Title :
Propagation and control of quality in the extended manufacturing supply chain: Theoretical models, methodologies and implementation perspectives
Author :
Wibbelmann, M.H. ; Cheng, K. ; Forbes, A.
Author_Institution :
Sch. of Eng. & Design, Brunel Univ., Uxbridge, UK
Abstract :
Statistical quality and process control are integral to the production process, ensuring continuous, in-control operations and enquiring into the micro processes, structures and dimensions that determine conformance. Quality management systems (QMS) and inspection plans tend to be confined to the firm and do not account for external processes. In recent years a shift toward supply chain (SC) dominated thought has pervaded many areas of manufacturing well beyond the traditional purchasing and logistics functions. This shift in focus opens interesting avenues for investigation in the domain of quality control, particularly with regard to design of quality measurement systems that integrate across the distributed production network. The present paper asks how quality propagates through the SC and proposes a model for the design of a distributed QMS that facilitates traceability, optimisation and quality assurance. We discuss how design parameters and cross boundary integration affect process output and other performance measures, and the use of uncertainty in strategy building.
Keywords :
inspection; manufacturing systems; quality assurance; quality control; statistical process control; supply chain management; cross boundary integration; distributed production network; inspection plan; logistics function; manufacturing supply chain management; optimisation; purchasing; quality assurance; quality management system; quality measurement system; statistical process control; statistical quality control; Continuous production; Inspection; Logistics; Particle measurements; Process control; Production systems; Quality control; Quality management; Supply chains; Virtual manufacturing; performance; statistical quality control; supply chain management; uncertainty;
Conference_Titel :
Industrial Engineering and Engineering Management, 2008. IEEM 2008. IEEE International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-2629-4
Electronic_ISBN :
978-1-4244-2630-0
DOI :
10.1109/IEEM.2008.4738134