) April 23, 2018 -- At the 2018 Advanced Process Modelling (APM) Forum this week, process industry organisations presented on digital design and operations applications ranging from accelerating development of the next generation of pharmaceuticals to realising millions of dollars per year in increased profit for large process plants.
Introducing the conference, Prof. Costas Pantelides, MD of conference host Process Systems Enterprise (PSE), described the current wave of digitalisation as the culmination of many years of advanced modelling and IT development. “This is a time of extraordinary opportunities for the process industries” he said.
Keynote speaker Mathias Oppelt of Siemens described how high-fidelity process models containing deep process knowledge bring a new level of power to digitalisation initiatives being delivered by automation companies. Siemens later demonstrated digital twin technology for an ethylene plant, implemented using PSE’s gPROMS Olefins software. SABIC showed how new online technologies improved yield by 2% at a large petrochemicals plant, representing tens of millions of dollars per year, and BASF described how digital technologies that combine data and models are enabling an enhanced innovation approach with strong focus on customers and markets.
Keynote speaker Suracha Udomsak, R&D director at SCG Chemicals, said “APM is a key element of our Digital Manufacturing platform. It accelerates innovation by making the development workflow faster, cheaper and safer”.
On the Formulated Products side, keynote speaker Ben Weinstein of Procter & Gamble described how a strategic decision many years ago to back a digital design approach has accelerated innovation across P&G.
Pharma keynote Neil Hodnett of GSK showed how system modelling is applied to accelerate development and transfer of robust manufacturing processes, particularly in the move to continuous processing, through the use of virtual DoEs for in-silico QbD.
Roche, Pfizer, Ferring, Novartis, Sandoz, UCB, Syngenta, Danone and FrieslandCampina described benefits of applying advanced mechanistic modelling to improve drug product manufacture, increase R&D efficiency and reduce risk in scale-up and tech transfer.
Pantelides adds “a common theme is that it is now possible to easily capture deep process knowledge in the form of predictive models, then use these within a digitalisation framework to generate value at every step”.
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