Yesp StudioConfidential · Enterprise Manufacturer
22% reduction in unplanned downtime and proactive scheduling for critical assets.
Aging OT and unplanned downtime were eroding throughput across multiple lines.
Context, scope, and success criteria
Several production lines were experiencing avoidable downtime because maintenance was largely reactive and the telemetry being collected was not standardized enough to support reliable forecasting. The plant had strong technical expertise, but no shared reliability model across lines or sites.
- Reduce unplanned downtime on the highest-impact asset classes without disrupting existing maintenance workflows.
- Improve maintenance planning confidence by giving planners early warning signals they could trust.
- Integrate predictions into frontline operations so the plant floor could act on them, not just inspect dashboards.
- Create a repeatable pattern that could be rolled out to other sites.
Why the work started
Aging OT and unplanned downtime were eroding throughput across multiple lines.
What we built
Predictive maintenance powered by digital twins on Azure IoT with closed-loop work-order automation.
Legacy versus modern flow
Reactive maintenance processes, fragmented machine telemetry, and no standard model for prioritizing asset risk.
Azure IoT digital twins connected to predictive models, CMMS automation, and plant-level reliability dashboards for closed-loop maintenance.
How the work was executed
Established sensor quality baselines, model targets, and digital twin definitions for the top asset classes.
Trained failure prediction models using maintenance history, downtime logs, and live telemetry signals.
Integrated alerts and work-order automation into the CMMS so planners received action, not just predictions.
Introduced reliability review dashboards to compare predicted failures against actual outcomes.
Controls and delivery rhythm
Model performance, false-positive rates, and asset coverage were reviewed in a cross-functional reliability board every sprint, with plant leadership signing off on rollout thresholds.
Plant reliability improved with proactive intervention patterns, stronger maintenance-resource allocation, and less unplanned disruption to production schedules.
Results and next steps
22% reduction in unplanned downtime and proactive scheduling for critical assets.
Expansion to additional sites is underway, along with energy optimization signals that can be layered into the same digital-twin foundation.
Have similar architecture bottlenecks?
We can map the same modernization pattern to your infrastructure, release process, and operating model.