Analisa Produktivitas Sistem Perawatan Mesin Penggiling Kedelai Menggunakan Metode Overall Equipment Effectiveness (OEE) Dan Failure Mode And Effects Analysis (FMEA) Dengan Pendekatan CMMS Di CV. Tahu Bandung NN

Atikah; Tiara; Surya Perdana; Sri Hartini; Siska Wahyuningsih

Authors

Atikah Universitas Indraprata PGRI
Tiara Universitas Indraprata PGRI
Surya Perdana Universitas Indraprata PGRI
Sri Hartini Universitas Indraprata PGRI
Siska Wahyuningsih Universitas Indraprata PGRI

Keywords:

CMMS, Failure Mode and Effect Analysis, Overall Equipment Effectiveness, Perawatan, Six Big Losses

Abstract

Machine maintenance is important to maintain smooth production, because a decrease in the condition and productivity of the machine can disrupt the production process. CV Tahu Bandung NN is a company that produces Bandung tofu and is located at Jl. Aridho, Jatimulya Village, Cilodong District, Depok City, West Java 16413. This study aims to determine the OEE value, the types of losses that most affect the machine, identify major failures, and compile an effective machine maintenance schedule to increase productivity. The methods used in this study are Overall Equipment Effectiveness (OEE), Six Big Losses, and Failure Mode and Effect Analysis (FMEA). The OEE method is used to measure machine effectiveness. Six Big Losses identifies six major losses that reduce machine performance, while the FMEA method analyzes potential component failures and determines the priority of handling them based on the level of risk. The results showed that the average value of the Overall Equipment Effectiveness (OEE) of the soybean grinding machine in November 2024 was 68.34%, still below the JIPM standard ≥85%, which indicates that the machine's effectiveness is not optimal. Six Big Losses analysis shows that the losses that most affect machine performance are Reduced Speed Losses (35.60%) and Breakdown Losses (5.68%). The results of the analysis using the Failure Mode and Effect Analysis (FMEA) method show that the drive motor component has the highest RPN value of 252, making it a top priority in maintenance. The preparation of machine maintenance schedules can be done effectively using CalemEAM CMMS software.

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