Tolerance analysis based on Monte Carlo simulation: a case of an automotive water pump design optimization
Eduardo Umaras,
Ahmad Barari and
Marcos Sales Guerra Tsuzuki ()
Additional contact information
Eduardo Umaras: Escola Politécnica da Universidade de São Paulo
Ahmad Barari: University of Ontario Institute of Technology (Ontario Tech)
Marcos Sales Guerra Tsuzuki: Escola Politécnica da Universidade de São Paulo
Journal of Intelligent Manufacturing, 2021, vol. 32, issue 7, No 7, 1883-1897
Abstract:
Abstract Successful products are those presenting the highest quality at a fair cost. Although different approaches can be used to define the concept of quality, functional reliability is always a major requirement, due to implications such as safety and user losses regarding maintenance expenses, and product availability. Intelligent designs are robust and result in a fair cost. Robust designs are those insensitive to sources of variation occurring during the product life, keeping their performance under variable use conditions, like thermal and stress effects. The robustness approach is a function of two main design criteria: low complexity and tolerance design. Design for manufacture and assembly is closely related to decreasing complexity. Tolerance design is a tool in which the unavoidable manufacturing variations are considered during product development. This work presents a proposal for an intelligent design in an actual application by considering design simplification through the reduction of parts for an automotive water pump. The tolerance analysis is performed by means of a powerful statistical approach—a Monte Carlo simulation—in which process behavior is randomly simulated representing a high production volume. Additionally, service thermal effects are also contemplated, and assembly tests are proposed for automatic rejection of non-conforming parts, assuring high reliability and full compliance with functional requirements. This is an example of integrated design–manufacturing work aiming at both cost saving and improved reliability.
Keywords: Monte Carlo simulation; Design for manufacture and assembly; Automotive pump; Water pump; DFMA; DFM; DFA (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations:
Downloads: (external link)
http://link.springer.com/10.1007/s10845-020-01695-7 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:joinma:v:32:y:2021:i:7:d:10.1007_s10845-020-01695-7
Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10845
DOI: 10.1007/s10845-020-01695-7
Access Statistics for this article
Journal of Intelligent Manufacturing is currently edited by Andrew Kusiak
More articles in Journal of Intelligent Manufacturing from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().