An Improved Value Stream Mapping to Prioritize Lean Optimization Scenarios Using Simulation and Multiple-Attribute Decision-Making Method

Abstract

Manufacturing organizations have been witnessing transformation in business strategy from mass production to lean philosophy. Value Stream Mapping (VSM) is one of the primary analytical tools for identifying waste and transforming the production environment into lean operational state. However, traditional VSM lacks the capability to handle conflicting factors in the improvement scheme and to prioritize multiple improvement initiatives. VSM enables only a static analysis of a system, and a static model does not allow assessing how the system will be affected to various scenarios with different parameters in the future-state map. Moreover, VSM optimization is a typical multiple-attribute decision-making (MADM) problem that involves the evaluation of multiple performance metrics such as inventory levels, lead times and service levels. Therefore, this paper proposes an improved VSM procedure that incorporates simulation and MADM, using grey Taguchi method, to overcome the limitation of standard VSM. Simulation introduces a dynamic dimension to VSM, and grey Taguchi method prioritizes the scenarios with a minimum number of test series. A lean implementation program is conducted in a footwear manufacturing company to validate the improved VSM procedure. Two alternative future-state VSMs are proposed, each with nine different scenarios, and the identified optimal solution realizes the reduction in defect rate, work-in-process inventory and lead time, as well as the improvement in order fulfilment rate. The improved VSM procedure enables practitioners to determine the optimal future-state VSM according to the preference of practitioners on multiple performance criteria.