Predictive maintenance therefore harbors a Great potential for savings in operation and maintenance of machines. However, the prerequisite for predictive maintenance is first of all that the relevant Data collected on faults, failures and repairs that occur in order to be able to analyze them. The more complete the underlying Data basis the more accurate the predictions can be.
No predictive maintenance without a solid database
Without a Comprehensive and reliable database as a basis, predictive maintenance is not possible. Companies that want to use predictive maintenance in the future should therefore start early, Targeted data to collectfor example through a digital service solution.
The Continuous data acquisition The digitalization of maintenance and repair is the basis for further measures. If data on malfunctions and failures of machine parts is recorded digitally, it can be used as a Basis for future evaluations serve. Ideally, this can prevent machine downtime.
Prevention instead of reaction: from breakdown to preventive maintenance
If repairs are only carried out after a system component has failed, this is referred to as "Reactive" or "Breakdown Maintenance".1 This results in increased costs due to unforeseen downtime and increased personnel costs. This is because trained personnel are needed at short notice to get the broken-down machine up and running again as quickly as possible. In addition, the necessary spare parts must be available quickly.
It is better to avoid such failures by Regular maintenance measures to prevent failure. Defined maintenance plans and the precautionary replacement of components before the probability of failure increases to an unacceptable level are called "Preventive maintenance".2 Regular maintenance work can ensure that High availability of the systems and the service life of the machines is increased.
The maintenance processes required for this can be Digitization more efficiently, quickly and cost-effectively. In addition, this can create a database that can be used in the future as a Basis for predictive maintenance - predictive maintenance - can serve.
Our customers rely on digital service solutions for maintenance processes
For these reasons, one of our customers from the intralogistics sector decided to opt for Maintenance processes in the area of battery charging technology to a Digital service solution to set. The aim is to make the maintenance process for batteries more efficient and transparent to design and a database for a Evaluation of maintenance data to collect.
In collaboration with doubleSlash, the maintenance process for batteries has been digitized. The service technicians now need no paper forms but can enter all maintenance data via a mobile application. The app supports the service technician at every maintenance step and allows you to flexibly select maintenance types and react to faults. All data that can already be determined by the system no longer needs to be entered, but is provided automatically.
For example, the batteries are simply scanned in - the system then automatically sets the master data and selects the required maintenance type for the respective battery. This allows the service technicians to focus on the critical process steps concentrate and devote more time to them. This improves the overall process quality.
In order to provide the service technicians on site with optimum support in their work, they were directly involved in the development of the application. This enabled the digitalized maintenance process to be optimized so that it is precisely tailored to your requirements.
After the application had proven itself in productive use, the process for the Maintenance of chargers also digitized. With the expanded application, the maintenance process can now be carried out for both batteries and chargers.
Conclusion: Continuous data collection and regular analysis as the basis for predictive maintenance
All maintenance data entered by the service technicians is collected and centrally stored. The data collected provides an initial impression of repair cases and the frequency of certain faults. These Data can now be analyzed and further processed become.
Based on the data collected from the maintenance processes carried out, our customer would like to implement comprehensive reporting in the future. To the continuous data acquisition then comes a Regular data analysis added. This is the basis for further measures and a decisive step towards predictive maintenance.
Find out more about predictive maintenance here
You might also be interested in these blog posts:
Best practices in the implementation of predictive maintenance - a field report
The future of predictive maintenance: On the way to intelligent-prescriptive-predictive maintenance
Sources:
1 http://www.businessdictionary.com/definition/breakdown-maintenance.html
2 http://www.businessdictionary.com/definition/planned-maintenance.html
