Date: Thursday, July 20, 2023 - 6:30 pm to 8:30 pm

Location: In-Person at Courtyard Toronto Markham (65 Minthorn Blvd, Markham, ON)

*Venue space is limited. Please register as soon as possible. (Food and refreshment will be provided.)

Registration: https://www.eventbrite.ca/e/peo-york-predicting-equipment-failures-with-ai-why-how-tickets-657729626017?aff=oddtdtcreator

Event Information:

Equipment maintenance makes up about 30% of OPEX costs on average across all sectors. Given the market competition, push for sustainability, and inflationary costs, how do you make your maintenance efficient? Predict the failures ahead and be prepared to execute maintenance.

Performing maintenance after equipment failure causes longer downtime, is expensive, hazardous, and leaves customers dissatisfied. In contrast, a Predictive Maintenance (PdM) strategy, where the impending equipment failure is detected earlier, maximizes the equipment availability given the cost and project constraints. However, maintenance programs are ridden with implementation challenges restricting the value gained from it. Multiplying the traditional Predictive Maintenance with AI/ML algorithms will automate the analysis, expand the coverage to the whole system, and detect failures earlier giving longer times to respond. The resulting maintenance plan is optimized and dynamic for the changing conditions, directly improving the Availability & OEE metrics. The presentation will showcase how ML algorithms are integrated into standard maintenance processes. Attendees will see an example case and learn the workflow.

Agenda:

6:30 - 6:35 pm Event Starting

6:35 - 7:30 pm Presentation

7:30 - 8:00 pm Q & A

8:00 - 8:30 pm Professional Networking

Our Guest Speaker:

Arun Gowtham, P.Eng., CRE, CMRP

Founder, Owtrun Reliability

Arun Gowtham is a Certified Reliability Engineer with international experience in leading organizational Asset Management programs at Hydrogen Fuel Cell, Pharmaceutical, Chemical, and Composite manufacturing industries. Arun has successfully applied Reliability-Centered Maintenance (RCM) tools to optimize equipment maintenance plans, resulting in increased uptime and cost savings. He has complemented his maintenance analysis with Design for Reliability (DfR) strategies to sustain the reliability improvement achieved. His journey into the exciting field of Reliability Engineering started with thesis work 'Predictive Modeling & IETM support for RCM' and since then has extended into various Industry 4.0 technologies such as Industrial Internet of Things (IIoT), Automation, Remote Fleet Management, and Predictive Maintenance.

Arun's current focus is on applying AI to augment Reliability & Maintenance tasks. His research work on ML-based Predictive Maintenance was well received at RAMS & MainTrain conferences, leading to a patented approach. He holds a MS Mechanical Engineering from Drexel University, PA, USA. He volunteers as Secretary at PEMAC GTA Chapter, and Education Chair at SRE Ottawa; and is a licensed Engineer in Ontario (PEO).

Oliver Xiao, P.Eng.

Director, Business and Community Outreach

PEO York Chapter

*By registering and attending In-Person PEO York Chapter events, attendees acknowledge the voluntary compliance of all host venue safety policies and local Public Health Requirements. Your participation is voluntary, PEO and PEO York Chapter decline any responsibilities and liabilities to event participants. Attendees also acknowledge and give PEO York Chapter full consent to use, reproduce and publish photos taken during the event.

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