Using industry 4.0 to face the challenges of predictive maintenance: A key performance indicators development in a cyber physical system. (September 2022)

• Record Type: Journal Article
• Authors: Pilar Lambán, María; Morella, Paula; Royo, Jesús; Carlos Sánchez, Juan
• Is Part Of: Computers & industrial engineering. Volume 171(2022)
• Publication Date: 2022-09
• Subjects: Cyber physical system -- Industry 4.0 -- Predictive maintenance -- Key performance indicators; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2022.108400
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: Our research implements a CPS based on 5 levels methodology. CPS processes data in real time and transform it into relevant information. Industry 4.0 contributes to the evolution and improvement of companies. Real time KPIs implementation improves productivity and reduces maintenance costs. A dashboard of maintenance and other KPIs allows multidisciplinary decision-making. Abstract: The fourth industrial revolution is transforming the industrial environment. This work focuses on the application of 4.0 technologies to solve the problems that predictive maintenance currently faces, e.g., performing maintenance only when necessary or processing data in real time to provide relevant information. Particularly, the implementation of a CPS is carried out in a machine tool capable of acquiring data in real time. At the same time, a series of maintenance indicators have been defined, developed, and implemented that provide the user with relevant information on the status of the machine to enhance decision-making.