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Monday

Explore Automate 2026 Conference presentations from Monday.

The AI for Industry Challenge Solving the High Value Bottleneck in Electronics Assembly by Jimmy Baraglia

The AI for Industry Challenge Solving the High Value Bottleneck in Electronics Assembly by Jimmy Baraglia

This presentation by Jimmy Baraglia explains the AI for Industry Challenge, which brings together AI researchers, software engineers, and roboticists to solve difficult electronics assembly problems. It focuses on automating cable handling, bridging simulation to real-world robotics, and using AI to improve industrial automation quality and scalability.

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Understanding Time-Of-Flight with Dr Daniel Lau

Understanding Time-Of-Flight with Dr Daniel Lau

This presentation by Dr. Daniel L. Lau explains how time-of-flight cameras work, including direct time-of-flight, indirect time-of-flight, gated/pulsed approaches, continuous-wave methods, and commercial camera behavior. It uses diagrams and camera examples to show how light timing, phase shift, ambient light, and reflected signals are used to calculate distance.

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Neil Farrow and IO-LINK

Neil Farrow and IO-LINK

Neil Farrow explores IO-Link as a standardized communication technology for sensors and actuators. It covers IO-Link basics, masters and sensors, wiring advantages, IODD files, diagnostics, retrofit strategies, analog-to-digital improvements, database connectivity, Industry 4.0 use cases, predictive maintenance, and ROI benefits from reduced wiring, faster setup, and lower downtime.

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Being Data First Removing the Ambiguity of Today and Preparing to Augment the Future by Thomas Kuckhoff

Being Data First Removing the Ambiguity of Today and Preparing to Augment the Future by Thomas Kuckhoff

 Thomas Kuckhoff explains how factories can become data-first to maximize uptime and prepare for agentic AI. It focuses on capturing high-value process insight, building trustworthy baselines, piloting edge-based data systems, scaling without rip-and-replace, and using IO-Link, EtherCAT, edge devices, open protocols, and contextual data to support future AI adoption.

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Alternative Methods of Hazardous Energy Control by Rushiraj Patwardhan

Alternative Methods of Hazardous Energy Control by Rushiraj Patwardhan

Rushiraj Patwardhan explains hazardous energy control, Lockout/Tagout procedures, LOTO policy requirements, relevant U.S., European, and international standards, and when alternative methods may be used. It emphasizes task-based risk assessment, equivalent protection, verification, validation, and examples such as limited-speed tool changes, interlocked movable guards, and complex production-line zoning.

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Francis Vatakencherry Predict Simulate Act with AI Assisted Factory Twin

Francis Vatakencherry Predict Simulate Act with AI Assisted Factory Twin

This presentation explains how AI-assisted factory twins can help manufacturers move from disconnected data and reactive reporting toward predictive, adaptive operations. It covers smart manufacturing, digital twins, AI-driven data orchestration, predictive maintenance, energy transparency, asset intelligence, bottleneck analysis, and shopfloor optimization using Siemens and BorgWarner examples.

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Getting Started in Industrial Robotics by Bob Rochelle

Getting Started in Industrial Robotics by Bob Rochelle

Bob Rochelle introduces the basics of industrial robotics, including the business case for automation, common robot applications, ROI justification, robotics market trends, robot terminology, robot types, collaborative applications, system components, safety, reliability, and how robot manufacturers, system integrators, and end users work together.

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The Software First Factory Automation and AI Are Rewriting Manufacturing by Tom Kelly

The Software First Factory Automation and AI Are Rewriting Manufacturing by Tom Kelly

This presentation by Tom Kelly explains how AI, automation, additive manufacturing, generative design, simulation, and digital twins are reshaping manufacturing. It highlights Automation Alley’s role in Michigan’s Industry 4.0 ecosystem, including Project DIAMOnD, AI adoption examples, and case studies showing cost reduction, faster lead times, distributed manufacturing, and practical first steps for technology adoption.

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Srivatsav Nambi Self-Learning Vision Systems

Srivatsav Nambi Self-Learning Vision Systems

This presentation by Srivatsav Nambi explains why traditional vision systems fail in production due to product variation, drift, maintenance burden, missed defects, and lost operator trust. It introduces self-learning vision systems that learn “normal” from live production, detect anomalies, support operator feedback, use governed updates, and integrate with existing cameras, PLCs, SCADA, MES, and quality systems.

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Michael Mahfet Why ROI Is Not One of the Top Reasons Collaborative Robots Are Justified by Businesses

Michael Mahfet Why ROI Is Not One of the Top Reasons Collaborative Robots Are Justified by Businesses

Michael Mahfet argues that collaborative robots are often justified for reasons beyond traditional ROI. He focuses on labor availability, operational continuity, flexibility, scalability, quality, consistency, safety, ergonomics, engagement, faster deployment, and risk reduction as stronger business drivers for cobot adoption.

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Braden Fioresi Virtual Commissioning for Real Communication

Braden Fioresi Virtual Commissioning for Real Communication

This presentation by Braden Fioresi explains how virtual commissioning improves communication in automation projects. It covers the move from manual drafting and CAD to simulation, emulation, interactive models, VR/AR, and operator training, showing how digital models help teams verify motion, cycle time, robot positions, and stakeholder understanding before physical implementation.

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Marc Fuentes The Future Of Digital Manufacturing In The Era Of Physical Ai

Marc Fuentes The Future Of Digital Manufacturing In The Era Of Physical Ai

This presentation by Marc Fuentes of Eclipse Automation argues that Physical AI technology is already ready, but adoption fails when organizations cannot absorb it. It defines Physical AI as AI that perceives, decides, and acts in the physical world, then explains why automation business cases should focus less on labor savings and more on throughput, quality, risk, change management, and capital planning.

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Introduction to Industrial AI Agents by Kence Anderson

Introduction to Industrial AI Agents by Kence Anderson

This course introduces industrial AI agents as the next evolution of automation, showing how multi-agent systems combine perception, learning, strategy, planning, deduction, and language to improve industrial decision-making and process control.

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