DocumentCode :
3746828
Title :
A methodology for continuous quality assurance of production data
Author :
Jon Bokrantz;Anders Skoogh;Jon Andersson;Jacob Ruda;Dan L?mkull
Author_Institution :
Department of Product and Production Development, IT Tools, Division of Production Systems, Chalmers University of Technology, H?rsalsv?gen 7, Gothenburg, SE-41296, SWEDEN
fYear :
2015
Firstpage :
2088
Lastpage :
2099
Abstract :
High quality input data is a necessity for successful Discrete Event Simulation (DES) applications, and there are available methodologies for data collection in DES projects. However, in contrast to standalone projects, using DES as a day-to-day engineering tool requires high quality production data to be constantly available. Unfortunately, there are no detailed guidelines that describes how to achieve this. Therefore, this paper presents such a methodology, based on three concurrent engineering projects within the automotive industry. The methodology explains the necessary roles, responsibilities, meetings, and documents to achieve a continuous quality assurance of production data. It also specifies an approach to input data management for DES using the Generic Data Management Tool (GDM-Tool). The expected effects are increased availability of high quality production data and reduced lead time of input data management, especially valuable in manufacturing companies having advanced automated data collection methods and using DES on a daily basis.
Keywords :
"Quality assurance","Production","Organizations","Lead"
Publisher :
ieee
Conference_Titel :
Winter Simulation Conference (WSC), 2015
Electronic_ISBN :
1558-4305
Type :
conf
DOI :
10.1109/WSC.2015.7408323
Filename :
7408323
Link To Document :
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