Digitalisation need for the industrial SME sector

the industrial SME sector is currently facing huge challenges, but also . Scarcer, more expensive resources, new production methods and fragile supply chains are also challenging the medium-sized industrial enterprises. Digitalisation and automation can be the game changers to master the challenges of the future. How can we use all these huge amounts of data that we have been collecting for a long time to use limited resources more efficiently and sustainably in the future? And what quite surprising potentials can be realised with it? 

Digitalisation has now also arrived in the production of conservative industries. What has happened in the last few years?

In fact, we have reached the point today where we do not yet have end-to-end solutions for the entire supply chain, but we do use artificial intelligence and algorithms in some areas to support and fuel management decisions.

In recent years, Syngroup has digitised entire production networks for some of its customers. What does that mean?

This is one of the most exciting applications in the context of digitalisation, where we really do move entire networks into a digital twin - the individual sites, the production possibilities, the machines, the capacities. We also import the customer networks into a digital system at the geodata level and thus have the possibility to play out the most diverse scenarios with this digital twin.

What are the main applications?

The main applications we see are in the area of classic strategic production decisions. Where to build new sites, where to place new machines to be optimal in the network, and how to maintain supply source stability when it comes to fail-safety, as seen last. What happens if a site is taken out of this production network, can I still ensure supply security? A number of important questions, from investments to network resilience to supply chain issues, can be followed very well and continuously and thus create a basis for management decisions.

So definitely strategic issues …

Yes, definitely. It is not a tool for day-to-day operations but for operational strategic decisions, which are usually made by the CEO or COO.

What were the lessons learned for the companies with which you implemented this?

A CEO we have been working with for a long time said it was so unemotional, purely technical. Certain locations are often preferred, there are grown, prefabricated opinions, but the algorithm simply calculates and all these emotions are out of the discussion. And there are new, previously unknown possibilities to be able to say at the push of a button how a new structure works, how it is optimal, how it can be optimised. We see that about 15% of the controllable costs can be reduced according to the algorithm. How this is then implemented is another matter, but it provides a very good basis for management decisions.

 What have you learned in the implementation?

For us, it was exciting to look after the topic for some clients for years. It is about finding the right level of aggregation between too much detail and too much aggregation. For us, it's about providing management with a tool in a pragmatic way and also optimising it on an ongoing basis. Together with the management, we address the issue of strategic production management and support them in making their company more efficient and successful.

 If there is one tip you would like to give to managers on the subject of digitalisation in manufacturing, what would it be?

Finding a right, pragmatic means. That means using things, recognising the purpose and the ROI. What do I want to invest and what do I consider worthwhile and what do I want to see in a consistent implementation. There are great systems, but when I see how they are implemented on the shop floor, in production, there is still a lot to do.

Thanks a lot.