NDLI: Probabilistic and Monte Carlo risk models for carbon nanomaterial production processes

Content Provider	IEEE Xplore Digital Library
Author	Ok, Z.D. Isaacs, J.A. Benneyan, J.C.
Copyright Year	2008
Description	Author affiliation: Mech. & Ind. Eng. Dept., Northeastern Univ., Boston, MA (Ok, Z.D.)
Abstract	Given considerable uncertainty surrounding the occupational, consumer, and environmental, health and safety (EHS) risks of various nanomaterial manufacturing processes, modeling their relative risks and benefits is especially important. This paper discusses possible risk assessment methods that might be useful in such applications and explores three probabilistic approaches in greater detail: Monte Carlo (MC) simulation models, Bayesian belief networks, and multi-criteria decision trees. These approaches are illustrated for single wall carbon nanotubes (SWNT) produced via high pressure carbon monoxide (HiPco) processes to study the impact of inherent uncertainties and early EHS standards decisions on predicting long-term manufacturing costs, occupational health (OH) exposure risks, and associated tradeoffs. Until research progresses on the EHS risks of nanomaterials, these types of analyses can provide useful information for private and regulatory decision-makers and for guiding research priorities.
Starting Page	1
Ending Page	6
File Size	1512733
Page Count	6
File Format	PDF
ISBN	9781424422722
DOI	10.1109/ISEE.2008.4562944
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-05-19
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Monte Carlo methods Production Uncertainty Manufacturing processes Health and safety Risk management Bayesian methods Decision trees Carbon nanotubes Costs uncertainty HiPco occupational health risk SWNT
Content Type	Text
Resource Type	Article

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