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AI App for Safer Machinery Troubleshooting

An LLM-powered application designed to improve machinery troubleshooting and enhance safety protocol adherence of its workers within a manufacturing setting.
LLM App for Safer Machinery Troubleshooting


A top Fortune 500 manufacturing organization faced the challenge of managing multiple machinery types while also having to ensure its workers’ adherence to stringent safety protocols. The organization had multiple manuals and databases containing information on equipment troubleshooting steps, safety protocols, and pre-repair routines. Workers needed to navigate through these resources before initiating repairs for malfunctioning machines. Unfortunately, this process was time-consuming and ineffective. Faced with these challenges, the organization sought LeewayHertz’s collaboration to architect a solution that would streamline this complicated process, enhance operational efficiency, and ensure the workers’ strict adherence to safety standards across its manufacturing units.


As a solution, LeewayHertz developed a custom LLM-based application that seamlessly integrated the organization’s static machinery data and dynamic safety policies. A hybrid approach was adopted, effortlessly combining LLM fine-tuning designed for static equipment data with embedding methodologies dedicated to dynamic safety policies. The result was an intelligent application comprising a comprehensive knowledge base, offering precise and accurate responses to the queries posed by the company’s workers. Prompt engineering techniques further customized the application, offering context-aligned guidance to the manufacturing company’s workers, ultimately contributing to a more efficient and safe work environment.

How Does the App Work?

How Does the App Work


Safety Compliance:

It offered clear instructions on how to handle equipment safely.

A User-friendly Interface:

Its user-friendly, easily navigable interface enabled workers to handle machinery tasks easily.

Efficient Troubleshooting:

The app facilitated workers to have quick access to relevant information for fixing machinery issues.

Requisite Form Automation:

It offered clear instructions on how to handle equipment safely.

The Outcome.

Swift Query Handling :

The app provided ready access to accurate information, reducing search time and improving troubleshooting efficiency.

Reduced Accidents:

The app helped minimize on-floor accidents by reinforcing safety practices.

Context-aligned Responses:

Offered precise guidance aligning with the organization’s equipment/safety rules and protocols.

Operational Efficiency:

The application facilitated automated knowledge sharing, reducing reliance on human resources.

Final Product.

Technologies Employed.