A stochastic evaluation framework to improve the robustness of manufacturing systems

Date published

2023-01-03

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Volume Title

Publisher

Taylor & Francis

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Article

ISSN

0951-192X

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Citation

Pagone E, Haddad Y, Barsotti L, et al., (2023) A stochastic evaluation framework to improve the robustness of manufacturing systems, International Journal of Computer Integrated Manufacturing, Volume 36, Issue 7, July 2023, pp. 966-984

Abstract

This work presents a framework to assess the robustness of manufacturing systems. Robustness, which is an indicator of the system’s ability to maintain its desired performance in face of disturbances, is quantified considering the variance of manufacturing system performance indicators. According to the framework, key objectives are first explicitly defined to guide a thorough exploration of the manufacturing system structural and dynamic characteristics. Several simulation experiments, orchestrated methodically through experimental design, are run and statistically analysed through analysis of variance (ANOVA) tests, including also financial implications. The framework has been tested and validated against a case study where the robustness of the manufacturing system with regard to six aerospace product types is evaluated. The mentioned case study proved that the framework has the potential to improve the robustness of manufacturing systems, identifying the most and least disruptive dispatching policies.

Description

Software Description

Software Language

Github

Keywords

Robustness, manufacturing systems, discrete event simulation, applied statistics, system simulation

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Attribution-NonCommercial-NoDerivatives 4.0 International

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