Smart Die Casting Solutions: Towards Future Innovations

With the continuous promotion of Industry 4.0, intelligent manufacturing has become an important trend in the development of the manufacturing industry. As a metal forming process, die casting is widely applied in various fields such as automotive, 3C, and electronics. However, traditional die casting production processes face problems such as information silos, low production efficiency, and unstable quality control.

The smart die casting solution has emerged to bring revolutionary changes to the foundry industry by integrating advanced technologies such as the Internet of Things (IoT), cloud computing, big data analytics, and artificial intelligence (AI). This innovative solution enables intelligent management of foundries, significantly enhancing production efficiency and product quality while effectively reducing production costs.

1.Equipment Networking and Information-based

Production:Building the Cornerstone for Digital Factories

The primary step of the smart die casting solution is to achieve equipment networking and comprehensive informatization of production processes. To this end, we have introduced Yi CMS (Equipment Networking and Condition Monitoring System) and Yi MES (Manufacturing Execution System). These two systems enable enterprises to digitize production scheduling, management oversight, quality assurance protocols, warehousing and logistics, personnel management, and equipment data collection and maintenance management. The core value of this module lies in making the production process transparent and enabling real-time monitoring, which lays essential foundation for subsequent data analysis and intelligent optimization.

1.1 YIZUMI Condition Monitoring System (Yi CMS)

Yi CMS is a key bridge connecting the production lines with automated equipment alongside other physical entities to MES system. It undertakes the collection of vital production data, comprehensive monitoring of operational workflows, and strict control over production quality.

1.2 YIZUMI Manufacturing Execution System (Yi MES)

Yi MES is an integral framework governing both control and management of the entire production workflow by meticulously monitoring output generation, task allocation, and progress tracking at each stage of manufacturing. By leveraging MES system, enterprises can achieve refined management of the production process, enhancing production efficiency and response speed. The MES system enables real-time collection of diverse datasets from on-site operations, providing strong, accurate information support for production decision-making.

2. Die Casting Data Analysis Platform:

UncoveringData Value

Building upon equipment networking and information-based production, the smart die casting solution further establishes a closed-loop data analysis platform for die casting quality. With big data technology at its core, this platform efficiently completes the cleaning, processing, and feature extraction of process big data by integrating data resources from the Yi CMS and Yi MES systems. On this basis, we have developed digital models and data analysis tools for the processes, providing robust data support for process optimization and quality control.

2.1 Process Data Cleansing and Processing

Big data is the cornerstone of intelligent manufacturing. A vast amount of data is generated in the die casting production process, including equipment operating data, production process data, and quality inspection data. However, these data often contain a large amount of noise and outliers, necessitating advanced data cleaning and processing technologies to extract valuable information.

2.2 Digital Model of Process

The process digital model is fundamental for achieving process optimization and quality control. By analyzing the characteristics and patternsof the die casting processes, we have constructed a precise mathematical model for the process. This model can simulate and predict various complex situations in the production process, providing a solid theoretical basis for optimizing process parameters, and helping enterprises achieve more efficient production and stricter quality control.

2.3 Data Analysis Tools

Digital analysis tools are key to achieving process optimization and quality control. By developing and applying various data analysis algorithms and tools, we can delve into production data and uncover potential patterns and problems in the production process, thus providing scientific evidence for production decision-making.

3. Intelligent Process-aided Commissioning:

Innovation of Process Management

Intelligent process-aided commissioning is an integral part of the smart die casting solution. Leveraging a big data platform, it utilizes process knowledge mining technology and an intelligent process optimization assistant to provide comprehensive digital and intelligent commissioning services for remote process distribution and diagnosis. Implementing this module enhances the accuracy and efficiency of process adjustments, significantly minimizing the impact of human factors on production.

3.1 Process Knowledge Mining Technology

Process knowledge plays a key role in the die casting production. With the assistance of process knowledge mining technology, we extract process patterns and practical experience from massive production data and establish a process knowledge base. The knowledge helps guide the setting and adjustment of process parameters and improve process stability and product qualification rate.

3.2 Intelligent Process Optimization Assistant

The intelligent process optimization assistant is essential for achieving process intelligence. It automatically adjusts process parameters and optimizes processes based on the established rules and models within the process knowledge base. Additionally, it can dynamically modify these parameters in response to real-time data feedback during production, ensuring the stability of the entire production.

3.3 Remote Process Distribution and Diagnosis

Remote process distribution and diagnosis are vital components for realizing process intelligence. The remote process distribution system enables the transmission of optimized process parameters directly to the production site, enhancing the efficiency of process adjustments. The remote diagnosis system allows for real-time monitoring of the production process and timely detection and resolution of any issues that may arise.

4. Model-based Quality Sorting:

Improving Process Management Efficiency

Quality is the backbone of the manufacturing industry. The smart die casting solution implements a model-based quality sorting mechanism by integrating machine learning to provide abnormal quality alerts, intelligent sorting of defective products, and root cause analysis. The module leverages big data analyses and machine learning algorithms to monitor and analyze quality data in real time during the production process. It enables therapid detection and effective resolution of quality issues,and enhances the efficiency of product quality inspections while reducing inspection costs.

4.1 Abnormal Quality Alerts

Abnormal quality alerts serve as the first step in the quality sorting process. The system can predict and identify potential quality defects through real-time monitoring of quality data during the production process and in-depth analysis of quality data using machine learning algorithms. Upon finding a defect, the system promptly issues an alert, allowing enterprises to implement measures and avoid the production of batches of defective products.

4.2 Sorting of Defective Products

The sorting of defective products is a critical step of quality control. Utilizing advanced technologies like image recognition and machine vision, the system can automatically and accurately identify and sort outdefective products, significantly enhancing the efficiency and precision of quality control.

4.3 Quality Root Cause Analysis

Quality root cause analysis plays a vital role in improving product quality. By thoroughly analyzing the underlying causes of quality issues, we can address them at their source, thereby enhancing product reliability and stability and ensuring continuous product quality optimization.

5. Dynamic Optimization of Control

Parameters:Pursuing Extreme Accuracy

Optimizing control parameters is vital in the die casting production process. The smart die casting solution offers dynamic optimization of these parameters through technologies such as intelligent locking force and intelligent mold opening and closing. This module can automatically and accurately adjust various die casting machine control parameters based on real-time production data and comprehensive historical data analysis, ensuring production process stability and high-accuracy product output.

Conclusion

The smart die casting solution integrates five core modules to realize digital, intelligent, and automated die casting production. The solution not only enhances production efficiency and product quality, but also effectively reduces production costs and energy consumption, providing essential technical support for the sustainable development of enterprises. As technology continues to advance and be used in practical sectors, smart die casting solutions are poised to play an increasingly vital role in the future of the manufacturing industry.