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Predictive Maintenance

Predictive Maintenance

Forecasting the performance of your assets is the most optimum state you can operate in, and it requires a well-planned journey. We can design and execute the plan to set the predictive maintenance foundation and analyze your equipment to map the need for context specific algorithms to ensure precision forecasting.

A fancy software solution that can be purchased and installed relatively instantly simply does not do the trick when it comes to achieving a state of predictive maintenance. Your maintenance foundation must be set in order to start that journey toward a set-up where AI and Machine Learning is possible.

We know what it takes to set that foundation, and that is to have the following in place:

  1. As-built Technical Documentation
  2. As-built Technical Hierarchy, i.e. your CMMS digital twin
  3. Maintenance Data Classification & Characteristics
  4. Asset Designed Failure Codes and Causes

Your organization must have your technical documentation to match your CMMS asset register and be validated as-built. This enables the possibility of creating and assigned the equipment specific classification and characteristic data, which gives your CMMS the opportunity to differentiate similar equipment types, i.e. the same equipment type place in the same operating context. At last your CMMS must be able to collect the right failure data, which is what happened and why did it happen? Many organizations believes they are in a state where this scenario is close by, but in reality, the journey towards it is comprehensive and takes discipline. We know how to build a customized plan for that journey and take your organization to the needed maturation level towards a predictive maintenance environment.

In order to achieve the final step your organization must know how your equipment acts. Both your practical experience combined with theoretical equipment knowledge are to be put in the system. What is it that your organization are to measure and monitor with the predictive maintenance algorithms? We have the expertise within many practical operations, but our key skills lies within the theoretical knowledge of what data your organization must measure and try to predict. Our engineers and data experts will assist you in setting up the solution for your predictive maintenance environment and make sure your solution fits your business.

Affiliated Services:
  • As-built Technical Documentation

    Reduce your time spend on the search for and increase the trust towards your technical documentation by choosing a solution that will ensure a complete as-built mapping of your assets. Juel + Krøyer has the technical expertise to conduct line walks, regardless of the industry, and the digitalizing knowledge to implement the solution efficiently.

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  • Asset Register - As-built Techincal Hierarchy

    The backbone of any maintenance management system is the asset register. To ensure everything from cost transparency between asset types and systems to equipment failure analysis. The as-built technical hierarchy in the system must be aligned with the physical installed assets – creating a simple easy to use digital twin.

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  • Maintenance Data Classification & Characteristics

    A well-designed classification and characteristic system that fits your maintenance organization and describes your maintenance objects will set the foundation for future optimizations, create more profit and enable an accurate predictive maintenance set-up.

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