Nation’s First “Standard” for General Management of Product Quality Reliability Released, Already Used to Guide Enterprises
On November 26, led by the Shanghai Market Supervision and Regulation Bureau, the market supervision and regulation departments of Beijing, Tianjin, Shanghai, and Chongqing jointly held the Product Quality Reliability Innovation Conference, where they collectively released the “General Management Guide for Product Quality Reliability,” marking the nation’s first “standard” for general management of product quality reliability. Additionally, 31 enterprises were awarded for the “Best Practices” in product quality reliability innovation for the year 2024, and six enterprises received awards for typical cases of FMEA (Failure Mode and Effects Analysis) application innovation practices for the same year.
(Image provided by the Shanghai Market Supervision and Regulation Bureau showing the conference scene)
Product quality reliability refers to the ability of a product to fulfill its intended functions under specified conditions and within a specified time frame. It is a core indicator reflecting the level of product quality and a production factor driving industrial innovation and the development of new industrialization.
In 2023, Shanghai took the lead in launching pilot projects for product quality reliability innovation. In 2024, the four municipalities of Beijing, Tianjin, Shanghai, and Chongqing jointly issued the “Opinions on Jointly Carrying Out Innovative Practices in Product Quality Reliability to Empower High-Quality Development in Manufacturing” through policy synchronization, resource sharing, and complementary advantages.
The “General Management Guide for Product Quality Reliability” released at the conference systematically established a comprehensive quality management framework addressing issues commonly faced by Chinese enterprises in product quality reliability management, such as outdated management concepts, inconsistent technical standards, and inadequate management systems.
This technical guide has been used to provide “one-enterprise, one-policy” guidance to enterprises. During the development of the TeSys Giga contactor product at Schneider Electric Industrial Control Co., Ltd. in Shanghai, advanced technologies such as machine learning were deployed to empower new product development, intelligent supply chain decision-making, end-to-end data platforms, and flexible production line maintenance, integrating a reliability design framework throughout the product’s entire lifecycle. Facing the issue of inconsistent stability in the traditional mechanical coil contactor industry, the technical team introduced a self-developed algorithm based on big data analysis to optimize the chip program, reducing the product’s pickup time degradation rate to less than 5%. In terms of key performance consistency, improvements in new product prototype development empowered by machine learning technology increased the product’s life test efficiency by 50%, shortened the test cycle by 2-3 months, and reduced the development cycle by 63%. Furthermore, through the implementation of reliability innovation, the enterprise achieved significant economic benefits, with 98% of customer orders delivered on time, increasing sales by over 70 million yuan for the company.
