Enterprise Knowledge Search
Rockwell needed to reduce the time and inconsistency involved in diagnosing machine faults, preserve retiring workers' tacit shop-floor knowledge, and shorten training time for new technicians supporting hundreds of machines.
Reported impact
Rockwell says the maintenance copilot has made troubleshooting faster and more consistent, reduced machine downtime and maintenance-related costs, accelerated onboarding for new workers, and created a reusable architecture for rollout across additional plants.
Rockwell Automation built its GenAI-Powered Maintenance Copilot on Microsoft Azure for the Singapore plant to turn hard-to-find troubleshooting knowledge into real-time guidance on the factory floor. The implementation draws on three explicit sources: veteran engineers’ expert know-how, data from Rockwell’s manufacturing software, and machine instruction manuals. Rockwell organizes this material in a database by symptom, cause and reaction. When a technician submits a natural-language question, Azure AI Search retrieves the most relevant prior fixes and manual passages, and Azure OpenAI Service in Microsoft Foundry uses GPT-5.4-mini to generate a step-by-step diagnosis and recommended actions. The copilot is served to workers on tablets and smart augmented reality goggles, while Azure security, identity and governance services provide enterprise protection and compliance. Microsoft Azure’s cloud-native architecture also supports scaling the design from one factory to deployments in Ohio, Poland and Mexico.
The copilot ingests veteran engineers’ troubleshooting knowledge, data from Rockwell’s manufacturing software, and machine instruction manuals into a database organized by symptom, cause and reaction. When a technician asks a natural-language question from a tablet or AR goggles, Azure AI Search retrieves relevant records and manual passages, Azure OpenAI Service with GPT-5.4-mini reasons over that context, and the system returns a step-by-step troubleshooting guide.
“Dey says his team built these AI tools leveraging the breadth of the Microsoft technology stack. This included Azure OpenAI Service and Azure AI Search for conversational experiences and intelligent reasoning, and Azure’s security, identity and governance services to ensure enterprise-grade protection and compliance.”
“Instead of it taking nine months for them to learn how to troubleshoot hundreds of machines, it takes three months.”
“Microsoft’s cloud-native architecture supports expansion from a single factory to global deployments.”
“Powered by Microsoft Azure and built using Azure OpenAI in Microsoft Foundry, this AI tool runs on Open AI’s large language model GPT-5.4-mini.”
“Since October 2025, technicians overseeing hundreds of machines at Rockwell Automation’s Singapore site have been using the GenAI-Powered Maintenance Copilot, an in-house AI assistant trained on its workers’ expert knowledge, data from its manufacturing software and the machines’ instruction manuals.”
“The key thing we want to solve is the loss of knowledge, what we call the tribal knowledge.”
“They spend less on servicing and spare parts, with Rockwell’s internal tracking showing costs are down by about 25 percent.”
“This consistent, targeted approach, according to Wang, has lowered their machines’ downtime by 33 percent.”
Review how this reference was scored and trace each normalized claim back to its documented source.
Scoring methodology
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Traceability
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
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