Jumpstart Your AI Projects: Explore Top AI Applications at the AI & Smart Automation Conference

From generative artificial intelligence (AI) to deep learning software, AI remains a popular topic in the industrial space and beyond. While AI technology can at times be overhyped or misunderstood, AI tools have undoubtedly helped open the door to new possibilities in manufacturing and industrial settings in the past few years across a range of different applications. However, AI is not magic, so launching a successful project must start with the correct specification of the tool for the application.

Industrial AI Beyond Just Deep Learning

Deep learning has been perhaps the most popular AI-related buzzword within the industrial automation space over the past several years, but today it’s helping solve real problems in practical applications. One such application is automated inspection. There, traditional rules-based machine vision algorithms excel in discrete analysis, including measurements, detecting known and quantifiable features, and reporting on features based on geometry, size, and other characteristics. Deep learning adds tremendous value in automated inspection when it comes to detecting subjective features, such as anomalies or defects, or performing classification or image segmentation.  

The realm of potential industrial AI applications continues to expand beyond just visual inspection. Some popular and emerging areas of AI deployment include:

• Simulation: Within manufacturing and industrial settings, simulation tools offer a means for designing, testing, and simulating systems such as robotics, autonomous mobile robots (AMRs), and autonomous vehicles. AI has helped open new possibilities within simulation. For example, companies can now deploy a digital twin of a physical system, such as a robot, a manufacturing process, or an entire plant floor, within an AI-generated simulation environment for development, testing, and refining before rolling out the physical system or infrastructure.
• Predictive technologies: AI algorithms are only as good as the data with which they are trained. As data collection improves over time, so do AI tools, such as those used for predictive maintenance. Traditional maintenance schedules are based on estimates of a machine or component’s life expectancy or recommendations from the manufacturer. Instead of relying on educated guesses or waiting until a machine ultimately fails, companies can take a data-driven approach to understanding how a machine is working and when it might fail. With an AI model, process data is captured through various sensors and fed to a machine learning system. The AI system learns the process to the extent that it can identify inefficiencies and predict the life span of equipment across the facility before any failures.
• Autonomous systems: Autonomous systems such as AMRs have been adding value in warehouses and factories for some time now, but the introduction of AI-enabled software has made these systems even more flexible. For example, AMRs equipped with AI can translate historical movement data into path planning. So if an AMR encounters a row in a warehouse that has previously often had obstructions, the robot is able to avoid this row as much as possible and calculate an alternate path.
• Large language models: Perhaps initially dismissed as a technology that could not practically serve the industrial automation space, large language models (LLMs), such as ChatGPT, have now carved out a useful niche. For example, companies such as Beckhoff and Siemens have leveraged LLMs to allow users to more quickly and easily program PLCs. Additional companies that have leveraged or plan to use similar AI tools include Microsoft, Boston Dynamics, Rockwell Automation, and Doosan.

Begin Your AI Journey in Person

For businesses looking to discover how AI might help — whether in the area of product design, process optimization, resource management, quality control, or beyond — A3 once again hosts its AI & Smart Automation Conference. This year’s conference takes place November 12–13, in Atlanta, Georgia. The conference features keynotes, general sessions, and networking opportunities and is targeted toward anyone currently using or interested in using AI technologies in manufacturing or industrial operations. Attendees can expect to learn about the latest advances in:

• Simulation
• LLMs
• Ease-of-use programming
• Smart robotics
• AI-based inspection
• Edge-to-cloud architecture
• Predictive technologies

In addition, the conference features a new four-hour course on designing autonomous AI agents, which are intelligent systems programmed to autonomously perform specific tasks. The course covers principles, strategies, and methodologies used to create these systems and includes theoretical instruction and hands-on projects designed to empower attendees to create, implement, and evaluate AI agents.

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The event will be held at the Georgia Tech Learning Center and is open for registration now. Learn more or register for the 2024 AI & Smart Automation Conference.