Digital process design involves far more than just the process simulation typically used to design and optimize processes.
It comprises an integrated set of techniques and methodologies that deploy validated digital twins of processes – embodying detailed physics and chemistry knowledge – to explore the decision space rapidly and effectively, optimize process and product designs and quantify and manage technology risk.
What is digital design?
Digital process design involves capturing all relevant information in a validated predictive model of the process, then using this model to explore the decision space and optimize the design using advanced analytical and optimization techniques.
Construct
Create high-fidelity models encompassing physicals and chemistry. In order to ensure a high degree of predictive capability, these typically involve first-principles chemical engineering that describes the detail of the underlying phenomena, but can include hybrid data-driven elements.
Validate
Validate empirical parameter against experimental or pilot data. This uses a model-targeted experimentation approach, where experiments are maximize the information in the model, rather than the performance of the process.
Analyse
Use the validated model to explore the decision space rapidly and effectively, by applying global system analysis techniques to determine the effects of uncertainty, variability and design choices on process design KPIs.
Optimize
Determine optimal values for many process design variables simultaneously, including integer decisions such as number of parallel trains or distillation column stages.
What are the benefits?
Digital design techniques are being systematically adopted by the process industries’ leading innovators because of the many benefits:
- Accelerated innovation. The ability to explore the decision space systematically, reduce experimentation time and integrate experimentation and design means faster time-to-market with new processes and products.
- High-performance processes. Full, rigorous optimization means better-designed, better-performing and more flexible processes able to produce the right quality product in the face of variability.
- Better products. Digital design makes possible the integrated design of formulated products and their manufacturing processes, resulting in better, higher-quality products. It also enables faster screening of formulations for viability early in the cycle.
- Reduced and better-managed risk. Global system analysis enables you to can quantify technology risk systematically and manage the effects of uncertainty, to make sure you can produce profitably come what may.
- Reduced experimentation. Model-targeted experimentation is used to support the creation of a validated, predictive model, rather than to perfect the process or product design (that is the role of the predictive model). This means that experimentation time and cost can be kept to a minimum, enhancing R&D effectiveness.
Who uses digital design and why?
SPSE’s digital design tools and methodologies are used across the spectrum of process industries:
…better drugs to market, faster
The Systems-based Pharmaceutics Alliance promotes digital design for simultaneous formulation of drug products and design of their manufacturing processes.
…better catalysts and reactors
New catalyst formulations are tested in high-fidelity virtual reactors, removing the need for expensive field trials.
…optimal process designs
Reactor and separation sections can be optimized simultaneously to take into account all interactions.
…accelerated fuel cell development
Digital design is used to design complex fuel cell systems and test how they perform during realistic drive cycles.
What does SPSE provide?
Siemens Process Systems Engineering has worked with some of the largest organisations in the process industries to evolve a definitive model-based approach to digital process design that can be applied across all process industry sectors from upstream oil & gas to pharmaceuticals and food.
The Siemens gPROMS Process and gPROMS FormulatedProducts environments are the only process modelling tools that offer true digital design capabilities, from concept or formulation to online operation.
