Condition-monitoring data only creates value when maintenance teams can turn it into timely decisions. In this Innovation Pitch, ENGING will focus on how predictive intelligence and real-time asset monitoring can help teams identify emerging issues earlier, understand asset condition and act on relevant alerts. The session connects three steps that are often treated separately: detecting potential failures, assessing what is happening to an asset, and turning that information into better maintenance planning. The aim is to move beyond simply collecting more data and show how condition insights can support faster, more focused operational decisions.

Technicians often lose valuable time searching for previous interventions, manuals and other context before they can start solving the actual problem. Afterwards, important knowledge can disappear again into free-text notes or unfinished reporting. Highsail approaches agentic AI around the complete technician workflow. Before the job, relevant context from work-order history, documentation and open actions is brought together. During the intervention, technicians can capture findings through voice and photos while the system helps structure the work performed. After technician review, the resulting information can be fed back into existing business systems and used to prepare follow-up actions. The result is a practical look at how AI can reduce administration while making maintenance knowledge more reusable.

Maintenance rarely fails because of a lack of individual systems. The harder challenge is connecting asset condition, maintenance priorities, available people, parts, planning and field execution. SAP’s Autonomous Asset Management vision uses AI assistants and agents to coordinate more of this chain. In this Innovation Pitch, discover how agentic AI can help interpret asset information, support maintenance decisions and increasingly connect the journey from an emerging asset issue to a planned and executed intervention. The exact industry scenario for the pitch will be selected closer to Asset Performance, reflecting the rapid development of these capabilities. The focus is therefore on what increasingly autonomous asset-management workflows could mean in practice rather than on one fixed use case.

AI can only be as useful as the maintenance processes and data it works with. SOA People therefore starts from the SAP maintenance foundation: reliable master data, consistent processes and usable information for the people creating and executing maintenance work. In this Innovation Pitch, discover how SOA People intends to extend Ready4 Asset Management with different AI roles. An AI Dashboard can highlight opportunities to improve the underlying data, AI Agents can be triggered to perform improvement tasks, and an AI Assistant can support end users when entering information. Rather than positioning AI as a separate layer, the session looks at how it can become part of the day-to-day process of building and maintaining a stronger SAP maintenance-data foundation.

Industrial organisations need to onboard new people faster while experienced employees increasingly carry knowledge that is difficult to transfer through manuals and classroom training alone. CHENEXT explores how a lifecycle digital twin can provide a shared environment for learning throughout the life of a plant. The same digital representation can support the onboarding of new employees, continued development of existing teams and learning across different operational roles. By bringing technicians, operators and other plant roles around a common environment, the approach aims to make plant knowledge easier to experience, reuse and develop over time rather than rebuilding training material separately for every function.

Shaft misalignment does not only make an alignment job more difficult; it can contribute to vibration, wear, energy losses and avoidable maintenance work on rotating equipment. In this live Innovation Pitch, Fluke will demonstrate the latest ROTALIGN Core and ROTALIGN Elite systems and show how newer measurement and guidance capabilities can simplify both standard and more complex shaft-alignment tasks. Attendees will see how single-laser technology, adaptive measurement options and real-time feedback help technicians set up, measure and correct alignment more efficiently. The session also looks at how alignment results can be validated and documented digitally, helping turn an individual alignment intervention into reliable maintenance information that can be shared and reused.

Capturing an abnormal sensor reading is only the beginning. The real maintenance challenge is shortening the path from detection to effective action. In this practical demo, delaware follows that complete chain using a wind-turbine scenario. When a sensor detects a reading outside the expected range, an intervention is created automatically. The system then determines a suitable technician based on asset requirements, location and required skills, and sends the job directly to the technician’s mobile device together with the relevant documentation and route information. The pitch demonstrates what becomes possible when condition data, maintenance workflows and field execution are connected — reducing the manual steps between knowing that something is wrong and getting the right person moving.

Duplicate materials, inconsistent descriptions and incomplete manufacturer information can make spare parts unnecessarily difficult to find, source and govern across multiple plants. SPARETECH’s Innovation Pitch focuses on the data foundation behind efficient MRO. In a practical demonstration, see how spare-parts data can move through a controlled workflow from creation to approval, while live duplicate checks help prevent new inconsistencies from entering the material master. Original manufacturer information can be used to enrich records, while AI generates structured descriptions according to company rules and in multiple languages. The result is a more consistent approach to spare-parts data that can reduce manual data work and make information easier for maintenance and procurement teams to use.

Condition monitoring can generate huge amounts of machine data, but reliability teams still need to determine which changes actually matter and what action should follow. ACCUREX combines automated analysis with ACOEM’s machinery-diagnostics expertise to help turn vibration information into clearer maintenance guidance. In this Innovation Pitch, discover how AI-supported anomaly detection can identify changes in machine behaviour, how automatic fault identification can reduce the amount of raw data specialists need to analyse manually, and how diagnostic results can be translated into maintenance recommendations. The objective is not simply to generate more alerts, but to help reliability teams focus their attention on the machines and diagnoses where expert intervention creates the most value.

Oil diagnostics can reveal developing wear, contamination and lubricant degradation, but drawing conclusions from multiple laboratory parameters, operating information and historical results still requires significant specialist expertise. Ecol is developing a new AI-supported approach that combines laboratory testing, historical data and expert knowledge with machine-learning and computer-vision techniques. In this Innovation Pitch, discover how AI can support different steps in the diagnostic process — from assessing samples and selecting relevant tests to interpreting results and identifying relationships across complex datasets. The ambition is to make diagnostic conclusions faster and more consistent while keeping them understandable for specialists, helping maintenance teams move from retrospective laboratory analysis toward earlier and better-informed maintenance decisions.

Lubrication is fundamental to rotating-equipment reliability, yet lubrication points are often managed separately from the systems used to monitor machine condition. Schaeffler’s Innovation Pitch looks at how connected smart lubricators can bring those activities closer together. Discover why Schaeffler is moving beyond conventional gas-driven lubrication cartridges for connected applications, how smart lubricators can be supervised through digital tools, and how lubrication status can be incorporated into the same OPTIME ecosystem used for machine condition monitoring. The result is a more connected view of lubrication and asset condition, giving maintenance teams greater visibility into lubrication points, machine status and alarms instead of treating them as separate maintenance activities.