Simulation Of Preventive And Corrective Maintenance Schedule In Reducing Machine Stoppage And Downtime - Tan, Sze Ming (Universiti Sains Malaysia, 2017)
Maintenance approaches or strategies has been studied since many decades ago and nowadays it varies from the complex mathematical approach to improved and simplified yet effective time-based strategies. However, simulation of maintenance strategies is an intermittent field of research thus current maintenance strategies simulation model created a benchmark to imitate the methodology of implement maintenance strategies in real production. Currently, the major drawback of most of the published researchers is in the application of only single machine, single maintenance strategies or multiple machines of the same type working in parallel which does not reflect the real and complex manufacturing system. Thus, this project is conducted to create a model of maintenance strategies integrated with a dynamic manufacturing system. The system consists of five different machines and each cycle time of machines differ considering the shift time of maintenance team and spare part availability. The work has been conducted using WITNESS 14 Manufacturing Performance Edition software. The model was developed to imitate a Surface Mounted Technology (SMT) production system by considering the changeover time, minor and major breakdown, corrective maintenance (CM) as well as preventive maintenance (PM) scheduling. The aim is to study the effect of maintenance strategies towards the machine downtime. The SMT line was simulated and evaluated based on the availability of individual machines via discrete event simulation system. Presuming that each machine has different degradation level, which follows a Weibull distribution, the maintenance scheduling strategies were planned based on First Come First Serve (FCFS) basis if the same type of maintenance strategies is due on different machines but prior to CM. The findings of this project demonstrated that a daily PM schedule can improve the system availability by 30% while increasing the availability of machine up to 90%.