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A Robustness Approach to Reliability

Pär Johannesson (Institutionen för matematiska vetenskaper) ; Bo Bergman (Institutionen för teknikens ekonomi och organisation, Industriell kvalitetsutveckling) ; Thomas Svensson (Institutionen för matematiska vetenskaper, matematisk statistik) ; Martin Arvidsson (Institutionen för teknikens ekonomi och organisation, Industriell kvalitetsutveckling) ; Åke Lönnqvist (Institutionen för teknikens ekonomi och organisation, Industriell kvalitetsutveckling) ; Stefano Barone (Institutionen för teknikens ekonomi och organisation, Industriell kvalitetsutveckling) ; Jacques de Maré (Institutionen för matematiska vetenskaper, matematisk statistik)
Quality and Reliability Engineering International (0748-8017). Vol. 29 (2013), 1, p. 17–32.
[Artikel, refereegranskad vetenskaplig]

Reliability of products is here regarded with respect to failure avoidance rather than probability of failure. To avoid failures, we emphasize variation and suggest some powerful tools for handling failures due to variation. Thus, instead of technical calculation of probabilities from data that usually are too weak for correct results, we emphasize the statistical thinking that puts the designers focus on the critical product functions. Making the design insensitive to unavoidable variation is called robust design and is handled by (i) identification and classification of variation, (ii) design of experiments to find robust solutions, and (iii) statistically based estimations of proper safety margins. Extensions of the classical failure mode and effect analysis (FMEA) are presented. The first extension consists of identifying failure modes caused by variation in the traditional bottom–up FMEA analysis. The second variation mode and effect analysis (VMEA) is a top–down analysis, taking the product characteristics as a starting point and analyzing how sensitive these characteristics are to variation. In cases when there is sufficient detailed information of potential failure causes, the VMEA can be applied in its most advanced mode, the probabilistic VMEA. Variation is then measured as statistical standard deviations, and sensitivities are measured as partial derivatives. This method gives the opportunity to dimension tolerances and safety margins to avoid failures caused by both unavoidable variation and lack of knowledge regarding failure processes.

Nyckelord: reliability prediction; variation; uncertainty; P-diagram; safety factors



Denna post skapades 2012-05-24. Senast ändrad 2016-07-01.
CPL Pubid: 157985

 

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Institutioner (Chalmers)

Institutionen för matematiska vetenskaperInstitutionen för matematiska vetenskaper (GU)
Institutionen för teknikens ekonomi och organisation, Industriell kvalitetsutveckling (2005-2016)
Institutionen för matematiska vetenskaper, matematisk statistik (2005-2016)

Ämnesområden

Matematisk statistik
Övrig industriell teknik och ekonomi

Chalmers infrastruktur