Improving the overall equipment effectiveness of automated machines in volume driven manufacturing

Abstract

The study outlines the framework concerning Overall Equipment Effectiveness (OEE) using Total Productive Maintenance in the Lubrichem automated volume driven machinery. This research has been carried out using the data obtained from electronic system called RS-production of October 2016 to March 2017 at Lubrichem Company. The data were obtained through a tool for Overall Equipment Effectiveness called RS-production. The tool system (RS-production) data was from four sections or department of Lubrichem Company (Automated volume driven machines, Automated maintenance workshop, Automated blending machines and Semi-automated machines) sections. A conceptual framework was designed to determine the effect of OEE on Lubrichem automated volume driven machinery and subsequently measures availability, performance and quality losses in a system or machines. The research survey was based on the sample of four divisions of Lubrichem industry (Automated volume driven machineries, Maintenance workshop, Automated blending machines and Semi-automated machines), including analysing the outcome of the research using excel. The objective of the thesis was to identify OEE losses, downtime sources and possible improvement. The availability losses and planning factor were the highest in all four divisions. To get rid of unplanned losses, root cause analysis was performed to lower prolonging of planned change overs and setups that require Single Minutes Exchange of Dies for external (SMED) and internal events. There is a frailty relationship of the unplanned equipment losses which were grouped into unplanned production breakdowns. The losses which were recorded were identified, analysed and split into two to provide potential solutions. Some of the losses were stated as 'no reason' because production teams did not furnish the data or information. This requires awareness, training and educating of production personnel who operate the machines.