Cognitive reliability and error analysis based on anticipatory failure determination

被引：0

作者：

Bai Z. ^{[1
]}

Chang M. ^{[1
]}

Peng Q. ^{[2
]}

Xu B. ^{[1
]}

机构：

[1] Hebei University of Technology, China

[2] University of Manitoba, Canada

来源：

Computer-Aided Design and Applications | 2020年 / 18卷 / 01期

关键词：

Anticipatory failure determination (AFD); Cognitive Reliability and Error Analysis Method (CREAM); Failure analysis; Produce design; Reliability; TRIZ;

D O I：

10.14733/cadaps.2021.130-143

中图分类号：

学科分类号：

摘要：

Market changes and diversity demands have brought great challenges for designers to build correct models and actively analyze and identify problems of a product in order to reduce probability of failures of the product. Product reliability and failure analysis is an important action to ensure that a product can work properly in its expected life time. Existing methods of the product reliability and failure analysis are mainly based on users’ experience. Product failures are analyzed based on historical records but relationships of product interconnection faults. This paper proposes an effective method that integrates the anticipatory failure determination and cognitive reliability and error analysis to search causes of failure modes of a product. TRIZ tools are used to find solutions to avoid or reduce the failure causes. The proposed method improves the product reliability and failure analysis effectively. Feasibility of the proposed method is verified in a case study of the failure analysis and reliability improvement of a pneumatic nail gun product. © 2021 CAD Solutions, LLC.

引用

页码：130 / 146

页数：16

共 25 条

[1]

Chen D., Fan Y., Li W., Human reliability prediction in deep-sea sampling process of the manned submersible, Safety Science, 112, pp. 1-8, (2019)

[2]

Chen R., Wei Z., Research of the failure cause analysis and solving model based on TRIZ & AFD, 2010 International Conference on Computer Design and Applications, 5, (2010)

[3]

Carvalho M.A., da Silva R.F., Anticipatory Failure Determination (AFD) for Product Reliability Analysis: A Comparison Between AFD and Failure Mode and Effects Analysis (FMEA) for Identifying Potential Failure Modes, Advances in Systematic Creativity, Palgrave Macmillan, Cham, pp. 181-200, (2019)

[4]

Gawdzinska K., Chybowski L., Souchkov V., Applying the Anticipatory Failure Determination at a Very Early Stage of a System's Development: Overview and Case Study, Multidisciplinary Aspects of Production Engineering, 1, 1, pp. 205-215, (2018)

[5]

Hiltmann K., Predicting Unknown Failures, Procedia Engineering, 131, pp. 840-849, (2015)

[6]

Hipple J., Predictive Failure analysis™: How to Use TRIZ in "Reverse

[7]

Hollnagel E., Cognitive Reliability and Error Analysis Method, (1998)

[8]

Hung C., Chen J.L., Eco-Innovation by Anticipatory Failure Determination (AFD) Method, Proceedings of the Design Society: International Conference on Engineering Design, 1, 1, pp. 3271-3280, (2019)

[9]

Jensen A., Aven T., Hazard/threat identification: Using functional resonance analysis method inconjunction with the Anticipatory Failure Determination method, Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 231, 4, pp. 383-389, (2017)

[10]

Khan F., Zuo M.J., Amin M.T., A bibliometric analysis of process system failure and reliability literature, Engineering Failure Analysis, (2019)

← 1 2 3 →