The recession in western manufacturing sector, a new geopolitical order, and shock waves from volatile policy-making ripple through the machine vision industry. In this panel discussion, the experts from Vision Markets will share a structured approach to assess the health of your business and exposure to the geopolitical risks. Learn how you can identify, prioritize, and implement your options from divesting/investing and the diversification to new business models and markets.  

Automated machine vision inspection is everywhere in today's world of manufacturing where human resources are at a premium and difficult inspections are needed at a faster pace.  With the integration of Deep Learning into these machine vision systems how do you know what these systems are passing good parts and failing bad parts?  Is using red rabbits or production managers making fake defects the way you test your systems?  Vision Validation is a new concept for machine vision systems that you can use to test your inspection system to determine if it is still operating within good parameters.  This can be done by having a challenge set of good/bad images that can be run past the system that in theory should produce the correct results.  Not only does the vision system pass/fail correctly, how do you know someone has not changed a parameter within your program that could fail good product or pass bad product?  Vision Validation is a new way to automate and routinely challenge/monitor your machine vision systems to verify that they are working correctly. 

I will explain in depth the idea and process behind how to set this up, and how to automate it so that you have confidence and control over your machine vision inspection systems.  Recalls are very expensive and potentially life threatening so this new technology can be used to help safeguard your production processes and flag any potential issues that may arise from program changes.  Vision validation is also a great way to assist with compliance with the FDA's 21 CFR Part 11 regulations.  

There are a lot of different paths I can take with this, but in the end Vision Validation is a really cool new technology that can be used to help automate the verification process for a machine vision system and then to verify that it is within the correct tolerances.  

Increasing demand for higher-bandwidth imaging across a range of established and emerging applications is driving the development of new technologies and solutions aimed at reducing processing requirements. This session will explore several of these innovative approaches to system and device design, including real-world application examples.

For existing deployments, new GigE Vision-to-Thunderbolt™ solutions expand platform options for system designers while optimizing CPU usage. By combining the cabling and multicasting benefits of GigE Vision, the efficiency of a PCIe frame grabber, and the plug-and-play convenience of Thunderbolt, these solutions enable the use of laptops, single-board computers, and embedded systems for high-bandwidth imaging.

In new device designs, Remote Direct Memory Access (RDMA) over Converged Ethernet v2 (RoCEv2) allows imaging data to be transferred directly from a camera or sensor to the host processor's memory --bypassing the CPU, operating system (OS), and cache. RoCEv2 paves the way for Ethernet-based imaging solutions that support bandwidths of 50, 100, 200, and even 400 Gbps, without increasing receive-side latency.

The promise of AI vision for manufacturing is clear: enhanced quality control and automated inspection. But what happens after the inspection? The true revolution lies in transforming the visual data into actionable intelligence. This talk, "Pixels to Profits: AI Vision for Smart Manufacturing," moves beyond simple defect detection to reveal how a comprehensive, cloud-native system can unlock unprecedented insight into factory floor operations.

We will demonstrate how our system leverages the power of the cloud for high-speed processing and robust data collection, turning raw visual information into a continuous stream of operational knowledge. Attendees will discover how this data is distilled into essential tools for the smart factory: daily digests of production quality, offering a clear and immediate snapshot of performance; and a remote system monitoring dashboard that provides real-time visibility and control from anywhere.

By focusing on the critical link between vision inspection and data-driven insights, this session will show how manufacturers can move from simply identifying problems to proactively understanding and optimizing their entire production process. We will illustrate how this data-centric approach not only boosts quality and efficiency but also provides the strategic intelligence needed to secure a lasting competitive advantage—ultimately turning every pixel into profit.

Discover how LUCID’s Triton Smart camera with Sony’s IMX501 sensor brings AI processing directly onto the sensor—eliminating the need for cloud or host systems. This session explores how on-sensor AI enables real-time, low-latency decision-making at the edge, ideal for smart manufacturing, logistics, and embedded systems. See how tools like Neurala’s Brain Builder streamline model training and deployment, making AI integration more efficient and accessible than ever.

This talk will examine the tradeoffs between Sequential Field Imaging (SFI) and Continuous Imaging (CI) in high-throughput, high-resolution applications. By comparing motion strategies, sensor technologies, and system constraints, we explore how to optimize imaging throughput without compromising quality. Attendees will gain practical insights into when to stop and shoot—and when to stop stopping.

The on-demand economy has put tremendous pressure on enterprises to increase efficiency, quality, and agility, while shortening cycle times. Organizations are being forced to improve output by speeding up production and fulfillment with non-stop automation. Improving output doesn’t mean compromising accuracy.

Zebra Machine Vision solutions enable doubling the accuracy levels to avoid bypass and increase the traceability of goods. By inspecting every part and parcel, customers reduce waste and costs, which improves margins by lowering the cost of exception handling and labor. In this context, it becomes imperative to provide intelligence at the edge that drives outcomes.

This webinar will address Zebra solutions that enable worker efficiency and edge intelligence that drives meaningful outcomes.

Machine Vision is transforming industrial inspection by enabling automated, data-driven evaluation of assets across manufacturing and instrastructure sectors. This talk explores the machine vision innovation pipeline--from compiling meaningful datasets and developing robust algorithms to deploying interoperable, real-world solutions. Emphasis will be placed on how inspection results can inform industrial asset life-cycle management when integrated with standardized frameworks, cloud computing, and industrial IoT platforms. This talk will also discuss how machine vision data feeds into digital twins for real-time monitoring, predictive maintenance, and system optimization.