4.7 Article

Applying Value Stream Mapping to eliminate waste: a case study of an original equipment manufacturer for the automotive industry

Journal

INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
Volume 54, Issue 6, Pages 1708-1720

Publisher

TAYLOR & FRANCIS LTD
DOI: 10.1080/00207543.2015.1055349

Keywords

plastic injection; automotive industry; value-stream mapping; continuous improvement; lean manufacturing

Funding

  1. Portuguese funds through the CIDMA - Center for Research and Development in Mathematics and Applications
  2. Portuguese Foundation for Science and Technology ('FCT-Fundacao para a Ciencia e a Tecnologia') [UID/MAT/04106/2013]

Ask authors/readers for more resources

Since its beginning, lean manufacturing has built a worldwide reputation based on results related to production improvement and cost reduction in several companies. This management philosophy focuses on customer value creation through the elimination of production wastes. Lean methods and techniques have spread their scope from the automotive industry to a wide range of industries and services. This article presents a case study that describes the use of the lean tool value stream mapping in the production process of automotive parts for a major automotive company. At the beginning of the project, relevant data from the process were collected and analysed. Subsequently, the initial process was mapped, the related wastes were identified, and then future processes were mapped and financial results were estimated. The proposals were presented on kaizen meetings, the action plan was discussed and the decision regarding which option to choose was taken. Consequently, the Cycle Time and the level of the workforce were reduced, the process was improved and savings were obtained.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available