Blue Eyes Intelligence Engineering & Sciences Publication (BEIESP)
Abstract
The intention of elimination of losses is to improve the efficiency and effectiveness of the production and reduce the unnecessary expenses. OEE is a performance metric of the machine or process and it provides information to the user to monitor and understand the actual situation of the machine compared to the ideal situation of the machine. Although six big losses are defined in the OEE, but it is still not clearly shows the scope of improvements in availability. Most of the time, users are more focus on the breakdown rather than setup process due to breakdown losses have greater impact on the OEE percentage. Therefore, excessive setup time or changeover time is hidden in the OEE. Furthermore, the frequency of the setup process and ideal setup time is not clearly stated in the OEE. The objective of this study is to visualize the availability losses by improve the classification of availability losses. The new classification of losses is examined by real data and it showed better visualization than traditional classification of losses. It is necessary to quantify these losses with modified OEE to visualize the losses in a better way
