Engineering Design Concept Optimization by Formal Methods
"Not choosing between good ideas — proving which one creates maximum value."
The Challenge
"We have multiple technically viable design options for our new facility, revamp, or energy transition project. How do we know which configuration truly maximizes long-term business value?"
Our Solution
We apply hybrid discrete optimization (integer programming, constraint programming, metaheuristics) to formally explore thousands of configurations and identify the optimal trade-off between CAPEX, availability, lifecycle cost (LCC), and risk.
Our Process Includes:
Enumerating all feasible design alternatives
We systematically generate the complete design space, ensuring no viable option is overlooked.
Modeling causal dependencies between equipment, processes, and financial outcomes
Using PDEL® methodology to capture the physics of failure and performance interactions.
Solving multi-objective problems with CPLEX/Gurobi
Industrial-grade mathematical programming solvers to handle complex constraint sets.
Delivering not just a recommendation, but a proof of near-optimality
Quantified confidence that the selected design is provably within X% of the theoretical optimum.
Major LNG Exporter – 1600 MSCFD Expansion
Summary
Optimized the design of a new compression and dehydration train by evaluating over 348 configurations. Solved for optimal redundancy levels, maintenance strategy integration, and power supply routing under uncertainty.
Behind the Scenes
- Tools: AspenTech Fidelis, Wolfram Mathematica, CPLEX
- Methods: Mixed-Integer Programming (MIP), Benders Decomposition
Outcome
- Proved 98.7% optimality
- Unlocked $MM in EBITDA through better configuration selection
Ready to prove which design maximizes your value?
Let's apply formal optimization to your next major project.
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