The maintenance sector has been one of the first to appreciate and embrace the potential of a more automated approach to industrial processes and production. The reasons are clear enough: the consequences of unplanned stoppages have significant impacts on costs, productivity and reputation. For example, a stoppage on an automotive line reliant on just-in-time (JIT) techniques results in major delivery back-ups which not only impact the line that has gone down, but also disrupt many other processes in the production chain. An unplanned stoppage in food or pharma processing can lead to entire product batches being spoiled and consequent failure to meet delivery targets: with all the potential for punitive penalties that this entails.
Preventative maintenance has evolved as a response to the need to increase OEE. Increasing digitalisation offers the potential to further improve predictive maintenance through condition monitoring, ensuring maintenance is only undertaken when it is genuinely needed. Offering a more intelligent approach to the maintenance regime, using prevention rather than cure, therefore results in real time and cost benefits which are deliverable now.
“Predictive maintenance is a stepping stone on the way to truly smart maintenance, in much the same way as digitalisation is a stage on the journey towards full Industry 4.0 adoption” Steve Sands of control and automation manufacturers Festo, says. “Digitalisation is certainly showing the way and offers practical lessons for what will be achievable on a universal scale as Industry 4.0 technology becomes the norm. From our own experience, we can say that the impact on people, and the way in which they are supported to respond to the challenges and opportunities associated with Industry 4.0, will be critical to success.”
He is referring to Festo’s investment in a highly-automated manufacturing facility at its factory in Scharnhausen, Germany. “As a global manufacturer of industrial control and automation components, Festo wanted to maximise the use of the emerging technologies to experience at first-hand the benefits and to better understand the impact on people and processes,” Sands adds. “We’ve already learned a great deal that will help us to support customers in the transition to fully or highly automated plants, not only in terms of technological application, but also through gaining a better understanding of the human aspects of how people respond to change.”
Testbed for Industry 4.0
The Scharnhausen Technology Plant is Festo’s main production facility for valves, valve terminals and control electronics, covering 66,000m2 of space arranged over four levels and housing a workforce of around 1,200 people.It is at the forefront of automation for the future and is a constantly evolving environment for intuitive human-machine interfaces, training and qualification, and innovative technologies.
To create the Industry 4.0 environment, Festo has either piggy-backed intelligence onto existing machines or, where the opportunity arose, embedded it in new equipment. For example, Scharnhausen uses Near Field Communications (NFC) for digital maintenance support. This means that equipment components can exchange data directly with the maintenance team without passing through a central database.
For the maintenance team, this presents new ways to interact with the factory equipment and gather useful data. Their main tool is a tablet equipped with a custom-developed app which, together with a mobile depth sensor, enables the user to access more information the closer they are to the components requiring attention.
At a high level the tablet may show an overview graphic of the entire plant layout and indicate that there is an alert raised on a machine on a production line. These alerts follow a simple grading system to indicate their urgency, enabling the team to prioritise their workload effectively. This makes the team far more responsive because they can direct their resources to the highest priority notifications first, i.e. those where a pending machine stoppage would seriously affect planned production. For less serious events, information about the reasons for the alert can be interrogated remotely without any need to interrupt production.The lowest category alert will simply be a notification that a part or a peripheral, such as ink in a label printer, requires replacement on a given date.
When intervention is necessary, co-ordination of people and parts is much slicker in the automated factory. “Our smart factory maintenance team can check the availability of components and tools so that everything necessary to undertake a scheduled maintenance task is to hand where and when it is needed,” Sands adds. “Using their tablets as an interface, the engineers can access information directly from the machine and its component parts, call up maintenance instructions, detailed 3-D models of the machine to check aspects like accessibility prior to starting work and even access detailed technical manuals or online help direct from equipment suppliers during the task.”
Clearly, this level of automation has meant significant changes for Festo’s maintenance team. First and foremost, they are now able to take a fully proactive approach to maintenance which moves beyond preventative maintenance. The ability to analyse condition data and interrogate an alert from anywhere within the factory means they are more mobile, more responsive and more efficient. The ability to access real-time information and analyse the situation before making any intervention has led to better man management. Automatic ordering of tools and parts has increased efficiency by eliminating journeys between the stockroom and the machines requiring attention.
There have also been positive impacts on a human level. “Psychologically, rather than dumbing down the maintenance role increased automation has elevated it,” Sands explains. “There is also more emphasis on understanding why a situation arose and how to solve it, capturing and sharing this knowledge around the team. Regular, repeat tasks therefore become easier because the engineer can benefit from shared experience for faster fixes and improvement suggestions.”
It is therefore no surprise that, at Scharnhausen, the training and learning facility is in the middle of the factory.
Where next for maintenance?
While Scharnhausen is a compelling example of how the adoption of Industry 4.0 will deliver positive change to the role of plant and maintenance engineers, there are still major challenges ahead. One aspect that should not be underestimated is the changing relationships between humans and machines. Increased automation means that there is less human control required, but far more data available. This redefines the role of the humans involved from data gatherers to interpreters and analysts.
Forthcoming Industry 4.0 developments will see machine learning becoming more common, with embedded intelligence allowing AI algorithms to detect data patterns indistinguishable to human minders and to propose corrective measures. Whilst in some applications a business case can be made now for the added sensors, intelligence and communications involved, the costs of implementing full automation will decrease rapidly due both to economies from the acceptance of standards and the cross-over of ideas between the consumer, IOT and Industry 4.0 worlds. For example, a joint research project called ParsiFAL is already developing better methods of data gathering: the prototype device has no standard battery or power source, but is looking at ways of harvesting energy from a magnet within a reciprocating pneumatic or hydraulic piston to charge the sensor that measures and periodically wirelessly transmits data.
“To make machine learning truly effective we need data about the performance of components in all environments to build better predictive models,” Sands observes. “The investment to achieve this will only come when the business case is available to pay for it. There are parallels with the car industry, where the myriad of monitoring systems has led to most drivers valuing the information about tyre pressures or servicing requirements that the vehicle can share.”
Augmented reality is another exciting area under development. The concept of a Digital Twin – a CAD-generated model that enables designers to simulate how a machine will function – is already possible. Industry 4.0 would see this model being taken much further, so that it can emulate its physical counterpart in real time throughout its operational life. Information about smart components will be held within the model and continuously updated. The Digital Twin of the future will capture information about modifications as they are made, eliminating the need to revise technical manuals as variations to the original design are introduced.
The level of standardisation required to make this kind of lifetime modelling a reality is one of the challenges for those committed to Industry 4.0, and a lot of work is being done to agree universal standards and protocols for communication of data. OPC UA has been successfully adopted as the agreed standard for communications interfaces within Industry 4.0 environments. Other standards are being worked on to extend these structured data sets: for example, an IO Link standard has yet to be incorporated and IO Link wireless will clearly be considered. Work is ongoing to incorporate embedded data using the Automation ML protocol.
“There is a lot at stake, and inevitably there will be winners and losers,” says Sands. “Anyone who remembers the battle of Betamax versus VHS when video technology was emerging will appreciate the scale of the challenge in agreeing the cross-border, cross-technology norms which will make Industry 4.0 accessible to everyone. Digitalisation is the ongoing and inevitable evolution; the agreement to a standardised model and convergence to a reduced set of agreed standards is the difference that those driving Industry 4.0 are striving for.”
The role of data will drive business models in the future, but there are still big questions being asked around the ownership and interpretation of data, as well as access and privacy issues to be addressed. Relationships between who generates, owns or uses data captured by Industry 4.0 enabled devices may well result in a whole new industry sectors, with companies who specialise in buying and selling data while others focus solely on its interpretation and application. The effects of this on the traditional parameters of plant and maintenance engineering are not yet known.
