Industrial technology has excelled profoundly in the past few decades, helping organisations throughout the world to be more efficient in all processes and keeping costs down. However, despite the abundance of several IT solutions, there exist many problems where more than one decision has to be made. Among the techniques supporting a multi-decisional context, simulations can undoubtedly play an important role as they provide what-if analysis and hence help to evaluate quantitative benefits. This thesis develops a simulation model for breakdown in an industrial machine, the main crusher in a cement factory. It also examines three important parameters (Drill Head, Dusting and Lubrication) of the crusher machine with the use of Bayesian network modelling which allows determination of suitable influencing factors in a precise and dynamic manner. The model also supports integration with management systems such as J.I.T, and MRPII. Witness simulation software has been used in this work to model the breakdown frequency of the Crusher machine and the associated parameters. The Bayesian Network Modelling is used to consider historical data and expert opinions; the Bayes’ approach takes into consideration off all existing parameters that affect the machine breakdown directly or indirectly. This tool is capable of establishing a probability based on the information gathered about the parameters. The simulation model is developed further to enable the Bayesian Network Modelling to be applied via the Chain Rule to calculate the probability of failure. The findings of this research show the approach developed in this work, where the Bayesian probability development process is integrated into the simulation model. This provides a unique and dynamic tool to aid decision making in understanding machine breakdowns. The resulting simulator is a decision making tool capable of analysing the status of the machine and the associated influencing factors. This uses an approach based on multiple performance measures and a user-defined set of inputs based on historical and expert opinion. This work provides a methodology to study the importance of key parameters of the crusher machine. This in effect highlights the correlation between the governing parameters and the occurrence of breakdown.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:582531 |
| Date | January 2013 |
| Creators | Abogrean, Elbahlul M. |
| Publisher | Manchester Metropolitan University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://e-space.mmu.ac.uk/313172/ |
Page generated in 0.0018 seconds