Leverage Predictive Maintenance and turn data into real business value
Predictive Maintenance is a strategy that uses sensor data and advanced algorithms, including AI and ML, to predict and detect potential failures before the production line stops. As a result, it can increase OEE by up to 15%, reduce downtime by dozens of hours per month, and deliver a return on investment as early as the first quarter.
If you are looking for a proven way to implement Predictive Maintenance, explore Smart RDM – a solution chosen by leading manufacturers in Europe, combining fast ROI with local support and service. Download our detailed implementation plan and see how, in just 3 months, you can move from the first measurement to an effective Predictive Maintenance system that truly improves your factory’s efficiency.
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Unique methodology – guarantee of success
Our implementation methodology combines industry knowledge, technical competence and best practices, guaranteeing unparalleled quality of the solution.
The proposed action plan, based on many years of experience, leads to precise forecasting of faults and optimization of operational processes. In one document you will find a comprehensive set of tools and strategies that will allow your company to quickly and safely implement modern technologies.
What makes her stand out?
- A detailed overview of practical information and valuable guidelines for every stage of project delivery.
- A step-by-step approach designed to minimize project risks and maximize business value for the organization.
- Implementation steps tailored to different technical and organizational requirements.
- An overview of how the latest technologies, advanced algorithms, and AI models are applied in practice.
- Backed by the experience of customers who have already implemented this solution (explore our case studies).
The solution is based on the Smart Hybrid Maintenance System (SHMS) concept, which combines different Predictive Maintenance methodologies. This approach was described in a scientific paper prepared by our experts and published in the MDPI journal Energies. By using the Hybrid Risk Index (HRI), calculated based on RCM and CBM methodologies, we gain greater control over the maintenance strategy and can precisely determine the optimal time for maintenance activities.
Implementing advanced maintenance algorithms in a real industrial environment is a major challenge, which is why many AI and Predictive Maintenance projects never move beyond the pilot stage.
At SmartRDM, we translate complex scientific models into practical, scalable solutions tailored to specific assets, processes, and operational needs.
Watch the video for a summary of the approach.
We also encourage you to read the full scientific paper.
What can you find by using Predictive Maintenance?
The basic parameter of production efficiency is OEE (Overall Equipment Effectiveness)
- Good OEE: 60% – 80% – this result already reflects the impact of digitalization, while still leaving room for further improvement.
- Excellent OEE: above 85% – achieved by companies with advanced digitalization and automated processes.
The example below makes it easy to calculate the potential benefits of implementing the system.
PdM implementation typically delivers a 5% to 15% improvement in OEE.
Example: If your annual revenue is PLN 300 million and your profit margin is 10%, each additional percentage point of OEE growth from a 60% baseline can increase profit by approximately PLN 0.5 million. Even the minimum expected improvement of 5% can therefore generate PLN 2.5 million in additional profit.
The lower the initial OEE level, the easier it is to achieve greater benefits. However, this may require higher investment in preparing the organization for Predictive Maintenance implementation.
Benefits of implementing a proven Predictive Maintenance strategy
- Reduced downtime – increased machine availability.
- Lower maintenance costs – reduced repair and service expenses.
- Knowledge base development – building and maintaining service best practices within the organization.
- Scalability – shorter initial implementation and the ability to quickly expand the deployment to new machines and equipment.
- Safety – fewer incidents and improved workplace safety.
Who is Predictive Maintenance for?
Our solutions are designed for:
Production managers
Our solutions optimize production processes by automating maintenance, which translates into fewer downtimes, lower operating costs and higher production efficiency.
Maintenance Team
Advanced tools enable faster fault detection and failure prevention, which reduces repair costs. The system provides quick access to key information, and the intuitive process support module facilitates effective communication.
Operators
The system guarantees greater operational certainty and a reduction in the number of failures, and its simple-to-use interface allows for easy reporting of problems. Additionally, operators benefit from an extensive knowledge base and AI support, which streamlines daily work.
What will you gain by downloading our methodology?
- You will learn how to implement Predictive Maintenance in your company step by step.
- You will learn how to use data from sensors and monitoring systems.
- You will get a ready-made plan for integrating PdM with current tools.
- You will learn tips on how to create an effective implementation team.
Download now and discover how Predictive Maintenance can improve your processes.
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Try our proven methodology
“Our methodology is aimed at companies that are just starting their adventure with PDM and want to better understand the implementation process, as well as at companies with experience in this field that, for various reasons, have not achieved the intended results.”
Gabriela Gic-Grusza
Unit & Product Manager Smart RDM