A Robustness Approach to Reliability
Artikel i vetenskaplig tidskrift, 2013

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.

safety factors

uncertainty

reliability prediction

variation

P-diagram

Författare

Pär Johannesson

Göteborgs universitet

Chalmers, Matematiska vetenskaper, matematisk statistik

Bo Bergman

Chalmers, Teknikens ekonomi och organisation, Industriell kvalitetsutveckling

Thomas Svensson

Chalmers, Matematiska vetenskaper, matematisk statistik

Göteborgs universitet

Martin Arvidsson

Chalmers, Teknikens ekonomi och organisation, Industriell kvalitetsutveckling

Åke Lönnqvist

Chalmers, Teknikens ekonomi och organisation, Industriell kvalitetsutveckling

Stefano Barone

Chalmers, Teknikens ekonomi och organisation, Industriell kvalitetsutveckling

Jacques de Maré

Göteborgs universitet

Chalmers, Matematiska vetenskaper, matematisk statistik

Quality and Reliability Engineering International

0748-8017 (ISSN) 1099-1638 (eISSN)

Vol. 29 1 17-32

Ämneskategorier

Annan maskinteknik

Sannolikhetsteori och statistik

Fundament

Grundläggande vetenskaper

DOI

10.1002/qre.1294

Mer information

Skapat

2017-10-08