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Abstract. This research has an objective to create the new indicator for evaluating the performance and efficiency of the machine. This indicator is built as purpose to solve the problems that occurred in Overall Equipment Effectiveness (OEE) indicator. OEE is the main indicator of TPM, which focuses on machine maintenance. This indicator emphasizes how to find loss in the machine with no consideration of production cost. As considering the priority between the machine without regarding the machine capacity, production cost and value of the products, it could cause the improper priority to the machine. Therefore, the researcher has built a new indicator and also implemented with fibre cement manufacturing company. In the case study that the machine had been implemented, the result represented that the machine which had the highest OEE at 76.7%, was not the machine that had the lowest production cost loss value. The machine's overall production loss value costs 25.01 million baht. The machine that has even the least production loss value costs 2.28 million baht has the OEE only 71.7%. This OEE is the lowest in all of machines. The data represents that the OEE cannot sequence the problems appropriately because of the differences of the machines, including production capacity, production cost and the value of the products. These all differences will directly affect to the production loss value of each machine. Consequently, the new indicator in this research has been built to solve these OEE problems. This indicator can sequence the problems of each machine by calculating the production loss and represents the results as the monetary unit.

With a steep increase of the global disaster relief efforts around the world, the relief supply chain and humanitarian logistics play an important role to address this issue. A broad overview of operations research ranges from a principle or conceptual framework to analytical methodology and case study applied in this field. In this paper, we provide an overview of this challenging research area with emphasis on the corresponding optimization problems. The scope of this study begins with classification by the stage of the disaster lifecycle system. The characteristics of each optimization problem for the disaster supply chain are considered in detail as well as the logistics features. We found that the papers related to disaster relief can be grouped in three aspects in terms of logistics attributes: facility location, distribution model, and inventory model. Furthermore, the literature also analyzes objectives and solution algorithms proposed in each optimization model in order to discover insights, research gaps and findings. Finally, we offer future research directions based on our findings from the investigation of literature review.

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