If ‘digital’ is the most overused buzzword going around that everyone boasts trying it out one way or another, the glorified software works on the basis of the foundation – hardware.
Today, the use of traditional monitoring units that have led to some catastrophes we know about is moving over and giving way to Industrial IoT units: small, smart and connected ‘things’ or hardware that are drops forming a big ocean. That is the ocean of unprecedented insights and far-reaching business benefits.
But the latter two cannot be reached without robust analytics software. That’s because the tremendous amount of data coming in from these sensors across a manufacturing plant have to be sifted, analyzed and transformed into actionable predictions. That is where the power of manufacturing IoT comes in.
Statistics by market research company IDC shows that the IoT spending will increase by 19% in 2018. Let’s take a look at how your industrial enterprise could benefit by using the right Industrial IoT analytics tools.
Understanding the Advantage Industrial IoT Analytics Holds over Traditional Analytics
There are many elements to set up and reap the dividends of a robust IoT framework. You need to have the sensors set up across your supply chain, product and support functions of your manufacturing, and also have the applications that can digest and generate insights and suggest possibilities to enable decision making.
Industrial IoT analytics takes a step ahead of traditional analytics. It collates data and suggests things to do, based on a central design architecture that drives insights from a central hub.
But analytics solutions like IoT in manufacturing adopts a decentralized approach to the analysis, keeping functions separate, and generating insights for each of them. Adapted from a whitepaper by Cognizant, the benefits are immense, considering the massive data sets generated every minute across the manufacturing enterprise.
It would be really irrational if centralized decision-making were applied. In your manufacturing facilities, you would want function or process-targeted insights to be generated instead of plant-wide metrics.
The potential of driving efficiency and monetary benefits are immense: A car manufacturer could track the life of the tyres embedded with sensors and could use that to aggregate the performance of similar-model cars across the region.
Take a broader view, and regulators can estimate the changing performance of tyres, to update safety standards on usage of tyres. In all of this, IoT performance and predictive analytics drives insights specific to improve the performance of tyres.
Predicting Breaking Down Assets, Achieving Hyper-Efficiency
This is one of the first boxes in a checklist of why enterprises adopt Industrial IoT solutions. Industries cannot allow even marginal loss of production, which can run into thousands, if not millions of dollars, opening up a window for competitors to capitalize.
That’s why forecasting points of failure in advance is key to schedule maintenance or replace ageing parts. Since manufacturing is a connected process, where interruption in one chain or function causes a domino effect across the entire production process, the power of predictive Industrial IoT analytics comes into play.
Even from a macro-view, if an equipment breaks in your factory, the products don’t reach the warehouse, can’t be shipped on time to the retailer, who in turn cannot sell them. All of this has a direct impact on the business.
Tyre maker Michelin uses sensors in the tyres they manufacture, both to alert drivers of high wear-and-tear, as well as to optimize their driving to improve tyre life.
A 37$ billion heavy equipment maker called John Deere now has sensors installed on all its tractors across the world.
The tractor helps the farmer monitor its performance, and identify a potential failure a month in advance. It helps the farm to plan a solution to avoid any significant disruptions.
The manufacturer worked with an industrial IoT manufacturing analytics provider from Bengaluru and has plans to scale up its predictive capabilities even further.
It Is Overhauling All Industries, Although The Scale of Adoption Is Not Uniform
Gartner cites about 6.4 billion things were in use during 2016, and the growth trajectory is steep. Last year, it expected around 5.5 million devices to be installed every day across the world.
Now that is a staggering figure, which conveys the enormous benefits that are having payoffs not just across functions, but across industries too.
Industrial IoT for large-scale enterprises can be applied across sectors, as long as there are stages and processes where raw material is converted to usable end-products.
In healthcare, equipments are being equipped with sensors to monitor performance, especially those that are life-supporting, where failure is not an option. In logistics and packaging, sensors on shelves and holding areas communicate with robotic carriers as well as personnel, to locate and manage items.
Manufacturing IoT helps discrete manufacturers build more robust versions of products, based on earlier learnings and finding faulty products to pull them off the assembly line before they are shipped.
Through this, assets are becoming more productive, and IoT analytics are identifying supply-chain gaps that could become unexpected growth drivers for a manufacturing facility like yours.
This growth, though uneven across industries is expected to balance out soon, as the awareness of this technology increases steadily.
Delivering Tailored Offerings For Client’s Changing Business Needs
The customers want things their way, and they want it now. We live in a world where brands who provide products consistently, and can detect and meet changing demands are the straight winners.
If you are surprised that this is talked about in the context of large-scale processes that roll out the same products over a hundred thousand times in a day, the Industry 4.0 is here, characterized by large application of Industrial IoT, and a connected networked of devices and measuring systems.
With the world moving towards an outcome economy, where meeting outcomes is taking the place of fulfilling needs, the enterprise sector has to evolve to match these outcomes. Look at what Harley Davidson did, for instance. It revamped its Pennsylvania facility, equipping it with sensors and location beacons to accelerate its manufacturing towards a customized product line.
Today, the factory has reduced its lead-time from 21-days to six hours, where none of the bikes look similar. Data flows in from 1,000 configuration choices customers can make, and the exact version is rolled out to that customer.
The power of industrial IoT manufacturing reveals itself when Harley rolls out a customized bike every 89 seconds. That’s massive, and shows how your customer requirements can be fed in to offer more tailored offerings. Even crafting products according to customer groups can be a great place to start.
Applying sophisticated Industrial IoT analytics at the source of the product chain itself, i.e. at the manufacturing phase is the key to mitigating many problems that wreak havoc later during the product lifecycle. But this doesn’t mean stripping the current checks and measures that are already in place, like meters and monitoring controls, with IoT.
A middle path to drive new age technologies by internet of things in industrial automation on top of legacy systems can leverage the capabilities of both. And though Industrial IoT analytics might not garner the recognized status of retail or small-scale analytics, the future can be created today itself
Look at the data from a research by IDC – 55% of discrete manufacturers have already taken efforts in IoT initiatives, like research and adoption.
And it is no surprise that manufacturing grabs one-fourth of the total IoT market. ABB, a connected device giant, and Hewlett Packard Enterprise are joining forces to provide combined solutions, leveraging their expertise in operations and information technology respectively.
With competition on rise, it’s time to discover the real potential of Industrial IoT analytics for your industrial facilities.