Dynamic Value Stream Mapping for production lead time improvement using Fuzzy Triangular analysis

• 第一著者: Manoharan, Thulasi
• フォーマット: 学位論文
• 言語: 英語
• 出版事項: 2023
• 主題: Production management; Value analysis (Cost control)
• オンライン･アクセス: http://psasir.upm.edu.my/id/eprint/115836/1/115836.pdf

Value Stream Mapping (VSM) is one of the lean tools that visualize a production process at the plant level and illustrate the flow of materials and information in the entire supply chain. The ongoing rise of digitalization is currently a major feature of production that increased demands for flexibility in the production system. Even though VSM application helped in visualizing the benefits of applying lean principles, it had several limitations that prevented it from being applied in a broader perspective. In high-variety and low-volume factories, the conventional VSM which is more static in nature, unable to give a real vision of the variability problems concerning the production process. Secondly, the development of future state VSM is mostly based on the trial-and-error principle because the future state is not validated in conventional VSM. As of this lack of validation the findings remain in the investigation stage without being applied in the actual manufacturing scenario at all. Hence the objective of this research is to determine process variability using Fuzzy-Number in dynamic value stream mapping (VSM). A future VSM is designed by implementing lean improvement tools and integrating with Discrete Event Simulation (DES) to improve the accuracy of analysis. The hybrids of fuzzy VSM and DES are then validated by applying in an industrial case study. A conveyor manufacturing company was selected as a case study based on the high variety and low volume type of manufacturing process. Triangular Fuzzy Number (TFN) approach was used to analyze variabilities in process parameters to identify their mean, minimum and maximum values and remove all the outliers. A current VSM was then designed and highlights all the non-value -added activities processes that need to be improved. Based on the identifications, an appropriate lean improvement tools were applied to develop an optimized future VSM. Both the current state and future state maps were verified using ARENA simulation models. ARENA simulation helps to simulate more than one future state alternatives and shows improvement ratio in terms of production lead time and value -added time and compares with current state values. As a result, second alternative of future state map shows 71.74% and 19.45% of improvement ratio in terms of production lead time and value- added time respectively compared to current VSM. In the second case study, the total production lead time of future value stream map shows 49.88% improvement compared to current VSM. The result of simulation validated using p-value analysis. The significance value of p-analysis shows less than 0.05 which is considered to be statistically significant and the null hypothesis should be rejected. It is concluded that, dynamic VSM is a suitable tool to visualize the value added and non-value- added activities in a flexible manufacturing system and apply appropriate lean tools in order to reduce the total production lead time and work-in-progress (WIP) inventory. This study can be further extended by investigating how the reduction of lead time and WIP inventory can be helpful in cost reduction of a company.