You might think social media has little to offer manufacturing, but Dr Ajith Parlikad explains why you should think again.
Maintaining assets used to be considered a ‘necessary evil’, but manufacturers now see strategic asset management as an important way of delivering value and achieving competitive advantage.
With the emergence of sensors and novel data collection technologies, we can connect and monitor assets in a way that is light years from the old method of maintenance, which was essentially ‘wait until a machine fails and then fix it’.
The Internet of Things (IoT) has enabled a new paradigm called “e-maintenance” where assets can be monitored remotely. This enables OEMs to provide innovative maintenance service solutions to their asset users.
Although IoT has made an enormous difference to asset management, it doesn’t have all the answers. Cue the ‘social network of things’, and the potential to revolutionise the management of assets.
One challenge is that industrial analytics tend to focus on individual machines in individual factories.
We now recognise that a factory – or a multi-sited production network – is greater than the sum of its parts, and if we are to make significant improvements to performance, we need to embrace the whole system, within and across factories and their associated supply chains.
Clearly, if a machine is connected to the internet you can gather and analyse vast amounts of data to optimise performance. However, to optimise a whole factory, the data needs to be viewed within the context of the entire system.
Who is Dr Ajith Parlikad?
- Senior Lecturer at the University of Cambridge
- Heads up the Asset Management Research Group, The Institute for Manufacturing (ifM)
- Deputy Director, IfM’s Distributed Information and Automation Laboratory (DIAL)
It may not be beneficial for the entire production system if each machine is maintained optimally, and may actually result in poorer performance.
And while IoT holds out the promise of a solution, in practice it struggles to deliver. Individual machines tend to be maintained by their OEMs, so there is often no single view of how the factory operates, making it impossible to develop a truly integrated asset management strategy.
Social interaction
We started to think about how best to create the conditions so machines could work together to improve overall factory performance.
As social animals, people interact with one another in the workplace in a way that can both support individual needs and collective performance. For instance, if you tell your boss you have a headache, they might advise you to take paracetamol or they might reduce your workload, if they think you have too much to do.
They do this so in the long term you become more productive. Our research applies this model of social interaction to the machine world.
It combines the concepts of IoT with social networking technologies (Web 2.0) to develop a ‘social network of things’. If machines can report their ‘status’ into a common data-sharing platform – or ‘social network’ – it becomes possible to create a single view of how the whole factory or production network is running.
A conveyor belt, for example, might report high levels of vibrations and will fail in five days’ time. With the right data links in place, a ‘maintenance app’ knows that maintenance is scheduled for eight days’ time.
The machine feeding products onto the conveyor can then calculate if both the conveyor belt and the machine slow down and prolong the life of the belt from five to nine days.
By slowing down the production line, it is possible to avoid either the conveyor belt failing in the middle of a production run, or incurring the cost of expediting maintenance activities.
In a scenario like this, it is the machines making the decisions. A human being looking at the same data – assuming they always have access to it – would consider the same options and calculate the implications of each in terms of cost and productivity for the system.
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Machines can do this much faster and more accurately than we can. To extend the social network analogy further, algorithms or ‘apps’ can be run on the social network platform, which look at these updates and determine, say, the best maintenance plan for the factory as a whole.
The digital evolution
‘Digital revolution’ is an overused phrase, however, the ‘social network of things’ has the potential to transform asset management as we know it.
By creating a social network-based, data-sharing platform, which enables machines to cooperate, we can build a smarter, more resilient and more productive system. It will also help us address another pressing manufacturing challenge – environmental impact.
By intelligently adjusting machine performance, the social network of things has the potential to help manufacturers dramatically reduce their energy consumption.
So if you thought that Facebook, Instagram and Snapchat had little to offer the world of manufacturing, you might need to think again – as the principles of social media look set to take asset management to another level.
