Int. J. of Reliability and Safety   »   2017 Vol.11, No.3/4

 

 

Title: Cost-reliability trade-off of path generating linkages using multi-objective genetic algorithm

 

Authors: Palaniappan Ramu; G. Saravana Kumar; Prashanth Neelakantan; Kiran Kumar Bathula

 

Addresses:
Department of Engineering Design, Indian Institute of Technology Madras, Chennai 600036, India
Department of Engineering Design, Indian Institute of Technology Madras, Chennai 600036, India
Petroleum Engineering and Geosciences, Applied Earth Sciences, TU Delft, Delft, the Netherlands
NICE Actimize, Pune, India

 

Abstract: The performance of a path generating linkage is measured in terms of the error in the generated path. The probability of producing its intended path is its reliability. Tighter tolerances in link lengths and joint clearances result in higher reliability but incur more costs. Therefore, it is desirable to understand the trade-off relationship between the costs and reliability. In the current work, a genetic algorithm is used to construct the Pareto trade-off front between cost and reliability by solving a bi-criterion optimisation problem. Statistical moments required to estimate reliability are computed by combining an approximate cumulative density function of error and a 3-point approximation technique. This approach uses a fraction of the samples compared to crude Monte Carlo simulation. The proposed approach is demonstrated on a four bar mechanism tracing a straight line and a closed path. It is observed that the Pareto front generated using the proposed approach with fewer samples compares well with the one generated with crude Monte Carlo simulation with a large sample set, thus offering enormous gains in computational efficiency.

 

Keywords: reliability; Pareto front; mechanism; Monte Carlo simulation; bootstrap.

 

DOI: 10.1504/IJRS.2017.10010834

 

Int. J. of Reliability and Safety, 2017 Vol.11, No.3/4, pp.200 - 219

 

Submission date: 12 Aug 2017
Date of acceptance: 15 Nov 2017
Available online: 31 Jan 2018

 

 

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