Or: Why you should take the first steps towards digitalization today rather than tomorrow
Everyone is talking about Industry 4.0. However, the buzzword is often only understood to mean the digitalization or automation of industry. Its actual definition, namely a complete change in the value chain through the digital networking of machines, systems and products, is often neglected. However, since the term "Industry 4.0" was coined in 2011, enough time has passed to put the business basis of German SMEs on a new footing. But little has happened so far.
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.
If the database is correct, all available data on products and machines must be stored in a digital image of the real object, the so-called digital twin. This will accompany us through the digital transformation to Industry 4.0. By analyzing the data available in the digital twin, it will not only be possible to increase quality or reduce production downtime in the future. Other use cases include smart products that respond to customer behavior, adaptable production (batch size 1), new business models and self-orchestrated production.
"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.
No matter how we look at it, the first step is to collect data and create a digital image of reality. This provides us with transparency and insights that help us to take further steps towards new digital business models. By networking products, the industry is able to develop digital ecosystems that no longer focus on the product but on the consumer. In future, manufacturers will be able to obtain information about the use of their products in order to set up further new business models.
