Angelo Hulshout is an experienced independent software craftsman and a member of the Brainport High Tech Software Cluster.

13 January

Angelo Hulshout has the ambition to bring the benefits of production agility to the market and set up a new business around that. At the start of a new year, he’s going back to the basics.

Over the past year, I’ve been filling up space here with seemingly random bits of information and experiences I got from the first steps of Shinchoku in the world of smart industry. This year, this is going to continue, but in a slightly different way – a bit more structured, to reflect the structure that’s slowly growing inside and around our business as well.

When starting something new, it’s very tempting to just shoot arrows in random directions and see if you hit anything. That’s not exactly what we did – luckily, our team is experienced enough to avoid that – but we have been wandering left and right a bit. That’s changing now, and that change will be reflected in my articles as well.

Fitting selection

First, I’ll be going back to the basics: what’s smart industry? Why is it important? And what is and isn’t part of it? Over the coming months, I’ll be addressing topics related to these three points, to create a better overview of smart industry for myself and my audience. If I can do that in a structured enough way, it may even result in a book, but let’s put that aside for now.

It’s not so hard to see why this is useful or may be useful for at least some of us: whenever smart industry, Industry 4.0 or smart factories are mentioned, a whole list of technologies is being dragged in as ‘essential’: big data, robots, internet of things, the cloud, machine learning, artificial intelligence, digital twins – to name a few common ones.

All of these technologies are useful, and all of them certainly relate to smart industry. However, reading such articles and blog posts might give the impression that they are smart industry, or at least the silver bullet to achieving it. That’s of course a very strong, slightly exaggerated statement, but since a lot of articles and blog posts are written by people specializing in one of these subjects, this wrong impression can easily arise.

Yes, smart industry is about technology, and it’s about automation. However, it’s not about any of these individual technical solutions we read and talk about – it’s about integral solutions, where a fitting selection of technologies must be made to solve a problem. Also, making industry smarter isn’t just about making more money in production; it’s also about reducing waste and being a bit more careful with our planet – finding a balance between the financial and environmental sides.

Data extraction

Being smarter, regardless of which goal is more important, depends on information, extracted from data. This is the common part of all technical solutions for smart industry: it relies on data extracted from production equipment, planning and tracking systems (MES), financial figures, energy consumption and many other sources. Without this data, putting robots, dashboards or machine learning algorithms in place is useless.

So, we need means to extract data from the factory to make it work. Then we can derive metrics to put on a dashboard, introduce algorithms to interpret the data and use digital twins to predict the effect of changes by extracting data from simulations. In the coming articles, I’ll go over the most important facets of smart industry, starting with data extraction. Care to join?

Edited by Nieke Roos