An integrated stochastic-fuzzy method for supply chain leanness evaluation in Iranian automotive small and medium enteprises

• 第一著者: Behrouzi, Farzad
• フォーマット: 学位論文
• 言語: English
• 出版事項: 2013
• 主題: TS Manufactures
• オンライン･アクセス: http://eprints.utm.my/id/eprint/38439/5/FarzadBehrouziPFKM2013.pdf; http://eprints.utm.my/id/eprint/38439/

In today’s competitive markets, companies have realized that there is an urgent need to improve the performance of the whole supply chain of which they are members. A measure of leanness is needed to provide decision support information such as the current leanness level, the progress of lean supply chain implementation, and the extent of potential improvements in the supply chain. In spite of the vast amount of studies on lean concepts and related tools and techniques, the evaluation of lean situation (leanness) is less investigated especially in a supply chain. In order to fill this gap, this research was carried out to systematically quantify the leanness of Small and Medium Enterprises' (SMEs) supply chain in the automotive industry with regard to stochastic and fuzzy uncertainties in performance measures. Particularly, four performance categories (quality, cost, delivery and reliability, and flexibility) along with 28 related metrics were developed as surrogates for leanness. These were achieved through a questionnaire survey, using experts' knowledge and experience from SMEs in the automotive industry in Iran. Factor analysis along with principal component analysis was used to validate the measures and metrics. Validity and reliability tests were consequently conducted. Following this, a stochastic-fuzzy method was developed to evaluate and predict the leanness of supply chain. The probability function of the total leanness was identified and different leanness situations were consequently evaluated and predicted. A total leanness index was also provided and connected to fuzzy sets (linguistic terms) to evaluate the current leanness level. The developed method was consequently tested and evaluated by using two case studies, and some management actions were suggested based on different values of leanness level. From the evaluation, it was found that the proposed method is applicable and easy to use. In addition, it was found that SMEs in Iran's automotive industry need to be given more attention in order to enhance their leanness level. This study contributes to expand the knowledge on supply chain leanness measurement and provides practical guidelines for manufacturing SMEs in the automotive industry to evaluate, predict, and improve the leanness of their supply chain using an integrated stochastic-fuzzy method.