Development and verification of predictive maintenance system in a solar cell manufacturing industry

Manufacturing industries need to find the best preventive maintenance strategy during their planning and scheduling. When a machine is taken down for maintenance, it does not produce a product for the company which means production is interrupted thus incurring loss to the company. Therefore, downtime for services needs to be minimized. Preventive Maintenance is a service being done by qualified personnel to ensure that the equipment is always in a good and safe operating condition. Preventive Maintenance is a set of activities taken based on a planned schedule either by time or a condition to prevent permanent or lengthy breakdowns. Example of a Preventive Maintenance are like changing lead screw bearing every year or servicing filter at every 50,000 running hours. Usually preventive maintenance is scheduled based on equipment vendor’s recommendation. Through experience running the equipment, engineers will be knowledgeable to adjust their schedule based on the nearest actual lifetime which is based on the history or record. Solar Cell manufacturing is facing high unscheduled downtime. The aim of this project was to develop a Predictive Maintenance System in a solar cell manufacturing environment. A Predictive Maintenance System in a solar cell manufacturing industry should reduce its equipment unscheduled downtime because not all types of problems can be prevented by using a scheduled maintenance alone. The machine operation involves process parameters and human interventions. Thus the preventive actions need to be taken before its breakdown. Nevertheless, having a scheduled preventive maintenance is the least a management should implement to reduce the machine breakdown if there is no form of other solution. This research had proposed to use a Continuous Improvement Program method by Vannest and Wassenhove which was developed in 1995 which aims to reduce downtime. This research then, had proposed a streamline and comprehensive tools for this continuous improvement program which are the use of Pareto Analysis and FMEA before starting any improvement activity. This research had also developed an improvised diagnostic method of Predictive Maintenance System that was from Groba et al. in year 2007. The Predictive Maintenance System that was developed from this research had used diagnostic method through use of failure limit(s) and its threshold limit(s). This Predictive Maintenance System was then developed and tested in one of solar cell manufacturing company in Peninsular Malaysia which had just operated in less than 5 years. It was verified that this Predictive Maintenance System had cause a reduction of unscheduled downtime of more than 23% for Deposition and Diffusion equipments in one Solar Cell manufacturing company. This research had successfully developed a streamline and comprehensive tools for Continuous Improvement Program which integrates with Predictive Maintenance System using threshold Limit(s) and failure Limit(s).

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