Design and optimization of poly(hydroxyalkanoate)s production plants using alternative substrates.

Area of Science:

• Biotechnology and Biochemical Engineering
• Process Systems Engineering
• Sustainable Materials

Background:

• Poly(hydroxyalkanoate)s (PHAs) are biodegradable polymers with significant market potential.
• Optimizing PHA production plant design is crucial for economic viability and sustainability.
• Existing production models often lack comprehensive analysis of diverse feedstocks and extraction methods.

Purpose of the Study:

• To develop a Mixed Integer Nonlinear Programming (MINLP) model for optimal PHA production plant configuration.
• To evaluate various carbon sources and PHA extraction techniques.
• To maximize the Net Present Value (NPV) of the PHA production project.

Main Methods:

• A superstructure-based optimization model was formulated using MINLP.
• The model incorporates detailed capital costs, mass and energy balances, product specifications, and operating constraints.
• The objective function maximizes the project NPV, implemented in an equation-oriented environment.

Main Results:

• The sugarcane-enzyme process emerged as the most economically promising option, achieving an NPV of $75.01 million.
• This optimal configuration demonstrated an energy consumption of 22.56 MJ/kg PHA and a production cost of $3.02/kg PHA.
• Economic sensitivity analysis was conducted to assess the robustness of the findings.

Conclusions:

• The MINLP model provides a robust framework for optimizing PHA plant design.
• The sugarcane-enzyme pathway offers a highly competitive route for sustainable PHA production.
• Further economic sensitivity analysis can guide investment decisions in PHA manufacturing.