A Model for Assessing the Widening of the Predictive Maintenance Strategy

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Author(s): 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
Source title: Advanced Models and Tools for Effective Decision Making Under Uncertainty and Risk Contexts
Source Author(s)/Editor(s): Vicente González-Prida (University of Seville, Spain & National University of Distance Education, Spain)and María Carmen Carnero (University of Castilla-La Mancha, Spain)
DOI: 10.4018/978-1-7998-3246-1.ch008

Keywords: Business & Management / Business and Organizational Research / Business Science Reference / Risk Management & Analysis

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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.

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A Model for Assessing the Widening of the Predictive Maintenance Strategy

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