Flexciton is using AI to help factories optimise production lines
Flexciton, the London-based startup that is using AI to help factories optimise production lines, has raised £2.5 million in funding, in a round led by Backed VC. Also participating is Join Capital and company builder Entrepreneur First. The young company pitched at EF’s 6th London demo day in 2016.
Riding the so-called “Industry 4.0” wave, Flexciton has developed an AI-driven solution to optimise the way manufacturers plan and schedule “multi-step production lines,” which it says is a complex mathematical task faced by all manufacturers. It’s also traditionally quite a manual one, with existing software solutions still leaving a lot of the heavy lifting to humans.
“Running every factory in the world is a plan for that factory’s production,” explains Flexciton co-founder Jamie Potter. “This plan dictates everything which goes on in the factory. Plan well and a factory can be very profitable but plan badly and the same factory could deliver late on customer orders, overspend on equipment and materials and have its margins destroyed”.
Potter says that typically a human manually creates a plan based on their past experience, which isn’t always optimal. “The difference between an Ok plan and the optimal plan is huge for a factory, planning well can save a single factory many millions of pounds per year. The problem is, finding that optimal plan is one of the hardest mathematical problems that exists in the real world”.
Which, of course, is where more machines can help. Flexciton’s AI technology learns from a factory’s data, and Potter says it can understand exactly how that factory works. “It can then search through the trillions of different options to find the most efficient production plan. The results can be staggering too as our technology has shown time and again that it is capable of double-digit performance gains to a factory!” he says.
Already revenue-generating, Flexciton has customers in the textiles, food, automotive and semiconductor sectors. “We love to work with particularly complicated factories. Here the planning problem is the hardest and this is where we add the most value,” says Potter.
To back this up, Flexciton has recruited a number of experts in the field of industrial optimisation and AI. The current Flexciton team has published over 140 peer-reviewed academic papers, which focus on the practical application of this technology in eight different industrial use cases. To boot, Flexciton’s senior optimisation scientist, Dr. Giorgos Kopanos, has even published a book on the subject.