Reliability modeling-based tolerance design and process parameter analysis considering performance degradation. (March 2021)

• Record Type: Journal Article
• Authors: Kong, Xuefeng; Yang, Jun; Hao, Songhua
• Is Part Of: Reliability engineering & system safety. Volume 207(2021)
• Publication Date: 2021-03
• Subjects: Quality improvement -- Tolerance design -- Process parameter analysis -- Helical springs -- Reliability modeling; Reliability (Engineering) -- Periodicals; System safety -- Periodicals; Industrial safety -- Periodicals; Fiabilité -- Périodiques; Sécurité des systèmes -- Périodiques; Sécurité du travail -- Périodiques; 620.00452
• DOI: 10.1016/j.ress.2020.107343
• Languages: English
• ISSNs: 0951-8320

Abstract

Highlights: A reliability model with temperature-humidity-mechanical stress covariate is built. A two-stage parameters estimation method is proposed based on NLS and MLE. A novel tolerance design is developed considering reliability constraint. An allowable range of quality fluctuation is derived with reliability constraint. A real case is given to show the implementation of the proposed methods. Abstract: Tolerance design and process parameter analysis have been widely used for reducing the fluctuation of product quality characteristics (QCs). Most existing works focus on finding the best compromise between manufacturing cost and tolerance of QCs. However, the performance degradation of products will lead to QCs deviating from design specifications, which is ignored in current researches. Motivated by the stress relaxation process of helical springs, we propose a more reliable tolerance design and process parameter analysis considering performance degradation. An accelerated degradation model is first constructed to reflect the degradation process of helical springs and the influence of the initial free length. Subsequently, considering the given reliability constraint, a tolerance design method based on degradation performance is developed to guide the quality improvement of helical springs. Furthermore, a new reliability model embodied with the influence of parameter fluctuation is proposed, and an allowable fluctuation range for the deviation and variance of the initial free length is derived, based on which the process parameter can be optimized to improve the manufacturing process. Finally, a real case study of helical springs is conducted to illustrate the implementation and effectiveness of the proposed method.