Revolution is in the air. Smart factories of the future will need to be innovative, nimble and smart; constantly changing and improving on the back of intelligent use of data. Professor Robert Harrison explains the challenges and opportunities for forward-thinking manufacturers.
If you haven’t heard of smart factories yet, you’ve probably heard of Industry 4.0 or the fourth industrial revolution. Smart factories are the next big predicted change to affect manufacturing, causing a new revolution in industry.
By integrating technology and information in real time, traditional factories will turn from cost centres into profitable innovation centres. Cyber-physical systems (CPS) will monitor the physical processes within modular structured factories, and a virtual copy of the physical world will be mined for data in real time, enabling decentralised decisions.
These new systems could, for example, identify run-time optimisation by feeding back information related to product, process and production resources, or identify best engineering re-use. We will be able to be ‘smart’ in our manufacturing choices, from product design and evaluation, right through to manufacturing, the supply chain and service provision.
The increasing availability and use of distributed industrial CPS devices and systems, if aligned with the Internet of Things (IoT) and Internet of Services (IoS), could radically change the nature of manufacturing and provide new opportunities to develop more-effective, finer-grained, and self-configuring automation systems.
To achieve this, manufacturers will need to make changes. To realise effective CPS for industrial automation implies the need for engineering tools capable of supporting distributed systems. This is coupled with a major shift in emphasis from traditional monolithic, specialism-based, isolated engineering tools and methods, towards integrated, cloud-based infrastructure based around an IoS and associated data.
Current automation systems engineering methods are frequently criticised for their poor performance in supporting re-use, and are often unable to effectively validate automation solutions across supply chains. Integration between real and virtual systems is often less than ideal, which makes it difficult to plot an efficient automation system lifecycle from specification and design, through to commissioning, validation, operation and reuse of systems.
Simply put, the engineering process we have at the moment is disjointed and it could be so much smarter.
Another oft-cited problem is that the majority of the automation tools currently at our disposal are vendor-specific and support largely closed control environments. While they may offer good point-solution functionality, are well supported, and can deliver robust operational systems, they often have limited agility.
These factors lead to delays and ultimately to poor lifecycle uses of information, with lessons learned not being fed back into subsequent iterations of the system.
… and the solution
Cyber-physical systems are distributed, heterogeneous systems connected via networks, and usually associated with the concept of the IoT. The vision for the new CPS lifecycle is one of seamless integration between engineering build and operational phases.
The digital model continuously updates to and from the physical system, and lessons learned are fed back into subsequent refinements of the system, making them ever smarter.
At WMG, we focus on the design and implementation of automation, systems engineering tools and methods adapted to the specific nature of CPS. Part of a new engineering software environment – vueOne – is currently being used to support Ford’s virtual engineering activity in powertrain assembly in the UK. vueOne is also being used to support engineering of battery and electric motor make-like-production systems in partnership with a range of automotive companies.
Properly supporting the full manufacturing lifecycle is important if we are to maximise the business benefits for the smart factory. At a simple level, once a digital model of a production station has been created, this information can be utilised via apps on mobile devices to enable support for production systems on the shop floor. This may be in the form of viewing digital data for monitoring and maintenance purposes.
However, in more sophisticated scenarios, augmented reality can be provided, overlaying key system information visually over physical views of the production system, and to support this we’re currently developing a suite of mobiles tools.
A key aspect of smart factories that will ensure they are truly successful is having a pipeline to progressively develop and then maximise the impact of innovative automation systems. For example, developing proof-of-concept systems from bench-top demonstrators, through full-scale pilot implementations, make-like production lines, and ultimately to factory installation, working closely with industry partners at all phases of this activity.