الفهرس 
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Abstract
The most important goal for all manufacturing company is to increase the productivity, which reflects to get better production line efficiency. There are many methods exist by which productivity could be analyzed and improved. Simulation software such allows users to monitor and identify the problems faced and hence improve the productivity of the company. Also identify major causes of production ineffciencies, how to develop and implement effective and efficient improvement plan along the production line; which not only reduces sudden sporadic failures in work shop, but also reduces the different losses during operation.Through the measure in terms of overall line effectiveness(OLE)index, the hidden problems would be exposed and resultant countermeasures can be executed based on continuous improvement framework and practices.
Overall line Effectiveness (OLE) used to measure productivity of production line. it is a powerful metric of manufacturing performance incorporating measures of the availability, performance efficiency, and quality of a given processes along the manufacturing line. when associated with the reason for six big losses(breakdown, setup,idle time,reduced speed time loss, reject on startup,production reject),OLE provides the means to compare and prioritize improvement efforts. The overall line effectiveness metric implement on production line, to be a clear measure on production improvements, also to find out what OLE dose and dose not tell the company. Another thing was to learn how to implement improvements to the processes studied. The main task of this work is developing a computer program to monitor production system and identify the line bottleneck on OLE metric.
The methodology depends on developing the overall line effectiveness (OLE) metrics, to be more accurate and suitable for implementing on a production line that all involving number of machines arranged in series and parallel.Also this methodology deal with each machine in the production line with its actual performance, therefore the appropriate loss and cause information is needed.
The proposed methodology was applied to a case study. Results show that major losses are closely related to frequency of changeovers in machining process, where the overall line efectiveness (OLE) metric were 46.84% areas of weakness were identified in the different processes along the production line in which the potential for improvement is embedded.