IIoT and the 4th industrial revolution
Connected devices and sensors, robotics, immersive reality and artificial intelligence are changing the world at an unprecedented speed, bringing a new level of technological sophistication. Analysts regard the IoT tidal wave as the 4th industrial revolution and for a good reason: after the birth and rise of the internet, IoT looks like the hottest thing for enterprises.
Last year’s predictions showed that in 2020 more than 20 billion devices will be on the IoT and the IoT product and service suppliers will surpass the $320 billion mark in revenue. The presumption is that IIoT will continue to have a big impact on industrial productivity and cost savings in the years to come, a study by Capgemini Digital Transformation Institute showing that more than 60% of the industrial-manufacturing sector is using IoT technology in operations and that number is almost sure to rise in the coming months. So IIoT is on everybody’s lips for a good reason right now. But also for a bad one.
It’s not only the hype of a new El Dorado for enterprises but the fact that the promised potential, in the internal operational sphere, is often going unrealized. “At many organizations, IoT initiatives designed to optimize operations do not achieve their goals or reach meaningful scale” found the Capgemini study, with “six out of ten organizations failing to take operational IoT initiatives past proof-of-concept stage or beyond implementation at one or two sites.”
The causes for all these are: the security concerns, no clear business case for the investment, a lack of analytical capabilities and uncertainty about IoT standards and protocols.
A few 2020 trends
Reaping the fruits of AI, robotics, and other revolutionary technologies requires means bringing together sensors, connectivity, cloud storage, processing, analytics and machine learning to transform business models and processes. Of course, all these require careful planning and significant effort across key areas of business processes and strategy.
One of the issues that arose in the last years is that the IT infrastructures needed to support the IIoT systems are obsolete. Assuming otherwise puts businesses at risk.
This brings us to the first trend we can identify for 2020 and that is the continuing importance of Edge Computing. With more IIoT devices in service on the factory floor, traditional cloud computing just can’t keep up so working with data at the device level performance is maximized, costs minimized and also the overall latency is improved. 5g speed will make edge computing even more valuable to the industry.
Manufacturing is at the forefront of this technology, as it allows businesses to differentiate their products and services from competitors while establishing new revenue streams. This brings us to the next trend, the Digital Twins. As more factories adopt IIoT, AI and machine learning, a virtual representation of a physical device or object is used to simulate processes and streamline production. The digital twin allows research-and-development teams to gather data to simulate physical objects in real-time situation and today 75% of organizations are taking advantage of IoT by using digital twins or are in the process of deploying it, according to Gartner.
IIoT also needs a robust cloud, which is leading to more reliance on managed cloud services in manufacturing, which can be named as the 3rd trend for 2020. These managed cloud services can be designated for specific device and data management, generating valuable and useful insights about connected products in manufacturing environments.
AWS, Google Cloud and Microsoft Azure are supporting this trend and IoT data platforms are quickly connecting, too.
Machine learning and AI have been trending upwards in the past couple of years and it’s certain we’ll see a greater connection between AI and IIoT. AI will drive and improve the IoT’s decision-making process by pushing computationally intensive analytics to the edge for scale and performance.
Finally, the 5th trend regards the human resource. While automation will continue to shift plant personnel roles away from dull, repetitive tasks, employees will move on to decision-making roles based on data support.
No need to worry though: machines aren’t replacing humans yet. Instead, there’s a new synergy between human and machines streamlining production and processes.
Human workers need to think differently on the job and that will require an on-going effort to train employees for often high-tech tasks in order to have successful IoT deployments. And that, of course, means investing time, money and energy to ensure that things go smoothly.
Applications and challenges
IoT applications in healthcare, autonomous vehicles and the intelligent enterprise continued to be the hot topics in the past years, industry leaders argue.
We already have success stories of agro-tech companies shifting models and specializing in post-harvest shelf-life and freshness management, improving product margins and profitability, from growers to retailers, all along the supply chain, not to mention reducing food waste, costing only the US $218 billions per year.
The suppliers and retailers are helped to manage the freshness and quality as well as the tracking and the traceability by use of sensor-based technologies.
The healthcare system is an important beneficiary of these new technologies, too; advances in IoT-connected biotechnology will take healthcare to the next level, with around-the-clock monitoring, targeted treatment and even automated doses of medication. Then, in the intelligent enterprise, “the IoT will connect the global supply chain from end-to-end, enabling pervasive visibility, proactive replenishment, and predictive maintenance”, says Mark J. Barrenechea, CEO and CTO at OpenText.
All these will bring us to the point where IoT will become the new standard in decision making around industries and in our everyday life.
A successful implementation comes from Harley Davidson, the leading global motorcycle manufacturer. It invested in a fully IoT-enabled plant, connecting key processes and devices in their production process on a single network. The impact was significant: operating costs dropped by $200 million, downtime reduced, and production efficiency went up. The company was also able to reduce its build-to-order cycle by a factor of 36, and grow overall profitability by 3% to 4%. Overall, the company became more operationally efficient and was able to respond to customers’ needs faster. While the IoT can bring these sorts of transformational benefits, many businesses are still grappling with how IoT applications can reach the scale required to maximize ROI.
But beware, because where lies the opportunity also lies the peril. Infrastructure automation specialists warn that the staggering rate that companies are deploying IoT sensors brings vast amounts of data when tracking things in real-time. This ensues that companies need to implement technology that can handle the constant stream of data in addition to looking at more effective ways to analyze that data in order to get actionable insight.
Analysts also believe that IoT will move from still being seen as a massive security risk for an enterprise, to a critical part of its success.
Industry 4.0 revolves around advances in technology. AI, edge computing, virtual testing and IIoT are all important drivers of the new manufacturing plant. Once the security issues that could undermine IoT progress will be dealt with, companies will be on track to take full advantage of this revolutionary technology.