It was the year Marilyn Monroe died and John Glenn became the first American to orbit the earth. The year 1962 was a standout year, not because of the Cuban missile crisis or The Beatles releasing their first single Love Me Do, but because of something much less glamorous but hugely significant to modern industry and living.
In a General Motors factory in West Trenton, New Jersey, UNIMATE, the world’s first industrial robot went online, performing spot welding and die castings. It was a moment of history, something which would ultimately change the face of manufacturing forever.
Today automation of some kind in factories is expected, at least among the larger manufacturers. Making anything on a grand scale demands it and businesses are increasingly attuned to the potential benefits.
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Three years ago a Boston Consulting report claimed that 72% of US manufacturers with sales of at least $1 billion said they were investing in additional automation or advanced manufacturing technologies. In just three years, there has been significant change. It’s not just large businesses that are now interested, it’s SMEs too and not just in the US either.
In the Industrial Internet Age, automation, robotics, and intelligent sensors and analytics are becoming commonplace. By 2019, more than 1.4 million new industrial robots will be installed in factories around the world, at least according to the 2016 World Robotics Report published by the International Federation of Robotics (IFR).
“In the race for automation in manufacturing, the European Union is currently one of the global frontrunners,” says the report. “65 percent of countries with an above-average number of industrial robots per 10,000 employees, are located in the EU. Outside of Europe, the strongest growth drivers for the robotics industry are found in China. In 2019, some 40 percent of the worldwide market volume of industrial robots will be sold there alone.”
There is no denying the global potential. Robots, sensors and all the harvested big data offer a sweet shop of opportunity, to drive down costs, improve performance, reduce environmental impacts and ultimately boost the quality and accuracy of everything made. That’s the vision, one built on widely available tools to aid analysis and prediction.
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We call it ‘brilliant’, a sort of super smartness that glues everything together and it can have the sort of impact on industry that UNIMATE had in 1962. We are truly in a new age of industrial change.
In the not too distant future, our supply chains will become self-improving, agile, connected and communicative – operating through a digital thread in real time. By collecting terabytes of data and driving the right decisions every day, we will be better able to optimise processes, costs, quality and condition-based maintenance.
We’re already seeing several industries where sensors are playing a big part in improving efficiencies. Gas turbines are a great example with a mixture of 400 physical and virtual sensors monitoring performance and temperatures and provide early warning on potential failures.
It is this aspect of automation that can have a wider impact. While factory robots and sensors improve performance and efficient manufacturing, they can also improve the accuracy of field service support.
As the factories get smarter, more brilliant, so do the service engineers. For example, they have remote insight into how machines are performing, access to analytics and predictive, pre-emptive maintenance, and ability to use a digital twin for training and diagnostic purposes, which is good news for the end customer as they want the product to work better for longer for the very lowest whole life cost. And good news for the service techs, as they can work on smarter more strategic things, and make smarter use of their time.
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Simply put when a product leaves the brilliant factory so does its digital DNA by virtue of all the data associated with the batch and serial number. This provides the installation and service engineers immediate access to data collected from within the design and creation phase of the products (assets) life such as complex asset assembly as illustrated by a digital twin.
So how does it work? It comes down to intelligence. Understanding what the data is telling you is the secret to understanding the next move. For service technicians that’s gold dust as it means predictive analysis – the ability to see problems before they occur and in some instances, stop them occurring either remotely or on site.
Understanding the problem before a site visit can also mean accuracy in sourcing the correct parts, reducing travel time, customer downtime and cost savings, as well of course, happy customers.
Service engineers using their skills and experience are also contributing to the knowledge of the product (asset) while it is in-service. This knowledge is organically captured and used to enhance the data set from which further algorithmic insight can be gained and provided to the service engineer to assist diagnostic or safety validation.
Servitisation, in combination with the sort of industrial automation and brilliant factory approaches we are talking about, will offer businesses a profit centre like no other. This will become the frontline for organisations keen to improve their field service support, customer retention and the cost of their inventory.
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At a time when businesses are looking to take greater control over their manufacturing costs in the face of unpredictable economies, reducing costs by as much as 40% (a GE prediction based on experience) in the factory will have a huge impact. Throw in the potential of a service centre becoming a profit centre and you have a recipe for a modern industrial business.
If history has taught us anything, it is that industrial change benefits the brave. George Devol and Joseph Engelberger’s New Jersey robotic vision has come a long way but with the level of smart industrial technology we have today, we can make our own history.
Sourced by Mark Homer is vice president Global Customer Transformation for ServiceMax
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