A production and sales data management method and system

Abstract

The application discloses a production and sales data management method and system, and particularly relates to the technical field of production management. The application carries out multi-dimensional dynamic correction on the initial predicted production capacity based on historical sales volume by combining demand data such as order fulfillment rate and demand trend rate and production equipment operation data such as equipment utilization rate and abnormal downtime length, realizes accurate matching of the planned required production capacity and actual market demand and enterprise production capacity, effectively solves the problem of production capacity surplus or deficiency caused by single reference to historical data in the existing production capacity planning, and makes the production capacity planning more scientific and adaptive.

Description

Technical Field

[0001] This invention relates to the field of production management technology, and more specifically, to a production and sales data management method and system. Background Technology

[0002] Under the general trend of digitalization and intelligent development in the manufacturing industry, production management and production-sales collaboration have become core links for enterprises to improve operational efficiency and reduce operating costs. Traditional production and sales management models rely heavily on manual experience to formulate production plans and set inventory levels, and there are prominent problems such as the lack of quantitative standards for supplier selection. They are difficult to adapt to the dynamic adjustment needs of modern production. Therefore, data-driven production and sales data management technology has emerged and become a key support for the manufacturing industry to achieve efficient production and sales collaboration.

[0003] However, existing technologies still have the following shortcomings in their application: First, existing capacity planning methods only refer to historical sales data and do not combine multi-dimensional data such as order fulfillment, demand change trends and production equipment operation status for dynamic correction. This leads to a mismatch between planned capacity and actual production capacity and market demand, which can easily result in overcapacity or undercapacity. Secondly, traditional inventory management often adopts a fixed safety stock setting method, without making differentiated dynamic adjustments based on the importance level of materials, the magnitude of demand fluctuations, and differences in procurement lead time. This can easily lead to shortages of key materials that cause production interruptions, or long-term stockpiling of general materials that tie up a large amount of working capital for enterprises, resulting in a disconnect between the inventory structure and actual production needs. Furthermore, the supplier management process lacks a multi-indicator quantitative evaluation system that combines delivery timeliness, fulfillment capabilities, and product quality. Moreover, when inventory shortages occur, it is impossible to quickly identify high-quality suppliers that can meet replenishment needs, resulting in insufficient emergency response capabilities in the supply chain.

[0004] Therefore, a production and sales data management method and system are introduced. Summary of the Invention

[0005] To overcome the above-mentioned deficiencies of the prior art, embodiments of the present invention provide a production and sales data management method and system.

[0006] To achieve the above objectives, the present invention provides the following technical solution: A production and sales data management method includes the following steps: Determine the required production capacity: Obtain the actual sales volume of the past x months and calculate the initial forecast required production capacity by averaging the sales volume; dynamically revise the initial forecast required production capacity based on recent demand data and external influence data to determine the estimated planned production capacity required for the next month; The demand dimension data includes order fulfillment rate, demand trend rate, and the proportion of urgent orders; the production operation dimension data includes equipment utilization rate, abnormal downtime, and average cycle time of processes. Capacity supply verification: The planned capacity is broken down by product process, and the theoretical load rate of each process is calculated; based on the pre-built process load and quality mapping table, the processing workload of each process is corrected by comparing the quality loss cost and capacity improvement benefit under the theoretical load, so as to obtain the effective capacity of each process; the effective capacity of all processes is integrated to form the execution capacity, and the required inventory corresponding to the execution capacity is matched based on the pre-set mapping rules. When the required inventory is greater than the warehouse inventory, the subsequent supply-side evaluation process is triggered. Supply-side assessment: After triggering the supplier screening instruction, suppliers that can meet the inventory gap requirements are selected as candidates; multiple indicators of the candidates are comprehensively calculated to obtain the supplier merit value, which is compared with the preset threshold to screen qualified suppliers and generate a list to be pushed to the management terminal. The evaluation indicators include supplier fulfillment rate, average delivery cycle, and material qualification rate. Production execution monitoring: Monitor the execution process of planned capacity and supplier fulfillment, collect actual operating data and conduct comprehensive analysis with planned data to obtain execution deviation values, and determine the deviation level based on the execution deviation values.

[0007] Specifically, the process of analyzing demand data is as follows: The order fulfillment rate is calculated by comparing the total number of valid orders to be delivered and the number of orders actually delivered on time and in full during the statistical analysis period. The analysis period is divided into the first half and the second half. The average monthly sales of the first half and the second half are calculated separately. The ratio of the average monthly sales of the second half to the average monthly sales of the first half is used to calculate the demand trend rate. Within the statistical analysis period, the delivery cycle is shorter than the pre-set total number of urgent orders. The ratio of these urgent orders to the total number of all valid orders in the same period is calculated to obtain the proportion of urgent orders.

[0008] Specifically, the process for determining the required baseline capacity is as follows: The demand estimate is obtained by comprehensively processing the order fulfillment rate, demand trend rate, and the proportion of urgent orders. A pre-defined demand valuation threshold is set. When the demand valuation is greater than the corresponding threshold, the demand difference is calculated by subtracting the demand valuation from the corresponding threshold. Preset demand difference ranges for each group, and each demand difference range corresponds to a correction coefficient. Match the demand difference with the demand difference range to obtain the corresponding correction coefficient. The baseline required capacity is obtained by multiplying the correction factor by the initial predicted capacity.

[0009] Specifically, the process of analyzing external impact data is as follows: The actual effective operating hours of the equipment and the rated total available hours of the equipment are calculated separately within the period. The ratio of the effective operating hours to the rated total available hours is used to calculate the equipment utilization rate. The duration of each production interruption event is counted and summed to obtain the total abnormal downtime within the corresponding period. Collect the actual processing time of a single product under stable production conditions for each process within the current analysis period, and calculate the arithmetic mean as the average cycle time of the process.

[0010] Specifically, the process for determining the planned production capacity is as follows: A comprehensive evaluation value is obtained by comprehensively processing equipment utilization rate, abnormal downtime, and average cycle time of each process. The reference range corresponding to the preset comprehensive evaluation value; When the comprehensive evaluation value is higher than the corresponding threshold, the difference between the comprehensive evaluation value and the threshold is calculated to obtain the comprehensive evaluation high difference value. Each group of comprehensive evaluation high difference value intervals is preset, and each group of comprehensive evaluation high difference value intervals corresponds to a high impact coefficient. The comprehensive evaluation high difference value is matched with the corresponding interval to determine the high impact coefficient. When the comprehensive evaluation value is lower than the corresponding threshold, the absolute difference is calculated to obtain the low difference value of the comprehensive evaluation. The low difference value range of each group of comprehensive evaluation is preset, and each group of low difference value range of comprehensive evaluation corresponds to a low impact coefficient. The low difference value of comprehensive evaluation is matched with the corresponding range to determine the low impact coefficient. The planned required capacity is obtained by multiplying the baseline required capacity by the impact coefficient.

[0011] Specifically, the process for obtaining the execution capacity is as follows: Based on the planned required capacity, the theoretical processing workload of each process is obtained by breaking down the product process route, and the theoretical load rate of each process is calculated by combining the equipment operating parameters. Based on the preset process load rate and quality mapping table, determine the corresponding loss value, and calculate the capacity improvement benefit of the theoretical task volume relative to the reasonable load range; The cost of quality loss in a single process is compared with the benefits of increased capacity, and the effective capacity of each process is obtained by adjusting the comparison results. Summarize the effective capacity of each process and take the minimum value as the overall execution capacity according to the bottleneck constraint principle of the production line.

[0012] Specifically, the process of comprehensively analyzing the indicators of each candidate supplier is as follows: The total number of batches delivered by the candidate suppliers in the current period and the number of batches delivered on time are statistically analyzed. The ratio of the number of batches delivered on time to the total number of batches delivered is used to calculate the candidate supplier's fulfillment rate. The average delivery cycle is the average time from receiving a purchase order to the actual receipt of materials by the selected supplier. The material qualification rate is calculated by comparing the total number of batches supplied by the candidate suppliers with the number of qualified batches in the current period. Preset the supplier's fulfillment rate, average delivery cycle, and the corresponding pass value for material qualification rate; The supplier's merit value is obtained by comprehensively processing the supplier's fulfillment rate, average delivery cycle, and material qualification rate. The supplier merit value is compared with the corresponding preset supplier merit value threshold. Suppliers with merit values ​​greater than the corresponding threshold are selected as candidates and a set is constructed as a qualified supplier set and sent to the management terminal.

[0013] Specifically, the process for obtaining the execution deviation value is as follows: The actual output is calculated as the total number of products that have been processed, inspected, and put into storage in the workshop during the production cycle. The total number of products that have actually been shipped and delivered to customers during the current period is taken as the actual delivery quantity. By using the supply chain management system or supplier management system, extract the total quantity of materials that qualified suppliers have actually received and put into storage during the current period, and use this as the actual total quantity received. Extract the planned required production capacity, planned delivery quantity, and total planned delivery volume from qualified suppliers within the specified period; The execution deviation value is obtained by comprehensively processing the actual output, actual delivery quantity, and actual total arrival quantity. A preset execution deviation value corresponding to the execution deviation value threshold is used to compare the execution deviation value with the execution deviation value threshold. When the execution deviation value is less than or equal to the corresponding threshold, it is determined to be a controllable deviation; When the execution deviation value is greater than the corresponding threshold, it is judged as a large deviation.

[0014] Specifically, a production and sales data management system includes: Capacity Determination Module: Obtain the actual sales volume of the past x months, calculate the initial forecast required capacity by the arithmetic mean; dynamically revise the initial forecast required capacity based on recent demand data and external influence data, and determine the estimated planned capacity required for the next month; The demand dimension data includes order fulfillment rate, demand trend rate, and the proportion of urgent orders; the production operation dimension data includes equipment utilization rate, abnormal downtime, and average cycle time of processes. Capacity supply verification module: The planned capacity is broken down by product process, and the theoretical load rate of each process is calculated. Based on the pre-built process load and quality mapping table, the processing workload of each process is corrected by comparing the quality loss cost and capacity improvement benefit under the theoretical load, so as to obtain the effective capacity of each process. The effective capacity of all processes is integrated to form the execution capacity. Based on the pre-set mapping rules, the required inventory corresponding to the execution capacity is matched. When the required inventory is greater than the warehouse inventory, the subsequent supply-side evaluation process is triggered. Supply-side evaluation module: After triggering the supplier screening instruction, select suppliers that can meet the inventory gap requirements as candidates; calculate the supplier merit value by comprehensively calculating multiple indicators of the candidates, compare it with the preset threshold, screen out qualified suppliers and generate a list to push to the management terminal. The evaluation indicators include supplier fulfillment rate, average delivery cycle, and material qualification rate. Execution monitoring module: Monitors the execution process of planned capacity and supplier fulfillment, collects actual operating data and performs comprehensive analysis with planned data to obtain execution deviation value, and determines the deviation level based on the execution deviation value.

[0015] The technical effects and advantages of this invention are as follows: This invention combines demand data such as order fulfillment rate and demand trend rate with production equipment operation data such as equipment utilization rate and abnormal downtime to dynamically correct the initial predicted capacity based on historical sales in multiple dimensions. This achieves a precise match between the planned capacity and the actual market demand and the enterprise's production capacity, effectively solving the problem of overcapacity or undercapacity caused by relying solely on historical data in existing capacity planning, and making capacity planning more scientific and adaptable.

[0016] This invention breaks down the planned capacity according to the process route and calculates the theoretical load rate of each process. Based on the mapping relationship between process load and quality, it compares the cost of quality loss with the benefits of capacity improvement, thereby correcting the effective capacity of each process and determining the execution capacity according to the bottleneck principle. This achieves refined verification and optimization of capacity from planning to execution, ensuring that production tasks are stably implemented while taking into account both output and quality, and improving the rationality and controllability of production organization.

[0017] This invention quantifies and selects suppliers based on indicators such as fulfillment rate, average delivery cycle, and material qualification rate. It also collects actual data on output, inventory, delivery, and supply and calculates execution deviation values ​​to achieve hierarchical monitoring. This enables standardized supplier selection and accurate determination of execution deviations throughout the production and sales process. It solves the problems of traditional supplier selection lacking quantitative standards and incomplete monitoring of the production execution process, thereby improving supply chain response efficiency and production and sales collaborative management. Attached Figure Description

[0018] Figure 1 This is a flowchart of a production and sales data management method according to the present invention.

[0019] Figure 2 This is a flowchart of a production and sales data management system according to the present invention. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] Example 1 like Figure 1 As shown, the steps of a production and sales data management method are as follows: Determine the planned production capacity: Collect historical actual sales data from the past x months, calculate the initial projected production capacity using the arithmetic mean method, where x is greater than 3 and is an even number; then, combine recent demand data and production operation data to dynamically adjust the initial projected production capacity and determine the planned production capacity required for the next cycle. The demand dimension data includes order fulfillment rate, demand trend rate, and the proportion of urgent orders; the production operation dimension data includes equipment utilization rate, abnormal downtime, and average cycle time of processes. Specifically: The analysis cycle is set by technical personnel based on the industry's production characteristics; The order fulfillment rate is calculated by dividing the total amount due for delivery of all valid orders within the statistical analysis period by the actual amount delivered on time and in full. ; To clarify, the order fulfillment rate reflects the actual degree to which historical orders are met. The lower the fulfillment rate, the larger the scale of unmet potential demand. The analysis period is divided equally into the first half and the second half. The average monthly sales volume in each half is calculated separately. The demand trend rate is obtained by dividing the average monthly sales volume in the second half by the average monthly sales volume in the first half. ; Additional explanation: The demand trend rate is used to reflect the direction and magnitude of changes in product demand within a cycle, and can intuitively quantify whether demand is growing, stable, or declining. The total number of urgent orders with a delivery cycle below a preset threshold within the statistical analysis period is then calculated as a ratio to the total number of all valid orders during the same period to obtain the proportion of urgent orders. ; Additional explanation: The percentage of urgent orders is used to measure the impact of sudden, urgent demands on regular production arrangements, so as to reserve corresponding margins in capacity calculations; The order fulfillment rate, demand trend rate, and proportion of urgent orders were normalized using the formula. The demand estimate is obtained after weighted calculation. ,in , , These are the corresponding preset weighting factors; Set a threshold for the demand estimate. When the demand estimate is higher than the threshold, calculate the difference between the demand estimate and the threshold. Preset multiple difference ranges and configure a corresponding correction coefficient for each range. Obtain the corresponding correction coefficient by matching the difference. The correction coefficient is set to 1.053-1.264, and the larger the demand difference, the higher the correction coefficient. When the demand estimate is less than the corresponding threshold, the correction coefficient is 1. Multiply the initial projected capacity by the correction factor to obtain the baseline required capacity; For example, technicians set the analysis period to three months prior to the current time point based on the industry's production characteristics, with an average monthly sales volume of 1,000 units during this period, and use this as the initial forecast of the required production capacity. According to statistics, the order fulfillment rate was 0.85, the demand growth trend rate was 0.12, and the proportion of urgent orders was 0.18% during the analysis period. After normalizing the three indicators, the demand estimate was calculated to be 1.42 according to the preset weights. The preset demand estimation threshold is 1.2. Since Dem is greater than the threshold, the calculated demand difference is 0.22. The preset interval matching correction coefficient is 1.136. Multiplying the initial projected required capacity of 1,000 units by the correction factor, we get a baseline required capacity of 1,136 units. During the analysis period, the actual effective operating hours of the equipment are compared with the rated total available hours, and the equipment utilization rate is obtained by the ratio of the two. ; Additional information: Equipment utilization rate reflects the actual production capacity efficiency of equipment under stable operating conditions; Production interruptions caused by unforeseen factors such as equipment failure, material shortage, process abnormality, quality abnormality, energy interruption, or personnel abnormality are considered abnormal shutdowns. Within the analysis period, the duration of each production interruption event is counted and accumulated to obtain the total abnormal downtime within the corresponding period. ; Additional information: The total duration of abnormal downtime can quantify the actual loss of effective production time caused by unforeseen factors within the cycle. After removing extreme values ​​caused by equipment failure, personnel operation, material abnormalities, etc., the actual processing time of a single product under stable production conditions for each process within the current analysis period is collected, and the arithmetic mean is calculated as the average cycle time of the process. ; Additional explanation: The average cycle time of a process is used to quantify the actual production time per unit product, reflecting the true processing efficiency of the production line. Normalize the equipment utilization rate, abnormal downtime, and average cycle time of each process, and substitute them into the formula. The comprehensive evaluation value is obtained after weighted calculation. ,in , , These are the corresponding preset weighting factors; To elaborate further, the comprehensive evaluation value is used to comprehensively and quantitatively evaluate the production operation status and demand fluctuations within a set period. The higher the comprehensive evaluation value, the higher the equipment utilization rate, the shorter the abnormal downtime, the shorter the average cycle time of the process, the smoother the fluctuation of the cycle demand relative to the historical average level, the higher the production operation stability and production efficiency, and the conditions to support higher capacity output. The reference range corresponding to the preset comprehensive evaluation value is 1. When the comprehensive evaluation value is higher than the corresponding threshold, the difference between the comprehensive evaluation value and the threshold is calculated to obtain the comprehensive evaluation high difference value. Each group of comprehensive evaluation high difference value intervals is preset, and each group of comprehensive evaluation high difference value intervals corresponds to a high impact coefficient. The comprehensive evaluation high difference value is matched with the corresponding interval to determine the high impact coefficient. The high impact coefficient is set between 1.0536 and 1.1349, and the smaller the overall evaluation difference, the larger the high impact coefficient is matched. When the comprehensive evaluation value is lower than the corresponding threshold, the absolute difference is calculated to obtain the low difference value of the comprehensive evaluation. The low difference value range of each group of comprehensive evaluation values ​​is preset, and each group of comprehensive evaluation low difference values ​​corresponds to a low impact coefficient. The low difference value of the comprehensive evaluation value is matched with the corresponding range to determine the low impact coefficient. The low impact coefficient is set between 0.853 and 0.949, and the smaller the overall low difference, the larger the low impact coefficient is matched. The planned required capacity is obtained by multiplying the baseline required capacity by the impact coefficient. Capacity supply verification: The planned capacity is broken down by product process, and the theoretical load rate of each process is calculated; based on the pre-built process load and quality mapping table, the processing workload of each process is corrected by comparing the quality loss cost and capacity improvement benefit under the theoretical load, so as to obtain the effective capacity of each process; the effective capacity of all processes is integrated to form the execution capacity, and the required inventory corresponding to the execution capacity is matched based on the pre-set mapping rules. When the required inventory is greater than the warehouse inventory, the subsequent supply-side evaluation process is triggered. Specifically: Based on the planned capacity, the corresponding product process route is retrieved, and the overall planned capacity is broken down layer by layer according to the sequence of each process route to obtain the theoretical processing task for each process. Retrieve the operating parameters of equipment for each process, including the rated production time of the equipment, the number of equipment configured, and the historical equipment utilization rate; Each process combines the processing time of a single product in the corresponding process, multiplies the theoretical processing workload of the process by the processing time of a single product, and obtains the total processing time required for a single process to complete the production task; Based on the number of equipment configured in each process, the rated production hours of a single piece of equipment, and relevant equipment operating parameters, the overall effective available production hours of the process are calculated. The theoretical load rate of each process is obtained by calculating the ratio of the total working hours required for a single process task to the effective available working hours of the corresponding process. A mapping table between process load rate and quality is pre-built. Based on the theoretical load rate of each process, the corresponding loss standard is matched to obtain the loss value of the corresponding process. Pre-set a reasonable load range for the process, determine the standard production task corresponding to the load range, calculate the difference between the current theoretical production task of the process and the standard task corresponding to the reasonable load to obtain the overload output quantity, extract the revenue standard of a single product, and obtain the capacity increase revenue brought by the process maintaining the theoretical task compared to the reasonable load range. Internal horizontal comparison within a single process: Compare the quality loss cost of each process with the corresponding capacity improvement benefits: If the benefit of capacity increase is higher than the cost of quality loss in this process, the original theoretical production task is retained as the effective capacity of the process; if the benefit of capacity increase is lower than or equal to the cost of quality loss in this process, the task is adjusted to a reasonable load range standard, which is used as the effective capacity of the process. Summarize the effective capacity of all production processes after the correction, and take the minimum effective capacity of each process as the overall execution capacity according to the production line bottleneck constraint principle. The pre-defined capacity-inventory mapping rules, based on the theoretically required inventory corresponding to the overall execution capacity, obtain the actual warehouse inventory quantity by reading warehouse ledger data; A supplier screening instruction is triggered when the actual warehouse inventory is less than the theoretically required inventory. Supply-side assessment: After triggering the supplier screening instruction, suppliers that can meet the inventory gap requirements are selected as candidates; multiple indicators of the candidates are comprehensively calculated to obtain the supplier merit value, which is compared with the preset threshold to screen qualified suppliers and generate a list to be pushed to the management terminal. The evaluation indicators include supplier fulfillment rate, average delivery cycle, and material qualification rate. Specifically: The fulfillment rate is calculated by comparing the total number of deliveries made by the candidate suppliers with the number of deliveries made on time within the cycle. ; The average delivery cycle is defined as the average time from order acceptance to material receipt by the selected supplier. ; The material qualification rate is calculated by comparing the qualified batches of the candidate suppliers with the total number of supplied batches. ; The default supplier fulfillment rate, average delivery cycle, and material qualification rate are respectively marked as follows: , , ; The supplier fulfillment rate, average delivery cycle, and material qualification rate are calculated using the formula. The supplier's merit value is obtained after weighted calculation. ,in , , These are the corresponding preset weighting factors; The supplier merit value is compared with a pre-set threshold, and suppliers with merit values ​​higher than the threshold are selected to form a qualified supplier set and pushed to the management personnel terminal. Production execution monitoring: Monitor the supplier's performance process, collect actual operation data and analyze it together with the planned data to obtain the execution deviation value, and determine the deviation level based on the execution deviation value; The actual operating data includes actual output, actual delivery quantity, and actual total arrival volume; Specifically: The production management system extracts the total number of products that were actually processed, inspected, and put into storage during the production cycle as the actual output. ; The order management system is used to extract the total number of products that have actually been shipped and delivered to customers within the current period as the actual delivery quantity. ; Using the supply chain management system or supplier management system, extract the total quantity of materials that qualified suppliers have actually received and put into storage during the current period, as the actual total quantity received. ; The planned capacity required during the extraction cycle is marked as ; Extract planned delivery quantities from the order management system. ; Extract the planned total delivery volume from qualified suppliers and mark them as follows: ; After normalizing the actual output, actual delivery quantity, and actual total arrival quantity, the formula is used. The execution deviation value is obtained after weighted calculation. ,in , , These are the corresponding preset weighting factors; Additional explanation: The execution deviation value is used to quantify the degree of deviation between the plan and the actual situation. It does not distinguish between positive excess or negative shortfall, but only reflects the degree of execution alignment. The smaller the value, the closer the actual output, actual delivery quantity, and actual total arrival quantity are to the planned values; the larger the value, the more significant the deviation between actual execution and plan. A preset execution deviation value corresponding to the execution deviation value threshold is used to compare the execution deviation value with the execution deviation value threshold. When the execution deviation value is less than or equal to the corresponding threshold, it is determined to be a controllable deviation; Additional explanation: When a deviation is determined to be controllable, it means that although the actual execution deviates slightly from the plan, it is within a reasonable range overall. Regardless of whether it is a positive excess or a negative slight deficiency, the production schedule will not be adjusted, and the actual data and deviation values ​​for the current period will be archived in the historical database. When the execution deviation value is greater than the corresponding threshold, it is judged as a large deviation; Additional information: When a significant deviation is identified, it indicates that the actual deviation from the plan has exceeded the preset range, and an alert will be sent to the management personnel's terminal. The system automatically sends a warning message to the management personnel, indicating that the current production execution judgment has a large deviation.

[0022] The above formulas are all dimensionless calculations. Dimensionless calculations can be performed using various methods such as standardization, which will not be elaborated here. The formulas are derived from software simulations based on a large amount of collected data, and the preset parameters in the formulas can be set by those skilled in the art according to the actual situation.

[0023] Example 2 Please see Figure 2 As shown, based on the production and sales data management method provided in Embodiment 1 of this application, Embodiment 2 of this application proposes a production and sales data management system. Embodiment 2 is merely a preferred embodiment of Embodiment 1, and the implementation of Embodiment 2 will not affect the individual implementation of Embodiment 1.

[0024] Specifically, Embodiment 2 of this application provides a production and sales data management system, including: Capacity Determination Module: Obtain the actual sales volume of the past x months, calculate the initial forecast required capacity by the arithmetic mean; dynamically revise the initial forecast required capacity based on recent demand data and external influence data, and determine the estimated planned capacity required for the next month; The demand dimension data includes order fulfillment rate, demand trend rate, and the proportion of urgent orders; the production operation dimension data includes equipment utilization rate, abnormal downtime, and average cycle time of processes. Capacity supply verification module: The planned capacity is broken down by product process, and the theoretical load rate of each process is calculated. Based on the pre-built process load and quality mapping table, the processing workload of each process is corrected by comparing the quality loss cost and capacity improvement benefit under the theoretical load, so as to obtain the effective capacity of each process. The effective capacity of all processes is integrated to form the execution capacity. Based on the pre-set mapping rules, the required inventory corresponding to the execution capacity is matched. When the required inventory is greater than the warehouse inventory, the subsequent supply-side evaluation process is triggered. Supply-side evaluation module: After triggering the supplier screening instruction, select suppliers that can meet the inventory gap requirements as candidates; calculate the supplier merit value by comprehensively calculating multiple indicators of the candidates, compare it with the preset threshold, screen out qualified suppliers and generate a list to push to the management terminal. The evaluation indicators include supplier fulfillment rate, average delivery cycle, and material qualification rate. Execution monitoring module: Monitors the execution process of planned capacity and supplier fulfillment, collects actual operating data and performs comprehensive analysis with planned data to obtain execution deviation value, and determines the deviation level based on the execution deviation value.

[0025] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, ATA hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. The semiconductor medium can be a solid-state ATA hard disk.

[0026] It should be understood that in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0027] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0028] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0029] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0030] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0031] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable ATA hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0032] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for managing production and sales data, characterized in that, Includes the following steps: Determine the required production capacity: Obtain the actual sales volume of the past x months and calculate the initial forecast required production capacity by averaging the sales volume; dynamically revise the initial forecast required production capacity based on recent demand data and external influence data to determine the estimated planned production capacity required for the next month; The demand dimension data includes order fulfillment rate, demand trend rate, and the proportion of urgent orders; the production operation dimension data includes equipment utilization rate, abnormal downtime, and average cycle time of processes. Capacity supply verification: The planned capacity is broken down by product process, and the theoretical load rate of each process is calculated; based on the pre-built process load and quality mapping table, the processing workload of each process is corrected by comparing the quality loss cost and capacity improvement benefit under the theoretical load, so as to obtain the effective capacity of each process; the effective capacity of all processes is integrated to form the execution capacity, and the required inventory corresponding to the execution capacity is matched based on the pre-set mapping rules. When the required inventory is greater than the warehouse inventory, the subsequent supply-side evaluation process is triggered. Supply-side assessment: After triggering the supplier screening instruction, suppliers that can meet the inventory gap requirements are selected as candidates; multiple indicators of the candidates are comprehensively calculated to obtain the supplier merit value, which is compared with the preset threshold to screen qualified suppliers and generate a list to be pushed to the management terminal. The evaluation indicators include supplier fulfillment rate, average delivery cycle, and material qualification rate. Production execution monitoring: Monitor the execution process of planned capacity and supplier fulfillment, collect actual operating data and conduct comprehensive analysis with planned data to obtain execution deviation values, and determine the deviation level based on the execution deviation values.

2. The production and sales data management method according to claim 1, characterized in that, The specific process for analyzing demand data is as follows: The order fulfillment rate is calculated by comparing the total number of valid orders to be delivered and the number of orders actually delivered on time and in full during the statistical analysis period. The analysis period is divided into the first half and the second half. The average monthly sales of the first half and the second half are calculated separately. The ratio of the average monthly sales of the second half to the average monthly sales of the first half is used to calculate the demand trend rate. Within the statistical analysis period, the delivery cycle is shorter than the pre-set total number of urgent orders. The ratio of these urgent orders to the total number of all valid orders in the same period is calculated to obtain the proportion of urgent orders.

3. The production and sales data management method according to claim 1, characterized in that, The specific process for determining the required capacity for the benchmark is as follows: The demand estimate is obtained by comprehensively processing the order fulfillment rate, demand trend rate, and the proportion of urgent orders. A pre-defined demand valuation threshold is set. When the demand valuation is greater than the corresponding threshold, the demand difference is calculated by subtracting the demand valuation from the corresponding threshold. Preset demand difference ranges for each group, and each demand difference range corresponds to a correction coefficient. Match the demand difference with the demand difference range to obtain the corresponding correction coefficient. The baseline required capacity is obtained by multiplying the correction factor by the initial predicted capacity.

4. The production and sales data management method according to claim 1, characterized in that, The specific process for analyzing external impact data is as follows: The actual effective operating hours of the equipment and the rated total available hours of the equipment are calculated separately within the period. The ratio of the effective operating hours to the rated total available hours is used to calculate the equipment utilization rate. The duration of each production interruption event is counted and summed to obtain the total abnormal downtime within the corresponding period. Collect the actual processing time of a single product under stable production conditions for each process within the current analysis period, and calculate the arithmetic mean as the average cycle time of the process.

5. The production and sales data management method according to claim 1, characterized in that, The specific process for determining the planned production capacity is as follows: A comprehensive evaluation value is obtained by comprehensively processing equipment utilization rate, abnormal downtime, and average cycle time of each process. The reference range corresponding to the preset comprehensive evaluation value; When the comprehensive evaluation value is higher than the corresponding threshold, the difference between the comprehensive evaluation value and the threshold is calculated to obtain the comprehensive evaluation high difference value. Each group of comprehensive evaluation high difference value intervals is preset, and each group of comprehensive evaluation high difference value intervals corresponds to a high impact coefficient. The comprehensive evaluation high difference value is matched with the corresponding interval to determine the high impact coefficient. When the comprehensive evaluation value is lower than the corresponding threshold, the absolute difference is calculated to obtain the low difference value of the comprehensive evaluation. The low difference value range of each group of comprehensive evaluation is preset, and each group of low difference value range of comprehensive evaluation corresponds to a low impact coefficient. The low difference value of comprehensive evaluation is matched with the corresponding range to determine the low impact coefficient. The planned required capacity is obtained by multiplying the baseline required capacity by the impact coefficient.

6. The production and sales data management method according to claim 1, characterized in that, The specific process for obtaining the execution capacity is as follows: Based on the planned required capacity, the theoretical processing workload of each process is obtained by breaking down the product process route, and the theoretical load rate of each process is calculated by combining the equipment operating parameters. Based on the preset process load rate and quality mapping table, determine the corresponding loss value, and calculate the capacity improvement benefit of the theoretical task volume relative to the reasonable load range; The cost of quality loss in a single process is compared with the benefits of increased capacity, and the effective capacity of each process is obtained by adjusting the comparison results. Summarize the effective capacity of each process and take the minimum value as the overall execution capacity according to the bottleneck constraint principle of the production line.

7. The production and sales data management method according to claim 1, characterized in that, The specific process of conducting a comprehensive analysis of the indicators of each candidate supplier is as follows: The total number of batches delivered by the candidate suppliers in the current period and the number of batches delivered on time are statistically analyzed. The ratio of the number of batches delivered on time to the total number of batches delivered is used to calculate the candidate supplier's fulfillment rate. The average delivery cycle is the average time from receiving a purchase order to the actual receipt of materials by the selected supplier. The material qualification rate is calculated by comparing the total number of batches supplied by the candidate suppliers with the number of qualified batches in the current period. Preset the supplier's fulfillment rate, average delivery cycle, and the corresponding pass value for material qualification rate; The supplier's merit value is obtained by comprehensively processing the supplier's fulfillment rate, average delivery cycle, and material qualification rate. The supplier merit value is compared with the corresponding preset supplier merit value threshold. Suppliers with merit values ​​greater than the corresponding threshold are selected as candidates and a set is constructed as a qualified supplier set and sent to the management terminal.

8. The production and sales data management method according to claim 1, characterized in that, The specific process for obtaining the execution deviation value is as follows: The actual output is calculated as the total number of products that have been processed, inspected, and put into storage in the workshop during the production cycle. The total number of products that have actually been shipped and delivered to customers during the current period is taken as the actual delivery quantity. By using the supply chain management system or supplier management system, extract the total quantity of materials that qualified suppliers have actually received and put into storage during the current period, and use this as the actual total quantity received. Extract the planned required production capacity, planned delivery quantity, and total planned delivery volume from qualified suppliers within the specified period; The execution deviation value is obtained by comprehensively processing the actual output, actual delivery quantity, and actual total arrival quantity. A preset execution deviation value corresponding to the execution deviation value threshold is used to compare the execution deviation value with the execution deviation value threshold. When the execution deviation value is less than or equal to the corresponding threshold, it is determined to be a controllable deviation; When the execution deviation value is greater than the corresponding threshold, it is judged as a large deviation.

9. A production and sales data management system, applied to the production and sales data management method according to any one of claims 1-8, characterized in that, include: Capacity Determination Module: Obtain the actual sales volume of the past x months, and calculate the initial forecast required capacity by using the arithmetic mean; Based on recent demand data and external impact data, the initial forecast required capacity is dynamically revised to determine the estimated planned capacity required for the next month. The demand dimension data includes order fulfillment rate, demand trend rate, and the proportion of urgent orders; the production operation dimension data includes equipment utilization rate, abnormal downtime, and average cycle time of processes. Capacity supply verification module: The planned capacity is broken down by product process, and the theoretical load rate of each process is calculated. Based on the pre-built process load and quality mapping table, the processing workload of each process is corrected by comparing the quality loss cost and capacity improvement benefit under the theoretical load, so as to obtain the effective capacity of each process. The effective capacity of all processes is integrated to form the execution capacity. Based on the pre-set mapping rules, the required inventory corresponding to the execution capacity is matched. When the required inventory is greater than the warehouse inventory, the subsequent supply-side evaluation process is triggered. Supply-side evaluation module: After triggering the supplier screening instruction, select suppliers that can meet the inventory gap requirements as candidates; calculate the supplier merit value by comprehensively calculating multiple indicators of the candidates, compare it with the preset threshold, screen out qualified suppliers and generate a list to push to the management terminal. The evaluation indicators include supplier fulfillment rate, average delivery cycle, and material qualification rate. Execution monitoring module: Monitors the execution process of planned capacity and supplier fulfillment, collects actual operating data and performs comprehensive analysis with planned data to obtain execution deviation value, and determines the deviation level based on the execution deviation value.

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