A Comprehensive Analysis of Sensitivity in Simulation Models for Enhanced System Understanding and Optimisation-Reference-Cited by-同舟云学术

A Comprehensive Analysis of Sensitivity in Simulation Models for Enhanced System Understanding and Optimisation

Published:2024-04-01 Issue:4 Volume:12 Page:716
ISSN:2227-9717
Container-title:Processes
language:en
Short-container-title:Processes

Author:

Grznár Patrik¹^ORCID,Gregor Milan¹,Mozol Štefan¹^ORCID,Mozolová Lucia¹,Krump Henrich²,Mizerák Marek³,Trojan Jozef³^ORCID

Affiliation:

1. Department of Industrial Engineering, Faculty of Mechanical Engineering, University of Žilina, Univerzitná 8215/1, 010 26 Žilina, Slovakia

2. Department of Plastics, Rubber and Fibers, Faculty of Chemical and Food Technology, Slovak University of Technology in Bratislava, Radlinského 9, 812 37 Bratislava, Slovakia

3. Department of Industrial and Digital Engineering, Faculty of Mechanical Engineering, Technical University of Košice, Park Komenského 9, 040 01 Košice, Slovakia

Abstract

This article delves into sensitivity analysis within simulation models of real systems, focusing on the impact of variability in independent input factors (x) on dependent system outputs (y). It discusses linear and nonlinear regression to analyse and represent relationships between input factors and system responses. This study encompasses three sensitivity analysis areas: factor screening, local sensitivity analysis, and global sensitivity analysis, highlighting their roles in understanding the significance of factors in simulation models. The practical application of sensitivity analysis becomes clear through a case study in a manufacturing system. The case study utilises the Simio simulation system to investigate the impact of input factors on production lead time and work in process (WIP). The analysis uses regression to quantify the impact of seven factors, showcasing the most significant ones with tornado charts and emphasising the application of sensitivity analysis to optimise system responses.

Funder

Slovak Research and Development Agency

VEGA

Publisher

MDPI AG

Link

https://www.mdpi.com/2227-9717/12/4/716/pdf

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