Intelligent production management system for factory production

Abstract

The present invention discloses an intelligent production management system applied to factory production, relates to the technical field of factory production management, and solves the technical problem that the prior art does not consider how to reasonably set a production schedule and process orders in an orderly and efficient manner when there are multiple orders with the same delivery date; the present invention analyzes the quantity of stored materials at monitoring nodes based on production information and replenishes them in time; classifies orders based on order information and arranges the priority of orders; predicts whether the order can be delivered on time based on order information and production information; if so, the factory produces at a normal speed; if not, the production plan is adjusted; by monitoring the quantity of stored materials, reasonably arranging the production sequence of orders, and adjusting the production plan in time, all-round intelligent monitoring of factory production is achieved, thereby improving the production efficiency and economic benefits of the factory.

Description

Technical Field

[0001] The present invention belongs to the field of factory production management, and specifically relates to an intelligent production management system applied to factory production. Background Art

[0002] Smart factory is a new stage in the development of modern factory informatization. It is based on digital factory and uses Internet of Things technology and equipment monitoring technology to strengthen information management and services.

[0003] The invention patent application with publication number CN116957253A discloses a factory production management system and method, which includes: a planning and scheduling module, a linkage adjustment module and a plan execution module. The planning and scheduling module is used to receive the production delivery plan, arrange the production delivery plan, generate an initial production scheduling plan, and transmit the initial production scheduling plan to the linkage adjustment module. The initial production scheduling plan includes several main processes, and each of the main processes includes several operation units; the linkage adjustment module is used to receive the initial production scheduling plan, and adjust the time of the main process and the operation unit according to the current production capacity, generate a revised production scheduling plan, and transmit the revised production scheduling plan to the plan execution module; the plan execution module is used to receive the revised production scheduling plan and execute the revised production scheduling plan. It is used to solve the defect of low scheduling efficiency in the prior art, realize automatic scheduling of production control, and improve production efficiency.

[0004] The above-mentioned prior art arranges the initial production schedule according to the production delivery plan, and adjusts the production schedule according to the current real-time production capacity to improve production efficiency and enable on-time delivery; but it does not consider how to reasonably set the production schedule and process the orders in an orderly and efficient manner when there are multiple orders with the same delivery date; therefore, the present invention provides an intelligent production management system for factory production. Summary of the invention

[0005] The present invention aims to solve at least one of the technical problems existing in the prior art; to this end, the present invention proposes an intelligent production management system applied to factory production, which is used to solve the technical problem that the prior art does not consider how to reasonably set up production scheduling and process orders in an orderly and efficient manner when there are multiple orders with the same delivery date.

[0006] To achieve the above-mentioned object, the first aspect of the present invention provides an intelligent production management system applied to factory production, comprising a data analysis module, and a data acquisition module and a plan adjustment module connected thereto;

[0007] Data collection module: used to collect order information and production information; order information includes customer information, order demand and delivery date; production information includes storage material quantity, production output and procurement time;

[0008] Data analysis module: used to analyze whether the storage material quantity at the monitoring node reaches the corresponding expected material quantity; if not, analyze the material purchase quantity based on the expected material quantity and order demand; if yes, analyze whether the storage material quantity meets the order demand; if yes, there is no need to purchase materials; if not, analyze the material purchase quantity; and,

[0009] Categorize and prioritize orders;

[0010] Plan adjustment module: Based on order information and production information, predict whether the order can be delivered on time; if yes, the factory will produce at normal speed; if not, adjust the production plan.

[0011] Preferably, the expected material quantity corresponding to the storage material quantity at the monitoring node includes:

[0012] Extract the order demand data of several years from the historical data; count the order demand between the kth monitoring node and the k+1th monitoring node in several years, and perform average processing to obtain the expected material quantity corresponding to the storage material quantity at the kth monitoring node; where k is the monitoring node number, and k starts from 0, k is an integer, and the last monitoring node is the last day of each year.

[0013] By analyzing historical data, the present invention can identify patterns and trends in order demand, thereby more accurately predicting future material demand; enterprises can adjust inventory levels, reduce capital occupation and storage costs caused by excessive inventory, and through accurate prediction of demand, they can prepare sufficient materials in advance and reduce the risk of not being able to meet customer orders due to out-of-stock, thereby improving customer satisfaction and market share.

[0014] Preferably, when the storage material quantity at the monitoring node does not reach the corresponding expected material quantity, analyzing the material purchase quantity according to the expected material quantity and the order demand quantity includes:

[0015] Determine whether the expected material quantity meets the order requirement; if yes, the material purchase quantity is the difference between the expected material quantity and the stored material quantity; if no, the material purchase quantity is the difference between the stored material quantity and the order requirement; and,

[0016] The material purchase quantity is the difference between the order quantity that can be generated by the warehouse material quantity and the order demand quantity.

[0017] Preferably, the difference between the storage material quantity and the order demand quantity includes:

[0018] If a product is composed of i types of materials, and the proportions of each material are x0, x1, ..., xi; through the formula Calculate the demand quantity WQi of the i-th material in the order demand quantity; perform difference processing on the material demand quantity and the corresponding warehouse material quantity to obtain the purchase quantity of each type of material quantity; where DQ is the order demand quantity; i is a positive integer.

[0019] The present invention can ensure that the purchased materials just meet the order requirements by accurately calculating the material purchase quantity, avoiding excessive inventory backlogs, reducing capital occupation and storage costs; at the same time, it avoids the problem of material expiration or deterioration caused by excessive purchases, and also reduces the waste of resources caused by inaccurate demand forecasts; it ensures that there are enough materials to respond to order requirements in a timely manner, reduces order delays or cancellations, and improves customer satisfaction and loyalty.

[0020] Preferably, the material purchase quantity is the difference between the expected material quantity and the stored material quantity, including:

[0021] Match the expected material quantity with the stored materials one by one, perform difference processing, and obtain the purchase quantity of each type of material.

[0022] Preferably, the categorizing of the orders and arranging the order priorities include:

[0023] Classify and number the orders according to the delivery date, and arrange the production of the orders in the order of delivery date;

[0024] When there are several orders with the same delivery date, the customer's credit index is analyzed based on the customer information; the orders with the same delivery date are sorted according to the order of the credit index.

[0025] The present invention ensures that orders are completed on time by sorting by delivery date, thus avoiding the inconvenience caused to customers by delayed delivery; and for orders with the same delivery date, the needs of high-quality customers are given priority based on the customer credit index of the order, which helps to establish long-term and stable customer relationships; at the same time, orders from customers with high credit ratings are given priority, which helps to speed up capital recovery, improve cash flow, and reduce bad debt risks; the efficient and accurate order processing process demonstrates the professionalism and reliability of the enterprise, and helps to enhance market competitiveness and brand image.

[0026] Preferably, the production sequence of the orders with the same delivery date is arranged according to the credit index of the customer, including:

[0027] Extract the customer's on-time delivery rate and average annual order volume from the customer information, and use the formula Calculate the customer's credit index; sort the credit index from large to small, which is the production order of the order; among them, JFL is the on-time delivery rate, that is, the proportion of orders delivered on time from the beginning of cooperation to the current customer to the total order volume; NDL is the average annual order volume, that is, the average annual order volume from the beginning of cooperation to the current customer.

[0028] The on-time delivery rate in the formula of the present invention reflects the reliability of the customer, and the average annual order volume reflects the customer's demand and stability for the company's products or services. The combination of the two can more accurately evaluate the customer's credit index; through the credit index, the company can identify high-value and high-credit customers, so as to implement more targeted customer service strategies, such as giving priority to their orders, providing customized services, strengthening communication and cooperation with them, and thus deepening customer relationships.

[0029] Preferably, based on the order information and production information, predict whether the order can be delivered on time, including:

[0030] Extract the order delivery date, production output and procurement time from the order information and production information, and use the formula The remaining production quantity SQj is calculated; where j is the order category code; DQj is the order demand of the jth order; YQj is the produced output; T0j-T1j-CGT is the remaining delivery time, and T0j is the delivery date; T1j is the current date, and the current date is before the delivery date; CGT is the procurement time, which is obtained by analyzing the current date; V is the production speed of a single production line; N is the number of production lines;

[0031] If the remaining production quantity SQj=0, the order can be delivered on time; if the remaining production quantity SQj≠0, the order cannot be delivered on time.

[0032] The present invention reflects the production progress and remaining workload of each order by analyzing the remaining amount to be produced. By calculating the remaining amount to be produced, the enterprise can promptly discover possible production delays, gain time for taking remedial measures, rationally plan production lines and human resources, avoid idle or overloaded resources, improve the flexibility and response speed of the overall production system, ensure on-time delivery of orders, enhance customer trust and satisfaction with the enterprise, help maintain and expand customer relationships, and enhance market competitiveness.

[0033] Preferably, the purchase duration is obtained by analyzing the current date, including:

[0034] Get the date when the purchased materials arrive at the warehouse and mark it as the material arrival date; determine whether the current date is before the material arrival date; if yes, the procurement duration is the difference between the material arrival date and the current date; if no, the procurement duration is 0.

[0035] Preferably, if the order cannot be delivered on time, the production plan is adjusted, including:

[0036] Calculate the number of production lines required based on the remaining delivery time and remaining production volume , that is, start MN spare production lines to produce simultaneously.

[0037] The present invention calculates the number of required production lines according to the remaining delivery time and the remaining production volume, and starts the spare production line in time, which can process more production tasks in parallel, thereby significantly improving the overall production efficiency and maintaining the continuity and stability of production; and in the case of large orders or tight delivery time, starting the spare production line can ensure that the products can be delivered to customers on time, avoiding breach of contract and loss of reputation;

[0038] Compared with the prior art, the present invention has the following beneficial effects:

[0039] 1. The present invention analyzes the order demand at each monitoring node through historical data, that is, identifies the trend of the order demand at the monitoring node in the future, so as to more accurately predict the future material demand, prepare sufficient materials in advance, and compare them with the order demand, and then accurately analyze the required material purchase quantity, purchase in time, and ensure that the storage material quantity meets the material quantity demand of the order demand without causing excessive backlog or shortage of materials;

[0040] 2. The present invention arranges production of orders in sequence according to the delivery date, and the production order of orders with the same delivery date is determined based on the customer's credit index, which reflects the customer's reputation and the stability of the cooperative relationship. Among the orders with the same delivery date, orders with a high customer credit index are given priority, which improves the orderly and efficient processing of orders, reduces the potential loss of accounts receivable of the enterprise, and helps to build and maintain long-term, mutually beneficial customer relationships;

[0041] 3. The present invention analyzes whether the amount of stored materials at the monitoring node reaches the corresponding expected material amount based on production information; if not, analyzes the material purchase amount according to the expected material amount and order demand; if yes, analyzes whether the amount of stored materials meets the order demand; if yes, there is no need to purchase materials; if no, analyzes the material purchase amount; classifies orders based on order information, and arranges the priority of orders; predicts whether the order can be delivered on time based on order information and production information; if yes, the factory produces at a normal speed; if no, adjusts the production plan; the present invention realizes all-round monitoring of factory production and improves the factory's production efficiency and economic benefits by monitoring the amount of stored materials, reasonably arranging the production sequence of orders, and making timely adjustments to the production plan. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0043] Figure 1 It is a schematic diagram of the system structure of the present invention;

[0044] Figure 2 It is a schematic diagram of the process of the present invention;

[0045] Figure 3 A schematic diagram of a method for arranging order production sequence of the present invention;

[0046] Figure 4 The figure is a flow chart of the production plan adjustment analysis method of the present invention. DETAILED DESCRIPTION

[0047] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. 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.

[0048] See also Figure 1-Figure 2 , the first aspect of the present invention provides an intelligent production management system for factory production, including a data analysis module, and a data acquisition module and a plan adjustment module connected thereto;

[0049] The data collection module collects order information and production information; among them, order information includes customer information, order demand and delivery date; order demand is the sum of orders with the same delivery date; production information includes storage material quantity, produced output and procurement time;

[0050] The data analysis module analyzes whether the storage material quantity at the monitoring node reaches the corresponding expected material quantity; if not, the material purchase quantity is analyzed based on the expected material quantity and order demand; if yes, whether the storage material quantity meets the order demand; if yes, there is no need to purchase materials; if not, the material purchase quantity is analyzed;

[0051] Among them, the analysis process of the expected material quantity corresponding to the storage material quantity at the monitoring node is as follows:

[0052] For example, the data of the storage material quantity in M ​​years is obtained from the historical data, and it is divided according to the monitoring nodes. If the monitoring node is set on the first day of each month, the monitoring nodes are numbered in sequence, that is, January 1 is marked as 0, January 2 is marked as 1, ..., December 1 is marked as 11;

[0053] The order demand between monitoring node 0 and monitoring node 1 is processed by ratio with M to obtain the expected material quantity corresponding to the storage material quantity at monitoring node 0; the order demand between monitoring node 1 and monitoring node 2 is processed by ratio with M to obtain the expected material quantity corresponding to the storage material quantity at monitoring node 1; and so on, the expected material quantity corresponding to the storage material quantity at 11 monitoring nodes is obtained;

[0054] It should be noted that, except for the last monitoring node, other monitoring nodes are set at different time nodes as needed; and because the last monitoring node is the last day of each year, the order demand is already included in the adjacent monitoring nodes, so there is no need to analyze the expected material quantity corresponding to the storage material quantity here.

[0055] When the storage material quantity at the monitoring node does not reach the corresponding expected material quantity, determine whether the expected material quantity meets the order demand; if yes, the material purchase quantity is the difference between the expected material quantity and the storage material quantity; if no, the material purchase quantity is the difference between the storage material quantity and the order demand; and,

[0056] The material purchase quantity is the difference between the order quantity that can be generated by the warehouse material quantity and the order demand quantity.

[0057] It should be noted that the difference between the storage material quantity and the order demand quantity is analyzed as follows:

[0058] If a product is composed of i types of materials, and the proportions of each material are x0, x1, ..., xi; through the formula Calculate the demand quantity WQi of the i-th material in the order demand quantity; perform difference processing on the material demand quantity and the corresponding warehouse material quantity to obtain the purchase quantity of each type of material quantity; where DQ is the order demand quantity; i is a positive integer.

[0059] It should be noted that the order demand is the quantity of products that need to be produced.

[0060] The demand for each type of material in the present invention is closely related to the ratio of the material in the product and the order demand. If the ratio of the material in the product and the order demand are both large, the demand for the material is large; if there are fewer such materials in the warehouse materials, they need to be purchased.

[0061] The difference between the expected material quantity and the stored material quantity is analyzed as follows:

[0062] Match the expected material quantity with the stored materials one by one, perform difference processing, and obtain the purchase quantity of each type of material.

[0063] See also Figure 3 ,In addition, the orders are classified and prioritized;

[0064] Specifically, the orders are classified and numbered according to the delivery date, orders with the same delivery date are grouped together, and the production of the orders is arranged in the order of the delivery dates; and,

[0065] Orders with the same delivery date are arranged in production order based on the customer's credit index.

[0066] Specifically, the on-time delivery rate and average annual order volume of customers are extracted from customer information, and the formula Calculate the customer's credit index; sort the credit index from large to small, which is the production order of the order; among them, JFL is the on-time delivery rate, that is, the proportion of orders delivered on time from the beginning of cooperation to the current customer to the total order volume; NDL is the average annual order volume, that is, the average annual order volume from the beginning of cooperation to the current customer.

[0067] It should be noted that the order with the highest credit index of the customer will be arranged for production first among the orders with the same delivery date, and the other orders will be arranged in order according to the credit index of the customer.

[0068] The present invention evaluates the credibility of customers through a credit index; the credibility of customers is closely related to the on-time delivery rate and the average annual order volume of customers; if the on-time delivery rate and the average annual order volume of customers are both high, it means that the customer has no arrears in order transactions, has a high degree of integrity, and has a high degree of trust in the factory, so the customer is a long-term and reliable partner with a high credit index.

[0069] The plan adjustment module predicts whether the order can be delivered on time based on order information and production information; if so, the factory will produce at normal speed; if not, the production plan will be adjusted.

[0070] See also Figure 4 Specifically, the delivery date, production output and procurement time of the order are extracted from the order information and production information, and the formula The remaining production quantity SQj is calculated; where j is the order category code, DQj is the order demand of the j-th order, YQj is the produced output, T0j-T1j-CGT is the remaining delivery time, and T0j is the delivery date, T1j is the current date, CGT is the procurement time, which is analyzed based on the current date, V is the production speed of a single production line, and is a fixed value, is the rated production speed of the production line, and N is the number of production lines.

[0071] The present invention evaluates whether the order demand can be completed on time according to the remaining production volume to be produced. The evaluation criteria for on-time completion are closely related to the order demand, the produced volume, the remaining delivery time and the number of production lines. If the remaining production volume SQj=0 is calculated, the order can be delivered on time; if the remaining production volume SQj≠0, the order cannot be delivered on time. The number of production lines required is calculated according to the remaining delivery time and the remaining production volume. , that is, start MN spare production lines to produce simultaneously.

[0072] The present invention evaluates the required number of production lines by the remaining production volume, the remaining delivery time and the production speed of a single production line, and enables the orders to be delivered on time by activating an appropriate number of spare production lines.

[0073] Among them, the procurement time is analyzed according to the current date, and the analysis process is as follows:

[0074] Get the date when the purchased materials arrive at the warehouse and mark it as the material arrival date; determine whether the current date is before the material arrival date; if yes, the procurement duration is the difference between the material arrival date and the current date; if no, the procurement duration is 0.

[0075] Part of the data in the above formula is calculated by removing the dimension and taking its numerical value. The formula is a formula closest to the actual situation obtained by software simulation of a large amount of collected data; the preset parameters and expected material quantity in the formula are set by technical personnel in this field according to actual conditions or obtained through simulation of a large amount of data.

[0076] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. Intelligent production management system applied to factory production, characterized by: It includes a data analysis module, and a data acquisition module and a plan adjustment module connected thereto; Data collection module: used to collect order information and production information; order information includes customer information, order demand and delivery date; production information includes storage material quantity, production output and procurement time; Data analysis module: used to analyze whether the storage material quantity at the monitoring node reaches the corresponding expected material quantity; if not, analyze the material purchase quantity based on the expected material quantity and order demand; if yes, analyze whether the storage material quantity meets the order demand; if yes, there is no need to purchase materials; if not, analyze the material purchase quantity; and, Categorize and prioritize orders; Whether the storage material quantity at the monitoring node reaches the corresponding expected material quantity includes: Extract the order demand data of several years from the historical data; count the order demand between the kth monitoring node and the k+1th monitoring node in several years, and perform average processing to obtain the expected material quantity corresponding to the storage material quantity at the kth monitoring node; where k is the monitoring node number, and k starts from 0, k is an integer, and the last monitoring node is the last day of each year; The material purchase quantity is analyzed based on the expected material quantity and order demand, including: Determine whether the expected material quantity meets the order requirement; if yes, the material purchase quantity is the difference between the expected material quantity and the stored material quantity; if no, the material purchase quantity is the difference between the stored material quantity and the order requirement; Plan adjustment module: Based on order information and production information, predict whether the order can be delivered on time; if yes, the factory will produce at normal speed; if not, adjust the production plan.

2. The intelligent production management system applied to factory production according to claim 1 is characterized in that: The difference between the storage material quantity and the order demand quantity includes: If a product is composed of i types of materials, and the proportions of each material are x0, x1, ..., xi; through the formula Calculate the demand quantity WQi of the i-th material in the order demand; perform difference processing on the material demand and the corresponding warehouse material quantity to obtain the purchase quantity of each type of material; where DQ is the order demand; i is a positive integer.

3. The intelligent production management system applied to factory production according to claim 1 is characterized in that: The material purchase quantity is the difference between the expected material quantity and the storage material quantity, including: Match the expected material quantity with the stored materials one by one, perform difference processing, and obtain the purchase quantity of each type of material.

4. The intelligent production management system applied to factory production according to claim 1 is characterized in that: The above-mentioned classification of orders and arrangement of order priorities include: Classify and number the orders according to the delivery date, and arrange the production of the orders in the order of delivery date; When there are several orders with the same delivery date, the customer's credit index is analyzed based on the customer information; the orders with the same delivery date are sorted according to the order of the credit index.

5. The intelligent production management system applied to factory production according to claim 4 is characterized in that: The production sequence of orders with the same delivery date is arranged according to the customer's credit index, including: Extract the customer's on-time delivery rate and average annual order volume from the customer information, and use the formula Calculate the customer's credit index; sort the credit index from large to small, which is the production order of the order; among them, JFL is the on-time delivery rate, that is, the proportion of orders delivered on time from the beginning of cooperation to the current customer to the total order volume; NDL is the average annual order volume, that is, the average annual order volume from the beginning of cooperation to the current customer.

6. The intelligent production management system applied to factory production according to claim 1 is characterized in that: Based on order information and production information, predict whether the order can be delivered on time, including: Extract the order delivery date, production output and procurement time from the order information and production information, and use the formula The remaining production quantity SQj is calculated; where j is the category code of the order; DQj is the order demand of the j-th order; YQj is the produced output; is the remaining delivery time, and T0j is the delivery date; T1j is the current date, and the current date is before the delivery date; CGT is the procurement time, which is analyzed based on the current date; V is the production speed of a single production line; N is the number of production lines; If the remaining production , the order can be delivered on time; if the remaining production , the order cannot be delivered on time.

7. The intelligent production management system applied to factory production according to claim 6 is characterized in that: The purchase duration is analyzed based on the current date and includes: Get the date when the purchased materials arrive at the warehouse and mark it as the material arrival date; determine whether the current date is before the material arrival date; if yes, the procurement duration is the difference between the material arrival date and the current date; if no, the procurement duration is 0.

8. The intelligent production management system applied to factory production according to claim 6 is characterized in that: If the order cannot be delivered on time, the production plan will be adjusted, including: Calculate the number of production lines required based on the remaining delivery time and remaining production volume , that is, start The backup production lines are in production at the same time.

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