The Process Scaelup Journey Part 1: From Innovation to Commercialisation

CPI has helped over 1,000 businesses bridge the gap from beaker to bulk but scaling up isn’t as simple as making it bigger – it’s where many innovations falter. In this first article of a new series, CPI’s Alex Smith explores the key questions every team should ask before they scale up

SCALING UP a process often starts with the same simple question of “how do I make my process bigger?” However, you’ll need to answer a long list of questions during a scaleup exercise, some of which are technical, some financial, some strategic, and some are even personal.

All these questions must be asked and answered at the right time during your scaleup journey to ensure you scale in the most effective way and give your business the best chance of success. We could quite easily fill the pages here simply by listing these questions, but instead here are a few examples to get us started:

• Do I understand the steps in scale that are needed to prove my process and unlock future investment? How many steps are needed, and what is an appropriate scale for the next step?
• What is the immediate priority for the next scale of operation? Is it generation of material for testing? Technology demonstration? Confirming the suitability of larger scale industrial equipment for my process etc?
• Do I fully understand the economics of my process at production scale?
• Are there any hazards in my process that aren’t an issue in the lab but will cause significant design challenges at scale?
• Is anyone else already doing what I’m doing? Who is my competition, and how is my process different or better?
• How big is the market I’m selling into, and how much of that market do I realistically believe I can take?
• Do I understand the supply chain for raw materials? Is there a robust and substantial supply available for all the materials I need?
• What is my level of risk appetite, and that of my investors?
• Do I have a clear prioritisation between time, cost and quality?

In a series of articles over the coming year, our team of experts at CPI will share how to address some of the key considerations when scaling up your process, each of which I will introduce in this article.

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CPI

CPI is a founding member of the High Value Manufacturing Catapult – a network of innovation centres established to enable process scaleup and help companies navigate the journey between the invention of novel processes and the establishment of those processes at commercial scale. Their highly experienced team of process development scientists, engineers and process operators are constantly striving to help businesses bring bright ideas to market across a wide range of process industry sectors. With over 650 technical experts and over £220m (US$293m) of innovation and scaleup assets, they’ve helped SMEs unlock over £3bn in private investment since their inception in 2004.

Staying smaller to scale smarter

Scaling up a process means putting it in bigger vessels, right?

Not always. Using tools like Computational Fluid Dynamics (CFD) modelling, it’s possible to replicate elements of the performance of large-scale vessels in much smaller systems. This enables the running of “scale-relevant” experiments to generate useful and relevant data for scaleup without the associated costs of running large equipment and buying large quantities of material.

It might feel odd to run your kit below its peak performance, but in most scenarios, the ability of a benchtop reactor to run a process bears almost no relevance to the likely performance of the process at production scale.

At CPI, we often speak about how we may deliberately run our benchtop reactors badly, which raises an eyebrow, but is absolutely the right approach to ensuring the data you’re generating is scale relevant. To clarify, of course we don’t just mean we generally run things badly. There’s a science to understanding specifically how “badly” to run your benchtop equipment to mimic the inevitable performance limitations of large-scale equipment to ensure you can stress-test your process against those blockers and confirm that your process is in fact scalable.

Take mixing performance for example – an addition made to a benchtop reactor system will likely be fully mixed into the process within a second or two. At 10,000 L scale or beyond, that same addition may take minutes to become fully mixed. If your process is particularly sensitive to concentrations of certain components, then the impact of slow mixing may be significant. It would be prudent then to run experiments in the lab replicating that slow mixing, to ensure the impact on the process is understood before committing to a large-scale run. The use of CFD modelling enables us to determine exactly how to set up a benchtop reactor to replicate the mixing performance of a larger system.

Through scaledown operation you’re also able to test a far broader range of operating conditions and processing approaches, as the cost of failure is relatively low so there is naturally more freedom to take creative risks. Just think, for the cost of a single process run at 1,000 L scale generating effectively one data point, you could run a significant programme of work at 10–100 L scale, generating numerous data points and significant learning about the performance of your process, all while ensuring that data is still relevant and can be directly applied to any subsequent confirmation runs to be carried out at 1,000 L.