Two-dimensional fuzzy fault tree analysis for chlorine release from a chlor-alkali industry using expert elicitation

The hazards associated with major accident hazard (MAN) industries are fire, explosion and toxic gas releases. Of these, toxic gas release is the worst as it has the potential to cause extensive fatalities. Qualitative and quantitative hazard analyses are essential for the identification and quantification of these hazards related to chemical industries. Fault tree analysis (FTA) is an established technique in hazard identification. This technique has the advantage of being both qualitative and quantitative, if the probabilities and frequencies of the basic events are known. This paper outlines the estimation of the probability of release of chlorine from storage and filling facility of chlor-alkali industry using FTA. An attempt has also been made to arrive at the probability of chlorine release using expert elicitation and proven fuzzy logic technique for Indian conditions. Sensitivity analysis has been done to evaluate the percentage contribution of each basic event that could lead to chlorine release. Two-dimensional fuzzy fault tree analysis (TDFFTA) has been proposed for balancing the hesitation factor involved in expert elicitation. (C) 2010 Elsevier B.V. All rights reserved.

Competing for the Recreational Dollar: An Analysis of the California Commercial Passenger-Carrying Fishing Vessel Industry

California has a large and diverse marine recreational fishery. Anglers on commercial passenger-carrying fishing vessels (CPFV's) harvest a substantial proportion of California's marine recreational fisheries landings, accounting for about 40 percent and 16 percent of the total 1986 marine recreational catch in southern and northern California, respectively (NMFS, 1987). In 1986, 459,369 CPFV anglers landed some 2,835,021 fish in southern California, while 200,925 CPFV anglers landed 1,240, 100 fish in central and northern California.

Value chain analysis of the Egyptian aquaculture feed industry

The commercial aquaculture feed industry in Egypt is growing at a rapid rate. As a result, the number of fish feed mills has increased from just 5 mills producing about 20,000 t per year in 1999, to over 60 mills with a current production estimate of 800,000–1,000,000 t/year. The performance of the aquafeed industry in Egypt is not well understood, as the value chain structure has not yet been mapped. This study aims to assess the status of the fish feed sector in Egypt, with an emphasis on: mapping and understanding fish feed value chains, describing the main actors and stakeholders within the chain, assessing value chain performance, identifying major strengths and weakness of the sector, and suggesting appropriate actions, management and development strategies.

Wear analysis and prediction of the life of a riveting die used in the automotive industry

Knowledge on the life span of the riveting dies used in the automotive industry is sparse. It is often the case that only when faulty products are produced are workers aware that their tool needs to be changed. This is of course costly both in terms of time and money. Responding to this challenge, this paper proposes a methodology which integrates wear and stress analysis to quantify the life of a riveting die. Experiments are carried out to measure the applied load required to split a rivet. The obtained results (i.e. force curves) are used to validate the wear mechanisms of the die observed using scanning electron microscopy. Sliding, impact, and adhesive wears are observed on the riveting die after a certain number of riveting cycles. The stress distribution on the die during riveting is simulated using a finite element (FE) approach. In order to confirm the accuracy of the FE model, the experimental force results are compared with the ones produced from FE simulation. The maximum and minimum von Mises' stresses generated from the FE model are input into a Goodman diagram and an S-N curve to compute the life of the riveting die. It is found that the riveting die is predicted to run for 4 980 000 cycles before failure.