Can We Trust AI in a Product’s Lifecycle?
What you’ll learn:
- What Bosch Rexroth thinks about AI in product design.
- How manufacturing is adopting AI, from the company’s perspective.
I was able to get a little time from Garrett Wagg, the ctrlX AUTOMATION Product Manager – Automation & Electrification for Bosch Rexroth. Via email, I asked a series of questions based on the theme “Can we trust AI in a product's lifecycle?” Here’s what he had to say.
How is AI growing in integration within manufacturing?
AI integration in the manufacturing process has drastically grown and transformed how many companies manufacture their products. Growing factors like data availability, machine learning, decreased cost of computing power, advanced AI platforms, and government funding initiatives has led to this integration.
The key benefits this integration adds includes, predictive maintenance, quality control, process optimization, advanced robotic deployment, and demand forecasting.
Is AI accelerating the transition to fully automated processes? If so, how?
Yes, AI is significantly accelerating the transition to fully automated processes. AI integration implements enhanced machine decision-making, improves perception and understanding of the manufacturing environment, and can drastically improve human-robot collaboration.
Traditional automation relies on pre-programmed functions and fixed algorithms in the manufacturing process, while AI empowers machines to make intelligent decisions based on real-time data, adapting to changing conditions and optimizing their performance.
How do control systems play a critical role in managing AI utilization?
Control systems are very critical in implementing and managing AI platforms. The control system in a manufacturing setup would act as the bridge between the AI’s insights and the physical world where those insights are executed.
The control system would ensure the AI’s recommendations are acted out in a safe, efficient, and reliable manner. This would be done through an AI module alongside a PLC device like the Bosch Rexroth ctrlX CORE equipped with the Hailo extension module communicating with a ctrlX safety controller and a variety of sensors closing the data exchange loop.
How does a control system based on an open platform differ in its AI capabilities from controls that operate in a closed system?
Control systems based on open platforms offer significant advantages in AI capabilities compared to closed systems. These advantages include flexibility and customization, where a user is not locked into a proprietary system and can adjust their AI tools based on the application or new features in the market. Other advantages include interoperability, enabling fast communication and data exchange between the control system and other systems, such as ERP, MES, and data historians, to better leverage a system’s data.
What are the risks of increased AI adoption, and are there any safeguards being developed?
AI is a powerful and useful tool, but there are some risks in AI adoption. Some of these risks include security vulnerabilities, where data is maliciously manipulated causing AI to make the incorrect decision.
Another security risk is data privacy. AI algorithms often require large amounts of data, which may include sensitive personal information. The collection, storage, and use of this data raise privacy concerns, particularly if the data is not properly protected. Researchers, policymakers, and industry leaders are working on safeguards for some of these concerns by implementing bias detection, false data identification, and privacy, preserving AI platforms.
How should manufacturers approach integrating AI into their processes, and what are some of the key considerations to keep in mind?
Integrating AI into the manufacturing processes is a strategic undertaking that requires careful planning and execution. A phased approach, focusing on clear objectives and addressing potential challenges, is often the most successful.
Some key considerations to keep in mind include identifying pain points in your process, maximizing data collection, setting measurable goals, and determining what kind of ROI you are receiving from your implemented AI. Lastly, keep safety and security at the forefront of your manufacturing process.
