Improve quality, learn English - TS16949 (IV)
3.1 Definition and terms in the automotive industry
In the construction of the quality system in the automotive industry, precise definitions and terms are crucial. They are the cornerstone of the operation of the entire system, providing unified standards and clear guidance for communication and operations among all parties.
3.1.1 Control Plan
The control plan can be regarded as a key tool for controlling product quality. It is a documented description that covers the systems and processes required to control products. Simply put, it is like a "battle map" for product quality control. This document details every link from raw material procurement, production and processing to the final product delivery, and clarifies the standards and requirements to be followed in each step. Through the control plan, enterprises can systematically monitor and manage product quality to ensure that each product meets the specified quality standards. For example, in the production process of automobile parts, the control plan will specify the inspection standards for raw materials, the parameter ranges of processing technology, the detection methods for finished products, etc. In this way, product quality can be controlled at each key node, and potential quality problems can be discovered and solved in a timely manner.
3.1.2 Organizations with design responsibility
Organizations with design responsibility play a core role in the research, development, and production of automotive products. Such organizations have the authority to formulate new product specifications or modify existing ones. This means they have a high degree of autonomy and decision - making power during the product design stage. However, this power is not unlimited and needs to be exercised within the scope defined by the customer. The organization's responsibilities include not only designing new products but also testing and verifying the design performance. Within the application scenarios specified by the customer, the organization must conduct strict tests on various performances of the product to ensure that the designed product can meet the actual usage requirements. For example, if an automobile manufacturer commissions a component supplier with design responsibility to design a new - type engine, the supplier needs to carry out a large amount of testing and verification work according to the performance requirements and application scenarios put forward by the automobile manufacturer during the design process. Only when the design performance passes a series of strict tests can it enter the next production stage.
3.1.3 Error prevention
Error proofing is an important quality control concept and method in the automotive manufacturing process. It focuses on taking measures to prevent the production of non - conforming products during the design and development stages of products and manufacturing processes. Traditional quality control methods often emphasize post - production inspection, that is, products are tested after they are manufactured, and non - conforming products are reworked or scrapped after being detected. In contrast, error proofing focuses on prevention at the source. By optimizing the design of products and manufacturing processes, it eliminates the factors that may lead to the production of non - conforming products. For example, on the automotive assembly line, special tooling fixtures are designed to ensure that parts can only be installed in the correct way, avoiding the production of non - conforming products due to human operation errors. Or sensors and control systems are installed on production equipment. When an abnormality occurs in the production process, the equipment can automatically stop running to prevent the continued production of defective products. This method can greatly improve production efficiency, reduce production costs, and also enhance the overall quality of products.
3.1.6 Manufacturing
Automobile manufacturing is a complex and large - scale process that encompasses multiple different manufacturing or assembly stages. Starting from the production of raw materials, progressing to the manufacturing of production parts or service parts, and then through various assembly and surface treatment processes, each stage has a significant impact on the quality of the final product. The quality of the raw materials directly determines the basic quality of the subsequent products, so the selection and inspection of raw materials are of crucial importance. The manufacturing of production parts or service parts requires strict adherence to process requirements to ensure the precision and performance of each component. The assembly stage is like putting together a "jigsaw puzzle" of various components, and it is necessary to ensure that the installation positions and connection methods of each part are correct. In addition, welding, heat treatment, painting, electroplating or other surface treatment processes can not only improve the strength, corrosion resistance and aesthetics of the product, but also enhance the overall performance of the product. For example, the welding quality of the automobile body directly affects the strength and safety of the body, and the painting process can protect the body from the external environment while enhancing the appearance quality of the automobile.
3.1.7 Predictive maintenance
Predictive maintenance is a data-driven maintenance method that uses process data to predict possible failure modes and thus take measures in advance to avoid maintenance problems. In the traditional maintenance model, enterprises usually adopt the methods of regular maintenance or post-fault maintenance. Regular maintenance often involves equipment maintenance and inspection at fixed time intervals, which may lead to problems of over-maintenance or under-maintenance. Post-fault maintenance, on the other hand, only conducts repairs after the equipment breaks down, which will result in production interruption and increased maintenance costs. Predictive maintenance is different. It establishes a health model of the equipment by performing real-time monitoring and analysis on various data during the equipment operation, such as parameters like temperature, pressure, and vibration. Once abnormal data is detected, it can predict possible failure modes and arrange maintenance plans in advance. For example, for large mechanical equipment on an automobile production line, if data analysis predicts that a certain key component may fail in the near future, the enterprise can prepare maintenance personnel and spare parts in advance and conduct preventive maintenance during the normal operation intervals of the equipment to avoid production stagnation caused by sudden equipment failure. This maintenance method can improve the reliability and availability of equipment, reduce maintenance costs, and enhance the production efficiency of enterprises.