Exploring the Use of ChatGPT with Manufacturing Systems

Maggio 17, 2023

Last month I asked ChatGPT which benefits its integration with a manufacturing execution system (MES) could provide and what the role of a system integrator could be in such a scenario. It provided me four main benefits and some good ideas on the role of a system integrator in the implementation of a ChatGPT solution integrated with MES.

The main benefits it identified were:

  • Provide real-time information and updates on the status of various processes and equipment in a manufacturing facility.
  • Support proactive maintenance and troubleshooting for operators.
  • Streamline the reporting process.
  • Enhance the overall user experience with a conversational interface that is intuitive and user-friendly.

Impressed with these initial responses, I decided to dig deeper into the value generative AI (artificial intelligence) can bring to the manufacturing world. Unfortunately, ChatGPT was made unavailable in Italy (where we are located) due to privacy concerns—we Italians always find very effective way to stay behind on innovation. So, I used Bing Chat that accesses ChatGPT-4 through APIs (application programming interfaces).

Following is the result of my interview with ChatGPT via Bing Chat:

Q. I’m a little confused about how generative AI can help provide real-time information on the status of processes and equipment in a manufacturing facility. What is the added value with respect to more traditional solutions like SCADA?

A. Generative AI models like ChatGPT can be used to analyze written reports and data from quality control inspections, identifying patterns and trends in product defects. They can also be used for predictive maintenance by analyzing data from sensors and other sources to predict when equipment will fail and schedule maintenance before it happens (ChatGPT source: How Can ChatGPT Be Used by Manufacturing Organizations?). ChatGPT can continuously improve its performance by using machine learning algorithms that learn from previous experiences to generate more efficient Gcode (ChatGPT source: Assessing the capabilities of ChatGPT to improve additive manufacturing).

SCADA (supervisory control and data acquisition) systems are used to monitor and control industrial processes. They are typically used in large-scale manufacturing facilities where there are many different processes that need to be monitored and controlled (ChatGPT source: ChatGPT is changing manufacturing…here’s how to use it). While SCADA systems are useful for monitoring and controlling industrial processes, they are not designed to analyze data in real-time or provide predictive maintenance (ChatGPT source: How Can ChatGPT Be Used by Manufacturing Organizations?).

ChatGPT can provide real-time information on the status of processes and equipment in a manufacturing facility by analyzing data from sensors and other sources in real time (ChatGPT source: How Can ChatGPT Be Used by Manufacturing Organizations?). This allows operators to quickly identify issues with equipment or processes and take corrective action before they become major problems (ChatGPT source: ChatGPT is changing manufacturing…here’s how to use it).

Q. So, in your opinion, the main advantage of ChatGPT with respect to a SCADA system is the continuous learning capability. But couldn’t they embed some data analysis capability?

A. Yes, that’s correct. While SCADA systems can be used to monitor and control industrial processes, they are not designed to analyze data in real-time or provide predictive maintenance.

However, it is possible to embed some data analysis capability into a SCADA system by using machine learning algorithms. This would allow the system to analyze data in real-time and provide predictive maintenance.

ChatGPT can be used in conjunction with a SCADA system to provide real-time information on the status of processes and equipment in a manufacturing facility. This allows operators to quickly identify issues with equipment or processes and take corrective action before they become major problems.

Q. Do you think that a conversational interface could make a manufacturing execution system or a maintenance system more user friendly? Could this help in compensating for the loss of experience that many manufacturers are experiencing due to the aging workforce megatrend?

A. Yes, conversational interfaces can make a manufacturing execution system or a maintenance system more user-friendly by providing a natural language interface that allows users to interact with the system in a more intuitive way. This can help compensate for the loss of experience that many manufacturers are experiencing due to the aging workforce megatrend.

Conversational interfaces can be used to provide real-time information on the status of processes and equipment in a manufacturing facility, allowing operators to quickly identify issues with equipment or processes and take corrective action before they become major problems. They can also be used to provide predictive maintenance by analyzing data from sensors and other sources to predict when equipment will fail and schedule maintenance before it happens (ChatGPT source: Development of manufacturing execution systems).

Q. Which data sources would you use to provide manufacturing operators the information they need to run their daily tasks? Is there any recommendation on what kind of information should be provided to you to make the information you provide more accurate?

A. There are many data sources that can be used to provide manufacturing operators with the information they need to run their daily tasks. These include data from sensors on equipment and processes, data from enterprise resource planning (ERP) systems, data from manufacturing execution systems (MES) and data from other sources. To make sure that the information I provide is as accurate as possible, it’s important to have access to high-quality data. This means that data should be collected automatically whenever possible to minimize errors and ensure that it’s up to date. It’s also important to have a good understanding of what kind of information is most important for operators to have in order to perform their daily tasks effectively (ChatGPT source: Learning from the most advanced AI in manufacturing and operations).

Q. Could the integration of ChatGPT with a manufacturing execution system be a threat to a manufacturer’s intellectual property or industrial patents?

A. It is possible that integrating ChatGPT with a manufacturing execution system could pose a threat to a manufacturer’s intellectual property or industrial patents. However, it is important to note that ChatGPT is not designed to steal intellectual property (ChatGPT source: Is ChatGPT a cybersecurity threat?). To protect their intellectual property and industrial patents, manufacturers should implement strict security measures such as encryption and access control. They should also limit access to sensitive data by only allowing authorized personnel to access it (ChatGPT source: Intellectual Property in ChatGPT).

I honestly found the answers somehow less precise and impressive than in my previous experiments. I don’t know if that’s because of the Bing interface or, when digging deep into a very specific topic, the system struggles with the base of information it needs to generate good answers. I still believe it’s quite impressive and in my next blog I will provide my considerations and overall view on ChatGPT’s current potential with manufacturing systems.

Originally published on Automation World – May, 2023