Despite high automation, production downtime occurs repeatedly. The reasons for this are diverse. In addition to operating errors, hard-to-measure product and packaging material properties (e.g., the random nut distribution in chocolate or varying cardboard moisture) lead to process fluctuations. Since it is generally more economical to run processes with the highest possible output in the physical, but fault-prone, boundary area, these fluctuations lead to frequent micro-stops that must be resolved by operators. In this article, you will learn why there are significant differences in the competence to act and how the duration of unplanned production downtime can be significantly reduced through the intelligent combination of automation and human knowledge.
Ironies of Automation – why technology alone does not prevent production downtime
The basic idea behind it: Automation is supposed to reduce human error, but this very fact creates new risks.
Three core aspects characterize this concept:
- Automated systems are developed by humans – and precisely here, planning or programming errors can arise.
- If technology fails, it is still humans who must intervene. However, due to their previously passive role, they often lack the necessary practice to react quickly and correctly in critical moments.
- For effective troubleshooting, humans need an up-to-date understanding of the situation, deep process knowledge, and confidence in their actions. However, these very skills suffer when operators are only passively observing for long periods and hardly actively intervene in events.
What was once formulated as a theoretical observation is now evident in the practice of many production companies as a real cause for extended reaction times – and ultimately also for avoidable production downtime.
Between Wishful Thinking and Reality: Why Automation Weakens Human Responsiveness
The idea of a completely error-free and self-controlling production persists, but reality shows: Even in highly automated plants, humans remain an indispensable factor for
success. Production downtime often occurs precisely when this fact is overlooked.
For a long time, a simple rule applied to the division of tasks between humans and machines: everything that can be reliably automated is handled by technology, while humans remain responsible for flexibility and improvisation.
However, a new conflict of objectives arises precisely here today: The more tasks machines take over, the less frequently operators have to intervene – but when they do, it usually concerns particularly critical situations.
The problem: These rare interventions require maximum attention, quick analytical skills, and comprehensive process understanding – but precisely these suffer when humans are hardly actively involved in process control for long periods.
A human-machine system is more than the sum of its individual parts. When areas of responsibility are eliminated, this directly affects performance in the remaining tasks. This correlation is often underestimated in practice – with noticeable consequences: delayed reactions and longer production downtime in critical moments.
How Peerox Meaningfully Connects Humans and Automation
At Peerox, it was clear from the concept phase: A successful reduction of production downtime can only be achieved if the role of humans in the system is considered from the outset.
A concrete example of this is a feature within our software that automatically suggests suitable knowledge cards for recurring malfunctions. For this, a machine learning algorithm analyzes past feedback from operators as well as patterns in machine and process data and calculates a percentage probability of how well a card matches the current situation.
Precisely such functions are no coincidence, but an expression of a fundamental design principle at Peerox: The entire system was developed to specifically support human-machine interaction – always oriented towards the cognitive abilities of the users.
Our goal is not only to provide technical support but to actively strengthen the decision-making ability and reaction speed of people in production – to sustainably reduce production downtime.
