(185i) Uncertainty Analysis Including Safety, Environmental and Economic Performance of Chemical Processes

Traditionally, major decisions for chemical process design have been based on economic and technical analysis. This approach is usually carried out considering average values to key data such as feedstock and product prices, capital and operating costs, as well as process related variables, such as reactor performance or equipment efficiency. The incorporation of uncertainty at the process design stage aims to take explicitly into account uncertainty sources and associated variations of economic and process conditions to provide better solutions as compared to the traditional use of single design variables based on nominal values. In this work, we develop a systematic integrated framework to include uncertainty at the design stage of a chemical process. Furthermore, the typical techno-economic analysis is expanded to include safety and sustainable factors to generate a more comprehensive analysis of the process potential. Within the proposed design framework, an insightful assessment of uncertainty’s effect on the safety, environmental and economic characteristics of the process are carried out by generating ranges for the performance indicators, supported by probabilistic methodologies. To illustrate the proposed approach, cases of study related to processes to produce ethylene and methanol are considered, where uncertainty is incorporated to the three performance indicators using Monte Carlo techniques. Two variables that affect the three indicators were considered under uncertainty, namely raw materials prices and compressor efficiencies in the methanol synthesis loop for the methanol process, and raw material prices and catalyst yield for the ethylene processes. Detailed performance profiles are reported, and risk-reward zones and inherent trade-offs are highlighted as part of the identification of profitable design options. Also, as a special feature of the approach, implications on key safety properties of the process are examined concurrently.