Identification of to-be-improved components for redesign of complex products and systems based on fuzzy QFD and FMEA
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Since the activities to design complex products and systems (CoPSs) mainly focus on redesign of the existing CoPSs to satisfy customer requirements and improve product reliability, identification of the to-be-improved components plays a key role in the redesign process. In the existing methods to identify the to-be-improved components, customer requirements are primarily considered while the failure knowledge, a critical information to improve product reliability, is often ignored. The objective of this research is to identify the to-be-improved components considering both customer requirements and product reliability. The customer requirements are used in redesign through quality function deployment, while the reliability is used in redesign through failure mode and effects analysis (FMEA). Different from the traditional FMEA, the failure causality relationships between and within components are analyzed in this work to provide a means of making use of failure information more effectively for constructing a directed failure causality relationship network. In this network, the failure modes of all components are modeled as vertices, and the causality relationships between failure modes are modeled as directed edges. A new index is introduced to calculate the importance of component from the viewpoint of reliability through integrating the internal and external failure effects. Fuzzy permanent function is developed to measure the internal failure effects, while the external failure effect index is developed to measure the external failure effects. A case study for identification of the to-be-improved components for the operation device of a crawler crane is implemented to demonstrate the effectiveness of the developed approach.
KeywordsIdentification of to-be-improved components QFD Fuzzy FMEA Directed failure causality relationship network Fuzzy permanent function
This project is supported by National Natural Science Foundation of China (Grant Nos. 51475290, 51075261), Research Fund for the Doctoral Program of Higher Education of China (No. 20120073110096), and Natural Sciences and Engineering Research Council (NSERC) of Canada (Grant No. 185788).
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