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Scenario Description

The picture is generated by AI

In the context of intelligent manufacturing, the quality management of customers, products, and supply chains faces multiple challenges. In terms of customer quality, there are challenges of diversity, personalization, and high expectations; in terms of product quality, there are challenges of complexity, multi-mode, and new technologies; in terms of supply chain quality, there are challenges of cross-regional, long chains, and difficult management; in terms of process quality, there are challenges of complex product processes, high employee turnover, and high quality loss costs.

solution

Lianbao Technology's Quality Cloud brings together product quality management digital systems, supplier quality management systems, process quality digital systems, and customer quality management digital systems.

The project adopts BS and CS architecture. Users use WEB API to interact with the server through computers and mobile applets. The test software and packaged standard modules are stored through OSS services to ensure consistency through blockchain technology. The project is independently developed by the enterprise team and fully imports the devops process. It adopts a virtualized private cloud deployment method and performs big data analysis on the generated data to provide data support for new product development.

At the same time, it adopts edge hardware and IoT data collection technology, deploys 83 sets of self-developed data collection edge boxes, and 46 microservice functions cover the entire business process. The data lake has a cumulative data volume of 100+TB, and the accuracy rate of natural language supervised deep learning technology reaches 85%.

Results

Quality Cloud solves the problems of systematic verification and refined execution of supplier quality management standards, end-to-end quality information lag of materials, extensive management and execution differentiation of suppliers and personnel with different attributes, inability to trace horizontally, and low timeliness of manual management. It also promotes closed-loop management of execution information consistency, greatly improves collaborative efficiency, and realizes pre-emptive closed-loop management of real-time quality control and prevention.

According to calculations, the quality digitalization system has introduced 800+ projects, executed 3.82 million times in total, and can support 5,000+ test machines for online testing at the same time, increasing equipment utilization by 10% and test efficiency by 15%. Lianbao's key quality indicators have increased year by year in the past three years. Among them, the first failure rate (IFIR) in 2021 decreased by 10%, the cumulative failure rate (RA) within the warranty period decreased by 11%, and the product first pass rate (FPY) increased by 0.3%.

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