quantitative safety and health assessment based on fuzzy inference and ahp at preliminary design stage

quantitative assessment is the most important means to identify hazard potential and manage risk for an industrial process. the implement of quantitative assessment in the early stage will help to develop inherently safer process, eliminating the hazard and reduce the possibility of accidental chain events and the magnitude of consequences. in this paper, after reviewing the presently available assessment method, we present the disadvantages of current technology in several aspects. focusing on the main disadvantage of subjectivity in two aspects of index valuing and weighting, which is a serious barrier to measure the real level of process safety, we propose a quantitative assessment method integrated fuzzy inference and analytic hierarchy process(ahp) to quantify safety and health hazards of chemical process route in preliminary design stage. the purpose of integrating fuzzy inference into it is to reduce the subjectivity of index valuing system. the fuzzy inference system is designed without medium variable in order to eliminate its negative effect on assessment result. index weighting is determined by ahp more objectively based on the ordering of inherent safety guidewords. finally, the proposed method is applied to assessment nine competing routes of acetic acid manufacture to present its improvement.