Mohamed, N.M.Z.NikKhan, M. Khurshid2016-10-072016-10-072011Mohamed NMZN and Khan MK (2011) Knowledge based system implementation for lean process in low volume automotive manufacturing (LVAM) with reference to process manufacturing. Chemical Product and Process Modeling. 6(2): Article 7.90007697http://hdl.handle.net/10454/9541YesGlobal manufacturing industry mostly depends on new product development and processes to become competitive. The product development process for automotive industry is normally complicated, lengthy, expensive, and risky. Hence, a study of lean manufacturing processes for low volume manufacturing in automotive industry is proposed to overcome this issue by eliminating all wastes in the lengthy process. This paper presents a conceptual design approach to the development of a hybrid Knowledge Based (KB) system for lean process in Low Volume Automotive Manufacturing (LVAM). The research concentrates on the low volume processes by using a hybrid KB system, which is a blend of KB system and Gauging Absences of Pre-requisites (GAP). The hybrid KB/GAP system identifies all potential waste elements of low volume process manufacturing. The KB system analyses the difference between the existing and the benchmark standards for lean process for an effective implementation through the GAP analysis technique. The proposed model explores three major lean process components, namely Employee Involvement, Waste Elimination, and Kaizen (continuous improvement). These three components provide valuable information in order for decision makers to design and implement an optimised low volume manufacturing process, but which can be applied in all process manufacturing, including chemical processing.en© 2011 De Gruyter. Reproduced in accordance with the publisher's selfarchiving policy.Low volume automotive manufacturing (LVAM); Knowledge based system; Gauging absences of pre-requisites (GAP); Lean process optimisationKnowledge based system implementation for lean process in low volume automotive manufacturing (LVAM) with reference to process manufacturingArticlehttps://doi.org/10.2202/1934-2659.1601