A Fuzzy Linear Programming for Improvement of Accident Investigation in Industrial Processes

Accident models and analysis its methods involves how an accident happens and organizing which causal factors helps the accident and which recommendations are issued. Industries such as air traffic control, nuclear power plants, space missions, chemical and petroleum industry, healthcare and patient safety is leading to potentially disastrous failure modes and new kinds of safety issues as well. These industries are facing with numerous models developed for accident investigation; however, little effort has been devoted in order to develop methodology in accident investigation. The main purpose of this study is to develop a model for screening and ranking of the appropriate accident investigation models in different application fields. So first of all the appropriate factors describing advantages and disadvantages of the accident models are determined through a literature review. After that some of accident investigations that uses more in industries listed to rank with the most important criterion of industries and accident investigation models. Then a fuzzy data envelopment analysis (FDEA) is presented to find the most appropriate accident model according to its pros and cons. The application of the proposed model is illustrated through subjective analysis of accident models accessible in nuclear power, aviation, and chemical industries.

Keywords:

Accident Investigation , Fuzzy DEA , Industries , Safety system