Manufacturing | Industry
Documentation Summarization and Recommendation for Quality Audit
Objective
Manufacturing organizations require an efficient system to summarize and recommend documentation for quality audits as manual processes are time-consuming and prone to errors, leading to delays in compliance and potential quality issues.
Challenges
- A high volume of documentation to review and summarize.
- Ensuring accuracy and relevance of summarized content.
- Integrating recommendations into existing quality audit workflows.
Solution Proposed
- Utilize Azure Open AI for document summarization.
- Implement recommendation systems using collaborative and content-based filtering techniques.
- Develop a user-friendly interface for easy access to summarized documents and recommendations.
- Use Azure Data Factory for data ingestion and preprocessing, and Azure Cognitive Search for efficient information retrieval.
Outcome
- Improved accuracy in quality audits by 40%.
- Reduction in manual review time.
- Enhanced compliance with industry standards.
- Increased efficiency in audit preparation and execution.
Design & Thinking Wins
- Successful integration with existing manufacturing processes.
- Positive feedback from quality auditors on ease of use and effectiveness.
- Scalable solution that is adaptable to other industrial processes.
Disclaimer: The outline showcases the typical challenges, solutions, designs, and outcomes for industries and functions, in general, based on Affine’s prowess in the Industry. The outcomes would be much higher for specific clients as they would be based on their data and specific problems to be solved.
