Optimizing convexity defect in a tile industry using fuzzy goal programming

In most designed experiments, the main focus is to find the factor settings that optimize a quality response regardless of engineer's preferences about factor settings. Further, in tiles industry convexity defects result in huge quality costs as well as production losses. This research, therefore, aims at optimizing convexity defect while considering process engineers' preferences using fuzzy goal programming (FGP). Three two-level key process factors are considered, including below-rollers temperature, above-rollers temperature, direct blow air. Experiments are conducted with two repetitions; in each the convexity is measured on four tiles. Two optimization techniques are employed to determine the combination of optimal factor settings, including the Taguchi method and latter technique. The Taguchi approach and FGP approach provide relative improvements of 61.2% and 41.2%, respectively. Although the former technique reduces convexity larger than latter approach, it failed to satisfy the preferences on the settings of process factors. In contrast, the optimal factor settings obtained using FGP completely satisfy engineers' preferences. In conclusion, FGP successfully optimizes process performance and completely satisfies process engineers' preferences in tiles industry.