A Simplified Method for Optimal Sensor Distribution for Process Fault Diagnosis in Multistation Assembly Processes

Abstract

The fault diagnosis plays an important role for product quality improvement in the multistation assembly processes (MAPs) and the efficiency of diagnosis significantly depends on the sensor distribution strategy, such as the number and location of the sensor. The diagnosis-oriented sensor distribution optimization in MAP has been studied for the purpose of a full diagnosis of the process faults with the minimum sensing stations number as well as the minimum sensor number. However, the existing studies are time consuming with the complex analysis and calculation processes, and no intuitive principles are given directly according to the process configuration. In this paper, a simplified method for the optimal sensor distribution is presented for a fully diagnosis of the process faults. First, two different types of assembly modes are defined and the variation transmissibility ratios for these two assembly modes are discussed based on the process configuration. Then, the conditions for between-station diagnosability and within-station diagnosability are analyzed, respectively. Based on the results, the optimal sensor distribution method is derived finally. After comparing with the former methods, the optimal sensor distribution in this paper is based only on the process configuration without using for model-based matrix computation. Therefore, the proposed method greatly simplified the process.