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Title: Cost benefit analysis of condition monitoring in batch process plants
Author: Rajan, B. S.
Awarding Body: University of Wales Swansea
Current Institution: Swansea University
Date of Award: 1999
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Condition monitoring has been used as an aid to maintenance for some considerable time. The cost effectiveness of the use of condition monitoring has been well established for continuous running and critical plant. However, the effectiveness of using condition monitoring has not been investigated for situations in which these techniques are utilised in conjunction with smaller, non-continuously operating plant. The principal purpose of the present investigation was to establish a methodology for determining the cost effectiveness of implementing any condition monitoring methodology prior to the purchase of the necessary instrumentation and to allow rational decisions to be made. In order to achieve this aim, the financial and other data that has been used to derive the method has been acquired from the Glaxo Wellcome primary manufacturing facility at Ulverston in Cumbria. The formulae used in the derivation of the decision making process have been established by statistical analyses of the data collected at the plant. In total, 83 pumps, 88 fans and 88 gearboxes were subjected to detailed survey to generate the data which was derived the model. The data has been separately analysed for each machinery class within the plant but in order to be able to analyse plants which comprise of a number of individual machines of different machinery classes, a logical derivation of the cost saving per machine is developed. In order to be readily usable by plant engineers or others without a detailed understanding of the concepts involved, the model has been programmed onto a MS Exel© spreadsheet. It has been set up such that when parameters and other data are entered the decision is given in "Yes/No" terms. The intermediate steps in the decision tree logic can also be accessed, as required. A series of sensitivity tests were also undertaken to be able to quantify the influence of the different variables on the outcome. These results are also recorded as part of this thesis. An initial assessment of the transferability of this method to other industries is also presented and discussed.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available