Making the shift from smart factories to living services
The Industrial Internet of Things (IIoT) is transforming the way manufacturers approach matters such as resource allocation, production processes and the workforce. In time, companies will gain even more benefits from the highly automated, end-to-end production integration of intelligent products and services made possible by the IIoT. Edy Liongosari, chief research scientist and managing director at Accenture Labs, talks about critical trends and uncovers advantages that have yet to be widely discussed.
Operational safety and efficiency are two of the most clear-cut advantages the IIoT brings from the outset. Edy Liongosari believes those are the obvious ones because the return on investment of such initiatives is much simpler to calculate and measure. “When we talk about new products and services, however, the business cases are typically built with a lot of assumptions. Therefore, the confidence on those business cases is lower. But that’s exactly where the big opportunities are.”
Liongosari says that safety and efficiency are just part of the first of four waves of IIoT adoption. The next wave – which he believes has greater transformational impact – consists of the creation of smart products and smart services. “It’s vital to consider how you are going to be able to use the physical products that you have and to think about the product as a way – as a channel if you will – to sell and deliver what we call living services,” he shares.
Living services are contextually aware digital services designed to anticipate and respond to customer needs in real-time through the channel that you have. Liongosari mentions one example that emerged from the IOT Solutions World Congress in 2016: Bigbelly is a connected trash bin that knows exactly when to compact waste and when to unload it. He also cites Claas, the German agricultural machinery manufacturer that has partnered with the free field mapping service 365FarmNet. Together the two use their respective fields of expertise to bring about precision farming, in turn driving the future of agriculture.
A universal standard
In a manufacturing setting, thanks to the convergence of Operational Technology and Information Technology, manufacturing equipment is increasingly connected with larger enterprise systems – from manufacturing execution systems, production management, logistics and enterprise resource planning systems – to allow manufacturers to plan, monitor and adjust their production in real-time.
Liongosari, however, is of the opinion that a universal standard to allow equipment from multiple vendors to communicate and collaborate will not become the norm, at least not in the short term. “It’s primarily because of the diversity of the use cases, environmental conditions, and laws and regulations that fall under the IIoT. For example, the diversity of IIoT infrastructure requirements such as energy consumption, computing and bandwidth availability, mobility and security makes it very hard to have just one sole industry standard,” he explains. However, there are plenty of efforts to make specific IIoT standards to interoperate – to the extent it can be reasonably done – through a variety of testbeds.
“You can see the borders between various industries slowly disappearing because a lot of newcomers are coming to your game very, very quickly. The possibility is really big.”
According to Liongosari, there are four key trends impacting the IIoT. The first deals with automation and artificial intelligence (AI). Our ability to automate or augment work processes using machine intelligence can now be done at the unprecedented scale and precision through the use of AI techniques.
In an automotive manufacturing plant, for example, cameras can be used to learn and detect refined defects in a product. Rather than wait for a batch run to be completed before defects are found, those can be detected in real-time. “Sometimes you don’t realize the presence of small defects until much later on, resulting in a significant loss of work,” he explains, adding that in many cases, existing surveillance cameras can be repurposed for defect prevention in quality assurance by embedding some intelligence in them. “This is what we call the next generation of automation.”
The second key trend is about human and machine interaction. “The industrial workforce itself is changing significantly,” he says. A human workforce is augmented with wearable computing capabilities to significantly increase their efficiency as well as agility, allowing them to take on new tasks at the speed like never before. In addition, collaborative robots – or cobots – that have been used for hospitality and concierge services, are now being expanded to perform simple and repetitive tasks on the factory floor, such as those in Amazon’s warehouses.
The third comprises platforms and ecosystems. “One critical element of smart products is their ability to sense, configure, and respond based on the needs of the customers,” states Liongosari. “It’s not just selling your products and services but the ability to turn the product itself into a platform – just like in Android or iOS – to allow others to build upon it and use it to build a set of rich and interconnected living services provided by a lush ecosystem of business partners.”
The last key trend is cybersecurity, which is rising in importance due to vulnerabilities to attacks, espionage and data breaches brought about by increased connectivity and data sharing. Liongosari brings up the denial of service attack by a Mirai-based botnet that affected IoT devices in September 2016 as a reminder of the importance of cybersecurity in this highly interconnected world.
“In addition to security, privacy and data ethics are increasingly critical especially given the vast amount of customers’ and employees’ data that companies now have access to. In some cases, the concept of data ownership in an organization is being seriously questioned as ownership implies that the organization can do whatever it wants with the data,” says Liongosari.
The use of such data is highly dependent on many factors beyond data privacy laws and regulations. For example, organizations need to factor in the original intention of data when it was provided or captured, ethical interpretation of the analyzed data, and how the results are being used and shared ethically. “How are you going to interpret data uniformly across different countries, laws, interpretations and usages? The meaning of data ownership may change or the term may completely disappear.”
Seizing the opportunity
In order for manufacturers to chart a path of growth through the IIoT, Liongosari offers sound advice. “You can start small in a sense that you can focus on operational efficiency – that there is a specific return on investment that you drive toward. But at the same time, you need to think big because the opportunity is a considerable one,” he says.
“You can see the borders between various industries slowly disappearing because a lot of newcomers are coming to your game very, very quickly. The possibility is really big.” To seize the opportunities of the Industrial Internet of Things, Liongosari sums it up with this mantra: “Start small, think big, and iterate fast.”
Edy Liongosari works as chief research scientist and managing director at Accenture Labs
Image credit: Zapp2Photo / Shutterstock.com