Abstract
In this article, two alternative approaches to include variability analysis in value stream mapping (VSM) are presented. Notoriously, VSM is one of the best tools to map a process and to identify its main criticalities in order to enhance lean manufacturing. Unfortunately, in the standard approach, data are recorded on the map as deterministic, disregarding the real variability of the process. This is a strong limit because, especially within manufacturing processes, variability has a significant impact on costs and leads to several wastes. Therefore, it must be carefully analysed and reduced before lean manufacturing can be set into place. To overcome this weakness, this article proposes two alternative approaches based on statistics and fuzzy algebra, respectively. Both methods are designed to support practitioners and can be easily applied to several industrial applications. Their practicality is finally demonstrated through an industrial application of relevance. Obtained results are compared and respective advantages/disadvantages are presented and discussed.
Acknowledgements
The authors would like to thank the referees for their valuable suggestions and useful comments that made it possible to greatly improve the structure and the quality of this article.