Event calendar

In this session, we'll use real manufacturer stories to explain how they use OEE data to identify recurring losses — from changeover variance to microstops — and how they use that data to prioritise the improvement efforts that deliver the biggest return.
You’ll see how manufacturers move from high-level OEE scores to specific, repeatable improvements that reduce recurring issues — not just better reporting.

Learn how to create, save, and visualise KPIs in Maintmaster, including how to display them on the start page and summary pages for clearer insights into your work order flow.

This webinar guides you step by step through building KPIs, storing historical values, and integrating them into dashboards so your team can access key metrics instantly.

This webinar explains how integrating CMMS and OEE data changes day-to-day decisions: downtime linked to assets, failures tied to work orders, and maintenance work prioritised by production impact rather than urgency alone.

You’ll see what integration looks like in practice, what data is shared, and how it supports better conversations between maintenance and operations.

Learn how to transform a brand-new workflow  -  such as operator maintenance - into a fully functioning process in Maintmaster.

This webinar guides you step by step through mapping the flow, defining routines, setting conditions, and building selections so your operator-driven maintenance work becomes structured, visible, and easy to manage.

This session breaks down what’s required to move from concept to value: workcentre definitions, equipment scope, downtime categorisation, data sources, and the roles maintenance and operations must play. It also clarifies what Maintmaster supports and what needs to be defined internally.

You’ll see how clear definitions make OEE data usable for maintenance and operational decisions.

Your maintenance logs contain the answers to recurring failures — but they’re buried in messy notes and tribal knowledge. In this webinar, discover how Maintmaster MI uses AI to structure work order comments, detect recurring fault patterns, and build a searchable Troubleshooter database from the data you already have. Learn how to reduce MTTR, retain critical know-how, and move from reactive firefighting to proactive, prevention-driven maintenance.