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Predictive Maintenance
Predictive Maintenance

Make maintenance measures efficient to reduce maintenance costs

Our solution for predictive maintenance opens up innovative opportunities for companies

Our solution for predictive maintenance opens up innovative opportunities for companies

Maintenance planners must regularly tackle the challenge of maximizing the availability of machines while minimizing material consumption due to maintenance and repairs. They also need to ensure excellent product quality.

Conventional approaches to maintenance typically fail to meet these requirements. Why is that the case? Data from multiple machines and processes is only rarely evaluated intelligently. Consequently, insights that could otherwise be obtained remain unexploited.

Optimizing the use of resources with predictive maintenance

Predictive maintenance in practice: resistance spot welding

Resistance spot welding involves a spot welder with copper-alloy electrode caps. The degree of wear on these caps plays a key role in the quality of spot welds. Electrode caps are typically maintained at fixed intervals: milled after a specified number of spot welds, and then replaced after a specified number of milling cycles. Caps tend to be replaced sooner than necessary to avoid quality issues.

Thanks to suitable machine-learning algorithms, Data Analytics can use process data to help identify the optimum time for maintenance. Predictive maintenance thus provides several benefits for welding:

  • Less downtime and optimum maintenance intervals increase output.
  • Welding quality is ensured through milling at the right time.
  • The useful life of electrode caps can be extended, reducing costs of materials subject to wear.

What to expect from predictive analytics?

Predictive maintenance

Our expert in manufacturing analytics interviews Bosch ConnectedWorld attendees about the potential of predictive analytics in manufacturing. Discover the innovative opportunities for the improvement of your production opened up through predictive maintenance.

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Using the Production Performance Manager for maintenance

This graphic shows an example of maintenance steps in response to a machine failure. The upper half portrays the conventional approach, while the lower half makes clear how using the Production Performance Manager improves the maintenance process.

Comparison of maintenance steps Icon lens
Using the Production Performance Manager for maintenance

What are the arguments in favor of predictive maintenance?

Detecting machine breakdowns early on improves the efficiency of maintenance work and opens up entirely new opportunities for your company.

Tapping the potential of new business models
Create new market opportunities by offering your customers additional services regarding maintenance and resource optimization.


Increasing efficiency of maintenance
Intelligent Industry 4.0 solutions – such as Manufacturing Analytics and the Production Performance Manager – facilitate integrated, trouble-free processes throughout a company and for the duration of the maintenance process.

Optimized maintenance services
Optimal scheduling of maintenance measures reduces costs, boosts customer satisfaction, and distinguishes your portfolio from those of competitors.

Boosting operational productivity
More predictable scheduling of maintenance measures helps avoid the expenses of unscheduled production downtime and cuts resource costs.