Manufacturing | Demand & Production Planning
Shop Floor Daily Action Slip/Document Summarization
Objective
Manufacturing companies generate many daily action slips and documents on the shop floor that are critical for tracking operations, maintenance, and quality control. Manually summarizing these documents is time-consuming and prone to errors, leading to inefficiencies and potential oversight of crucial information.
Challenges
- A high volume of daily documents requiring summarization.
- Variety in document formats and terminologies used.
- Need for accurate and concise summaries to support decision-making.
- Integration with existing Business Intelligence (BI) systems.
Solution Proposed
- Utilize Azure Open AI GPT 4o model for document summarization.
- Implement Machine Learning (ML) models to identify critical information for text classification and entity recognition.
- Integrate with BI tools like Tableau or Power BI for visualization and reporting.
- Engineering efforts to ensure seamless data flow and system integration.
Outcome
- Reduction in manual summarization time by 80%.
- Improved accuracy by eliminating manual typos and errors in capturing critical information.
- Enhanced decision-making with real-time summarized insights.
- Seamless integration with existing BI systems, improving overall workflow efficiency.
Design & Thinking Wins
- Successful deployment in cross-functional manufacturing plants.
- Positive feedback from users on the ease of accessing summarized data.
- Recognition for innovation in AI-driven document management solutions.
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.
