The ability to create a connected enterprise promises game-changing possibilities for manufacturers. MACH 2020 will give visitors the chance to evaluate these technologies and understand the potential for their businesses.
Machines equipped with sensors feeding data to a cloud platform offer the potential for that data to be analysed and interpreted to feed back into streamlined operations, higher quality and optimised OEE (Overall Equipment Effectiveness).
Andy Yearsley, who is the EMEA Industrials Sector Lead at MACH exhibitor Hitachi Consulting, says: "Being connected is only a step on the way. The difficult bit is taking that data and driving value from it. You might be connected, but are you smart?
He says that Hitachi Consulting is one of the very few organisations that can provide an end-to-end solution from collecting the data from the machine to applying the data science to make better business decisions and implement them on the shop floor.
"It will differ from client to client, but typically it is applying insight and analytical data science to understand what that data is telling you in terms of what has happened, what is happening and what is therefore likely to happen in the future.
"We can build models to automate much of the production of that insight, making sense of the data. We then feed that insight back into the equipment so that it becomes semi-autonomous and reacts to optimise production."
An example is an electric motor. If sensors detect a trend in, say, temperature or vibration, the data could suggest that it is heading towards failure. The motor can then respond by slowing down to postpone that failure and send out an alert to the maintenance team to say -- 'I am going to break down in 200 cycles, come and fix me' -- so someone can come along at the end of the shift to mend it and there is no interruption to production.
On a larger scale, a multitude of sensors could be producing data across, say a car factory, or on a train or aircraft. Rather than having a schedule of planned maintenance, the machines can tell you when they will need to be maintained depending on how hard you have been working them. This means you can extend service intervals, reduce service costs and increase uptime.
SMEs can get the benefits too says Andy Yearsley.
"One of the fallacies out there is that only big companies can drive value from this kind of approach."
He says that putting the required sensors on a machine, sending the output to a big data platform and then applying some analytical data science could cost less than £10,000 per machine.
"If you have an asset producing high value, low volume components it doesn't take long to recover that investment if you are able to reduce down time and increase quality -- because this can help inform you about quality too. It is all about Overall Equipment Effectiveness -- how much good stuff you are getting out of your machine in the time available."