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The purpose of this paper is to investigate the feasibility of using recycled glass sand as filler for epoxy mortar floor intermediate coating. Four physical properties and 10 chemical reagents are studied. The particle size of recycled glass sand and the type of hardening agent are two important factors that may influence these physical properties and chemical reagents. Thus, an L9 orthogonal array is used for the experiments. The optimum factor level combination is found by minimizing the total quality loses of these physical properties and chemical reagents. The results show that the optimum factor level combination meets all the specifications of these physical properties and chemical reagents. Thus, recycled glass sand can be reused as filler for epoxy mortar floor intermediate coating. Therefore, the goal of saving energy, reducing carbon consumption and producing green building material can be achieved.

In some flexible manufacturing systems, group technology principles divide parts naturally into groups so that substantial set-ups occur only when switching production between groups. We discuss the scheduling of one such real-life manufacturing process. We develop a practical heuristic for the economic lot scheduling problem in this group technology environment. The heuristic is relativelysimple,yet performs well. An example is solved in detail. Acomputational study verifies the heuristic's capabilities and suggests extensions for improvement.

In Taguchi's parameter design, the significant parameter levels are found by maximising the signal-to-noise ratio of the quality characteristic. In the analysis of variance (ANOVA) of signal-to-noise ratio, the combination of column effects to better estimate error variance is referred to as pooling. Taguchi has suggested the strategy of pooling up. When using the pooling-up strategy, there will be a tendency to make the alpha mistake more often. In this paper, it is assumed that (1) the quality chartacteristic is normally distributed and (2) the mean and standard deviation of each factor level combination are equal, then the null hypothesis should be no significant factor. Thus, the alpha risk is that some factors are misidentified as significant factors. The purpose of this paper is to investigate the alpha risk of the Taguchi method for the-larger-the-better (LTB) type problem with orthogonal array, L 8 , by simulation. The results show that the alpha risk is very high.