Impact of human performance variation on the accuracy of manufacturing system simulation models
| dc.contributor.advisor | Baines, Tim | |
| dc.contributor.author | Siebers, P-O. | |
| dc.date.accessioned | 2016-10-14T09:28:18Z | |
| dc.date.available | 2016-10-14T09:28:18Z | |
| dc.date.issued | 2004-10 | |
| dc.description.abstract | The research described in this thesis is concerned with human performance modelling as an aid in the process of manufacturing systems design and re-design. Most manufacturing systems are highly complex constructs and their behaviour is of a dynamic and stochastic nature. They have to be constantly designed and re-designed as organisations are continually being pressured to change their manufacturing facilities, technologies, methods, people and products. All design methods have some form of evaluation where discrete event simulation models are usually used to undertake a comparative analysis of different system designs. Within these discrete event simulation models it is common practice to represent workers as simple resources, often using deterministic performance values. Conversely, the work measurement literature indicates that worker task performance varies between different workers carrying out the same task and moreover for the same worker when repeating a task. The current approach of representing workers within discrete event simulation models ignores the potentially large effect that human performance Variation can have on system performance. This omission affects in particular simulation models of labour intensive manufacturing systems like manual assembly flow lines. It appears that this adds to the inaccuracy of the simulation model output and that consequently the simulation model does not react the behaviour of a real system in an appropriate way. A research programme has been designed to investigate these issues. First, a long term data collection exercise has been conducted to quantify the performance Variation of workers in a typical automotive manual assembly flow line. The data have then been used in form of frequency distributions to represent worker performance Variation at individual Workstations within manual assembly line simulation models. Through designed simulation experiments the impact that this form of worker performance Variation representation has on the accuracy of manual assembly line model behaviour has been investigated. Overall this research has found that adding worker performance Variation models into manual assembly flow line models has an impact on the accuracy of these simulation models. The magnitude of the impact depends very much on the type of Variation to be represented as well as on the system to be modelled. This evidence is an important result to support justification for further research in this area. For a more sophisticated approach of modelling worker performance Computational Organisation Theory using the multi-agent paradigm has been identified as the most suitable way forward. | en_UK |
| dc.identifier.uri | http://dspace.lib.cranfield.ac.uk/handle/1826/10750 | |
| dc.language.iso | en | en_UK |
| dc.publisher | Cranfield University | en_UK |
| dc.rights | © Cranfield University, 2004. All rights reserved. No part of this publication may be reproduced without the written permission of the copyright holder. | en_UK |
| dc.title | Impact of human performance variation on the accuracy of manufacturing system simulation models | en_UK |
| dc.type | Thesis or dissertation | en_UK |
| dc.type.qualificationlevel | Doctoral | en_UK |
| dc.type.qualificationname | PhD | en_UK |