(726c) Design & Optimization of Hazardous Chemical Supply Chains with Seasonal Variations Using Total Cost of Process Risk (TCPR) Framework | AIChE

(726c) Design & Optimization of Hazardous Chemical Supply Chains with Seasonal Variations Using Total Cost of Process Risk (TCPR) Framework

Authors 

Khan, F., Memorial University of Newfoundland
Hasan, F., Texas A&M University
In the design of chemical supply chains, there is a need to capture variabilities that might be present. These variabilities might be seasonal like in the case of agricultural supply chains or daily like hydrogen supply chains. Traditionally, much of the focus with addressing these variabilities has been on the impact of economics. However, these variabilities can have an impact on safety especially at the process level. This is a challenging problem as quantifying safety as a function of scale is difficult. To illustrate this, we examined the different technology routes that are used for the production of glyphosate. Glyphosate is the most used herbicide in the world, with over 800 million kg used annually as of 2014 [1]. To produce glyphosate there are three major pathways used in industry: the hydrocyanic acid (HCN) route, diethanolamine (DEA) route, and glycine route [2,3]. Each pathway consists of varying chemicals, process units, and operating conditions. Using the Fire & Explosion Damage Index (FEDI) and Toxic Damage Index (TDI) we demonstrate how the hazards change with scale and how the choice of least hazardous route depends on the scale [4,5]. Previous works have shown how such indices can be incorporated into the design and optimization of supply chains [6]. However, the use of indices as constraints along with variability considerations could lead to conservative designs that are economically infeasible. Thus, there needs to be a way to better capture the tradeoffs between safety and cost.

As such, we propose a Total Cost of Process Risk (TCPR) Framework that can be used to assess risk at various scales. For the purposes of this work, the focus will be on the supply chain scale and the production of glyphosate with seasonal demand variability considerations. Safety indices are utilized initially to identify the hazards in the supply chain for the storage, transportation, and production of glyphosate. The indices are converted into damage radii and then used in assigning the cost for mitigating and managing all aspects of process safety risk. This risk includes the cost of production loss, cost of asset loss, cost of health loss, and risk transfer premiums [7]. The TCPR is then included in the objective as one of the economic considerations along with the investment and operating costs. Results demonstrate how the tradeoff between the TCPR with the other economic considerations can affect the decisions regarding the design of the supply chain.

References:

[1] Benbrook, C.M. 2016. Trends in glyphosate herbicide use in the United States and globally. Environmental Sciences Europe. 28(3).

[2] Yushchenko, D.Y., Khlebnikova, T.B., Pai, Z.P., Bukhtiyarov, V.I. 2021. Glyphosate: Methods of Synthesis. Kinetics and Catalysis. 62, pp. 331 – 341.

[3] Feng, D., Soric, A., Boutin, O. 2020. Treatment technologies and degradation pathways of glyphosate: A critical review. Science of The Total Environment. 742, 140559.

[4] Khan, F.I., Abbasi, S.A. 1998. Multivariate Hazard Identification and Ranking Systems. Process Safety Progress. 17(3), pp. 157 – 170.

[5] Khan, F.I., Husain, T., Abbasi, S.A. 2001. Safety Weighted Hazard Index (SWeHI): A New, User-friendly Tool for Swift yet Comprehensive Hazard Identification and Safety Evaluation in Chemical Process Industries. Process Safety and Environmental Protection. 79(2), pp. 65 – 80.

[6] Roy, N., Mannan, M.S., Hasan, M.M.F. 2020. Systematic incorporation of inherent safety in hazardous chemicals supply chain optimization. Journal of Loss Prevention in the Process Industries. 68, 104262.

[7] Khan, F.I., Amyotte, P.R. 2005. I2SI: A comprehensive quantitative tool for inherent safety and cost evaluation. Journal of Loss Prevention in the Process Industries. 18(4 – 6), pp. 310 – 326.