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Top 5 Digital Transformation Trends In Manufacturing For 2020

02 Oct 2019
Top 5 Digital Transformation Trends In Manufacturing For 2020
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One of the most appealing things about digital transformation is that it moves quickly — and slowly — all at the same time. The tendencies we see on the horizon for Industry 4.0 in 2020 are quite similar as trends that we've seen growing … revolutionizing … during the last few years. The difference is not so much in the technology, it’s in the number of companies beginning to utilize it, and the reasons why.
 
Case in point: the Internet of Things. Technologists, have been talking about the enormous IoT benefit for manufacturing, literally, for some time. Going into the 2020s, however, it’s not only the technologists that are spouting the benefits. It is the manufacturing companies themselves discerning the significant affect of connecting one’s work and processes to the IoT. It is also the significantly demanding consumers who want higher quality goods, often with responsible manufacturing practice, right now this very moment. If there’s one thing that’s clear, it’s that manufacturers will be experiencing increasing pressures in cost, efficiency and quality in the coming decade. And in addition they're finding that new tech adoption—be it IoT, 5G, AI, enterprise resource planning, or VR/AR training—is the only way to survive.
 
The following are some of the biggest technologies continuing to expand in 2020, and the factors why.
 
Internet of Things: Less I and More AI
 
First, can we all celebrate the fact that we've (basically) dropped the additional I from the IIoT? Increasingly, digitization isn’t happening by industry — it is taking place everywhere. The IoT used in manufacturing overlaps at innumerable points with IoT in retail, consumer goods, healthcare, martech, and simply about everything else. In fact, the continuous interplay of all those avenues of data and connectivity are providing exceedingly important insights that are changing the way manufacturing is being run. Besides that, we are seeing a convergence of AI and IoT, with some companies like SAS Software touting AIoT as the next wave for IoT based on Gartner’s prediction of more than 80% of IoT projects encompassing AI.
 
For instance, yes, the IoT promises cost savings. It helps provide insights on processes, costs, productivity, etc. But in the mean time, it is also providing information about the supply chain — the quality of parts and products being used, where they came from, and how they were grown, bought, or created. More and more, customers are demanding that the things they buy are manufactured responsibly. And manufacturers — not just for brands selling the products being manufactured — are being held accountable for those details thanks to the IoT.
 
Research from MPI Group have discovered approximately 70% of manufacturers credit the IoT with elevating their profitability. Research reveals manufacturing companies will invest some $267 billion by 2020. Clearly, they are starting to get the message that the technology can provide incredible value for them. Another noteworthy data point is that 90% of manufacturing companies in the United States today have fewer than 500 employees, according to the National Association of Manufacturers. Will they have the capacity to invest in, and support employees knowledgeable of, the IoT? It is questionable. And also it may be the one thing that causes small manufacturers to drop out of the digital transformation game altogether.
 
Predictive Everything
 
Research reveals a single hour of downtime can equate to $100,000 in losses in a manufacturing environment. Using data, AI, and predictive analytic, some say manufacturers can reduce planned outages by 50%. IBM says it can even reduce unplanned outage by 15%. Predictive analytics help companies better understand how their machine work, and why they fail, which allows them to prevent those failures altogether. Going forward: not just a nice to have, but a must-have for manufacturing environments.
 
Definitely, manufacturers today are operating in an environment that is full of risks and unknowns — how will the market change? How will it be damaged? Where will their business take them, geographically? Will they be able to find partners in those areas that share the same level of commitment to quality as they do? With so many global variables at hand, predictive analytics can help manufacturers make better, smarter, faster, and less risky decisions about everything from machine maintenance to supply chain optimization, all of which impacts customer experience; from the quality of goods produced to when customers receive orders.
 
5G
 
Yes, we are now ultimately hitting an age when 5G will play a role in improving (reducing) latency, providing high bandwidth, and allow for quality realtime communication on an extensive scale. With 5G, manufacturers can begin to improve their use of sensor, cloud, centralized tracking, quality inspection, etc., forming an “ecosystem” of smart manufacturing. Absolutely, we may see an ever growing disparity between 5G have and have-nots in 2020 (much like IoT). But it will certainly play a bigger role in smart manufacturing moving forward.
 
The big trends in the digital transformation of manufacturing are likely to be rounded out with technology like 3-D printing will continue to allow companies to make faster, cheaper prototypes while AR and VR will continue to allow for better, safer training across the board. These are not really new trends, but rather areas of continuous improvement for manufacturing.
 
It is essential to also reiterate the growing connectedness of consumer demands that will play a way more significant role in changing manufacturing for the better in the coming year than those technologies themselves. Today, every company is here to serve the customer, no matter how far away from the customer they may have functioned in the past. Transformational trends such as the (A)IoT and 5G will force them to do that even more in the coming decade. It will also make that level of accountability possible.
 

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