Implementation of predictive maintenance in various Industry: A Review

  • Tito Lukito Universitas Mercu Buana, Indonesia
  • Rosi Herlianti Universitas Mercu Buana
  • Malinda Mayanti Universitas Mercu Buana
  • Lien Herliani Kusumah Universitas Mercu Buana
Keywords: Predictive maintenance, Manufacturing Industry, Internet of Things

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

Author Biographies

Rosi Herlianti, Universitas Mercu Buana

Teknik Industri

Malinda Mayanti, Universitas Mercu Buana

Teknik Industri

Lien Herliani Kusumah, Universitas Mercu Buana

Teknik Industri

Published
2025-01-31
How to Cite
Tito Lukito, Rosi Herlianti, Malinda Mayanti, & Lien Herliani Kusumah. (2025). Implementation of predictive maintenance in various Industry: A Review. TEKNOSAINS : Jurnal Sains, Teknologi Dan Informatika, 12(1), 133-144. https://doi.org/10.37373/tekno.v12i1.1338