Asset Performance Management

Assembly Line

Eliminate blind spots with asset monitoring across the plant


Author: Paul Heine

Topics: Asset Performance Management

Organizations: Sensata Technologies

With technology-driven insights that don’t put pressure on headcount, plant managers can look to scale asset monitoring goals beyond critical assets to see machine health for all plant assets.

Read more at Plant Engineering

How to Use Data in a Predictive Maintenance Strategy


Author: Lucinda Reynolds

Topics: Manufacturing Analytics, Asset Performance Management

Organizations: Uptake

Free-Text and label correction engines are a solution to clean up missing or inconsistent work order and parts order data. Pattern recognition algorithms can replace missing items such as funding center codes. They also fix work order (WO) descriptions to match the work actually performed. This can often yield a 15% shift in root cause binning over non-corrected WO and parts data.

With programmable logic controller-generated threshold alarms (like an alarm that is generated when a single sensor exceeds a static value), “nuisance” alarms are often generated and then ignored. These false alarms quickly degrade the culture of an operating staff as their focus is shifted away from finding the underlying problem that is causing the alarm. In time, these distractions threaten the health of the equipment, as teams focus on making the alarm stop rather than addressing the issue.

Read more at Uptake Blog

Industry 4.0 and the pursuit of resiliency


Author: Kate Carroll de Gutes

Topics: Zero Defect Manufacturing, Visual Inspection, Asset Performance Management

Organizations: IBM

There are two parts to the Zero D story. Visual inspection and asset performance management (APM). Visual inspection uses computer vision models focused on quality inspection. APM uses machine learning models based on time series data to determine health of assets and probable failures in the future. Toyota is using Maximo Visual Inspection, and now they are also using the Maximo Asset Performance Management (APM) suite. They tested Maximo APM on some of their machinery that does liquid cooling and found that was another problem area for them. By implementing the software into this pilot, they are now able to monitor the asset health 24×7 and predict probability of failure in the future.

Read more at IBM Blog

Siemens Energy HRSG Digital Twin Simulation Using NVIDIA Modulus and Omniverse