FMEA-CM based quantitative risk assessment for process industries—A case study of coal-to-methanol plant in China

Abstract

Coal-to-methanol enterprises in China face many risk factors that pose a serious threat to the safety of the company's production. Therefore, it is imperative to conduct risk assessments of coal-to-methanol plants. A failure mode and effects analysis (FMEA) is a significant analysis method in risk evaluation. However, due to the uncertainty in the risk analysis process, the assessment results may not be sufficiently accurate. To reduce the uncertainty, especially randomness and fuzziness in the evaluation process, a cloud model (CM) is utilized to improve the FMEA, and the FMEA-CM approach is proposed. First, the qualitative language terms are converted into the quantitative numerical characteristics of the cloud model, enabling the fuzziness and randomness in the evaluation process to be comprehensively considered. Second, the cloud weights of S, O and D are calculated by using the interval analytic hierarchy process (IAHP) and the CM. Moreover, the cloud risk priority number (CRPN) is put forward to improve the accuracy of the traditional RPN, and the CRPN algorithm is given. Finally, to rank risk events, the technique for order preference by similarity to an ideal solution (TOPSIS) method, improved by cloud distance based on Hamming distance, is put forward. A coal-to-methanol plant in Yinchuan, China, is introduced to demonstrate the applicability of the proposed FMEA-CM approach. Compared with the results obtained from the traditional FMEA and fuzzy TOPSIS method, the results obtained from the adoption of the FMEA-CM approach show that the FMEA-CM is a more accurate and effective method for the risk assessment of a coal-to-methanol plant.