Modelling and Improving Maintenance Decisions: Having Foresight with Simulation and Artificial Intelligence 2002-01-0471
Machine breakdowns are one of the main sources of disruption and throughput fluctuation in highly automated production facilities. One element in reducing this disruption is ensuring that the maintenance team responds correctly to machine failures. It is, however, difficult to determine the current practice employed by the maintenance team, let alone suggest improvements to it. ‘Knowledge based improvement’ is a methodology that aims to address this issue, by (a) eliciting knowledge on current practice, (b) evaluating that practice and (c) looking for improvements. The methodology, based on visual interactive simulation and artificial intelligence methods, and its application to a Ford engine assembly facility are described.
Citation: Robinson, S., Alifantis, A., Hurrion, R., Edwards, J. et al., "Modelling and Improving Maintenance Decisions: Having Foresight with Simulation and Artificial Intelligence," SAE Technical Paper 2002-01-0471, 2002, https://doi.org/10.4271/2002-01-0471. Download Citation
Author(s):
S. Robinson, A. Alifantis, R. D. Hurrion, J. S. Edwards, J. Ladbrook, T. Waller
Affiliated:
University of Warwick, United Kingdom, Aston University, United Kingdom, Ford Motor Company, United Kingdom, Lanner Group, United Kingdom
Pages: 10
Event:
SAE 2002 World Congress & Exhibition
ISSN:
0148-7191
e-ISSN:
2688-3627
Also in:
Foresight Vehicle Technology: Consumer Driven Design, Manufacturing, Supply Chain, and Purchasing-SP-1694, SAE 2002 Transactions Journal of Materials & Manufacturing-V111-5
Related Topics:
Artificial intelligence (AI)
Assembling
Production
Simulation and modeling
Automation
SAE MOBILUS
Subscribers can view annotate, and download all of SAE's content.
Learn More »
