Risk, quantification

The. statement goes on to acknowledge the contribution of the Reactor Safety Study (WASH-1400) to risk quantification but points out that safety goals were not the study objectives and that the uncertainties make it unsuitable for such a purpose. After pointing out that the death I f any individual is not "acceptable," it states two quantitative objectives ... 

This type of classification has the advantage of offering a more suitable scale for risk quantification (this is precisely why it was chosen). It can be compared with a quantitative variabie. Besides, it takes into account four main factors of risk aggravation ... 

Sinclair, W.K. (1981). The scientific basis for risk quantification, page 3 in Quantitative Risk in Standards Setting, Proceedings of the Sixteenth Annual Meeting of the National (Council on Radiation Protection and Measurements, Proceedings No. 2 (National Council on Radiation Protection and Measurements, Bethesda, Maryland). 

The fundamental question of risk assessment for potential human carcinogens requires definition of substances that exceed an evidentiary threshold. Once the scientific evidence establishes a substantial basis for conclusion of known or potential human cancer, it is then in order to determine a procedure for risk quantification. Quantitative risk assessments must always be read with the qualitative evidence of the likelihood of carcinogenicity. 

Ultimately, research in the halogen cycles and the interface between natural and anthropogenic fluxes is directed towards risk quantification and reduction, through research questions such as Do environmental transformation reactions... 

Chemical Carcinogenesis, Hazard Evaluation, and Risk Quantification... 

Some of the limitations associated with risk quantification are discussed below. 

Grose is not alone in expressing concern about the vaUdity of risk quantification systems. These quotes come from Improved Risk Communications, a text prepared under the guidance of the Committee on Risk Perception and Communication as a project of the National Research Council ... 

The risk quantification procedure, after having obtained the in(ter)operabili1y level in (for) each... 

Jung WS, Han SH, Yang JE, 2008. New method for an efficient risk quantification of external events, Trans of Korean Nucl Society Spring Meeting, May 29, 2008 KEPCO (Korea Electric Power Corporation), 2004. Probabilistic Safety Assessment for Ulchin Units 3 4 - Level 1 PSA for External Events... 

Lock, E.A. and Hard, G.C. (2010) Alpha2u-globulin nephropathy and chronic progressive nephropathy as modes of action for renal tubule tumor induction in rats, and their possible interaction. In Cancer Risk Assessment—Chemical Carcinogenesis, Hazard Evaluation, and Risk Quantification, (Hsu, C.H. and Stedeford, T. Eds.), pp. 248-255, John Wiley Sons, Ltd., Oxford, England. 

The risk quantification models presented in the remaining sections of this chapter are based on the dissertations of the author s doctoral students (Yang, 2006 Bilsel, 2009) and the resulting publications of their doctoral work (Yang and Ravindran, 2007 Bilsel and Ravindran, 2011,2012). 

The risk quantification models discussed in this chapter will take a broader view of supply chain risk and model it as a function of occurrence, impact, detectability, and recovery. Methods to quantify each risk component will be developed. We will begin with the development of a basic risk quantification model as a function of impact and occurrence. Separate mathematical models will then be developed for risk detectability and risk recovery time. All the models will be integrated and illustrated with a case study on risk adjusted multi-criteria supplier selection model at the end of the chapter. 

VaR models were first developed for the financial industry in the early 1990s. They are considered as a standard measure for market risk and used extensively in portfolio risk management. From the financial point of view, VaR measures the maximum possible loss in the market value of a given portfolio. Considering the characteristics of VaR type risks caused by rare events, the concept of VaR can be applied to risk quantification in supply chain management also. 

There are several ways to include detectability of disruption risks in supply chain risk models. One way is to directly use the values in the MFPT matrix, the ntij values, and create an objective function to minimize the number of transitions between suppliers and the buyer. Otherwise, the MFPT values may not be suitable to use directly in risk quantification since values in the MFPT matrix are in transitions and need to be transformed to actual time units (e.g., hours, days, or weeks) for proper use in disruption quantification. This transformation to time units is supply chain specific, since the speed with which the information spreads through the nodes depends on the information technology systems implemented at each node and the availability and strength of connection among the nodes. For instance, if a buyer has implemented an ERP system that allows communication with all tiers of his supply chain, he would have much better connectivity to any supplier and the transition times would be much shorter than buyers that do not have a similar visibility. We call the time it takes any disruption news to reach from node i to j as the disruption delay between nodes i and j and denote it as Aij. 

Literature on Supply Chain Risk Quantification and Management... 

Bilsel, R. U. 2009. Disruption and operational risk quantification models for outsourcing operations. PhD dissertation. University Park, PA Pennsylvania State University. 

Yang, T. and A. Ravindran. 2007. Supply risk quantification in supply chain. Working paper. University Park, PA Department of Industrial Engineering, Pennsylvania State University. 

We devote an entire chapter to managing risks in the supply chain, emphasizing risk quantification models and risk mitigation strategies, and presenting important problems that extend beyond the traditional treatment of supply chain management. 

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