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The fastest way for manufacturers to achieve growth in a new world of industrial connectivity is to leverage new technologies.
A transition to automated data and process management is irrefutable, and while this heralds smart supply chains that bring enhanced agility, productivity and profitability, many are adopting a "wait and see" approach.
Industry 4.0 is one of the five areas the UK government plans to focus on developing in a bid to boost the post-Brexit British economy. This came after the announcement that £4.7 billion would be available for research and development into robots, artificial intelligence, 5G mobile technology and smart energy.
Only 11% of UK manufacturers think the UK is geared up to take advantage of the fourth industrial evolution, which begs the question: why are we still so hesitant about its implementation?
In this article, we look at the four key concerns for manufacturers and aim to eradicate any fears surrounding your transition.
As the PwC Annual Survey suggests, "The biggest challenge for industrial leaders isn't technology – it's the people."
The future is not complete automation; this is simply not realistic. There will still be a great need for human intervention and supervision.
Training programs may need a rethink and recruitment processes will need tweaking. This causes concern for those in higher management and HR.
In fact, a need for re-training could become a lucrative business itself with the potential introduction of learning factories.
It's natural for employees to feel intimidated by new technologies and AI (artificial intelligence) that could inevitably replace them. This increases the pressure on CEOs and HR departments. But we can be safe in the knowledge that the role of the workforce is evolving, rather than vanishing.
Skilled individuals and teams will become multi-disciplined and develop skillsets in more challenging areas. Rather than performing mundane tasks, their skillsets will be developed to oversee and coordinate production.
There are many skills machines can’t emulate, such as critical thinking, management of complex situations and emotional intelligence. By preparing new training schemes that empower employees to embrace and develop Industry 4.0 technologies, they become more open to change, able to adapt to new roles and working environments and accustomed to continuous interdisciplinary learning.
Health and Safety
With a highly adaptable workspace comes new health and safety risks. Health and safety is at the heart of any employer's risk assessments and new machinery implementation.
Risk assessments of equipment will now have to be more rigorous than ever, taking into account all aspects, from individual components right through to operator ‘touch points’.
Safety sensors are also available, where the system can immediately sense if a human operator has moved into an unsafe area or is in a hazardous position. Innovative programming can allow the machinery to slow down to safe speed, or power down completely to allow the individual to move away from the hazard.
Much of the new equipment and machinery introduced during the transition will be built with safety features. For example, compatible drives which can be used to create a machine protocol with a unique number, highlighting immediately a potential safety issue if a different protocol is used. Look out for these where feasible to minimize risks and the need for intensive testing.
Today, according to Gartner, there are five billion connected devices worldwide. This is monumental progression for industrial connectivity.
But with increased connectivity comes the increased risk of cyber threats. And with innovations such as remote control of machinery and robotics, it creates opportunities for remote hackers.
The risks of data and manipulation affecting your entire supply chain are heightened.
This can be managed by asking your EMS provider if they have an auditable security policy and can demonstrate how your IP will be kept safe and secure.
If and where possible, select equipment and software with built in safety features.
The thought of AI has many business owners hot under the collar. Cost, maintenance, and the unknown potential of machine-to-machine communication… it can all seem a bit out of reach—a bit sci-fi, even.
With almost half the chief executives questioned as a part of PwC’s annual survey, expressing concerns that investors, employees and the wider public would distrust the concept, it’s not surprising that many remain cautious.
As new technologies emerge, they tend to have a ripple effect on other areas within the industry. The wrong approach could set a company up financial, operational and reputational damage.
Smart robots and digital twinning for example, are making it a possibility for engineers to control, amend and test operational equipment remotely. But how can you guarantee your systems will communicate with each other effectively?
With a robust quality management system in place, you can identify and avoid damaging scenarios and abnormalities before they take place. The end goal is acceleration through introducing exponential technologies—welcoming processes that let machines do the work for us, but where humans ultimately maintain the control. Employers and employees need to be quick to learn if we are to successfully implement and control such intelligence systems.
Rather than adopting the ‘wait and see’ approach—which could see you fall behind competitors in the long run—keep an eye on competitors and monitor new technologies to see how they can be used to improve delivery customer satisfaction and efficiencies within your own production lines.
Of course, manufacturers are inherently cautious. But we advise you take the ‘think big, start small’ approach. Transition is still a work-in-progress for many. Start testing new methods and technologies to and stay up to date with the market. This will equip you with the information to tackle any concerns head on, reassuring your employees, stakeholders and customers along the way.
This article originally appeared on the JJS Manufacturing blog, which can be found here.