4 MIN READ
Turbocharging the medical device industry to tackle COVID-19
Before joining Team Consulting, my background was in mechanical engineering focused on internal combustion engines. Moving to medical device design and development, I was confident that I could draw on my experiences to add a new perspective to the business that would improve on its ability to respond efficiently, and creatively, to customer needs.
Seven months into my role, I was pulled into an urgent project to assist the UK Government with the rapid development of an emergency ventilator in response to the COVID-19 pandemic. Faced with the task of delivering a highly complex and safety-critical medical device in a matter of weeks, our team had to find ways to de-risk the project wherever possible.
As we began our work, it soon became clear that the bellows type ventilator concept we were pursuing bore an uncanny resemblance to an engine. Engines are, in their simplest form, air pumps that use pistons, cylinders, valves, and manifolds to control the flow and pressure of gases, which was exactly what our ventilator concept did. The question in my mind was how these similarities and my previous experience could be leveraged to benefit the project.
One of the most developed and well used aspects of modern engine development is predictive simulation, where advanced software packages are used to help predict the effects of potential changes in a prototype. For example, being able to understand how a small design change to an intake port can be critical given the time and cost associated with manufacturing prototype parts for testing. As well as saving resources, predictive simulation enables the full system performance to be optimised in the virtual world in a way that would otherwise be impossible.
It quickly became clear that this type of predictive simulation was exactly what was needed to assist the ventilator project.
Working in collaboration with MAHLE Powertrain, in just three days, a model was constructed in the GT-Suite simulation environment, which was then correlated to data measured from a series of prototypes. This was a phenomenal effort despite being hampered by the lockdown restrictions in place at that time, which has meant that the team working on this have still not met in person to this day.
The model proved to be integral in reducing project risk on several fronts. Firstly, it helped to build an understanding of the system performance and highlighted issues with test components. A great example of this was during the model correlation activities, when the only way to get the model and data to match was to introduce an air leak at the lung. This led us to find a pin hole in one of the test lung bladders, an issue that may never have been spotted otherwise.
Incorporating the model also enabled enabled sensitivity studies to be conducted based on design of experiments (DOE) principles, to ensure potential sources of variation in the system performance were understood and accounted for. Alongside this, it also provided a platform that allowed mitigation of some of the risks associated with having to make design changes, due to off the shelf parts availability. Changes could be quickly assessed and feasibility established without losing time to sourcing, building and testing prototypes.
Fortunately, the COVID emergency evolved in such a way that the emergency ventilator we developed was not required to enter production. However, the development and application of this predictive model using an automotive focused toolkit did showcase that drawing on talent from other industries can deliver real benefits to a project. It also reaffirmed why Team holds an open-minded policy to recruitment and a willingness to embrace innovative solutions to complex problems.