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Fast and Furious Technology: From HFT to IoT

The conditions for the new machinery are getting stricter and the commissioning of new production lines by manufacturers is getting harder and harder. Hence comes the idea of adding an IoT platform to the production machines so that conditions during commissioning can be monitored precisely. This means that commissioning goes faster with less effort and the end result should be that the manufacturers get paid sooner rather than later. 

The next step for the company is predictive maintenance—being able to sell the machine with guaranteed overall equipment effectiveness (OEE) or deliver a maintenance service with minimum effort. Being able to guarantee uptime is of strategic importance during sales negotiations. The owner of the company mentioned that these types of projects are so important that the company’s future depends on it.

However, the third and final step is what attracted my attention. The company came to the realization that once it adds an IoT platform to its machines, the data is not only relevant for them, but also for the bakeries. Properly presented, the data can give valuable insights in quality control questions. For example, if bread comes out burned, you might want to figure out what went on 20 minutes before, and if you know that those conditions are harmful, you can try to spot them in time or prevent them.

And then a challenge presented itself, one somewhat similar to what the HFT traders had. The CEO said that it might sound strange coming from a man who has been selling ovens for decades: “We know how to bend steel and how to put a fire into it, but how you get a loaf of bread out of it—I don’t have the faintest idea.”

Building a Relevant Platform

So maybe companies know that getting the platform right is the key to their success and to opening up whole new business models. But, at the same time, it is so difficult because the recipes for that success are guarded as if they are the queen’s crown jewels. If a company has very little expertise in data science, how does it build up a relevant platform? 

These are challenging questions that can overwhelm most companies if taken on all at the same time. However, with an understanding of IoT technology, there are ways to address the challenges successfully.

First, you have to make sure you conquer the technical expertise required for IoT. Many companies are tempted to do R&D on how to acquire connectivity skills, and end up building device connectivity and management functionality themselves. Don’t fall into that trap; these features are not strategic anymore as they can be purchased off the shelf. Take time to evaluate IoT platforms and select one that is modular and future-proofed. 

Be on the lookout for a low-code environment that not only can connect any device, sensor, or machine over any network and provides flexible choices with SaaS, PaaS, on-premise, hybrid, or edge deployment, but also comes with solutions for enterprise integration, API management, and is prepared to support you in your advanced analytical needs. In this way, you will be independent enough to avoid vender lock-in and can grow in the direction you want to in the future.

Low code means that the technology allows you to start up rapidly, registering and connecting devices in minutes with easy-to-use control panels to set up rules for situations in your organization.

Make sure that you evaluate your deployment architecture. Although going cloud is the fashion, there is a realization dawning in IIOT that having a distributed architecture is better suited to dealing with the physical challenges the real world throws at you. So make sure that your platform can run in the cloud but also supports the edge in such a way that analytical decisions which influence the continuity of operations can be taken at all times, even with intermittent connection to the internet.

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