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Digital combines with physical manufacturing

Industry 4.0 promises a convergence of physical and cyber systems. Smart manufacturing and the smart factory are seeing more and more systems and products produced by factories, linked to the Internet – known as the Industrial Internet of Things (IIoT). But how will data be collected during production? What will that data be used for, and how will it feed back into manufacturing and design?


“Japan and Germany are said to be the most advanced countries in terms of digitising internal operations across the supply chain”

Cyber-physical systems and smart factories

Cyber-physical systems can be defined as integrations of computation, networking and physical processes, such as machining or other manufacturing processes like additive layer manufacturing or 3D printing. Embedded computers and networks monitor and control these physical processes, with feedback loops where physical processes affect computations, and vice versa. Massive volumes of data are generated, collected and subsequently analysed.

There are numerous benefits to smart manufacturing. According to research in 2016 by PwC, 72% of manufacturing enterprises predict their use of data analytics will substantially improve customer relationships and customer intelligence throughout the product lifecycle. 86% of manufacturers expect to secure gains from both lower costs and additional revenue from the increased digitisation of manufacturing, according to PwC, with 35% of companies adopting Industry 4.0 expecting revenue gains of more than 20% over the next five years.

Japan and Germany are said to be the most advanced countries in terms of digitising internal operations across the supply chain.

According to PwC, “Industry 4.0 focuses on the end-to-end digitisation of all physical assets and integration into digital ecosystems with value chain partners encompassing a broad spectrum of technologies”.

According to Forbes, for a factory or system to be considered Industry 4.0, it must include machines, devices, sensors and people that connect and communicate with one another. It must also include information transparency, in which the systems create a virtual copy of the physical world through sensor data in order to contextualise information, sometimes known as the ‘digital twin’. It should include technical assistance: both the ability of the systems to support humans in making decisions and solving problems, and the ability to assist humans with tasks that are too difficult or unsafe for humans, as with co-bots, or new forms of robotics and automation. Finally, says Forbes, it must include decentralised decision-making ¬¬– the ability of cyber-physical systems to make simple decisions on their own.


Smarter manufacturing

The IIoT is about interconnected systems that allow production systems and individual machines – and even products – to talk to each other, capturing huge volumes of data from the manufacturer and its processes, and the manufacturing supply chain. At Essentra Components this data is already helping engineers understand their manufacturing processes and supply chain in much greater detail than previously possible.

The data can be used for predictive maintenance, for example, helping companies understand what is happening with a machine before a fault occurs. Computer control can mean more reliable and consistent quality levels, and productivity and output. At Essentra Components, some machines are already connected for predictive maintenance purposes.


Improved efficiencies and costs

In general, by becoming more efficient, manufacturers can cut their operational costs. The IIoT will come to rely heavily on sensor technology and sensors that are widely deployed on both machines and within products. This means that machines become sources of data. Companies can collect and analyse information based on real-time data, helping them make quicker, more informed decisions on inventory, labour planning, purchasing and production.

Ultimately, this can improve time to market and lower costs. Improved efficiency is traditionally part of any continuous improvement program, but manufacturers can mine their operations for value, continually improving their processes with the data harnessed. Opportunities previously unknown become apparent, giving them a competitive edge.


Barriers to change

It is only human to resist change. Adjusting employees to new technologies can be difficult, so careful workplace planning for smart manufacturing is essential. There is also already a substantial skills shortage in manufacturing and engineering in the UK, so the skills needed to implement smart manufacturing solutions could be hard to come by. A skills gap in IT already exists worldwide, so recruiting workers for the digital side of smart manufacturing could present a challenge. Britain will need more than 2.2million workers with digital skills by 2020. In the US, 3.5 million jobs in manufacturing are expected to be created over the next decade, but the lack of skilled workers means that 2 million of those jobs will go unfilled. Companies everywhere will have to think about upskilling employees.

Finally, the interconnectivity of Industry 4.0 means a cyber attack could have a devastating impact. Cyber security shouldn’t merely be a priority, but an essential part of the planning and operations of any Industry 4.0 strategy.

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