Evaluation of manufacturing process in low variety high volume industry with the coupling of cloud model theory and TOPSIS approach

Abstract

Abstract Failure Mode and Effect Analysis (FMEA) is one of the most commonly used techniques for identifying and minimizing potential failures in various products and process designs. The traditional FMEA approach has limitations due to generic rating scales and experts' number-based assessments, which might not produce the desired results. The current research uses a hybrid approach of coupling Cloud Model Theory (CMT) with hierarchical Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to deal with uncertainty, including randomness and fuzziness in the identification of risks and failures in a cigarette manufacturing industry. The results show that this hybrid approach is more effective in classifying failures in the production process. The findings reveal that out of the three fundamental units of cigarette manufacturing machinery, most of the failures affecting the production of the cigarette manufacturing process belong to MAX, which supports filtration and inspection of filtered cigarettes. The study identifies salient problem areas that the managers must give special attention to enhance the production process's efficiency. The significance of the study lies in the identification of failure modes with rank order which the managers will find quite valuable for finally achieving the desired level of customer satisfaction and production efficiency.