Webinars
Choosing the Most Suitable Predictive Maintenance Sensor
When monitoring the health of a machine, tasked with keeping a process running, it is vitally important to select the most suitable sensors to ensure faults can be detected, diagnosed and even predicted thus avoiding unplanned downtime and loss of revenue. In this webinar we will discuss which predictive maintenance sensors are vital to early detection of faults in a PdM application as well as their strengths and weaknesses.
- Chris Murphy
- Analog Devices, Inc
Integrating Condition Monitoring with CMMS
Modern manufacturing facilities are utilizing asset condition monitoring technologies to detect problems in equipment and notify staff. Diagnostic sensors are used to track the physical condition of equipment and detect issues in temperature, vibration and other other factors. However, implementing condition monitoring isn’t helpful unless there is a mechanism in place to create plans of action when these problems are detected..
- Frank Harmuth
- DPSI
Lower Your TCO with Automatic Lube Systems
Learn how you can enhance your plant’s reliability and reduce your total cost of ownership with automatic lubrication systems.
- Preston Rubottom
- Lubrication Engineers
Building Blocks for Reliability – Reliability Performance Model
As Technical Director for AVT Reliability Group, Lee McFarlane will outline the building blocks of industrial plant reliability and areas of focus. By reviewing 28 key areas and conducting a basic gap analysis process, you can start to build and embrace cultural change towards a high reliability focused organisation.
- Lee McFarlane
- AVT Reliability
Predictive Maintenance – Fantasy or Reality?
Advances in AI and machine learning have been tremendous in recent years and impact our lives in many different and significant ways. We’ve seen self-driving cars become a reality, we are able to communicate with our homes using Alexa, and we are able to draft responses to our emails using AI virtual assistants. In this webinar, we will discuss a methodology for building hybrid engineering and machine learning models that may be applied cross-equipment and industry.
- Alexandra Gunderson
- Unifai
Implementation Do’s and Don’ts
As a certified reliability leader, Raymond Lattanzio has overseen the implementation of over 100 new CMMS systems. This has shown him which clients succeed with their systems, which do not, and why. In this webinar, he draws from his experience to give us some dos, don’ts, and key points for success with CMMS, including getting buy-in from every level of the organization, pacing yourself, and keeping it simple.
- Raymond Lattanzio
- Fluke Corporation
Coolant Testing: 5 Reasons to Start Now
Have you lost an engine and wish you could have caught the problem before the point of no return? What if you could determine the root cause all together and stop future failures? Participating in coolant testing can do exactly that. Testing your system's coolant, along with the lubricant, provides the complete picture of what's going on and can identify potential catastrophic engine failures.
- Emily Featherston
- POLARIS Laboratories
Introduction to Electrical Signature Analysis (ESA)
Introduction to Electrical Signature Analysis (ESA). Find out how and where to implement ESA testing. Review examples of different electrical and/or mechanical issues.
- Bill Kruger
- ALL-TEST Pro
Profitable Condition Monitoring
This webinar covers how condition-based maintenance fits into Industry 4.0 and examples of what a KPI toolbox can include. Hedlund provides models, such as the DuPont model, that show how we can use CBM to influence the ROI of a company. At the end, he illustrates his point with a case study from a paper mill.
- Håkan Hedlund
- SPM Instrument AB