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General regression model for prediction of spot weld sizes
KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Welding Technology.ORCID iD: 0000-0002-9849-1754
KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Welding Technology.ORCID iD: 0000-0002-6061-662X
2011 (English)In: International Congress on Advances in Welding Science and Technology for Construction, Energy and Transportation Systems, 2011Conference paper, Published paper (Other academic)
Place, publisher, year, edition, pages
2011.
Keyword [en]
RSW, weld prediction, multiple linear regression analysis, ANOVA, step-wise regression
National Category
Production Engineering, Human Work Science and Ergonomics
Identifiers
URN: urn:nbn:se:kth:diva-139506OAI: oai:DiVA.org:kth-139506DiVA: diva2:687339
Conference
International Congress on Advances in Welding Science and Technology for Construction, Energy and Transportation Systems (AWST - 2011) 24-25 October 2011, Antalya, Turkey
Note

QC 20140114

Available from: 2014-01-14 Created: 2014-01-14 Last updated: 2014-01-14Bibliographically approved
In thesis
1. Process planning of resistance spot welding
Open this publication in new window or tab >>Process planning of resistance spot welding
2013 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Manufacturing engineering in general has experienced an increased demand of process planning in order to optimize processes to reduce costs, environmental impact and increase time efficiency. Resistance spot welding (RSW) is a common and large-scale joining method in several manufacturing industries indicating significant potentials of efficient process planning.

The goal of this thesis is to establish new knowledge for updated and improved process planning of RSW in industrial applications. The goal is expressed by two research questions targeting the issues of process variations and potential of numerical methods of the RSW process. The research questions are expressed in terms of weld size, which is the main interest in RSW process planning.

As any large-scale manufacturing process, RSW involves variations in results – the weld size is known to vary, both as a result of intentional dependent parameters such as process parameters and as a result of unintentional variations in welding conditions. A series of physical and numerical analysis have been performed in order to gain knowledge of such variations.

The unintentional variations, which result in varying weld sizes in apparently identical conditions, were analyzed through both controlled laboratory welding and welding in industrial production environments. The results of the analysis showed the magnitude of standard deviations in both environments and the distribution of weld sizes. The analysis showed that common standard deviations in controlled laboratories and industrial production are approximately 0.3 mm and 0.9 mm, respectively and that weld sizes are distributed showed promising fit to both Normal and Weibull distributions.

The intentional variations of weld sizes due to process parameters, which is the most important aspect of RSW process planning, have traditionally been analyzed through physical testing. In the present thesis two numerical methods were evaluated; regression analysis and FE simulations. For the regression analysis several models were generated and showed a standard deviation of residuals between model and physical results of 0.5 mm. For the FE simulations, material models for the RSW were generated and the simulations showed a standard deviation compared to physical testing of 0.68 mm. In conclusion, the present thesis presents results, which help quantify variations in weld sizes and present the capability of numerical methods of the RSW process.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2013. vi, 56 p.
Series
TRITA-IIP, ISSN 1650-1888 ; 13:01
National Category
Engineering and Technology
Identifiers
urn:nbn:se:kth:diva-117807 (URN)
Presentation
2013-02-05, Sal M311, Brinellvägen 68, KTH, Stockholm, 10:00 (English)
Opponent
Supervisors
Funder
XPRES - Initiative for excellence in production research
Note

QC 20130205

Available from: 2013-02-05 Created: 2013-02-05 Last updated: 2014-01-14Bibliographically approved

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Andersson, OscarMelander, Arne

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