Intelligent fault detection & maintenance planning

 

Detect faults early and implement a proactive maintenance plan to avoid unscheduled downtime

Faults in plant and machinery are a major problem for many manufacturers and customers. They may not occur frequently, but they are often detected too late leading to unscheduled downtime. The resulting maintenance operations can be lengthy and inefficient. This in turn can lead to significant extra cost, unhappy customers and in the worst case, considerable damage to your reputation.

With our intelligent fault detection, you can monitor your plant and machinery in real time so that faults and breakdowns can be detected or predicted early on. This allows you to implement a proactive maintenance plan for increased efficiency and lower costs.

We start with your challenges

These are the most common challenges involved in achieving intelligent planning of your maintenance processes:

  • Challenge 1: Networking and management of plant assets by integrating suitable IoT technologies.
  • Challenge 2: Efficient processing and storage of machine data, for example, in a cloud-based application.
  • Challenge 3: Condition monitoring through the use of appropriate dashboards.
  • Challenge 4: Selection and implementation of suitable methods for detecting and predicting faults, such as rule-based or machine learning methods for analysing high-frequency vibration data.
  • Challenge 5: Proactive maintenance planning with automated notifications, for example.
  • Challenge 6: Integration of external data sources through the use of standardised APIs for ERP or MES systems, for example.

Benefits of AI-based fault detection

Monitoring the condition of your plant and machinery around the clock in real time gives you a clear picture of when maintenance measures are due or whether there are impending problems. With effective maintenance planning, you can greatly reduce machine downtime and actively extend the service life of your plant and machinery. Your benefits with our software for intelligent fault detection at a glance:

 

  • The condition of plants can be monitored effectively.
  • Potential faults are detected early and start to occur less frequently.
  • Maintenance measures can be planned in advance.
  • Lengthy, unscheduled downtimes are avoided.
  • Minimisation of costs for maintenance and downtime.
  • External data sources and 3rd party systems can be efficiently connected.
  • Prefabricated software modules that can be individually customised allow a precise and timely rollout of the application (time to market).
  • Our best practices can be enhanced and refined collaboratively by your in-house experts and data science teams via our application.

Our approach to intelligent fault detection

Example: High-frequency vibration data is measured in real time on a networked ball bearing and sent to a backend provided by us. The data is analysed using a machine learning model. Any damage to the ball bearing is thus detected at an early stage and with a high degree of accuracy. This allows an intelligent, proactive maintenance plan to be set up before a fault or breakdown occurs, avoiding lengthy downtimes. Depending on the given framework conditions and the data available, simpler approaches for condition monitoring or rule-based analysis, for example, can be implemented in the first step if required and then enhanced later in a second step to implement predictive AI algorithms. This can be the first step towards intelligent fault detection

Ihre Entscheidungshilfe zur sicheren Fernwartung (german whitepaper)

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How we support you with predictive fault detection and maintenance planning

Our services

  • Connect: Remote device management and administration, integration of third-party systems, user management and user personalisation
  • Maintain: Efficient processing of large data volumes and real-time data, rule-based device condition monitoring with customised dashboards, condition-based monitoring, AI-based fault detection with sophisticated machine learning methods
  • Consult: Exploration and requirements gathering, introduction / installation & setup / customising / project planning, training, operations and support, consulting services regarding the introduction of new, billable business models and digital services

Results and artefacts:

  • You get a custom-built software solution with which you can monitor plant and machinery, detect faults early, and implement a proactive maintenance plan.
  • The software is cloud ready but can also be provided as an on-premises solution

 

What we bring to the table:

  • Multiple years of project experience in the connected things environment of mechanical and plant engineering.
  • We know from numerous predictive maintenance projects which processes, methods, technologies and best practices are best suited to your needs.
  • We have established partnerships (Azure Gold Partner, PTC Partner, and so on).
  • We offer professional project management using agile methods and prefabricated software artefacts for a shorter time to market
  • We have extensive experience in implementing new, billable digital services.

Successful examples of AI-based fault detection in practice

How can we support you with intelligent fault detection and maintenance planning?

Your contact

Danny Claus
Danny Claus
Machine Learning Expert

Phone
+49 7541 70078-771