In the manufacturing company, an efficient production floor affects the productivity of the company. Thus, a well design production floor layout assists the company to achieve its objectives. In this regard, this study aims to design a new alternative production floor layout for the XYZ manufacturing company. The company facing the facility layout problem (FLP) where their workstation on the production floor was not located based on the activity-relationship. Thus, the company struggles to reduce the distance travel of their workers from one station to another by re-layout their production floor. The Systematic Layout Planning (SLP) method was used to determine the best new alternative layout for the company. Subsequently, the AnyLogic simulation software was utilized to test the effectiveness of the layout by using the number of steps as the parameter. As a result, it is found that the total number of steps of workers in the production floor can be reduced from 16,554 steps (in existing layout) to 15,956 steps (in new alternative layout).

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Multilayer Perceptron Network (MLP) has a better prediction performance compared to other networks since the structure of the MLP is suitable for training processes in solving prediction problems. However, to the best of our knowledge, there is no rule of thumb in determining the number of hidden nodes within the MLP structure. Researchers normally test with various numbers of hidden nodes to obtain the lowest square error value for optimal prediction results since none of the approaches has yet to be claimed as the best practice. Thus, the aim of this study is to determine the best MLP network by varying the number of hidden nodes of developed networks to predict cycle time for producing a new audio product on a production line. The networks were trained and validated through 100 sets of production lots from a selected audio manufacturer. As a result, the 3-2-1 MLP network was the best network based on the lowest square error value compared to the 3-1-1 and 3-3-1 networks. The 3-2-1 predicted the best cycle time of 5 seconds to produce a new audio product. Hence, the prediction result could facilitate production planners in managing assembly processes on the production line.

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