Please use this identifier to cite or link to this item: https://hdl.handle.net/10316.2/33327
Title: Maintenance strategies to reduce downtime due to machine positional errors
Authors: Shagluf, Abubaker
Longstaff, A. P.
Fletcher, S.
Keywords: maintenance strategies;down time;OEE;TPM;decision making;predictive calibration
Issue Date: 2014
Publisher: Imprensa da Universidade de Coimbra
Faculdade de Ciências e Tecnologia da Universidade de Coimbra, Departamento de Engenharia Mecânica
Journal: Colecao:http://hdl.handle.net/10316.2/33309
Abstract: Manufacturing strives to reduce waste and increase Overall Equipment Effectiveness (OEE). When managing machine tool maintenance a manufacturer must apply an appropriate decision technique in order to reveal hidden costs associated with production losses, reduce equipment downtime competently and similarly identify the machines’ performance. Total productive maintenance (TPM) is a maintenance program that involves concepts for maintaining plant and equipment effectively. OEE is a powerful metric of manufacturing performance incorporating measures of the utilisation, yield and efficiency of a given process, machine or manufacturing line. It supports TPM initiatives by accurately tracking progress towards achieving “perfect production.” This paper presents a review of maintenance management methodologies and their application to positional error calibration decision-making. The purpose of this review is to evaluate the contribution of maintenance strategies, in particular TPM, towards improving manufacturing performance, and how they could be applied to reduce downtime due to inaccuracy of the machine. This is to find a balance between predictive calibration, on-machine checking and lost production due to inaccuracy. This work redefines the role of maintenance management techniques and develops a framework to support the process of implementing a predictive calibration program as a prime method to supporting the change of philosophy for machine tool calibration decision making.
URI: https://hdl.handle.net/10316.2/33327
ISBN: 978-972-8954-42-0 (PDF)
DOI: 10.14195/978-972-8954-42-0_16
Rights: open access
Appears in Collections:Proceedings of Maintenance Performance Measurement and Management (MPMM) Conference 2014

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