A method for evaluating the capacity of a cabin production line for mixed-flow production of multiple products considering the impact of production sequence

Abstract

The present invention proposes a method for evaluating the capacity of a cabin production line for mixed-flow production of multiple products that takes into account the influence of the production sequence, including: calculating the effective operating time according to the number of working days, the design base of the day and time, and the failure rate of each device specified in the production task; calculating the actual demand for each type of product and grouping the original production tasks in combination with the product type, planned production quantity and qualified rate; optimizing the production sequence based on the grouping results and product processing information using the Palmer heuristic algorithm, combined with the equipment idle time index, calculating the shortest total processing time and equipment load rate; comparing the effective operating time with the shortest total processing time, judging whether the capacity can meet the production, and evaluating the operating efficiency and resource utilization in combination with the equipment load rate. The present invention comprehensively considers the influence of the production characteristics of the flow workshop and the production sequence, improves the accuracy of the capacity evaluation through precise calculation and optimized sorting, and provides a scientific basis for production task planning.

Description

Technical Field

[0001] The present invention relates to the technical field of production line capacity assessment, and in particular to a method for assessing the capacity of a cabin production line for mixed-flow production of multiple products taking into account the influence of production sequence. Background Art

[0002] In order to efficiently utilize resources and reduce production costs, modern factories are actively promoting lean production models such as Just-In-Time Production. In this process, the capacity assessment of the production line is particularly critical. A capacity assessment method that can be combined with specific production scenarios and has high accuracy and efficiency can not only help factories quantify the work efficiency and capacity of the production line, but also provide strong support for the formulation of production plans and the rational allocation of resources, thereby optimizing the utilization efficiency of the production line and helping to achieve lean production goals.

[0003] In response to this demand, many scholars have conducted research on capacity assessment methods around different production scenarios. For example, some scholars have proposed a capacity assessment method for civil aircraft manufacturing projects suitable for small-batch production by comprehensively considering the capacity of workstation tooling resources and skilled human resources; some scholars have used the representative product method and fuzzy evaluation sets to assess the capacity of discrete production lines; and other scholars have constructed a quantitative assessment method for aviation product production capacity based on the idea of ​​"decomposition-calculation-aggregation". These studies provide a rich theoretical basis and practical methods for production line capacity assessment.

[0004] However, most existing studies focus on the capacity assessment of discrete production lines, while relatively few studies focus on assembly lines. Even if some methods attempt to assess the capacity of assembly lines, they mainly simplify them into discrete models for analysis through the representative product method. This simplification ignores the impact of different product types and their production sequence on actual production efficiency in multi-variety mixed flow production. Therefore, this type of method has certain errors in the capacity assessment of multi-variety mixed flow production lines. It can be seen that there is an urgent need for an assembly line capacity assessment method that can comprehensively consider the production sequence and product diversity to better adapt to complex actual production needs. Summary of the invention

[0005] In view of the problems existing in the above-mentioned prior art, the present invention is based on the production task of multi-variety mixed flow, and innovatively includes the impact of the production sequence of the products to be produced on the actual production into the evaluation scope; at the same time, the waiting time caused by the subsequent processing equipment due to the limitation of the previous process in the actual production process is taken into account, and combined with the actual situation that in the multi-variety mixed flow production, the cabin production line usually decomposes large production orders into multiple small batches by quantity, so that the capacity evaluation results are more in line with the actual production line capacity performance. The method proposed in the present invention aims to solve the problem that the existing methods do not fully consider the impact of the production sequence, resulting in low accuracy of the production capacity evaluation results of the multi-variety mixed flow cabin production line.

[0006] In order to achieve the above technical objectives, the present invention proposes the following technical solutions:

[0007] A method for evaluating the capacity of a cabin production line for multi-product mixed flow production considering the impact of production sequence, which specifically includes the following steps:

[0008] S1. Calculate the effective operation time of the production line within the production task period according to the number of working days specified in the production task, the design base of days and hours, and the failure rate of each equipment on the production line;

[0009] S2. Calculate the actual production quantity of each product type based on the product type, planned production quantity and qualified rate; then group the original production tasks according to the proportion between the actual production quantity of each product type, so as to sort the subsequent production queue;

[0010] S3. Based on the grouping results and the occupied time of the product on the equipment, the Palmer heuristic algorithm is used to set the idle time index of the equipment to determine the final production queue of the original production task; and the shortest total processing time of the production line under the final production queue and the load rate of each equipment are calculated;

[0011] S4. Compare the effective operating time of the production line with the shortest total processing time, analyze the matching degree between task requirements and production capacity, and evaluate the operating efficiency and resource utilization of the production line in combination with the equipment load rate. Finally, the evaluation result of the production line capacity is obtained to guide the adjustment of production tasks and production lines.

[0012] Furthermore, step S1 specifically includes:

[0013] S11. Calculate the total running time of the production line within the production task period , the formula is:

[0014] ;

[0015] in, The number of working days for the deadline is Design base number for the time of day;

[0016] S12. Exclude the time when equipment on the production line is faulty based on the total operating time , we can get the effective normal operation time of the production line, the formula is:

[0017] ;

[0018] in, For the production line j The failure rate of each device.

[0019] Furthermore, step S2 specifically includes:

[0020] S21. Calculate the actual production quantity of each product in the production task. The formula is:

[0021] ;

[0022] in, is the actual production quantity required for the i-th product, is the planned production quantity of the i-th product in the production task, is the production qualification rate of the i-th product; Indicates rounding up;

[0023] S22, according to the actual production quantity of the i-th product , the original large-scale production task is divided into two parts. The first part includes The same minimum production cycle unit MPS is set. In each minimum production cycle unit, the number of products produced is In the second part, the number of products produced is indivual;

[0024] , , The calculation formulas are:

[0025] ;

[0026] ;

[0027] ;

[0028] in, is the minimum number of production cycle units; Indicates the product type. j Indicates the device number. m Indicates that the production task requires production m products, nIndicates that there are n equipment; is rounding down; mod is the remainder function.

[0029] Furthermore, step S3 specifically includes:

[0030] S31. Design the slope index, sort the production priorities of each product type, and give priority to the production of products with the largest slope index; if there are multiple products with the same slope index and all of them are the maximum value, they will be produced in sequence according to the original order in the production task; i The calculation formula of the slope index of this product is:

[0031] ;

[0032] in, is the time that the i-th product occupies the j-th device, and its calculation formula is:

[0033] ;

[0034] in, is the loading time of the i-th product on the j-th device, is the production and processing time of the i-th product on the j-th equipment, is the disassembly time of the i-th product on the j-th equipment;

[0035] S32. Calculate the average machine time occupied by each product type on the production line , and calculate the product's occupancy time coefficient on each device ; The calculation formulas are:

[0036] ;

[0037] ;

[0038] S33, according to the single cycle method, the products in the production task are produced in pairs, and the sum of the occupation time coefficients of the two products in the combination on each device is calculated; then the theoretical idle time coefficients and of each device in the combination during production are calculated according to the maximum value of the sum of the occupation time coefficients. ; The specific process is as follows:

[0039] The two products to be combined are ith product and kth product. When i≠k, it means a combination of different products; when i=k, it means a combination of different individuals of the same product. Calculate the maximum value of the sum of the occupation time coefficients of the combination of ith product and kth product on each device. , the formula is:

[0040] ;

[0041] in, Indicates the time coefficient of the kth product on each device;

[0042] According to Find the theoretical idle time coefficient and of each equipment when the combination of the i-th product and the k-th product is processed in the production line. , the formula is:

[0043] ;

[0044] Calculate the value of each combination , and sort them in order from smallest to largest Sort by The smaller it is, the higher the production priority of the two product combinations;

[0045] S34, according to the slope index and the theoretical idle time coefficient of each device and Schedule the two parts after the original production task is grouped to obtain the final production scheduling plan;

[0046] S35: Produce according to the final production sequencing plan obtained in step S34, and calculate the shortest total processing time under this sequencing plan , and combined with the obtained To calculate the equipment load rate of each equipment on the production line.

[0047] More specifically, step S34 specifically includes:

[0048] S341, firstly sort the production of the first part, and the production order of each group of minimum cycle production units in the first part is the same; the production sorting process of a single minimum cycle production unit is:

[0049] 1) Initialize the set to be sorted; first sort the various products in the minimum cycle production unit according to their respective production numbers. Put it into the collection to be sorted;

[0050] 2) The slope indicator The largest product is placed at the first position in the production queue and is deleted from the set to be sorted;

[0051] 3) Combined with the theoretical idle time coefficient of each device and , determine the next product in the production queue; when selecting a combination with the last product in the production queue from the set to be sorted The smallest product is placed next in the production queue and deleted from the set to be sorted;

[0052] 4) Repeat 3) until the set to be sorted is empty, and place all products in the production queue in sequence; output the production queue at this time, which is the final production queue of each group of minimum cycle production units in the first part;

[0053] 5) Connecting the final production queues of each group of minimum cycle production units in series, thus obtaining the final production queue of the first part;

[0054] S342, sort the production of the second part; similarly, initialize the set to be sorted first, and then use the last product in the final production queue of the first part as the benchmark for sorting. Size judgment: According to the process described in 3), all products in the second part of the to-be-sorted set are placed in the production queue in turn, so as to obtain the final production queue of the second part;

[0055] S343, arranging the final production queue of the first part before the final production queue of the second part, connecting the two in series, and obtaining the final production queue of the original production task.

[0056] More specifically, step S35 specifically includes:

[0057] S351, calculate the shortest total processing time , the relevant calculation model is expressed as follows:

[0058] Objective function:

[0059] ;

[0060] Mathematical description:

[0061] ;

[0062] ;

[0063] ;

[0064] ;

[0065] in, represents the completion time of the ath product in the final production queue on the jth device, is the occupancy time of the ath product in the final production queue on the jth device, It represents the completion time of the bth product in the final production queue on the nth device; b is the total number of b products in the production queue, and n is the total number of n devices on the production line;

[0066] S352, through the shortest total processing time To calculate the load factor of each device , and its calculation formula is:

[0067] ;

[0068] ;

[0069] in, For the Total production running time of each device, Shared for production tasks Product categories, For the The actual production quantity of the product required, For the The product is in The active time on each device.

[0070] Furthermore, step S4 specifically includes:

[0071] S41. First compare the effective operation time of the production line and the shortest total processing time :

[0072] like , it is considered that the production capacity of the production line is sufficient to support the corresponding production work, and the production task can be successfully completed on the production line;

[0073] like , it is considered that the production capacity of the production line is insufficient to support the corresponding production work, and the production tasks need to be adjusted and the production capacity of the production line needs to be upgraded;

[0074] S42. Evaluate the operating efficiency and resource utilization of the production line in combination with the equipment load rate, and adjust the production plan based on the evaluation results; specifically including:

[0075] when When , it is judged that equipment j is under high load, and the process it executes is considered to be the bottleneck process;

[0076] when When , it is judged that the device j is in normal load;

[0077] when When , it is judged that the device j is under low load;

[0078] For high-load equipment, when it is determined in step S41 that the production line capacity is insufficient, the production capacity is improved by optimizing the bottleneck process, including: adjusting the production task allocation and increasing the equipment capacity;

[0079] For low-load equipment, it indicates that the utilization rate of these equipment is low under the current product structure. When formulating production tasks, the equipment load is increased, including increasing the proportion of products with longer production processes on this equipment, thereby improving the equipment's capacity utilization rate;

[0080] For equipment with normal load, continue to maintain the existing production plan and dynamically adjust production tasks as appropriate to optimize the overall efficiency of the production line.

[0081] Based on the above technical solution, the present invention has at least the following beneficial effects:

[0082] 1. A detailed analysis was conducted on the actual operation of the cabin production line with mixed production of multiple products, and a capacity evaluation system considering the impact of the production sequence was proposed.

[0083] 2. Based on the actual operation of the production line, the original production order is broken down into multiple small orders according to the output quantity of each product variety, so as to achieve balanced output of each product variety within each cycle time. This mechanism ensures the flexibility and continuity of production and is particularly suitable for manufacturing environments that require collaborative production of multiple products.

[0084] 3. Based on the Palmer heuristic algorithm, the idle time of each device when the product is combined is taken into consideration, so that the proposed production queue sorting method can effectively avoid resource waste and improve production efficiency when facing multi-product production lines.

[0085] 4. By calculating and judging the load rate of each equipment, it provides the direction and focus of improvement for capacity improvement, helps identify bottleneck processes, and provides a scientific basis for the optimization of the production line. BRIEF DESCRIPTION OF THE DRAWINGS

[0086] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0087] Figure 1 A schematic flow chart of a method for evaluating the capacity of a cabin production line for mixed-flow production of multiple products taking into account the impact of the production sequence proposed by the present invention;

[0088] Figure 2 This is an example diagram of a serial cabin assembly line for mixed-flow production of multiple products involved in the present invention;

[0089] Figure 3 It is a schematic diagram of production task grouping in the method proposed by the present invention;

[0090] Figure 4 It is a schematic diagram of the production sequencing flow of a single minimum production cycle unit in the method proposed by the present invention. DETAILED DESCRIPTION

[0091] The following will be combined with the attached Figure 1-4 , the technical solutions in the embodiments of the present invention are clearly and completely described. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0092] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention.

[0093] In this embodiment, a cabin production line with mixed production of multiple products is taken as an example, and the method provided by the present invention is applied to perform capacity assessment. It should be noted that the following data and scenarios are all hypothetical and do not reflect any real situation. The specific settings are as follows:

[0094] Assuming the production period is 33 days, the types and quantities of the production tasks of the cabin production line are shown in Table 1 below; products A, B, C, D, and E in the table correspond to the 1st, 2nd, 3rd, 4th, and 5th products respectively;

[0095] Table 1 Production line production task table

[0096] ;

[0097] Secondly, assume that the production line is an assembly line, including five processes, and each process is equipped with one device. The qualified rate of each product, the time the product occupies each device, and the failure rate of each device entered in Table 1 are shown in Table 2 below:

[0098] Table 2 Occupancy time (minutes), pass rate and equipment failure rate of each product on each device

[0099] ;

[0100] Based on the above assumptions, a multi-product mixed flow production line is constructed, such as Figure 2 As shown, the capacity is evaluated by the method proposed by the present invention below;

[0101] like Figure 1 As shown, the present invention proposes a method for evaluating the capacity of a cabin production line for mixed-flow production of multiple products taking into account the influence of the production sequence, which specifically includes the following steps:

[0102] S1. Calculate the effective operation time of the production line within the production task period according to the number of working days specified in the production task, the design base of days and hours, and the failure rate of each equipment on the production line;

[0103] As a preferred implementation, step S1 specifically includes:

[0104] S11. Calculate the total running time of the production line within the production task period , the formula is:

[0105] ;

[0106] in, The number of working days for the deadline is Design base number for the time of day;

[0107] S12. Exclude the time when equipment on the production line is faulty based on the total operating time , we can get the effective normal operation time of the production line, the formula is:

[0108] ;

[0109] in, For the production line j The failure rate of each device.

[0110] In this embodiment, the design base number of the day Refers to the working hours of the production line every day under certain production conditions, after deducting the time lost due to shift change, planned equipment maintenance, maintenance shutdown, etc., and the value is determined according to the designed shift system; the shift system is divided into: one shift system, two shift system, and three shift system; in this embodiment, the two shift system is used, and the working time of each shift after deducting the lost time is 7 hours;

[0111] Because the production line is an assembly line, any failure of any equipment will cause the entire production line to stop working, so the effective operation time of the production line is the time when all equipment does not fail; Figure 3 In the case of the input information of the production line shown, combined with the data in Table 2, we can get:

[0112] The design base of the time of day set in this embodiment The production period is 840 minutes If the total running time is 33 days, then the total running time is:

[0113] ;

[0114] For the production task in this embodiment, the effective operation time of the production line It is 26601 minutes.

[0115] S2. Calculate the actual production quantity of each product type based on the product type, planned production quantity and qualified rate; then group the original production tasks according to the proportion between the actual production quantity of each product type, so as to sort the subsequent production queue;

[0116] As a preferred implementation, step S2 specifically includes:

[0117] S21. Calculate the actual production quantity of each product in the production task. The formula is:

[0118] ;

[0119] in, is the actual production quantity required for the i-th product, is the planned production quantity of the i-th product in the production task, is the production qualification rate of the i-th product; Indicates rounding up;

[0120] Because the planned production quantity in the production task What is required is not the number of products to be processed, but the number of qualified finished products after the production line is processed. Therefore, through this formula, the actual number of products to be processed by the production line (including qualified and unqualified products after processing) can be obtained, and this can be used as the basis for subsequent calculation of the completion time of the production task. In this way, the obtained capacity assessment results will be more in line with reality; through the data in Table 1 and Table 2, the actual production quantity required for various products can be obtained as shown in Table 3 below:

[0121] Table 3 Actual production quantity required for each product

[0122] ;

[0123] The production of aviation cabins has the following characteristics: the production cycle is long, and the production of a single cabin usually takes several hours; the product specifications are large, occupying a large processing and storage space, resulting in high inventory costs. At the same time, in order to achieve a balanced output of various products within each cycle time, a flexible and continuous production mechanism is required. Therefore, factories usually adopt a mode of dividing large tasks into multiple small tasks for production; this method is also adopted in this embodiment;

[0124] S22, according to the actual production quantity of the i-th product ,like Figure 3 As shown, the original large-scale production task is divided into two parts. The first part includes The same minimum production cycle unit MPS is set. In each minimum production cycle unit, the number of products produced is In the second part, the number of products produced is indivual;

[0125] , , The calculation formulas are:

[0126] ;

[0127] ;

[0128] ;

[0129] in, is the minimum number of production cycle units; Indicates the product type. j Indicates the device number. m Indicates that the production task requires production m products, n Indicates that there are n equipment; is rounding down; mod is the remainder function.

[0130] From Table 3, we can see that , and thus find the , , as shown in Table 4 below:

[0131] Table 4 Products and

[0132] ;

[0133] From this, we can calculate that of the two parts of the production task, the first part needs to produce 9 minimum production cycle units, and each minimum production cycle unit produces 3 A, 3 B, 1 C, 2 D, and 3 E; the second part needs to produce 7 A, 1 B, 0 C, 1 D, and 5 E.

[0134] S3. Based on the grouping results and the input production task information, the Palmer heuristic algorithm is used to set the idle time index of the equipment to determine the final production queue of the original production task; and the shortest total processing time of the production line under the final production queue and the load rate of each equipment are calculated;

[0135] As a preferred implementation, step S3 specifically includes:

[0136] S31. Design the slope index, sort the production priorities of each product type, and give priority to the production of products with the largest slope index; if there are multiple products with the same slope index and all of them are the maximum value, they will be produced in sequence according to the original order in the production task; i The calculation formula of the slope index of this product is:

[0137] ;

[0138] in, is the time that the i-th product occupies the j-th device, and its calculation formula is:

[0139] ;

[0140] in, is the loading time of the i-th product on the j-th device, is the production and processing time of the i-th product on the j-th equipment, is the disassembly time of the i-th product on the j-th equipment;

[0141] In the classic flow shop production scheduling heuristic algorithm, the Palmer method can quickly generate a better feasible solution. Therefore, this method is designed to first use the slope index The priority of each product type is ranked; the slope index and priority ranking of each product are shown in Table 5 below:

[0142] Table 5 Slope index and priority ranking of each product

[0143] ;

[0144] However, when a production task includes multiple products of the same type, the traditional Palmer method usually arranges the production of the same products in a centralized manner; this sorting method easily leads to excessive load on the equipment executing the bottleneck process in a certain period of time, while other process equipment is idle due to insufficient tasks, thereby reducing the overall production efficiency. Therefore, in the method proposed in the present invention, only the first product to be produced and processed is selected by the slope index, and the remaining products are sorted by setting the idle time index of the equipment; by adding subsequent sorting rules on the basis of the Palmer method, the effect of the method in the face of such production scenarios is significantly improved; the following steps S32-S33 are the specific process of calculating the idle time index.

[0145] S32. Calculate the average machine time occupied by each product type on the production line , and calculate the product's occupancy time coefficient on each device ; The calculation formulas are:

[0146] ;

[0147] ;

[0148] S33, according to the single cycle method, the products in the production task are produced in pairs, and the sum of the occupation time coefficients of the two products in the combination on each device is calculated; then the theoretical idle time coefficients and of each device in the combination during production are calculated according to the maximum value of the sum of the occupation time coefficients. ; The specific process is as follows:

[0149] The two products to be combined are ith product and kth product. When i≠k, it means a combination of different products; when i=k, it means a combination of different individuals of the same product. Calculate the maximum value of the sum of the occupation time coefficients of the combination of ith product and kth product on each device. , the formula is:

[0150] ;

[0151] in, Indicates the time coefficient of the kth product on each device;

[0152] According to Find the theoretical idle time coefficient and of each equipment when the combination of the i-th product and the k-th product is processed in the production line. , the formula is:

[0153] ;

[0154] Calculate the value of each combination , and sort them in order from smallest to largest Sort by The smaller the value, the higher the production priority of the two product combinations; therefore, combining the data in Table 2 and the above formula, we can get and and in accordance with The order from small to large is shown in Table 6 below:

[0155] Table 6 Product combinations and in accordance with Sort from smallest to largest

[0156] ;

[0157] Combined with Table 6 The ranking can be used to determine the priority of the products that will be put into production immediately after a certain product is put into production, as shown in Table 7 below:

[0158] Table 7 The production priority of subsequent products of different types of first-production products

[0159] ;

[0160] S34, combined with Table 5 and Table 7, according to the slope index and the theoretical idle time coefficient of each device and Schedule the two parts after the original production task is grouped to obtain the final production scheduling plan;

[0161] The specific production sorting process is:

[0162] S341, firstly sort the production of the first part, and the production order of each group of minimum cycle production units in the first part is the same; Figure 4 As shown, the production sequencing process of a single minimum cycle production unit is:

[0163] 1) Initialize the set to be sorted; first sort the various products in the minimum cycle production unit according to their respective production numbers. Put it into the collection to be sorted;

[0164] 2) The slope indicator The largest product is placed at the first position in the production queue and is deleted from the set to be sorted;

[0165] 3) Combined with the theoretical idle time coefficient of each device and , determine the next product in the production queue; when selecting a combination with the last product in the production queue from the set to be sorted The smallest product is placed next in the production queue and deleted from the set to be sorted;

[0166] 4) Repeat 3) until the set to be sorted is empty, and place all products in the production queue in sequence; output the production queue at this time, which is the final production queue of each group of minimum cycle production units in the first part;

[0167] 5) Connecting the final production queues of each group of minimum cycle production units in series, thus obtaining the final production queue of the first part;

[0168] In this embodiment, the production order of the first part is: according to the slope index, the first place in the group is determined to be E, and then according to the production priority, the production queue order of the group can be obtained as EBABABADEDEC, and the production queue of the first part is 9 groups connected in series, that is, (EBABABADEDEC)*9.

[0169] S342, sort the production of the second part; similarly, initialize the set to be sorted first, and then use the last product in the final production queue of the first part as the benchmark for sorting. For size judgment, all products in the to-be-sorted set of the second part are placed in the production queue in turn according to the process described in 3), and the final production queue of the second part is obtained; S341 shows that the last product in the sorting of each group of production queues in the first part is product C, so the sorting of the production queue of the second part is BADAAAAAAEEEEE;

[0170] S343, arranging the final production queue of the first part before the final production queue of the second part, and connecting the two in series, so that the final production queue of the original production task is:

[0171] (EBABABADEDEC)*9+BADAAAAAAEEEEE;

[0172] S35: Produce according to the final production sequencing plan obtained in step S34, and calculate the shortest total processing time under this sequencing plan , and combined with the obtained To calculate the equipment load rate of each equipment on the production line.

[0173] The calculation process of the shortest total processing time and equipment load rate is:

[0174] S351, calculate the shortest total processing time , the relevant calculation model is expressed as follows:

[0175] Objective function:

[0176] ;

[0177] Mathematical description:

[0178] ;

[0179] ;

[0180] ;

[0181] ;

[0182] in, represents the completion time of the ath product in the final production queue on the jth device, is the occupancy time of the ath product in the final production queue on the jth device, It represents the completion time of the bth product in the final production queue on the nth device; b is the total number of b products in the production queue, and n is the total number of n devices on the production line;

[0183] S352, through the shortest total processing time To calculate the load factor of each device , and its calculation formula is:

[0184] ;

[0185] ;

[0186] in, For the Total production running time of each device, Shared for production tasks Product categories, For the The actual production quantity of the product required, For the The product is in The time that the computer is busy on each device.

[0187] In this embodiment, the shortest total processing time is calculated according to the final production queue after the production sorting in step S34 (i.e., production in the order of (EBABABADEDEC)*9+BADAAAAAAEEEEE), the original production order (i.e., 34 A, 28 B, 9 C, 19 D, 32 E are produced in sequence), and only the Palmer method is used for sorting (i.e., 32 E, 19 D, 9 C, 28 B, 34 A are produced in sequence). The results are shown in Table 8 below:

[0188] Table 8 Results of three sorting methods

[0189] ;

[0190] From the comparison of the shortest total completion time of three different production sequencing methods in Table 8, it can be clearly seen that the shortest total completion time required by the method proposed by the present invention is significantly lower than the time obtained by simply producing in accordance with the production order sequence and the Palmer method. This shows that the sequencing method of this patent can obtain a better sequencing scheme for actual production and processing in a shorter time. For this reason, this method can improve the production capacity of the production line to a certain extent. At the same time, because the influence of factors such as production sequence and qualified rate are considered in this method, the shortest total completion time obtained is more in line with the actual situation, thereby improving the accuracy of capacity assessment.

[0191] At this time, calculate the load rate of each device, as shown in Table 9 below:

[0192] Table 9 Load rate of each equipment

[0193] ;

[0194] Next, the production line capacity is evaluated based on the shortest total processing time and equipment load rate.

[0195] S4. Compare the effective operation time of the production line with the shortest total processing time, analyze the matching degree between task requirements and production capacity, and evaluate the operation efficiency and resource utilization of the production line in combination with the equipment load rate, and finally obtain the evaluation result of the production line capacity to guide the adjustment of production tasks and production lines;

[0196] As a preferred implementation, step S4 specifically includes:

[0197] S41. First compare the effective operation time of the production line and the shortest total processing time :

[0198] like , it is considered that the production capacity of the production line is sufficient to support the corresponding production work, and the production task can be successfully completed on the production line;

[0199] like , it is considered that the production capacity of the production line is insufficient to support the corresponding production work, and the production tasks need to be adjusted and the production capacity of the production line needs to be upgraded;

[0200] In this embodiment, the shortest total processing time makespan = 25801 (minutes), the effective running time =26601 (minutes), , so the production task in this embodiment can be completed smoothly in the production line;

[0201] S42. Evaluate the operating efficiency and resource utilization of the production line in combination with the equipment load rate, and adjust the production plan based on the evaluation results; specifically including:

[0202] when When , it is judged that equipment j is under high load, and the process it executes is considered to be the bottleneck process;

[0203] when When , it is judged that the device j is in normal load;

[0204] when When , it is judged that the device j is under low load;

[0205] For high-load equipment, when it is determined in step S41 that the production line capacity is insufficient, the production capacity is improved by optimizing the bottleneck process, including: adjusting the production task allocation and increasing the equipment capacity;

[0206] For low-load equipment, it indicates that the utilization rate of these equipment is low under the current product structure. When formulating production tasks, the equipment load is increased, including increasing the proportion of products with longer production processes on this equipment, thereby improving the equipment's capacity utilization rate;

[0207] For equipment with normal load, continue to maintain the existing production plan and dynamically adjust production tasks as appropriate to optimize the overall efficiency of the production line.

[0208] In this embodiment, , Take 93% and 85% respectively; and then analyze it in combination with the data in Table 9; the load rate of equipment 5 is 97.21%, the highest among all equipment, and it is a high-load equipment (bottleneck process equipment), indicating that process 5 executed on this equipment is the bottleneck process in this production plan. If you want to increase production capacity without changing the product structure, you should give priority to improving the production capacity of process 5 and equipment 5 to alleviate the limitation of bottleneck processes on overall production efficiency. At the same time, the load rate of equipment 3 is 96.51%, which is also a high-load equipment (bottleneck process equipment), indicating that the process it executes also has a great impact on production capacity, and it should be listed as an object of concern that is equally important as equipment 5 to prevent further aggravation of the bottleneck effect.

[0209] In contrast, the load rates of equipment 1 and equipment 2 are 83.12% and 80.99% respectively, which are low-load equipment, indicating that the processing requirements of the corresponding processes 1 and 2 in the current product structure are relatively low. It is recommended to appropriately increase the task ratio of these processes in the overall production task plan to improve equipment utilization. At the same time, when optimizing the overall production capacity, the bottleneck process problem can be solved first, and the adjustment priority of processes 1 and 2 can be appropriately reduced.

[0210] The load rate of equipment 4 is 91.33%, which is a normal load equipment, indicating that its working efficiency is relatively balanced. It is recommended to maintain the current task allocation in the production plan to ensure that its load rate remains in a reasonable range to support the overall operation stability of the production line.

[0211] In summary, the method proposed in the present invention can effectively perform production sequencing when facing a cabin production line with mixed production of multiple products; while ensuring the flexibility and continuity of production, by considering the impact of the production sequence of the products to be produced on the actual production and the idle time of the equipment, it is possible to effectively avoid waste of resources, improve the production efficiency of the production line, and make the results of capacity assessment more accurate; in addition, it also provides improvement directions and key points for capacity improvement in combination with the equipment load rate, helps identify bottleneck processes, and provides a scientific basis for the optimization of the production line.

[0212] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0213] The above-mentioned embodiments only express several implementation modes of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the invention. It should be pointed out that, for a person of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the attached claims.

Claims

1. A method for evaluating the capacity of a cabin production line for multi-product mixed flow production considering the impact of production sequence, characterized in that: The specific steps include: S1. Calculate the effective operation time of the production line within the production task period according to the number of working days specified in the production task, the design base of days and hours, and the failure rate of each equipment on the production line; S2. Calculate the actual production quantity of each product type based on the product type, planned production quantity and qualified rate; then group the original production tasks according to the proportion between the actual production quantity of each product type, so as to sort the subsequent production queue; Step S2 specifically includes: S21. Calculate the actual production quantity of each product in the production task. The formula is: ； in, is the actual production quantity required for the i-th product, is the planned production quantity of the i-th product in the production task, is the production qualification rate of the i-th product; Indicates rounding up; S22, according to the actual production quantity of the i-th product , the original large-scale production task is divided into two parts. The first part includes The same minimum production cycle unit MPS is set. In each minimum production cycle unit, the number of products produced is In the second part, the number of products produced is indivual; , , The calculation formulas are: ； ； ； in, is the minimum number of production cycle units; Indicates the product type. j Indicates the device number. m Indicates that the production task requires production m products, n Indicates that there are n equipment; is rounding down; mod is the remainder function; S3, based on the grouping results, combined with the occupied time of the product on the equipment, the Palmer heuristic algorithm is used to set the idle time index of the equipment to determine the final production queue of the original production task; and the shortest total processing time of the production line under the final production queue and the load rate of each equipment are calculated; Step S3 specifically includes: S31. Design the slope index, sort the production priorities of each product type, and give priority to the production of products with the largest slope index; if there are multiple products with the same slope index and all of them are the maximum value, they will be produced in sequence according to the original order in the production task; i The calculation formula of the slope index of this product is: ； in, is the time that the i-th product occupies the j-th device, and its calculation formula is: ； in, is the loading time of the i-th product on the j-th device, is the production and processing time of the i-th product on the j-th equipment, is the disassembly time of the i-th product on the j-th equipment; S32. Calculate the average machine time occupied by each product type on the production line , and calculate the product's occupancy time coefficient on each device ; The calculation formulas are: ； ； S33, according to the single cycle method, the products in the production task are produced in pairs, and the sum of the occupation time coefficients of the two products in the combination on each device is calculated; then the theoretical idle time coefficients and of each device in the combination during production are calculated according to the maximum value of the sum of the occupation time coefficients. ; The specific process is as follows: The two products to be combined are ith product and kth product. When i≠k, it means a combination of different products; when i=k, it means a combination of different individuals of the same product. Calculate the maximum value of the sum of the occupation time coefficients of the combination of ith product and kth product on each device. , the formula is: ； in, Indicates the time coefficient of the kth product on each device; According to Find the theoretical idle time coefficient and of each equipment when the combination of the i-th product and the k-th product is processed in the production line. , the formula is: ； Calculate the value of each combination , and sort them in order from smallest to largest Sort by The smaller it is, the higher the production priority of the two product combinations; S34, according to the slope index and the theoretical idle time coefficient of each device and Schedule the two parts after the original production task is grouped to obtain the final production scheduling plan; S35: Produce according to the final production sequencing plan obtained in step S34, and calculate the shortest total processing time under this sequencing plan , and combined with the obtained To calculate the equipment load rate of each equipment on the production line; S4. Compare the effective operating time of the production line with the shortest total processing time, analyze the matching degree between task requirements and production capacity, and evaluate the operating efficiency and resource utilization of the production line in combination with the equipment load rate. Finally, the evaluation result of the production line capacity is obtained to guide the adjustment of production tasks and production lines.

2. The method for evaluating the capacity of a cabin production line according to claim 1, characterized in that: Step S1 specifically includes: S11. Calculate the total running time of the production line within the production task period , the formula is: ； in, The number of working days for the deadline is Design base number for the time of day; S12. Exclude the time when equipment on the production line is faulty based on the total operating time , we can get the effective normal operation time of the production line, the formula is: ； in, For the production line j The failure rate of each device.

3. The method for evaluating the capacity of a cabin production line according to claim 1, characterized in that: Step S34 specifically includes: S341, firstly sort the production of the first part, and the production order of each group of minimum cycle production units in the first part is the same; the production sorting process of a single minimum cycle production unit is: 1) Initialize the set to be sorted; first sort the various products in the minimum cycle production unit according to their respective production numbers. Put it into the collection to be sorted; 2) The slope indicator The largest product is placed at the first position in the production queue and is deleted from the set to be sorted; 3) Combined with the theoretical idle time coefficient of each device and , determine the next product in the production queue; when selecting the combination with the last product in the production queue from the set to be sorted The smallest product is placed next in the production queue and deleted from the set to be sorted; 4) Repeat 3) until the set to be sorted is empty, and place all products in the production queue in sequence; output the production queue at this time, which is the final production queue of each group of minimum cycle production units in the first part; 5) Connecting the final production queues of each group of minimum cycle production units in series, thus obtaining the final production queue of the first part; S342, sort the production of the second part; similarly, initialize the set to be sorted first, and then use the last product in the final production queue of the first part as the benchmark for sorting. Size determination: According to the process described in 3), all products in the second part of the to-be-sorted set are placed in the production queue in turn, so as to obtain the final production queue of the second part; S343, arranging the final production queue of the first part before the final production queue of the second part, connecting the two in series, and obtaining the final production queue of the original production task.

4. The method for evaluating the capacity of a cabin production line according to claim 1, characterized in that: Step S35 specifically includes: S351, calculate the shortest total processing time , the relevant calculation model is expressed as follows: Objective function: ； Mathematical description: ； ； ； ； in, represents the completion time of the ath product in the final production queue on the jth device, is the occupancy time of the ath product in the final production queue on the jth device, It represents the completion time of the bth product in the final production queue on the nth device; b is the total number of b products in the production queue, and n is the total number of n devices on the production line; S352, through the shortest total processing time To calculate the load factor of each device , and its calculation formula is: ； ； in, For the Total production running time of each device, Shared for production tasks Product categories, For the The actual production quantity of the product required, For the The product is in The active time on each device.

5. The method for evaluating the capacity of a cabin production line according to claim 1, characterized in that: Step S4 specifically includes: S41. First compare the effective operation time of the production line and the shortest total processing time : like , it is considered that the production capacity of the production line is sufficient to support the corresponding production work, and the production task can be successfully completed on the production line; like , it is considered that the production capacity of the production line is insufficient to support the corresponding production work, and the production tasks need to be adjusted and the production capacity of the production line needs to be upgraded; S42. Evaluate the operating efficiency and resource utilization of the production line in combination with the equipment load rate, and adjust the production plan based on the evaluation results; specifically including: when When , it is judged that equipment j is under high load, and the process it executes is considered to be the bottleneck process; when When , it is judged that the device j is in normal load; when When , it is judged that the device j is under low load; For high-load equipment, when it is determined in step S41 that the production line capacity is insufficient, the production capacity is improved by optimizing the bottleneck process, including: adjusting the production task allocation and increasing the equipment capacity; For low-load equipment, it indicates that the utilization rate of these equipment is low under the current product structure. When formulating production tasks, the equipment load is increased, including increasing the proportion of products with longer production processes on this equipment, thereby improving the equipment's capacity utilization rate; For equipment with normal load, continue to maintain the existing production plan and dynamically adjust production tasks as appropriate to optimize the overall efficiency of the production line.

Images