In:
Modern Applied Science, Canadian Center of Science and Education, Vol. 11, No. 1 ( 2016-10-14), p. 76-
Kurzfassung:
Uncertainty within supply chains increases the risk of not meeting objectives. Warehouses can absorb some of these uncertainties, by accumulating inventory. This accumulation has led many to consider warehouses as a source of waste in supply chains. Hence, there is limited research that seeks improving intrinsic warehouse efficiency; particularly in the context of Lean concepts and Value Stream Mapping (VSM). Since, warehouses seek to absorb uncertainty in supply chain by holding inventory; this uncertainty absorption may introduce variability to warehousing function itself. Therefore a methodology is required, which can capture the embodied dynamic within warehousing function. This paper reflects Lean concepts and, in particular, VSM to warehousing context and introduces some methods and guidelines to assure the proper application of VSM in what is an uncertain and dynamic system. In this paper, warehousing function is formulated based on some abstract processes which vary on their output status. This formulation facilitates identifying value-adding activities as one of the most substantial steps, yet confusing in application of VSM in warehousing context. The suggested methods enable fundamental statistical/mathematical analysis, which leverage VSM to a more dynamic evaluation tool. Application of the introduced approach will facilitate the decision making process for warehouse systems evaluation and improvement. The resultant methodology is applied to a factual case and this serves to demonstrate its practical application. It is worth mentioning that the findings applications, which can be termed ‘dynamic VSM’, are not limited to warehouses but can also be applied to any dynamic environment with non-deterministic processes.
Materialart:
Online-Ressource
ISSN:
1913-1852
,
1913-1844
DOI:
10.5539/mas.v11n1P76
Sprache:
Unbekannt
Verlag:
Canadian Center of Science and Education
Publikationsdatum:
2016
ZDB Id:
2436317-0
