Digital process design

Combining knowledge and data to enable rapid and effective innovation

Digital process design involves far more than just the process simulation typically used to design and optimise processes.

It comprises an integrated set of techniques and methodologies that deploy validated models of processes – embodying detailed physics and chemistry knowledge – to explore the decision rapidly and effectively, optimise process and product designs and manage technology risk.

Over the years PSE has worked with some of the biggest names in industry to evolve a definitive model-based approach to digital process design that can be applied across all process industry sectors.

What does digital design involve?

Digital process design comprises two main activities: creating validated predictive models, then deploying these to explore the decision space using a variety of analytical techniques.

1. Construct predictive models

Create validated models that are predictive across a range of scales and operating states via some or all of the following steps:

  • Construct first-principles, mechanistic models embodying process physics and chemistry (using library models where available)
  • Fit empirical model parameters, such as reaction kinetic parameters, to experimental data
  • Rigorously validate these models against experimental data to ensure their accuracy
  • If necessary, design further experiments for maximum information content.

2. Explore the decision space

Apply the validated models using analytical technologies such as simulation, global system analysis and optimisation to:

  • Explore the decision space rapidly and effectively using global system analysis (GSA) to systematically perform thousands of calculations for varying values of input factors
  • Similarly, use GSA to determine uncertainty and manage risk
  • Optimise the process or product design using process-wide MINLP optimisation with multiple decision variables
  • Perform steady-state and dynamic simulation to develop a deeper understand of the process or product performance

Who uses it?

The digital process design approach is used by leading innovators across the process industries. PSE is formally involved in several initiatives furthering the application of digital design:

  • the Systems-based Pharmaceutics Alliance, where we are a founder member
  • the Advanced Digital Design of Pharmaceutical Therapeutics (ADDoPT) project, involving four major pharma companies and a number of universities and SMEs, where we are project leader.

Where is it applied?

Digital design is widely applied in:

  • new equipment and process development, for example, to manage technology risk and accelerate deployment
  • the integrated design of robust formulated products and their manufacturing processes, for example, to accelerate new drug formulations to market
  • new catalyst development, where new formulations can be optimised then tested for performance in high-fidelity reactor models
  • development of new technologies such as fuel cells, where models can be used as analytic tools to generate information on micro-scale phenomena not observable from experiments

What are the benefits?

Key benefits of digital process design are:

  • accelerated innovation with faster time-to-market, through the ability to explore the decision space systematically, reduce experimentation time and integrate experimentation and engineering design activities
  • better-designed, better-performing and more flexible processes able to produce the right product quality product in the face of variability
  • better products, for example from the integrated design of formulated products and their manufacturing processes
  • better-managed technology risk, through the ability to systematically quantify and manage the effects of uncertainty
  • overall more profitable operations.

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