Manufacturing performance optimization: The simulation-expert mechanism approach

H Mebrahtu, R Walker, T Dionysopoulos, T Mileham

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

This paper presents an expert mechanism approach to manufacturing performance optimization using simulation as the base tool. The expert mechanism is integrated to the back end of a manufacturing simulator to interpret manufacturing simulation results, assess performance, and then, consistent with set constraints, to effect changes on controllable variables prior to the next run to improve performance. The expert mechanism has a knowledge base that includes proven operations management performance-enhancing methods. In contrast, existing commercial simulation-optimization methods use meta-heuristics in which a near-optimum value is searched from a population of alternative solutions, which can be inefficient in terms of time and cost. The findings of a real case study from a world-class manufacturing company are discussed to demonstrate the expert mechanism and compare it with one of the widely used commercial simulation optimizers.
Original languageEnglish
Pages (from-to)1625-1634
Number of pages10
JournalJournal Of Engineering Manufacture - Part B
Volume223
Issue number12
DOIs
Publication statusPublished - Dec 2009

Fingerprint

Simulators
Costs
Industry

Cite this

Manufacturing performance optimization: The simulation-expert mechanism approach. / Mebrahtu, H; Walker, R; Dionysopoulos, T; Mileham, T.

In: Journal Of Engineering Manufacture - Part B, Vol. 223, No. 12, 12.2009, p. 1625-1634.

Research output: Contribution to journalArticle

Mebrahtu, H ; Walker, R ; Dionysopoulos, T ; Mileham, T. / Manufacturing performance optimization: The simulation-expert mechanism approach. In: Journal Of Engineering Manufacture - Part B. 2009 ; Vol. 223, No. 12. pp. 1625-1634.
@article{77832fb7d5014dc8978c6f92dc495a68,
title = "Manufacturing performance optimization: The simulation-expert mechanism approach",
abstract = "This paper presents an expert mechanism approach to manufacturing performance optimization using simulation as the base tool. The expert mechanism is integrated to the back end of a manufacturing simulator to interpret manufacturing simulation results, assess performance, and then, consistent with set constraints, to effect changes on controllable variables prior to the next run to improve performance. The expert mechanism has a knowledge base that includes proven operations management performance-enhancing methods. In contrast, existing commercial simulation-optimization methods use meta-heuristics in which a near-optimum value is searched from a population of alternative solutions, which can be inefficient in terms of time and cost. The findings of a real case study from a world-class manufacturing company are discussed to demonstrate the expert mechanism and compare it with one of the widely used commercial simulation optimizers.",
author = "H Mebrahtu and R Walker and T Dionysopoulos and T Mileham",
year = "2009",
month = "12",
doi = "10.1243/09544054jem1485",
language = "English",
volume = "223",
pages = "1625--1634",
journal = "Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture",
issn = "0954-4054",
publisher = "Sage Publications",
number = "12",

}

TY - JOUR

T1 - Manufacturing performance optimization: The simulation-expert mechanism approach

AU - Mebrahtu, H

AU - Walker, R

AU - Dionysopoulos, T

AU - Mileham, T

PY - 2009/12

Y1 - 2009/12

N2 - This paper presents an expert mechanism approach to manufacturing performance optimization using simulation as the base tool. The expert mechanism is integrated to the back end of a manufacturing simulator to interpret manufacturing simulation results, assess performance, and then, consistent with set constraints, to effect changes on controllable variables prior to the next run to improve performance. The expert mechanism has a knowledge base that includes proven operations management performance-enhancing methods. In contrast, existing commercial simulation-optimization methods use meta-heuristics in which a near-optimum value is searched from a population of alternative solutions, which can be inefficient in terms of time and cost. The findings of a real case study from a world-class manufacturing company are discussed to demonstrate the expert mechanism and compare it with one of the widely used commercial simulation optimizers.

AB - This paper presents an expert mechanism approach to manufacturing performance optimization using simulation as the base tool. The expert mechanism is integrated to the back end of a manufacturing simulator to interpret manufacturing simulation results, assess performance, and then, consistent with set constraints, to effect changes on controllable variables prior to the next run to improve performance. The expert mechanism has a knowledge base that includes proven operations management performance-enhancing methods. In contrast, existing commercial simulation-optimization methods use meta-heuristics in which a near-optimum value is searched from a population of alternative solutions, which can be inefficient in terms of time and cost. The findings of a real case study from a world-class manufacturing company are discussed to demonstrate the expert mechanism and compare it with one of the widely used commercial simulation optimizers.

UR - http://www.scopus.com/inward/record.url?scp=72449167900&partnerID=8YFLogxK

UR - http://dx.doi.org/10.1243/09544054jem1485

U2 - 10.1243/09544054jem1485

DO - 10.1243/09544054jem1485

M3 - Article

VL - 223

SP - 1625

EP - 1634

JO - Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture

JF - Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture

SN - 0954-4054

IS - 12

ER -