The Continued Rise of AI and ML Integration
AI may seem like it’s having its heyday, but the truth is that we haven’t even seen a fraction of what it’s capable of. With possibilities of the future aside, it’s certainly true that AI is actively transforming industries across the board as companies and facilities adopt it into their practices more and more. Spearheading a significant portion of AI’s use is machine learning (ML). As Damien Fellowes writes for The Manufacturer, “In the manufacturing industry, Machine Learning (ML), a critical subset of Artificial Intelligence (AI), involves the use of sophisticated algorithms to learn from and make predictions based on data.”
ML in Manufacturing
Manufacturing is a prime example of an industry really beginning to benefit from the aid of ML. In addition to its role in analyzing data like mentioned above, the algorithms it produces can monitor equipment, streamline production schedules, detect anomalies in SCADA systems, and even help operators adhere to industry standards.
In additive manufacturing in the aerospace industry, specifically, the integration of AI and ML is pushing research and development forward and creating opportunities for the industry to “to correlate materials with specific parameter sets, achieving a consistent and reliable material output, and validating a robust process,” according to Brandon D. Ribic’s, Ph.D, article for Quality Magazine. This has inspired projects such as the Institute and the National Center for Defense Manufacturing and Machining’s (NCDMM) $3.2M initiative, “Demonstration of Novel Methods for Effective AM Process Qualification/Re-Qualification – Delta Qualification.”
Challenges with AI and ML Integration
Of course, with the benefits comes some drawbacks. For one, AI and ML integration can cause greater cybersecurity risk. It can widen the attack surface, fall victim to data poisoning, create a glitch in the supply chain, or even be the target of model theft. Some AI and ML integration also requires specific expertise, especially in highly specialized areas such as aerospace. Plus, it can still be costly. However, there are efforts to address this barrier. Boosted by the Department of Energy, the Clean Energy Smart Manufacturing Innovation Institute (CESMII) has been working to establish access to AI applications at a lesser cost. Tobey Strauch explains at Control Design that the program is “enabling small and large manufacturers to find ways of improving machines and integrating old and new platforms by using machine learning and artificial intelligence. Projects include load optimization in furnaces to save fuel during thermal processing. Machine diagnostics are being utilized to train on upset conditions. Digital twins are being used to simulate real-time process control and derive solutions without wasting product.”
Camera System Setup and Configuration Service
Addressing the issues around security and offering greater access will accelerate the potential of AI and ML integration, introducing the next phase as it becomes commonplace.
In the meantime, there are simple ways you can begin introducing AI and machine learning into your operations. One way is by installing a Cognex or Keyence camera system into your automation process. Cognex and Keyence cameras, known for their use of AI and machine learning, are designed to reduce startup time and simplify configuration.
At AtomTech, we specialize in integrating advanced camera systems into PLC-controlled environments. While we may not be vision system experts, our team is highly skilled in the setup and configuration of these cutting-edge cameras to ensure they work seamlessly within your existing control systems.
Our experienced technicians can assist with the installation, configuration, and integration of these AI-powered systems, enabling you to get your operations up and running quickly and efficiently. Trust us to handle the technical details, so you can focus on achieving your operational goals.
Let us help you make the most of your camera system investment.
Sources:
● “Transforming manufacturing with AI and machine learning: Real-world applications and data management integration” - Damien Fellowes, The Manufacturer
● “Exploring the Integration of AI and Machine Learning in AM Aerospace Applications” - Brandon D. Ribic Ph.D, Quality Magazine
● “AI and Machine Learning in Automation: The Security Imperative” - Vaibhav Malik, Automation.com
● “PLC integration with AI/ML can enable smart manufacturing” - Tobey Strauch, Control Design