Environmental protection industry production and manufacturing intelligent scheduling system based on data driving

Abstract

The invention relates to the technical field of industrial production and manufacturing scheduling, and particularly discloses an intelligent scheduling system for environmental protection industrial production and manufacturing based on data driving. After an emergency order insertion request is received, evaluating a delivery influence coefficient of each production equipment for executing emergency order insertion corresponding to each original production task; if the delivery influence coefficient of each original production task corresponding to the emergency order insertion executed by certain production equipment is 0, the production equipment is used as the production equipment for executing the emergency order insertion, otherwise, the maximum commodity quantity of each production equipment capable of producing the emergency order insertion is determined, so that the production sequence of each production equipment is dynamically adjusted, and the production efficiency is improved. According to the method, interference on original tasks can be reduced, the utilization rate of production resources is improved, the dynamic adjustment capability of the production plan can be optimized, production bottlenecks are reduced, and higher flexibility and adaptability are provided for enterprises.

Description

Technical Field

[0001] The present invention relates to the technical field of industrial production and manufacturing scheduling, and in particular to a data-driven intelligent scheduling system for environmental protection industry production and manufacturing. Background Art

[0002] Dynamic workshop scheduling is one of the key links for custom furniture companies to achieve intelligent production. In actual production workshops, emergency order insertion events often occur, and traditional workshop scheduling methods can no longer effectively deal with these emergencies. As customers' demands for personalized needs and delivery time become higher and higher, the production scheduling challenges faced by custom furniture companies are becoming more and more complicated. Traditional scheduling methods usually rely on pre-set production plans and static production scheduling plans. Once an emergency order occurs, it is often necessary to manually adjust the schedule, resulting in reduced production efficiency, delayed delivery, and even possible waste of resources and production bottlenecks. Current scheduling technology is insufficient in terms of resource utilization. When a piece of equipment is already close to full capacity, the system may still assign new tasks to it, causing it to become a production bottleneck. Other equipment with lighter loads may be idle and not fully utilized. This unbalanced resource allocation not only reduces overall production efficiency, but may also lead to excessive equipment wear or increased maintenance costs. Summary of the invention

[0003] In view of the deficiencies of the prior art, the present invention provides an intelligent scheduling system for production and manufacturing of the environmental protection industry based on data-driven.

[0004] The present invention solves the above technical problems through the following technical means: a data-driven intelligent scheduling system for environmental protection industry production and manufacturing, including a production task management module, an emergency order assessment module, a production delivery judgment module and a production scheduling optimization module, wherein the above modules are connected by wired and / or wireless connection to realize data transmission between the modules; Production task management module: used to manage the scheduling information of all original production tasks; Emergency order evaluation module: used to evaluate the delivery impact coefficient of each production equipment executing the emergency order corresponding to each original production task after receiving the emergency order request; Production delivery judgment module: If there is a production equipment that executes an emergency order and the delivery impact coefficients of all the original production tasks are 0, then the production equipment will be used as the production equipment for executing the emergency order. Otherwise, the production scheduling optimization module will be executed; Production scheduling optimization module: Determine the maximum number of goods that each production equipment can produce for emergency orders, and dynamically adjust the production order of each production equipment.

[0005] In a possible implementation, the production scheduling information of all originally scheduled production tasks includes delivery time, production priority, and remaining production quantity of each corresponding production equipment.

[0006] In a possible implementation, the evaluation of the delivery impact coefficient of each production equipment executing the emergency insertion order corresponding to each original production task is performed in the following specific evaluation process: Obtain the production demand XQ of the emergency order, and evaluate the delivery impact coefficient of each production equipment executing the emergency order corresponding to each original production task ; c is the number of each original production task, v is the number of each production equipment, They respectively represent the weight coefficients of the set calculation factors; is the production priority of the cth original production task, They represent the remaining delivery time and the total given production time of the cth original production task of the vth production equipment respectively; They represent the allocated production task volume and the maximum production task volume of the v-th production equipment respectively; The remaining production quantity of the v-th production equipment corresponding to the c-th original production task.

[0007] In a possible implementation, the specific calculation process of the equipment load evaluation index of each production equipment is as follows: , Indicates the maximum production task volume of the vth production equipment; Respectively represent the set weight coefficients, They represent the current real-time load and the historical average load of the v-th production equipment respectively. is the cumulative effect of the load on the vth production equipment; is the load fluctuation of the vth production equipment, and its specific calculation formula is: , i is the number of the historical time period, i=1,2,...n, n is the total number of historical time periods; Represents the historical load of the v-th production equipment in the ith historical time period.

[0008] In a possible implementation method, the load accumulation effect of each production equipment is calculated by the following specific formula: Based on the historical load of each production equipment in each historical time period , calculate the cumulative effect of the load on each production equipment , is the preset nonlinear load influence factor, usually , used to indicate the nonlinear effect of high load on production equipment. The greater the load, the more significant the effect on production equipment. is the health status coefficient of the production equipment, and the range is set to [0,1], where 0 means the production equipment is in good health, and 1 means the production equipment is in poor health. is the time decay factor, which indicates the decay value corresponding to the load cumulative effect decaying with time, and is set to ,when , indicating that the cumulative effect of the load does not decay over time and the corresponding attenuation value is generated. , indicating that the influence of the load in the earlier time period on the current cumulative effect is weakened, and d is the differential sign; The load critical value of each production equipment is set, indicating the safe service range of the production equipment. The load exceeding this critical value will significantly increase the failure risk of the production equipment; is the equipment health status of the vth production equipment; It is a time decay function, which means that the closer the load is to the current moment, the greater its influence on the cumulative effect.

[0009] In a possible implementation, the maximum number of commodities that each production device can produce for an emergency order is determined, and the specific determination process includes: Calculate the maximum number of products that each production equipment can produce for emergency orders , are the set adjustment coefficients, which are used to adjust the impact of production complexity, equipment health status and load fluctuation on production capacity. CD is the production complexity of the insertion order. represents the remaining available production time of the vth production equipment, shows the maintenance time required for the vth production equipment during the insertion period; Indicates the floor symbol.

[0010] In a possible implementation, the adjustment logic for dynamically adjusting the production sequence of each production device is as follows: Calculate the production priority adjustment coefficient of each production equipment corresponding to each original production task , is the production time required for the vth production equipment to produce the cth original production task, They are the set adjustment coefficients, which are used to adjust the impact of task complexity and equipment load on priority. is the production complexity of the cth original production task corresponding to the vth production equipment; Calculate the production priority adjustment coefficient for each production equipment corresponding to the production order , The remaining time for the task to be inserted. The time required to produce the task for the insertion order; Filter out the production priority adjustment coefficients of each production equipment corresponding to the production of the first original production task from the production priority adjustment coefficients of each production equipment corresponding to the production of each original production task; Screen out each production equipment whose production priority adjustment coefficient of the first original production task is less than the production priority adjustment coefficient of the corresponding production insertion order, and record it as each insertion order production equipment; Obtain the production priority adjustment coefficient of each insertion production device corresponding to the production of the first original production task, arrange them in ascending order, number each insertion production device according to the arrangement order of the production priority adjustment coefficient of the production of the first original production task, and number each insertion production device as 1, 2, ...g, ...G in sequence; Get the maximum number of goods that each order production device can produce for emergency orders , g is the serial number of each plug-in production equipment, g=1,2,...G, G is the total number of plug-in production equipment; Based on the production demand XQ of the emergency order, the minimum number of production equipment required for the order is calculated. ; According to the arrangement order of the production priority adjustment coefficients of each inserted production equipment corresponding to the production of the first original production task, the first k inserted production equipment are selected as emergency inserted production equipment, and the other production equipment is set to continue to produce the original production tasks.

[0011] Beneficial effects of the present invention: (1) The present invention can effectively reduce interference and delays to the original production tasks. Each production equipment has its own established production schedule when executing tasks. The addition of inserted tasks is likely to affect these plans, thereby causing delays in delivery time and even affecting the efficiency of the entire production chain. By evaluating the delivery impact coefficient of each device executing inserted tasks on the original tasks, the potential impact of inserted tasks on the original tasks can be quantified. If the delivery impact coefficient of a certain device on all original tasks is 0, this means that the device can execute the inserted task without affecting the original tasks. In this case, selecting the device to execute the inserted task can minimize interference with other tasks and ensure that the delivery time of the original task is not affected. This selection method can minimize the negative impact of inserted tasks on the overall production plan and maintain the continuity and stability of production; (2) The present invention can improve the utilization and flexibility of production resources. The utilization rate of production equipment is one of the important indicators for measuring production efficiency. By evaluating the maximum commodity production capacity of each device, the available production capacity of each device under the current load can be understood. For equipment with low load or spare capacity, it can be given priority to execute the insertion task, thereby avoiding idle or wasted resources. This method of dynamically adjusting the production sequence enables production resources to be optimally configured, fully utilizing the production capacity of each device, and improving the overall capacity utilization. At the same time, this also provides a guarantee for enterprises to improve production flexibility, enabling them to better respond to sudden production tasks or changes in market demand; (3) The present invention can also reduce the occurrence of production bottlenecks. In traditional order insertion processing, the addition of order insertion tasks often causes certain devices to be overloaded, thus forming a production bottleneck and affecting the efficiency of the entire production line. By evaluating the maximum production capacity and delivery impact coefficient of each device, the order insertion tasks can be reasonably allocated to prevent certain devices from becoming production bottlenecks due to excessive load. By balancing the equipment load, the overall operating efficiency of the production line can be improved and the production process can be smoother; (4) The present invention includes a production task management module, an emergency order evaluation module, a production delivery judgment module and a production scheduling optimization module. By evaluating the impact coefficient of each production equipment executing the emergency order on the delivery of the original production task, and dynamically adjusting the production sequence according to the maximum commodity production capacity of the equipment, it can not only reduce the interference with the original task and improve the utilization rate of production resources, but also optimize the dynamic adjustment ability of the production plan, reduce the occurrence of production bottlenecks, and provide enterprises with greater flexibility and adaptability. In a modern manufacturing environment, this method can help enterprises respond quickly to emergency order tasks while ensuring the smooth progress of the original production tasks, and ultimately achieve a dual improvement in production efficiency and customer satisfaction. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 It is a schematic diagram of the system module connection structure of the present invention. DETAILED DESCRIPTION

[0013] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are 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.

[0014] See also Figure 1As shown, the data-driven intelligent scheduling system for environmental protection industry production and manufacturing includes a production task management module, an emergency order assessment module, a production delivery judgment module and a production scheduling optimization module. The above modules are connected by wired and / or wireless connections to achieve data transmission between the modules; Production task management module: used to manage the scheduling information of all original production tasks; As a further improvement of the present invention, the production scheduling information of all originally scheduled production tasks includes delivery time, production priority and remaining production quantity corresponding to each production equipment.

[0015] Emergency order evaluation module: used to evaluate the delivery impact coefficient of each production equipment executing the emergency order corresponding to each original production task after receiving the emergency order request; As a further improvement of the present invention, the delivery impact coefficient of each production equipment executing the emergency insertion order corresponding to each original production task is evaluated, and the specific evaluation process is: Obtain the production demand XQ of the emergency order, and evaluate the delivery impact coefficient of each production equipment executing the emergency order corresponding to each original production task ; c is the number of each original production task, v is the number of each production equipment, They respectively represent the weight coefficients of the set calculation factors; is the production priority of the cth original production task, They represent the remaining delivery time and the total given production time of the cth original production task of the vth production equipment respectively; They represent the allocated production task volume and the maximum production task volume of the v-th production equipment respectively; The remaining production quantity of the v-th production equipment corresponding to the c-th original production task.

[0016] As a further improvement of the present invention, the specific calculation process of the equipment load evaluation index of each production equipment is: , Indicates the maximum production task volume of the vth production equipment; Respectively represent the set weight coefficients, They represent the current real-time load and the historical average load of the v-th production equipment respectively. is the cumulative effect of the load on the vth production equipment; β1 and β2 are used to adjust the impact of historical load and plug-in demand on load assessment. If the historical load has a greater impact on device health, β1 can be increased; if the plug-in demand has a greater impact on device load, β2 can be increased; β3: Used to adjust the impact of load fluctuation on load evaluation. If load fluctuation has a greater impact on equipment stability, β3 can be increased; β4: It is used to adjust the impact of the load accumulation effect on the load assessment. If the long-term high load of the equipment has a greater impact on the equipment, β4 can be increased; is the load fluctuation of the vth production equipment, and its specific calculation formula is: , i is the number of the historical time period, i=1,2,...n, n is the total number of historical time periods; Represents the historical load of the v-th production equipment in the ith historical time period.

[0017] As a further improvement of the present invention, the load accumulation effect of each production equipment is specifically calculated by the following formula: Based on the historical load of each production equipment in each historical time period , calculate the cumulative effect of the load on each production equipment , is the preset nonlinear load influence factor, usually , used to indicate the nonlinear effect of high load on production equipment. The greater the load, the more significant the effect on production equipment. is the health status coefficient of the production equipment, and the range is set to [0,1], where 0 means the production equipment is in good health, and 1 means the production equipment is in poor health. is the time decay factor, which indicates the decay value corresponding to the load cumulative effect decaying with time, and is set to ,when , indicating that the cumulative effect of the load does not decay over time and the corresponding attenuation value is generated. , indicating that the influence of the load in the earlier time period on the current cumulative effect is weakened, and d is the differential sign; The load critical value of each production equipment is set, indicating the safe service range of the production equipment. The load exceeding this critical value will significantly increase the failure risk of the production equipment; is the equipment health status of the vth production equipment; It is a time decay function, which means that the closer the load is to the current moment, the greater its influence on the cumulative effect.

[0018] Production delivery judgment module: If there is a production equipment that executes an emergency order and the delivery impact coefficients of all the original production tasks are 0, then the production equipment will be used as the production equipment for executing the emergency order. Otherwise, the production scheduling optimization module will be executed; Production scheduling optimization module: Determine the maximum number of goods that each production equipment can produce for emergency orders, and dynamically adjust the production order of each production equipment.

[0019] As a further improvement of the present invention, the maximum number of commodities that each production device can produce for an emergency order is determined, and the specific determination process includes: Calculate the maximum number of products that each production equipment can produce for emergency orders , are the set adjustment coefficients, which are used to adjust the impact of production complexity, equipment health status and load fluctuation on production capacity. CD is the production complexity of the insertion order. represents the remaining available production time of the vth production equipment, shows the maintenance time required for the vth production equipment during the insertion period; Indicates the floor symbol.

[0020] The maintenance time required for the equipment during the insertion period refers to the time that the equipment must be shut down for maintenance or upkeep during the execution of the insertion task; if the equipment needs to be shut down for maintenance during the insertion period, this time will not be available for production, thereby reducing the time the equipment can use to process the insertion order.

[0021] As a further improvement of the present invention, the adjustment logic of dynamically adjusting the production sequence of each production equipment is as follows: Calculate the production priority adjustment coefficient of each production equipment corresponding to each original production task , is the production time required for the vth production equipment to produce the cth original production task, They are the set adjustment coefficients, which are used to adjust the impact of task complexity and equipment load on priority. is the production complexity of the cth original production task corresponding to the vth production equipment; Calculate the production priority adjustment coefficient for each production equipment corresponding to the production order , The remaining time for the task to be inserted. The time required to produce the task for the insertion order; Filter out the production priority adjustment coefficients of each production equipment corresponding to the production of the first original production task from the production priority adjustment coefficients of each production equipment corresponding to the production of each original production task; Screen out each production equipment whose production priority adjustment coefficient of the first original production task is less than the production priority adjustment coefficient of the corresponding production insertion order, and record it as each insertion order production equipment; Obtain the production priority adjustment coefficient of each insertion production device corresponding to the production of the first original production task, arrange them in ascending order, number each insertion production device according to the arrangement order of the production priority adjustment coefficient of the production of the first original production task, and number each insertion production device as 1, 2, ...g, ...G in sequence; Get the maximum number of goods that each order production device can produce for emergency orders , g is the serial number of each plug-in production equipment, g=1,2,...G, G is the total number of plug-in production equipment; Based on the production demand XQ of the emergency order, the minimum number of production equipment required for the order is calculated. ; According to the arrangement order of the production priority adjustment coefficients of each inserted production equipment corresponding to the production of the first original production task, the first k inserted production equipment are selected as emergency inserted production equipment, and the other production equipment is set to continue to produce the original production tasks.

[0022] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

[0023] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0024] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A data-driven intelligent scheduling system for environmental protection industry production and manufacturing, characterized by: The system includes: Production task management module: used to manage the scheduling information of all original production tasks; Emergency order evaluation module: used to evaluate the delivery impact coefficient of each production equipment executing the emergency order corresponding to each original production task after receiving the emergency order request; Production delivery judgment module: If there is a production equipment that executes an emergency order and the delivery impact coefficients of all the original production tasks are 0, then the production equipment will be used as the production equipment for executing the emergency order. Otherwise, the production scheduling optimization module will be executed; Production scheduling optimization module: Determine the maximum number of goods that each production equipment can produce for emergency orders, and dynamically adjust the production order of each production equipment.

2. The data-driven intelligent scheduling system for environmental protection industry production and manufacturing according to claim 1 is characterized in that: The production scheduling information of all originally scheduled production tasks includes delivery time, production priority and the remaining production quantity of each corresponding production equipment.

3. The data-driven intelligent scheduling system for environmental protection industry production and manufacturing according to claim 1 is characterized in that: The specific evaluation process of evaluating the delivery impact coefficient of each production equipment executing the emergency insertion order corresponding to each original production task is as follows: Obtain the production demand XQ of the emergency order, and evaluate the delivery impact coefficient of each production equipment executing the emergency order corresponding to each original production task ; c is the number of each original production task, v is the number of each production equipment, Respectively represent the weight coefficients of the set calculation factors; is the production priority of the cth original production task, They represent the remaining delivery time and the total given production time of the cth original production task of the vth production equipment respectively; represents the equipment load evaluation index of the vth production equipment; The remaining production quantity of the v-th production equipment corresponding to the c-th original production task.

4. The data-driven intelligent scheduling system for environmental protection industry production and manufacturing according to claim 3 is characterized in that: The specific calculation process of the equipment load evaluation index of each production equipment is as follows: , Indicates the maximum production task volume of the vth production equipment; Respectively represent the set weight coefficients, They represent the current real-time load and the historical average load of the v-th production equipment respectively. is the cumulative effect of the load on the vth production equipment; is the load fluctuation of the vth production equipment, and its specific calculation formula is: , i is the number of the historical time period, i=1,2,...n, n is the total number of historical time periods; Represents the historical load of the v-th production equipment in the ith historical time period.

5. The data-driven intelligent scheduling system for environmental protection industry production and manufacturing according to claim 4 is characterized in that: The load accumulation effect of each production equipment is calculated as follows: Based on the historical load of each production equipment in each historical time period , calculate the cumulative effect of the load on each production equipment , is the preset nonlinear load influence factor, set to , used to indicate the nonlinear effect of high load on production equipment. The greater the load, the more significant the effect on production equipment. is the health status coefficient of the production equipment, and the range is set to [0,1], where 0 means the production equipment is in good health, and 1 means the production equipment is in poor health. is the time decay factor, which indicates the decay value corresponding to the load cumulative effect decaying with time, and is set to ,when , indicating that the cumulative effect of the load does not decay over time and the corresponding attenuation value is generated. , indicating that the influence of the load in the earlier time period on the current cumulative effect is weakened, and d is the differential sign; The load critical value of each production equipment is set, indicating the safe service range of the production equipment. The load exceeding this critical value will significantly increase the failure risk of the production equipment; is the equipment health status of the vth production equipment; It is a time decay function, which means that the closer the load is to the current moment, the greater its influence on the cumulative effect.

6. The data-driven intelligent scheduling system for environmental protection industry production and manufacturing according to claim 1 is characterized in that: The specific process of determining the maximum number of commodities that each production device can produce for an emergency order includes: Calculate the maximum number of products that each production equipment can produce for emergency orders , are the set adjustment coefficients, which are used to adjust the impact of production complexity, equipment health status and load fluctuation on production capacity. CD is the production complexity of the insertion order. represents the remaining available production time of the vth production equipment, shows the maintenance time required for the vth production equipment during the insertion period; Indicates the floor symbol.

7. The data-driven intelligent scheduling system for environmental protection industry production and manufacturing according to claim 1 is characterized in that: The adjustment logic of dynamically adjusting the production sequence of each production equipment is as follows: Calculate the production priority adjustment coefficient of each production equipment corresponding to each original production task , is the production time required for the vth production equipment to produce the cth original production task, They are the set adjustment coefficients, which are used to adjust the impact of task complexity and equipment load on priority. is the production complexity of the cth original production task corresponding to the vth production equipment; Calculate the production priority adjustment coefficient for each production equipment corresponding to the production order , The remaining time for the task to be inserted. The time required to produce the task for the insertion order; Filter out the production priority adjustment coefficients of each production equipment corresponding to the production of the first original production task from the production priority adjustment coefficients of each production equipment corresponding to the production of each original production task; Screen out each production equipment whose production priority adjustment coefficient of the first original production task is less than the production priority adjustment coefficient of the corresponding production insertion order, and record it as each insertion order production equipment; Obtain the production priority adjustment coefficient of each insertion production device corresponding to the production of the first original production task, arrange them in ascending order, number each insertion production device according to the arrangement order of the production priority adjustment coefficient of the production of the first original production task, and number each insertion production device as 1, 2, ...g, ...G in sequence; Get the maximum number of goods that each order production device can produce for emergency orders , g is the serial number of each plug-in production equipment, g=1,2,...G, G is the total number of plug-in production equipment; Based on the production demand XQ of the emergency order, the minimum number of production equipment required for the order is calculated. ; According to the arrangement order of the production priority adjustment coefficients of each inserted production equipment corresponding to the production of the first original production task, the first k inserted production equipment are selected as emergency inserted production equipment, and the other production equipment is set to continue to produce the original production tasks.

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