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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/11255

Title: Simulation of industrial support systems in the context of functional products
Authors: Kyosti, Petter
Reed, Sean
Lofstrand, Magnus
Andrews, J.D.
Karlsson, Lennart
Dunnett, Sarah J.
Issue Date: 2011
Publisher: Loughborough University
Citation: KYOSTI, P., REED, S., LOFSTRAND, M. ... et al, 2011. Simulation of industrial support systems in the context of functional products. IN: Prescott, D.R. and Remenyte-Prescott, R. (ed.). Proceedings of the 19th AR2TS, Advances in Risk and Reliability Technology Symposium, 12-14 April 2011, Stratford-upon-Avon, UK, pp.275-288.
Abstract: Functional Products, consisting of hardware and service support systems owned by the supplier, are sold to customers with a guaranteed availability of the function. The availability achieved is dependent on the reliability of both hardware and the service support system. The reliability of the latter can be defined as its ability to provide the required maintenance services in a timely manner. This paper reports simulation of a service support system from an industrial case study in order to predict its reliability. To identify and develop a suitable case together with an industrial partner company, a number of phone meetings were held in order to explain the research question, interview knowledgeable people and plan on-site visits and interviews. A number of interviews face to face were carried out with the industrial partners, where the goal was to obtain enough information to be able to model the support system correctly. The research involved both qualitative information gathering and applied computer aided simulation. An improved model for simulating a service support system is developed that considers the context in which the maintenance procedures are performed within a Functional Product. A software implementation of the model, developed by the authors, is applied to simulate the case study service support system in various scenarios such as different personnel availability and number of systems supported. The results show how the modeling can be used to improve and predict the reliability of the service support system.
Description: This is a conference paper.
Version: Accepted for publication
URI: https://dspace.lboro.ac.uk/2134/11255
Appears in Collections:Conference Papers and Presentations (Aeronautical and Automotive Engineering)

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