Condition Based Monitoring for Industrial Machines

Boston/Providence/New Hampshire Reliability Chapters

Please visit https://r1.ieee.org/boston-rl/

More than 38% of global energy is consumed by industry, and within industry almost 70% of electricity is consumed by electric motors. Given the huge energy cost associated with running these motors, even a 1% increase in operational efficiency will result in huge cost savings. Equipment maintenance is key to optimal motor performance.

In general, equipment maintenance can be divided into two broad categories. In the first, equipment is taken out of service on a regular schedule (Preventative Maintenance- PM) and in the second, maintenance occurs when the equipment fails (Corrective Maintenance or “run-to failure”). One occurs too early, the other too late; both are wasteful in terms of time and resources.

A third option is Condition-Based Maintenance/Condition-Based Monitoring (CbM). This places sensors where they can detect subsystem trends or excursions from baseline performance to alert process owners about specific problems- before failures occur- allowing replacement parts to be on hand at a conveniently planned repair time. The process owner is no longer replacing good parts on a scheduled maintenance plan, nor is he or she in crisis hair-on-fire mode because the equipment failed unexpectedly.

Please join us as Richard Anslow, System Applications Manager within the Industrial Automation Business Unit at Analog Devices, gives us a fascinating introduction to CbM, and how it can improve the availability and reduce costs of systems that we support and work with!

Presentation Overview

Background for CbM

• What is CbM?
• What are the benefits? What are the limitations?
• Real life examples.
  • How do I spot faults from FFT signatures of a motor?

Insights from Different CbM Sensor technologies

• Vibration
• Temperature
• Magnetic

Sensor types and Market outlook

Market outlook for wired and wireless sensors

Wireless sensor examples

Wired sensor examples

Cloud and Edge Artificial Intelligence

Speaker

Richard Anslow of Analog Devices, Inc.

Richard Anslow is a System Applications Manager within the Industrial Automation Business Unit at Analog Devices.

His areas of expertise are condition-based monitoring, motor control, and industrial communication design.

He received his B.Eng. and M.Eng. degrees from the University of Limerick, Limerick, Ireland. Recently he completed a postgraduate program in AI and ML with Purdue University.

Location:  This Webinar is to be delivered virtually.

At registration, you must provide a valid e-mail address to receive the Webinar Session link approximately 15 hours before the event. The link will only be sent to the e-mail address entered with your registration. Please double-check for spelling errors. If you haven’t received the e-mail as scheduled, please check your spam folder and alternate e- mail accounts before contacting the host.

Contact Event Host:  Michael W. Bannan.  Chair IEEE Boston/Providence/New Hampshire Reliability Chapter

Registration Starts 12 April 2023 12:00 AM Ends 09 May 2023 05:30 PM All times are (UTC-05:00) Eastern Time (US & Canada) No Admission Charge

Agenda

11:00 AM – Technical Presentation

11:45 AM – Questions and Answers

12:00 PM – Adjournment

The meeting is open to all. You do not need to belong to the IEEE to attend this event; however, we welcome your consideration of IEEE membership as a career enhancing technical affiliation.

There is no cost to register or attend, but registration is required.

Registration:  https://events.vtools.ieee.org/m/356460