Application of Fault Tree Analysis (FTA) in Developing Predictive Maintenance Strategies for Computer Base Interlocking (CBI) System in PT LRTJ

다국어 초록 (Multilingual Abstract)

his study aims to build Predictive Maintenance (PdM) by analyzing the causes of Computer Base Interlocking (CBI) system disruptions in PT Light Rail Transit Jakarta (LRTJ) Company using Fault Trees Analysis (FTA).

목차 (Table of Contents)

• TABLE OF CONTENTS
• CHAPTER 1 1
• 1.1. Background of LRT Jakarta 1
• 1.2. Problem Formulation 4
• 1.3. Research Objectives 5
• 1.4. Scope of Research 5
• 1.4.1 Research Objective 5
• 1.4.3 Geographical Limitations 6
• 1.4.4 Data Used 6
• CHAPTER 2 7
• 2.1 Theoretical Studies 7
• 2.1.1 Predictive Maintenance (PdM) 13
• 2.1.2 Fault Tree Analysis (FTA) 20
• 2.2 Theoretical Framework 26
• 2.2.1 Application of Fault Tree Analysis (FTA) 29
• 2.2.2 Application of Predictive Maintenance (PdM) 30
• 2.2.3 Stochastic and Probability Theory 30
• CHAPTER 3 32
• 3.1 Research Design 32
• 3.2 Research Location and Time 32
• 3.3 Data Collection Techniques 34
• 3.4 Research Variables 35
• 3.5 Data Analysis Techniques 36
• CHAPTER 4 38
• 4.1 Overview of CBI LRT Jakarta 38
• 4.2 FTA analysis process 40
• 4.2.1 Fault Tree Analysis (FTA) of CBI System 40
• 4.2.2 Minimum Cut-set (MCS) Analysis of CBI System 41
• 4.3 Stochastic analysis process 43
• 4.3.1 Probability Classification of CBI System 43
• 4.3.2 Failure Probability Analysis of the CBI System 46
• 4.3.3 Exponential Failure Probability Chart of CBI System 52
• CHAPTER 5 54
• 5.1 Summary of Findings 54
• 5.2 Suggestion 55
• CHAPTER 6 57
• 6.1 Implications for the Maintenance System at PT LRT Jakarta 57
• 6.2 Implications for the Development of Predictive Maintenance Strategies 58
• 6.2.1 Risk Classification Based on FTA Variables 59
• 6.2.2 Integration with Digital Monitoring Systems 59
• 6.2.3 Dynamic Maintenance Scheduling 59
• 6.2.4 Development of a Knowledge Repository and SOPs 59
• 6.3 Academic Implications and Future Research Opportunities 60