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What is Lubricant Analysis

Advanced Models and Tools for Effective Decision Making Under Uncertainty and Risk Contexts
A diagnostic technique of a Predictive Maintenance strategy involving the monitoring of a number of physical and chemical parameters of the lubricant used, to obtain information about the state of the machine and diagnose a possible failure.
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)
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.
Full Text Chapter Download: US $37.50 Add to Cart
More Results
Decision Making in the Choice of Condition-Based Maintenance Techniques in a Subsidiary of a Petrochemical Company
Is a condition-based maintenance technique, which brings together a set of techniques for the monitoring of the physical-chemical of the lubricant. These techniques allow the state of the lubricant and the presence of contamination and wear in the machinery to be diagnosed.
Full Text Chapter Download: US $37.50 Add to Cart
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