Quality prediction in manufacturing system design

Expected product quality is affected by manufacturing system design decisions. Product quality prediction would allow a manufacturer to make better choices of system parameters at the early design stage and, hence, enhance competitiveness through achieving higher quality levels. A Configuration Capability Indicator (CCI) that maps the manufacturing system configuration parameters into an expected product quality level has been developed. A hierarchical fuzzy inference system was developed for modeling the relationship between manufacturing system design parameters and the resulting product quality level. A configuration capability zone is proposed to graphically represent the configuration capability, for a system configuration that produces more than one product, and compare it to the benchmark six-sigma capability. The developed model has been applied to two case studies (Test Parts ANC-90 and ANC-101, and Rack Bar Machining) with different system configurations for illustration and verification. The results demonstrate the ability of the CCI to compare different system configurations from a quality point of view and to support the decision-making during the early stages of manufacturing system planning and design.