

[0114] K1+K2=1

[0115] K 221 +K 222 +K 223 =1

[0116] S7, determine the KPI value in each interference environment. For each interference environment, normalize each KPI to obtain: 11 , v 12 , v 21 , v 221 , v 222 , v 223 , v 23 , v 24 .like Figure 3 The normalized values ​​are weighted to obtain the KPI values ​​of the same category:

[0117] V1=K 11 v 11 +K 12 v 12

[0118]

[0119] Where v2 is:

[0120] Then perform weighted summation on the values ​​of the two types of KPIs to obtain: V = K1V1 + K2V2;

[0121] S8, determine the overall adaptability of the production line. Compare the values ​​of aKPI calculated under M different interference scenarios and obtain the maximum value V Max and minimum value V Min , the adaptability range of the production line is [V Min ,V Max ]. This adaptability interval represents the distribution range of the overall adaptability of the production line.

[0122] Or count the frequency of each interference environment in the historical operation, and assign weights k1, k2, k3, ... k according to the frequency. M , and then the overall adaptability of the production line is calculated by weighted calculation: Among them, V ‘ Indicates the overall adaptability of the production line, V i ′Indicates the KPI value under various interference conditions.

[0123] Embodiment 2

[0124] A computer-readable storage medium, characterized in that the computer-readable storage medium includes a stored computer program, wherein when the computer program is executed by a processor, the device where the storage medium is located is controlled to execute a production line adaptability quantitative evaluation method as described above.

[0125] The relevant technical solution is the same as that in Embodiment 1 and will not be described in detail here.

[0126] It will be easily understood by those skilled in the art that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A quantitative evaluation method for adaptability of a production line, characterized in that: include: According to the production parameters of the production line to be evaluated and the statistical distribution information of various production parameters, a discrete event simulation model of the production line is established; According to each interference environment of the predetermined production line and its countermeasures, multiple simulation experiments are performed on the simulation model to obtain multiple values ​​of the adaptability evaluation index of each production line under the interference environment; Performing statistical analysis on multiple values ​​of each adaptability evaluation index under each interference environment to obtain the adaptability value of the adaptability evaluation index under each interference environment; Based on the weights of various adaptability evaluation indicators, the adaptability values ​​of each adaptability evaluation indicator under each interference environment are weighted and summed to obtain the total adaptability value of the production line under the interference environment; The adaptability of the production line to be evaluated is quantitatively determined by the total adaptability value of each interference environment; The adaptability evaluation index is selected from the following indicators: Production efficiency indicators and production line buffer capacity indicators belonging to the dynamic performance of the production line; Interference detection speed index, interference mean recovery time index, compensation capacity index and maintenance cost index belonging to the maintainability of the production line; wherein the interference mean recovery time index includes the production line performance recovery time index, the compensation equipment conversion time index and the workstation function recovery time index; The production line buffer capacity index represents the ratio of the total number of products that can be accommodated in the buffer zone of the production line to the average number of products in process in the buffer zone; The interference detection speed index represents the average value of the detection speed of various types of interference detected by the production line; The compensation capacity index is represented by the relative compensation difference of production efficiency, and the relative compensation difference of production efficiency represents the ratio of the difference in production efficiency of the same production line under the conditions of no compensation capacity and with compensation capacity to the production efficiency of the production line under the condition of no compensation capacity; The maintenance cost represents the weighted cost of the production line's response measures to various types of disturbances; The compensation device conversion time index represents the ratio of the total conversion time of all devices with compensation function to the total conversion times of the compensation devices; The workstation function recovery time indicator indicates the time from when processing is stopped due to non-equipment failure to when processing is resumed.

2. The method for quantitatively evaluating the adaptability of a production line according to claim 1, characterized in that: When the production line to be evaluated is in the design stage, the adaptability evaluation indicators include: Production efficiency indicators and production line buffer capacity indicators belonging to the dynamic performance of the production line; It is a compensation capacity indicator of the maintainability of the production line.

3. The method for quantitatively evaluating the adaptability of a production line according to claim 2, characterized in that: The quantitative determination of the adaptability of the production line to be evaluated is specifically: The maximum and minimum values ​​of the total adaptability values ​​of each interference environment are determined, and the interval formed by the maximum and minimum values ​​is used as the adaptability distribution range of the production line to complete the quantitative evaluation of the adaptability of the production line.

4. The method for quantitatively evaluating the adaptability of a production line according to claim 1, characterized in that: When the production line to be evaluated is in operation, the adaptability evaluation indicators include: Production efficiency indicators and production line buffer capacity indicators belonging to the dynamic performance of the production line; The indicators of interference detection speed, interference mean recovery time, compensation capacity and maintenance cost belong to the maintainability of the production line.

5. The method for quantitatively evaluating the adaptability of a production line according to claim 4, characterized in that: The quantitative determination of the adaptability of the production line to be evaluated is specifically: Determine the maximum and minimum values ​​of the total adaptability values ​​of each interference environment, use the interval formed by the maximum and minimum values ​​as the adaptability distribution range of the production line, and complete the quantitative evaluation of the adaptability of the production line; or, The frequency of occurrence of each interference environment in the historical operation is counted, and a weight is assigned to each interference environment according to the frequency. The total adaptability value of each interference environment is weighted summed up as the adaptability of the production line to complete the quantitative evaluation of the adaptability of the production line.

6. A production line adaptability quantitative evaluation method according to any one of claims 1 to 5, characterized in that: The statistical analysis is performed on multiple values ​​of each adaptability evaluation indicator under each interference environment, specifically, a risk value analysis is performed on multiple values ​​of each adaptability evaluation indicator under each interference environment, and the risk value of the adaptability evaluation indicator under each interference environment is obtained as the adaptability value of the adaptability evaluation indicator under each interference environment.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored computer program, wherein when the computer program is executed by a processor, the device where the storage medium is located is controlled to execute a quantitative evaluation method for adaptability of a production line as described in any one of claims 1 to 6.

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