E3S Web Conf.
Volume 73, 2018The 3rd International Conference on Energy, Environmental and Information System (ICENIS 2018)
|Number of page(s)||6|
|Section||Technology, Culture and Society in Waste Management|
|Published online||21 December 2018|
Lean Manufacturing: Waste Reduction Using Value Stream Mapping
1 Department of Industrial Engineering, Faculty of Engineering, Diponegoro University, Semarang - Indonesia
2 Department of Industrial Engineering, Faculty of Industrial Engineering, Universitas Islam Indonesia, Yogyakarta - Indonesia
* Corresponding author: firstname.lastname@example.org
Cristal Sri Sujarwati is a small medium enterprise (SME) that produce keripik salak in Sleman, Yogyakarta. To survive and win industrial competition, Cristal Sri Sujarwati was required to improve its performance. But in reality there was a lot of waste in order fulfillment processes marked by ineffective and inefficient work. In this research, lean manufacturing aims to identify and eliminate waste so that the company could improve its performance in winning the industry competition. Lean manufacturing is a systematic approach used to identify and eliminate waste. This lean concept could improve responsiveness through waste reduction, continuous improvement and cost reduction. In order to identify and eliminating waste, a value stream mapping tools, waste weighting questionnaire, value stream analysis tools, and fishbone diagram are used. From the results of research, the dominant waste in the production process was waste defects, waiting, and unnecessary inventory. To eliminate waste, process activity mapping (PAM), the one of detailed mapping tools in VALSAT are used. From the results of the improvement recommendations analysis, lead time decreased by 80 minutes. From the analysis using PAM, there was a reduction of NVA activity from 3.10% to 1.01%.
Key words: Lean Manufacturing / Process Activity Mapping / Value Stream Mapping / VALSAT / Waste
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.