Optimization of Production Down Time in Innoson Plastic Manufacturing Company

Abstract

Optimization of production downtime in plastic manufacturing serves as a method to minimize machine downtime. This paper describes how to minimize machine downtime using multiple regression analysis in Statistical Package for Social Sciences (SPSS) and graphs was also used to predict the effective of downtime to cycle time, weight, production capacity, overall equipment effectiveness (OEE) and graphs were plotted accordingly. The Overall Equipment Effectiveness (OEE) of the company was also calculated. The study also investigated how maintenance practice constitutes downtime and how it can be reduced. Machine downtime is an effect time when machines are not productive. Although normal associated with manufacturing machines, the term can be used for any equipment usage. Minimizing equipment downtime in manufacturing operations provides a range of benefits leading to maximised efficiency and higher profits. Reducing downtime increases machine availability which in turn increases throughput. This allows more productivity either to meet outstanding orders when sales are buoyant or to reduce shifts or personnel costs when they are not. By optimising machine availability you can “tap the hidden factory” which can eliminate the need for capital expenditure on new machinery when it appears that full output capability has been reach. Minimising downtime also reduces order lead times and improves customer satisfaction. The reasons or causes for machine downtime can be many and varied and different from one machine to another. These can include problems with the actual machines such as breakdowns or jams but also due to other factors such as no machine operator being available, no materials, planned (or unplanned) maintenance. Others sometimes not directly recognized as causing downtime include staff breaks, planning and scheduling meetings, etc which if they cause a machine not to be running are a form of machine downtime. Accurate information is key to effective downtime management. It is crucial to have access to accurate and timely data to be able to understand the 2 extent of downtime and its causes. In some manufacturing operations this can be done manually by machine operators logging the duration and reasons for any downtime or stoppages. However this data is often inaccurate as the machine operator is understandably more focused on getting a machine running again once it has stopped than to diligently record the exact timing and reason. This method also incurs cost in terms of staff time collecting and processing the data and introduces a lag in the availability of the information to managers. To successfully minimise machine downtime all downtime must be recorded accurately and this can only be consistently achieved by an automated system that continuously collects data and processes it in real time so that it is available on demand for downtime analysis and reports. The use of automated system is particularly beneficial for continuous improvement programs where businesses are targeting ever increasing levels of efficiency (www.automation.com). The plastic industry is usually characterized by injection molding machine, extrusion machine, blow molding machines each one with their own unique method of taking raw plastic (sheet, pellets, and powders) adding heat and/or pressure to form a pre-defined shape. These machines, methods can be very complex plastic molds can be used on specific machine, adding a secondary constraint to the manufacturing process.