To respond to the globalization and fierce competition, manufacturers gradually realize the challenge of demanding customers who strongly seek for products of high-quality and low-cost, which implicitly calls for the quality improvement of the products in a cost-effective way. Traditional methods focused on specified process optimization for quality enhancement instead of emphasizing the organizational collaboration to ensure qualitative performance. This paper introduces artificial intelligence (AI) approach to attain quality enhancement by automating the selection of process parameters within the supply chain. The originality of this research is providing an optimal configuration of process parameters along the supply chain and delivering qualified outputs to raise customer satisfaction.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.