In the last decade, companies have faced rapidly changing customer requirements, combined with supply chain chaos. Pair that with cultural shifts in working arrangements, and manufacturers everywhere are looking for the technology they can depend on to see them through the turbulent world of modern business. But what are the specific challenges that Industry 4.0 helps tackle?
Companies that can implement Industry 4.0 at scale are restructuring their businesses to face today’s biggest business challenges. But if you are thinking of investing in Industry 4.0 what can you expect of it, and what problems will it really deal with? We’re glad you asked, and to answer that nice and quickly – it’s one of the best investments manufacturers can make. Let us show why.
There are three key challenges that production and manufacturing businesses face today. In no particular order, they are: financial challenges, organizational issues, and technological roadblocks. Interestingly, these challenges are what plague almost every sector with almost any event, and the same is true with Industry 4.0. While it can help to alleviate these three common challenges, it is in itself challenged by them when businesses try to make it a reality.
In a recent study, McKinsey found that “74 percent of cloud-related transformations fail to capture expected savings or business value”. The same survey also found that almost half of all surveyed organizations found cloud technology to be more complex than they expected. Another 40% overran their cloud budgets — some to a “significant degree”. Those findings alone demonstrate precisely what we’re talking about.
Thankfully, the lure of Industry 4.0 is its power to help solve fundamental problems in the world of manufacturing. New technologies, as well as the ways in which they can be interconnected, are giving rise to wider and wider adoption.
The right data can be a crucial part of designing automated systems that save you time, money, and headaches. Instead of just looking at data on a chart and coming up with interpretations, you can use machine learning to raise red flags and conduct predictive analytics that keep you one step ahead at all times.
One of the primary advancements we’re seeing on the shop floor is automated data collection. Having visibility into what’s taking place — like work orders, sales orders, and items in production — and what still needs to happen can make it much easier to make informed decisions throughout the manufacturing process.
Another innovation in the production process is robotic process automation (RPA). With this approach, anything that’s a repetitive, manual task is automated, freeing your people up to do more important and strategic tasks. As you implement this technology, however, you and your team will be responsible for “educating” the system about what to do in each scenario that might present itself.
One of our customers had IoT sensors on their HVAC systems, and they wanted our help to create a dashboard so that they could see real-time performance data and take action as needed. A building or real estate complex with multiple HVAC systems could be continuously analyzing data from the machines themselves, from weather forecasts, and from other HVAC systems in nearby buildings.
These data points would all feed into their analytics platform, providing automated decisions on when to run the HVAC system, when to store its energy, and when it might be underperforming or in need of maintenance. This is a fantastic way of keeping tabs on assets through a digital lens, rather than the resource heavy manual checks that many companies rely on.
A great example of AI inspection systems is optical recognition platforms that inspect items and use AI/ML to find flaws in manufactured parts or in components brought in from suppliers. By getting machines to make these judgments you can improve the quality process, both in terms of checking the time, and also in the consistency of checks made. Your people can then deal with the edge cases that will always exist, and use their skills and experience to add value where it’s needed most.
A company can also decrease the time to market of a new product with 3D additive prototyping. An AI tool can be built to create product mock-ups and prototypes with small variations, and do so far quicker than a team of people would be able to.
Once in the cloud, you’ll be able to leverage its benefits further to improve shop floor efficiency, use data to drive critical decision-making, and achieve a number of other digital outcomes. For example, Johnson & Johnson’s expanding partnership with Microsoft has driven its digital transformation. Initially selected for its ability to scale solutions to meet the needs of one of the world’s largest companies, Microsoft’s cloud services and expertise in diverse technologies, edge devices, IoT, machine learning (ML), and AI have enabled J&J to successfully transform into a digitally driven manufacturer.
With Azure, manufacturers have been able to leverage cloud, data, and AI to dramatically increase margin, operating income, and net income on revenue. By actualizing your data estate as a strategic asset, you’ll be able to drive efficiency, improve accuracy, and empower quality decision-making through heightened visibility.
We’ve barely scratched the surface of what Industry 4.0 can do, and how critical a handle on your data and systems is in making it a success. But, if you work with an expert these are the sorts of initiatives that you can roll, help your business cut costs, optimize your organization, and work with modern technology that will continue to power your business.
Want to bring Industry 4.0 into your business? Find out how InTWO can help, today.
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