An intelligent and inexpensive maintenance accelerator

Significantly shortening maintenance processes results in a massive decrease in overall production costs. Does that sound like an ambitious goal? Not for the modular maintenance software and system solution from Körber Digital: This Digital Uptime Solution ensures purposeful communication and continuous knowledge transfer – with the assistance of artificial intelligence (AI).

Damage to individual parts, blocked material feeds, dirt accumulation – there are many reasons for machine downtime. The only certainty is that it always costs money. And the longer the entire system stands idle, the faster the costs spiral upward. In practice, the questions of what sort of problem actually exists, how quickly it can be solved, and who is capable of solving it must all be answered under tremendous time pressure. This is backed up by a study conducted at a German car manufacturer, which showed that simply gathering information makes up 25 percent of the work of a maintenance technician. To look at it another way: If you are still searching for information, you cannot yet begin the actual repair work.

Improve processes – secure knowledge

With Industry 4.0 and the associated application of Data Science and machine learning, however, it’s no longer only about the acquisition of information by the Maintenance Technician. Much more can be done on the basis of complete data – from classification of the errors using artificial intelligence to analysis of the maintenance history of a machine and the creation of a database containing all the maintenance knowledge of a company. “These were precisely the goals we had in mind. This is why we took a comprehensive approach to planning the development of our digital decision center for Maintenance Managers,” explains Felix Raab, Product Owner at Körber Digital. “We not only want to reduce expensive downtimes to a minimum, we also want to comprehensively secure the knowledge that exists within the company. At the same time, we rely on a flexible and inexpensive payment model.” The following four topics play key roles in applications for the Digital Uptime Solution from Körber Digital:

1. Incident management: Perfecting employee communication

When the “right” expert shows up at the defective machine with the “right” information, tools, and replacement parts, the downtime can (theoretically) be quickly brought to an end. In practice, the mean time to repair is often longer: The Machine Operator generally does not address the problem himself. Instead, he describes the incident to the Maintenance Manager from a qualitative perspective. The Maintenance Manager then calls a Maintenance Technician, who must investigate the cause and perhaps even bring in an external expert. Valuable time is lost, and we all know that time is money. This is where the incident management functions of the new Körber Digital solution come in: “The software breaks through communication barriers and secures the transfer of information. It accelerates the communication between Maintenance Technicians, Machine Operators, and Maintenance Managers and continuously optimizes the way they work together.” The integrated ticketing system plays an important role here: Every incident is recorded on a ticket and classified. On this basis, the system learns to detect recurring problems on its own and to make suggestions about what measures should be carried out by the appropriate person. In other words, the software first of all ensures that the information arrives where it is needed much more quickly. “Our solution helps the user make the right decision and directly suggests relationships,” explains Raab. Moreover, the system checks the availability of the Maintenance Technicians in order to ensure the dynamic coordination of tasks at all times. Maintenance Managers have access to information about all incidents.

2. Use of AI: Classification of the situation in seconds

The cause of the downtime is determined in seconds by artificial intelligence (AI). Users immediately receive precise instructions regarding which replacement parts and tools are needed and how the error can be corrected. This eliminates the need for prolonged searches for information. The technical basis for this is the networking of the machine with AI. The machine data are divided up into segments, including the recorded downtime events. Generally speaking, the service technician automatically interprets the segment in his action report and assigns it a label – this is how AI learns. Elaborate Data Science projects are shortened in this way, since the interpretation of the data is performed continually by domain experts. When a sufficiently large number of segment-label pairs exists, the AI is in a position to recognize errors independently. “In developing this stage of functionality, we work very closely with our customers in the course of a very streamlined Data Science project,” explains Raab. “The development is much less time-consuming than is sometimes assumed.”

3. Knowledge management: Preserving the know-how of the “machine whisperers” 

According to the Federal Statistical Office, the average age of employees in Germany is currently about 44 years, which is already four years older than it was 20 years ago. Against this backdrop, companies must ensure that the knowledge transfer between older and younger employees functions smoothly and that key know-how is not lost with the departure of the “machine whisperers.” The solution from Körber Digital offers the ideal basis for this, since it not only collects all maintenance knowledge in a single location but also stores it in a comprehensive format with a uniform structure – which in turn simplifies the continuous documentation of new knowledge. All the participants receive fast, direct access to this knowledge.  

4. A digital lifetime record: A “data twin” for more reliable decision-making

In the age of Industry 4.0, data and information about the production process are particularly valuable. For example, such information allows better planning of resource utilization and the development of new business models. The basic prerequisites for such use, however, include having all the information available in a uniform format and continuous maintenance of the data. In many plants, this has not been the case so far. Instead, the data are distributed across various systems in different formats. The same applies, for example, when it comes to technical expansions and changes to the 3D models of the plant. Therefore, in its solution Körber Digital offers a comprehensive and up-to-date lifetime record for the machine – down to the individual components and including the entry of all service measures for later querying. Continuously generated action reports regarding maintenance work and incidents are linked here with administrative documents such as circuit diagrams, parts lists, and 3D models. This eliminates long, laborious searches in manuals and in the documentation of systems in a plant. It also serves as a source of information on troubleshooting and preparation for necessary tasks. This knowledge source can be used at any time, for example to continuously improve maintenance processes or to make wide-ranging investment decisions – it’s a perfect and simple point of entry into Data Science and Industry 4.0.

Summary: An inexpensive productivity boost

Uniform control over the communication processes during an incident, the option to integrate AI for incident recognition, and the establishment of a comprehensive knowledge portal covering all aspects of maintenance – within this framework, the new digital uptime solution from Körber Digital opens up tremendous potential. In fact, the experts at Körber Digital expect that repair times can be significantly reduced, depending on the usage scenario – with a simultaneous increase in productivity. With regard to possible users, a particular focus has been placed on the sectors of electronics manufacturing; paper, tissue, and glass production; food and beverage production; and the process industry. “In its simplest form, the starter version costs less than 100 euros per month per user. In other words, customers can test the system on a small scale for no risk and expand it as desired. We are convinced that our solution will prove its worth on the market,” Raab concludes.

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