INTEGRASI DAN PENGEMBANGAN SISTEM MACHINE LEARNING PADA KEGIATAN MAINTENANCE UNIT BGMF PT. FI - Rio Viryawan; Arif Suroso; Rokhani Hasbullah (School of Business, Bogor Agricultural University (SB-IPB), 2021)
The Big Gossan Mill Facility (BGMF) unit has a vital function to deliver tailing supporting Big Gossan underground mining. Plant maintenance strategies have been implemented to support its availability. This study aims to study integration of machine learning model into the plant maintenance and to formulate development of Machine Learning System in BGMF unit. The maintenance planning standards is used to integrate Machine Learning model through interview. The Industrial Internet Reference Architecture (IIRA) is applied to develop machine learning system. It uses interview method to formulate business viewpoint and usage viewpoint and observation to elaborate functional viewpoint and implementation viewpoint. The study results integration of machine learning model is done by state it as PD-200 Propelling Liquid alarm. It then should be followed up by the planning crew. The machine learning system development starts with formulation of Key Objectives and Fundamental Capabilities on the business viewpoint. The usage viewpoint defines two scenarios on machine learning system. The functional viewpoint elaborates system functionality. The implementation viewpoint designed network topology. It then emphasizes on key system characteristics. This research concludes that model integration into plant maintenance can minimize PD-200’s downtime and it’s system design can be done by IIRA. Keywords: IIRA, machine learning, maintenance improvement, predictive maintenance, predictive model