Variability and Uncertainty Analysis in Value Stream Mapping
Araibi Salahuddin Alaa1, A I M Shaiful2, Zuraidah Mohd Zain3
1Araibi Salahuddin Alaa, School of Manufacturing Engineering, Universiti Malaysia Perlis, Kampus Alam Pauh Putra, Arau, Perlis, Malaysia.
2A I M Shaiful, School of Manufacturing Engineering, Universiti Malaysia Perlis, Kampus Alam Pauh Putra, Arau, Perlis, Malaysia.
3Zuraidah Mohd Zain, School of Manufacturing Engineering, Universiti Malaysia Perlis, Kampus Alam Pauh Putra, Arau, Perlis, Malaysia.
Manuscript received on 09 December 2019 | Revised Manuscript received on 23 December 2019 | Manuscript Published on 31 December 2019 | PP: 533-538 | Volume-8 Issue-12S2 October 2019 | Retrieval Number: L109910812S219/2019©BEIESP | DOI: 10.35940/ijitee.L1099.10812S219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Lately, value stream mapping (VSM) is integrated with tools and techniques that belong to other areas of knowledge such as risk management (RM). It is well known tool in showing the value, value stream and the flow which represents three of lean manufacturing (LM) principles. This integration, gives more benefit in covering two of VSM issues such as considering the variability and uncertainty of production processes. In this paper, a model named variable value stream mapping (V-VSM) that integrates the two was showed, explained and tested. The model helps to generate the VSM in a dynamic way with the identification of current and potential risks. These risks might happen in the future bringing a strong impact on not reaching the main objectives in the defined time and cost. The model has been tested by conducting a case study in food sector. A current state map was built using both models, traditional VSM and V-VSM. The results showed the effect of variability and uncertainty on the total cycle time (CT) and lead time (LT) values, where the traditional VSM failed to show it by being a static tool. Comparing the results of both models show the differences in presenting the real state of manufacturing environment.
Keywords: Monte Carlo Simulation, Probability Distribution, Risk Management, Value Stream Mapping, Variability.
Scope of the Article: Network Modelling and Simulation