Parameter Prioritization in Techno-economic Model for Decision-making in the Petrochemicals Industry

The petrochemical industry plays a pivotal role in the global economy but continues to face significant challenges, including fluctuating oil prices, tightening environmental regulations, and high capital investment requirements. Hence, reliable techno-economic models are essential when companies approach Final Investment Decisions (FID), which determine the success of large-scale projects.

This study introduces a structured framework that prioritises and ranks the parameters that are most critical to such models. The approach combines the Objective Weighting Method (OWM) with the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) by using propylene oxide production as a case study.

The analysis discloses that the total revenue is the highest-priority parameter (P_i = 0.5280), followed by raw material cost (0.4576), utilities cost (0.2316), investment cost (0.2209), and fixed cost (0.1905).

By identifying the most influential parameters, this approach enables decision-makers to allocate resources more effectively, improve cost efficiency, and reduce uncertainty. When combined with sensitivity analysis, it empowers companies to assess the impact of changing conditions, thus strengthening risk management and increasing the likelihood of project success in an uncertain and highly competitive sector.

The Structured Entropy-TOPSIS framework is a strong, evidence-based tool that identifies the key factors in petrochemical investment decisions. The findings decrease decision-making uncertainty while increasing the chances of the project being successful, as management attention is directed towards the economic variables with high impact.