Why digital is becoming 'business as usual' in manufacturing

I was privileged recently to participate in a series of Roundtable discussions, hosted by Henrik von Scheel, on the topic of ‘Digital Ambition in Manufacturing’ with some of the UK’s great manufacturing organisations including: Astra Zeneca, BAE, Dyson, GlaxoSmithKline, Jaguar Land Rover, Megger, Mettler Toledo, Roll Royce, and Toyota to name just a few.

It was clear from the 5 individual group sessions that this topic is of great interest to all these companies. It revealed some interesting pointers as to where we all are in this journey and even a little twist I wasn’t expecting to hear.

To sum it up, one company put it so succinctly I used it as this article’s title.

Digital’s no longer a choice, it’s just a question of pace.

How far do you go?

Well, guess what, it’s that never-ending journey of continuous improvement again, some things are just constants. What we do know is we are all starting from different positions and infrastructure maturity and that needs managing. Green field sites offer the chance to create the ‘template’ and then the legacy sites are advised to cherry pick from the template as their needs will permit without breaking anything.

The same language we older IT laggards have been hearing for over 20 years is still prevalent and frankly still relevant today. It’s the technology and the price point that has changed what Digital can now deliver.

Latest technology

So, it is interesting to hear the top 3 Digital Business Drivers & Project initiatives going on right now in order of appearance are:

I won’t comment on the drivers as I believe they are still the “business constant” that will almost certainly never change.

As for projects, ubiquitous, low-cost connectivity and cheap devices have transformed the ability for companies to embark on internet of things (IoT) projects with genuine return on investment (ROI) and opened the door to the Data ocean that we now have to collect, automate and analyse.

Almost no companies admitted to having reached the stage of anything ‘predictive’, save for those in the Facilities Maintenance side of the business who are actively looking to IoT for preventive maintenance initiatives.

All the participants agreed with our host, Henrik von Scheel, that we are only really at the stage of collecting the data of ‘past events’ perhaps only milliseconds past, but after the event nevertheless.

IoT is the clear leading initiative...

…And we are talking about an audience of Manufacturers here, engineers, we know that a good engineer will have half a dozen things they will do to diagnose 90% of the issues they will find. These can be replicated, in the main, by a few simple, low devices that will measure the same things and AI and Machine Learning are not needed to do that.

That said we can still make great use of the data we’ve collected and analysed to identify faults, weaknesses and corrective actions that are still having a significant effect on operational efficiency.

So, the 'predictive' wave is yet to come!

And with it, I would suggest, we will begin to see the real adoption of AI and Machine Learning as it becomes clear human processing power is just not going to be enough.

As we continue to strive for operational efficiency, we are going deeper into automating the data flows and creating an ever more extensive ‘digital duplicate/twin’ of our real-world business. I don’t think ‘twin/duplicate’ is the right description because, when challenged, all the participants agreed we can now physically stop a factory in real-time just as quickly with a digital data breakdown as with a physical world breakdown.

I think a better analogy than digital ‘twin’ or a ‘duplicate’ is the ‘nervous system’, a vital organ for the physical world to be able to work and I would argue that today one cannot work without the other, and it is the new ‘business as usual’.

That means we need to apply the same level of robust care for these digital nervous systems to remain healthy, monitored, fed and watered to ensure continuous service, just as we do for our physical world operations. A significant and perhaps underappreciated burden that we must acknowledge and address.

For Data and Analytics, as one company said, a few simple IoT devices and the realisation that they needed to realign their data ‘along the time lines’ to see the true pattern, exposed the ‘eureka’ moment to an understanding that brought the massive efficiency improvement they identified. It illustrated that understanding how to analyse the data is a new skill that will be needed to make proper use of the data.

'People are still regarded as the critical component to making it all work'

Just a few of the larger companies had employed ‘Data Scientists’ already and this trend is set to increase with the tsunami of data we must now collect. And this brought up the little surprise I wasn’t expecting. People, well who would have thought, in the context of Digital Ambition people are still regarded as the critical component to making it all work.

Of course, I should have expected that, but what I wasn’t expecting was the strength of feeling and the general consensus across the board.

Digital ambition is not a ‘top-down’ initiative, it requires engagement with people across all levels to be successful. Whether it is new or not is a moot point.

Some people feel they have been doing this for 25 years or more already, admittedly IT people, but others from the Manufacturing side feeling this is just the continuous drive for operational efficiency now adopting the newly cost-effective Technology to enable these gains (business as usual).

What is clear is that the Digital infrastructures that we are building now, regardless of ambition, are not duplicates or twins they are the actual nervous system that makes the physical world work. Take care of it.

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