This is a stage of the lifecycle of a Predictive Maintenance strategy in which the amount of machinery to be controlled under the strategy, or its goals, is increased, once the period of return to investment is over. This stage could last 22 months or more, depending on the characteristics of the introduction, the machines chosen, and the business. The goals established for the PM strategy can thus be achieved some three years from the start of introduction.
Published in Chapter:
A Model for Assessing the Widening of the Predictive Maintenance Strategy
María Carmen Carnero (University of Castilla-La Mancha, Spain & University of Lisbon, Portugal) and Francisco Javier Cárcel-Carrasco (Universitat Politècnica de València, Spain)
Copyright: © 2021
|Pages: 23
DOI: 10.4018/978-1-7998-3246-1.ch008
Abstract
The essential aim of Industry 4.0 is to enable industries to be more productive, efficient, and flexible. A predictive maintenance strategy can make a positive contribution to all these things, as it uses industrial IoT technologies to monitor asset health, optimise maintenance schedules, provide real-time alerts about operational risks, and maximise uptime, and can provide digital services to customers based on data from its machines. It improves productivity, improves customer satisfaction, and therefore gives the company a competitive advantage. Nevertheless, decision making in relation to a predictive maintenance strategy is not systematised, and this may lead to some inappropriate decisions, which do not achieve the goal sought. This chapter describes a multicriteria model, designed with the analytic hierarchy process, to systematise decision making with respect to a predictive maintenance strategy.