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Real World Data Identification and Classification for Support of Virtual Confidence
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Produktion och automatiseringsteknik, Production and Automation Engineering)
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Produktion och automatiseringsteknik, Production and Automation Engineering)ORCID iD: 0000-0001-9690-890X
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Produktion och automatiseringsteknik, Production and Automation Engineering)
University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre. (Informationssystem, Information Systems)ORCID iD: 0000-0002-9421-8566
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2016 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Shortening of the product development process time is one of the main approaches for all enterprises to offer their products to the market. Virtual manufacturing tools can help companies to reduce their time to market, by reduction of the engineering lead time. Extensive use of virtual engineering models results in a need for verification of the model’s accuracy. This virtual engineering usability and assessment have been named virtual confidence. The two main factors of the achievement of this confidence are the accuracy of the virtual models and the virtual engineering results.

For controlling of both above factors, a complete virtual model and related virtual model knowledge are needed. These knowledges can be tacit or explicit. For exploring explicit knowledge, a data and information collection from different disciplines in the organization is needed.

In this paper, a data map with focus on the manufacturing engineering scope will be presented. This data map is generated from different data sources at a manufacturing plant, and gives an overview of different data that exist at different data sources, in the area of manufacturing. Combining real world data from different sources with virtual engineering model data supports, amongst others, establishment of virtual confidence.

Place, publisher, year, edition, pages
2016.
Keyword [en]
Virtual confidence, manufacturing knowledge, data map, Product lifecycle management (PLM), explicit knowledge
National Category
Other Engineering and Technologies not elsewhere specified
Research subject
Production and Automation Engineering; Information Systems
Identifiers
URN: urn:nbn:se:his:diva-13736OAI: oai:DiVA.org:his-13736DiVA: diva2:1110760
Conference
7th Swedish Production Symposium, Lund, Sweden, October 25-27, 2016
Projects
KDDS
Funder
Knowledge Foundation
Available from: 2017-06-16 Created: 2017-06-16 Last updated: 2017-09-28Bibliographically approved

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Morshedzadeh, ImanOscarsson, JanNg, Amos H.C.Jeusfeld, Manfred A.
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CiteExportLink to record
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