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DTSTART;TZID=America/New_York:20260226T173000
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DESCRIPTION:Debugging Complex Industrial Control Systems: From Field Failur
 es to AI-Assisted Diagnostics\n\nThis session focuses on how complex elect
 rical and control system failures present in live industrial automation en
 vironments and how experienced engineers diagnose and resolve them under r
 eal operational constraints. Using examples from production systems\, the 
 talk examines common failure patterns across power distribution\, machine 
 control logic execution\, motion and speed systems\, sensors\, I/Os\, and 
 industrial networks\, highlighting why root causes are often obscured by i
 nteracting faults across multiple system layers. The session then presents
  a structured\, practitioner-driven debugging approach that leverages live
  PLC or PC-based controller data\, alarms and trends\, electrical and moti
 on diagnostics\, and network behavior to isolate root causes while systems
  remain operational. Emphasis is placed on pattern recognition\, distingui
 shing true faults from nuisance signals\, and validating fixes without int
 roducing secondary issues. The talk concludes by showing how recurring deb
 ug data reveals reliability patterns that support preventative actions\, a
 nd how these same patterns enable emerging AI-assisted diagnostics and pre
 dictive monitoring using live controller and field data focusing on practi
 cal value\, current limitations\, and real-world applicability.\n\nSpeaker
 (s): Divya Srikakulapu\n\nRoom: Voltage Room\, March First Brewing & Disti
 lling\, 7885 E Kemper Rd\, Cincinnati\, Ohio\, United States\, 45249
LOCATION:Room: Voltage Room\, March First Brewing & Distilling\, 7885 E Kem
 per Rd\, Cincinnati\, Ohio\, United States\, 45249
ORGANIZER:dave@arcflashbrokerage.com
SEQUENCE:7
SUMMARY:IEEE Cincinnati February 2026 Meeting
URL;VALUE=URI:https://events.vtools.ieee.org/m/533891
X-ALT-DESC:Description: <br /><div class="WaaZC">\n<div class="rPeykc uP58n
 b MNX06c" data-hveid="CBAQAQ" data-ved="2ahUKEwiagM7jlbKKAxVEq4QIHWJIFzoQo
 _EKegQIEBAB">\n<div data-olk-copy-source="MessageBody">Debugging Complex I
 ndustrial Control Systems: From Field Failures to AI-Assisted Diagnostics<
 /div>\n<div data-olk-copy-source="MessageBody">&nbsp\;</div>\n<div>This se
 ssion focuses on how complex electrical and control system failures presen
 t in live industrial automation environments and how experienced engineers
  diagnose and resolve them under real operational constraints. Using examp
 les from production systems\, the talk examines common failure patterns ac
 ross power distribution\, machine control logic execution\, motion and spe
 ed systems\, sensors\, I/Os\, and industrial networks\, highlighting why r
 oot causes are often obscured by interacting faults across multiple system
  layers. The session then presents a structured\, practitioner-driven debu
 gging approach that leverages live PLC or PC-based controller data\, alarm
 s and trends\, electrical and motion diagnostics\, and network behavior to
  isolate root causes while systems remain operational. Emphasis is placed 
 on pattern recognition\, distinguishing true faults from nuisance signals\
 , and validating fixes without introducing secondary issues. The talk conc
 ludes by showing how recurring debug data reveals reliability patterns tha
 t support preventative actions\, and how these same patterns enable emergi
 ng AI-assisted diagnostics and predictive monitoring using live controller
  and field data focusing on practical value\, current limitations\, and re
 al-world applicability.</div>\n</div>\n</div>
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