Journal Article


Reliability improvement and risk reduction by inequalities and segmentation

Abstract

The paper introduces new domain-independent methods for improving reliability and reducing risk based on algebraic inequalities and chain-rule segmentation. Two major advantages of algebraic inequalities for reducing risk have been demonstrated: (i) ranking risky prospects in the absence of any knowledge related to the individual building parts and (ii) reducing the variability of a risk-critical critical output parameter. The paper demonstrates a highly counter-intuitive result derived by using inequalities: if no information about the component reliability characterising the individual suppliers is available, purchasing components from a single supplier or from the smallest possible number of suppliers maximises the probability of a high-reliability assembly. The paper also demonstrates the benefits from combining domain-independent methods and domain-specific knowledge for achieving risk reduction in several unrelated domains: decision-making, manufacturing, strength of components and kinematic analysis of complex mechanisms. In this respect, the paper introduces the chain rule segmentation method and applies it to reduce the risk of computational errors in kinematic analysis of complex mechanisms. The paper also demonstrates that combining the domain-independent method of segmentation and domain-specific knowledge in stress analysis leads to a significant reduction of the internal stresses and reduction of the risk of overstress failure.

Attached files

Authors

Todinov, Michael

Oxford Brookes departments

School of Engineering, Computing and Mathematics

Dates

Year of publication: Not yet published.
Date of RADAR deposit: 2019-10-11


Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License


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This RADAR resource is the Accepted Manuscript of Reliability improvement and risk reduction by inequalities and segmentation

Details

  • Owner: Joseph Ripp
  • Collection: Outputs
  • Version: 1 (show all)
  • Status: Live