Or: Why you should take the first steps towards digitalization today rather than tomorrow
Industrie 4.0 ist in aller Munde. Doch wird unter dem Schlagwort oft nur die Digitalisierung oder Automatisierung der Industrie verstanden. Ihre eigentliche Definition, nämlich eine vollständige Veränderung der Wertschöpfungskette durch die digitale Vernetzung von Maschinen, Anlagen und Produkten, wird gerne vernachlässigt. Seit der Begriff „Industrie 4.0“ 2011 geprägt wurde, ist jedoch genügend Zeit vergangen, um die geschäftliche Basis des deutschen Mittelstands auf neue Füße zu stellen. Geschehen ist bislang aber nur wenig.
Let's take a look back: Since 1970, machines have increasingly become connected in the course of the first automation of production. However, due to a lack of industry-wide standards, many manufacturers began to network their machines proprietarily.
Only the development of fieldbuses and their standardization in the late 1980s was able to stop the trend. This was a key starting point for the subsequent development process towards digitalization and Industry 4.0, as shared standards now enable machines and components from different manufacturers to communicate with each other without additional technical aids. The boundaries between the digital and physical worlds are becoming increasingly blurred and intelligent networked systems can now support activities along the entire value chain.
Using what's there: sensor technology as the key to success
But there is a catch: machines have a service life of several decades (> 30 years). As a result, fully networked machine parks will only become widely available in a few years' time. For this very reason, the steps must be smaller for the time being. Nevertheless, the "big picture" of Industry 4.0 - fully connected, changeable and self-orchestrated - must not be lost sight of.
In contrast to fully networked machinery, many sensors are already installed in production halls today. This is a first step towards Industry 4.0, as the collection of data allows important analyses to be carried out in a second step. Decisive "low-hanging fruit" that every manufacturing industry must harvest in order to produce efficiently and reduce costs. However, reducing costs cannot and must not be seen as the primary goal of Industry 4.0.
The "Minimum Viable Product" (MVP) principle should be applied here: For example, the power consumption of a machine can be used to determine the wear of the tool. Another application would be to draw conclusions about the deformation of tools based on measured pressure differences. In short: quick and simple solutions supported by intelligent algorithms.
In any case, empirical knowledge is required to make decisions based on these analyses. We talk about hybrid intelligence here, because the more automated we work, the more crucial human intervention is. In order to use this hybrid intelligence, experts from companies and IT experts must work together to model, analyze and draw the right conclusions. This is the only way for the previously collected data to unfold its full effect. Feeding the algorithms developed in this way into the processing procedures is the logical consequence.
Digital twin as an image of reality
The "low hanging fruit" is often forgotten; instead, companies attribute great potential to the use of artificial intelligence for process automation. And quite rightly so. However, the data quality must be right first. Companies attach great importance to this, but in reality, data silos and barely networked databases can be found in individual departments.
Wenn die Datenbasis stimmt, müssen alle verfügbaren Daten zu Produkten und Maschinen in einem digitalen Abbild des realen Objekts abgelegt werden, dem sogenannten Digitalen Zwilling. Dieser begleitet uns durch die Digitale Transformation zu einer Industrie 4.0. Durch die Analyse der im Digitalen Zwilling vorhandenen Daten wird es in Zukunft nicht nur möglich sein, die Qualität zu steigern oder Produktionsausfälle zu vermindern. Weitere Anwendungsfälle sind beispielsweise smarte Produkte, die auf das Verhalten des Kunden reagieren, bis hin zur wandelbaren Produktion (Losgröße 1), neuen Geschäftsmodellen und zu einer selbstorchestrierten Fertigung.
"Data is the new oil" and in order to monetize this, the industry must begin to understand the full significance of Industry 4.0 today. It is not yet too late. Experts predict that around 75% of industry will be connected by 2030. This applies not only to internal company networking, but also to the entire supply chain. In this way, the potential of digitalization can be exploited across the entire value chain.
Egal wie wir es drehen, der erste Schritt besteht darin, Daten zu sammeln und ein digitales Abbild der Realität zu schaffen. Dadurch verschaffen wir uns Transparenz und gewinnen Erkenntnisse, die uns helfen weitere Schritte in neue digitale Geschäftsmodelle zu wagen. Durch die Vernetzung der Produkte ist die Industrie in der Lage digitale Ökosysteme zu entwickeln, die nicht mehr das Produkt, sondern den Konsumenten in den Mittelpunkt rücken. Damit werden Hersteller zukünftig in der Lage sein, Informationen über die Verwendung ihrer Produkte zu erhalten, um weitere neue Geschäftsmodelle aufzusetzen.
