A method for quality loss assessment and early warning of key assembly process in complex precision equipment assembly workshop

Abstract

The invention discloses a quality loss assessment and early warning method for key assembly process of a complex precision equipment assembly workshop, belonging to the field of intelligent manufacturing technology. This method establishes a set of key assembly process quality loss evaluation index system, which includes five dimensions: abnormal material loss M, equipment failure loss E, abnormalproduct quality detection P, abnormal personnel loss S, quality problem handling cost C, etc. On this basis, a fuzzy comprehensive evaluation method based on variable weights is adopted to evaluate the quality loss of key assembly processes in complex precision equipment assembly workshop, and a BP neural network quality loss early warning model is established, which provides support for the effective control of quality loss of key assembly processes. The invention aims at effectively evaluating and early warning the quality loss of the key assembly process in the complex precision equipmentgeneral assembly workshop, and providing decision support for preventing and controlling the quality abnormal problems of the key assembly process in advance.

Description

technical field [0001] The invention relates to a quality loss assessment and early warning method of a key assembly process in a complex precision equipment assembly workshop, and belongs to the technical field of intelligent manufacturing. Background technique [0002] Complex precision equipment manufacturing enterprises are typical discrete manufacturing enterprises, and the assembly shop, as the gathering center of resource flow, planning flow, logistics, quality flow and information flow in the manufacturing process, is one of the main parts of the manufacturing process of the enterprise. In the actual assembly production process, the assembly workshop involves a large number of equipment, materials and personnel, and requires a high degree of network integration. At the same time, due to the different order specifications, the assembly process of different products is different from each other, the assembly process is changeable, the task is heavy, and the logistics i...

AI Technical Summary

Problems solved by technology

[0005] Aiming at the problems in the background technology, the present invention provides a quality loss assessment and early warning method for key assembly processes in complex precision equipment assembly workshops, and establishes a set of methods including abnormal material loss M, equipment failure loss E, product quality detection abnormality P, Five-dimensional key assembly process quality loss evaluation index system such as abnormal loss S and quality problem processing cost C; on this basis, a fuzzy comprehensive evaluation method based on variable weights is used to evaluate the quality loss of key assembly processes in complex precision equipment assembly workshops. Evaluated and studied a BP neural network-based early warning method for quality loss in key assembly processes, established a BP neural network early warning structure model, and provided decision support for effective control of quality loss in key assembly processes

Images