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All Journal Teknosains : Jurnal Sains,Teknologi dan Informatika
Rosi Herlianti
Universitas Mercu Buana
Agriculture, Biological Sciences & Forestry Automotive Engineering Computer Science & IT

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Implementation of predictive maintenance in various Industry: A Review Tito Lukito; Rosi Herlianti; Malinda Mayanti; Lien Herliani Kusumah
TEKNOSAINS : Jurnal Sains, Teknologi dan Informatika Vol 12 No 1 (2025): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika (On Progress)
Publisher : LPPMPK-Sekolah Tinggi Teknologi Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/tekno.v12i1.1338

Abstract

Predictive maintenance has become a crucial approach in the manufacturing industry, offering solutions to minimize downtime, optimize maintenance costs, and enhance operational efficiency. This paper reviews the definition, objectives, benefits, and implementation of predictive maintenance in the manufacturing sector. By leveraging advanced technologies such as the Internet of Things (IoT), machine learning, big data analytics, and cloud computing, predictive maintenance enables real-time monitoring of equipment conditions and failure prediction before they occur. The objectives are to reduce operational costs, increase equipment reliability, and optimize production performance. The benefits include reduced frequency and duration of downtime, lower repair costs, extended equipment lifespan, and improved workplace safety. Case studies discussed show that companies adopting this technology experience increased production efficiency and reduced maintenance costs. The conclusion of this paper suggests that companies invest in technology and infrastructure, develop employee skills, integrate systems, collaborate with technology providers, and conduct continuous monitoring and evaluation. With these steps, companies can more effectively implement predictive maintenance and achieve competitive advantages in an increasingly dynamic market
Co-Authors Lien Herliani Kusumah Malinda Mayanti Tito Lukito