Fukushima-Daiichi Accident has been analyzed from the viewpoint of good practice that is from resilience engineering viewpoint. The good cases of resilience response are observed in individual base and organizational base as below: The effectiveness of insight on accident cases (inundation in Madras, 9.11 terrorism and B.5.b. order for the countermeasures) and of the risk evaluation, Decision of continuation of sea water infusion (individual base), Reflection of the experience on Chuetsu-Oki Earthquake, Improvement of seismic building which is equipped emergency power source system and air conditioning system (organizational base), Deployment of fire engines (organizational base), The effectiveness of command system in ordinary time (on-site of organizational base), and Support by cooperation companies and manufacturers (designers and site workers of organizational base). It is important to ‘establish the feedback system on organization learning in ordinary time’, that is to establish the system admitting violation of order. The decision at on-site are given priority than other ones. The representative example is the decision of sea water infusion continuation which was given priority at on-site, even though the official residence and the main office of Tokyo Electric Power Company had ordered to stop the infusion. As successful (good practice) cases, ten comprehensive lessons were extracted by analyzing the seven incidents, such as Return of the Asteroid Explorer “Hayabusa”, US Airways 1549 Emergency Landing on Hudson River, Apollo 13 Survival, and four organizational accidents. When ten kinds of lessons are overlooked, we understood the timing of utilization of the lessons is different, so it is classified into three categories; Pre-Correspondence, Emergency Response, and Post-Correspondence.
CITATION STYLE
Ujita, H., & Sakuda, H. (2019). Analyses of Fukushima-Daiichi Accident and Other Seven Cases from Good Practice Viewpoint. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11569 LNCS, pp. 624–637). Springer Verlag. https://doi.org/10.1007/978-3-030-22660-2_46
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