Parts processing is a key link in mold manufacturing, and processing process design is an important and indispensable part of mold processing.
The process design usually includes a pre-structural manufacturability review and process program planning. It also involves preparing the process route, estimating process hours and costs, and managing both cost and schedule.
These processes are usually managed during the process design phase in order to guide production in a more scientific manner.
This work relies heavily on the technical skills of process engineers. They must have strong theoretical knowledge and practical production experience to support process design.
For example, process engineers must be more familiar with the processing principles of industrial equipment, working hours and costing principles, scheduling basis, etc., the design of the process program can be more adapted to production.
In addition, the quality of the processing process also needs to be familiar with the process plan of process engineers to organize and coordinate, to avoid equipment downtime or process lag.
The current process design relies heavily on manual input, resulting in low management efficiency and unstable quality. Therefore, it is urgent to optimize and improve the AI-based computer-aided process design system.
Overview of artificial intelligence-based computer-aided process design system
Computer-aided process design system (CAPP) usually refers to the machining process of computer-aided process design and process documentation.
The main task of the CAPP system in mold manufacturing is to convert mold design information into manufacturing data through computer-aided process design. It acts as a bridge between CAD and CAM and serves as a key component of the IMS system. This represents the traditional CAPP system.
The AICAPP system, based on artificial intelligence, is an advanced manufacturing platform. It integrates modern information technology, big data, artificial intelligence, and other emerging technologies. The system aims to achieve highly automated and intel
Automation design practice of mold processing process based on intelligent manufacturing system
1. Case Introduction
A home appliance enterprise produces a wave washing machine barrel shell injection mold, which has a complex structure, involves many processing procedures, and is difficult to account for working hours.
The traditional process design method relies on manual calculation and experience, resulting in a long manufacturing cycle, difficult cost assessment and control, and the process is prone to processing quality risks.
In order to improve manufacturing efficiency, the enterprise introduced the artificial intelligence-based computer-aided process design system (AICAPP).
Through the AICAPP system, the preliminary mold design file information is automatically imported into the system. The system then analyzes the part’s material, hardness, size, structure type, and polishing level. Based on these attributes, it intelligently selects the optimal process plan from the standard process database. It also automatically references the current parts. Process engineers only need to review and finalize the process design.
The system also provides standard working hours and cost references through the historical data in the process library to help engineers accurately control production costs.
At the same time, the AICAPP system interfaces with ERP and MES systems to achieve pre-scheduling and schedule management. It identifies possible schedule delays or resource bottlenecks during production. The system then outputs risk warnings to alert managers.
2. Optimization of mold machining process design
Process design is the key link to improve mold processing efficiency and reduce costs.
Traditional mold process design usually relies on experience and manual intervention, which is difficult to ensure the feasibility and economy of the process plan.
The AICAPP system uses artificial intelligence. It integrates big data, machine learning, and smart algorithms. This system supports mold processing. It offers accurate and efficient process solutions. It also helps reduce costs. (See Figure 1.) The system builds a process library. It pushes the best process plan. It matches man-hours with costs. It also handles pre-scheduling and manages schedules.
Figure 1 AICAPP-based mold processing process package
(1) Process library construction
Process library is the core component of AICAPP system, which contains information on process routes, working hours, costs, equipment and tooling selection of different parts.
The construction of process library needs to collect historical data, categorize, archive and continuously update. The key steps are as follows.
① Data collection and organization.
Collect historical work order data by interfacing with MES system, ERP enterprise management system and other systems, and establish standardized and modularized process templates through AICAPP system;
Process data classification.
After standardized processing, the process data is classified according to the set conditions to provide reliable basic data for the intelligent push system;
③ Dynamic update of process library.
After the production order is completed, through the intelligent learning function of AICAPP system, the standard process is automatically generated and managed in the library.
For example, in the process design, the process library will automatically generate different types of process libraries according to the product’s host category, structure type, part material, and so on.
(2) Intelligent delivery of optimal process solutions
Intelligent delivery function is one of the core advantages of AICAPP system.
Using intelligent algorithms, according to the attribute characteristics of the current part conditions, from the process library to automatically screen and compare, push out the optimal process plan, and refer to the following methods.
① Part characterization.
Import the part drawing file information, AICAPP system will automatically identify and analyze.
Including the size of the part, shape, material, hardness, polishing grade requirements and other information;
② Optimal process route matching.
The system combines the standard process data in the process library to analyze the attribute characteristics of the part and automatically match the optimal process route.
For example, the complex structure of the washing machine barrel shell mold parts, the system may recommend five-axis CNC machine tool process route, while the simple structure of the parts is recommended for ordinary three-axis CNC machine tool process route;
③ automatic reference and review.
The system pushes the optimal process program through the push and reference, the engineer can complete the process design work according to the actual situation after the audit.
(3) Man-hour and cost management
Man-hours and costs are key control elements in mold manufacturing. The AICAPP system intelligently matches the most compatible man-hours from the man-hours library. It automatically calculates costs, evaluates costs and durations during the process design stage, and outputs risk warning reports.
① Construction and maintenance of labor hour library.
Similar to process library, labor hour library is an important part of AICAPP system. The system will intelligently match the corresponding labor hour data.
For example, for complex parts, the calculation of working hours will be different from that of simple parts;
② Cost risk early warning management.
Based on the current accounting results, the AICAPP system will be compared with the set cost value to produce early warning reports and recommendations.
For example, the washing machine drum shell mold A plate processing time is long, high cost, the system will recommend adjusting the process route to reduce man-hours, reduce costs.
(4) Pre-scheduling and schedule management
During mold processing, the AICAPP system optimizes process design. It combines production plans and man-hour data for real-time pre-scheduling, ensuring the process design meets production needs.
①Based on matching the process and working hour libraries, the system generates real-time pre-scheduling orders. It uses the working hours from the current process design. The system also intelligently predicts the total working period for the entire mold processing.
② According to the current pre-scheduled production orders, real-time monitoring of the planned duration.
For example, if the working time of EDM process exceeds 4 days, it will be automatically warned.
3. Evaluation of the effect of program implementation
With the introduction of the AICAPP system, the process design flow of the washing machine drum shell mold has been significantly optimized.
To further evaluate the effect of system implementation, we compared key indicators before and after implementation (see Table 1). We specifically analyzed the impact of the AICAPP system on process design. We focused on dependence on engineers, labor intensity, design speed, and accuracy of hours and deadlines. The results show that compared to traditional design methods, intelligent design reduces manual work. It also greatly improves design efficiency. It also reduces the workload of process engineers and improves accuracy in working hours and deadlines.
Compared with the traditional process design mode, it can be seen that intelligent process design can reduce manual intervention, greatly improve the design efficiency and reduce the workload of process engineers.
Table 1 Processing efficiency indexes of washing machine drum shell mold before and after implementation
(1) Reduced dependence on process engineers
In the traditional process design process, process engineers need to participate in every decision-making process, including the selection of suitable process routes, labor hour accounting, cost evaluation, etc. With the introduction of AICAPP system, the system is able to reduce the workload of process engineers.
With the introduction of AICAPP system, the system can automatically match the optimal process program, intelligently push the optimal process design, and provide decision-making support for process engineers.
Reduce the dependence on manual operation.
(2) Reduce the labor intensity of process engineers
Process design requires high labor intensity, especially for process solutions, man-hours, and cost estimation. Engineers perform many manual calculations, which are time-consuming and prone to errors.
AICAPP system can automatically calculate the working hours and costs, which greatly reduces the repeated labor of process engineers.
(3) Process design efficiency
It usually takes 3~4 days to manually design a traditional process plan, and process engineers need to analyze and calculate each process in detail, and there are more manual adjustments.
The AICAPP system significantly shortens the process design time. It automatically generates the process plan and calculates working hours and costs. It also automatically matches process parameters and performs other related functions.
The efficiency of process design can be improved by about 50%, and the process design of a set of molds can usually be completed within 1~2 days.
(4) Improvement of the accuracy of working hours and duration
Man-hour accounting in process design relies heavily on engineers’ experience, leading to large errors. External factors also influence results. Manual scheduling makes it hard to ensure predictable timelines.
Intelligent CAPP system automatically matches the working hours and makes the accounting of working hours more accurate;
The system can pre-schedule the production in real time, monitor the changes of the working period in real time, and output early warning, thus improving the accuracy of working hours and working period.
It can be seen that the introduction of AICAPP system can improve the mold processing production efficiency, optimize the processing process, and improve the economic benefits of enterprises.
Conclusion
The automated design of mold processing process based on intelligent manufacturing system can effectively improve the efficiency and quality of mold processing.
Through the introduction of artificial intelligence-based computer-aided process design system AICAPP, can significantly shorten the production cycle and effectively reduce production costs.
The application of intelligent manufacturing system makes the mold processing process more flexible and efficient, with better production stability and maintainability.
Through the optimization of system integration and intelligent scheduling, the various links in the production process are efficiently coordinated to avoid the problems existing in the traditional production methods.
With the continuous development of intelligent manufacturing, the intelligent manufacturing system will continue to promote the manufacturing industry to a higher level of development, help enterprises to enhance competitiveness.