Streamline & Accelerate Material Safety Data Sheet (SDS) processing with our automated SDS Data Extraction Web Application

Armed Forces • Web Application, AI/ML Analytics

This case study explores the development of a web-based solution by DASH aimed at automating the extraction of data from Material Safety Data Sheets (SDS). The project's objective is to enhance efficiency by speeding up the process of data retrieval and management. The solution is delivered as a user-friendly web application designed to facilitate the uploading and processing of SDS files, thereby optimizing workflow and ensuring compliance with safety regulations.

About the Client

Pioneering Airpower Excellence

As a critical arm of the US government, is dedicated to maintaining air superiority, executing global strikes, ensuring rapid global mobility, conducting intelligence, surveillance, and reconnaissance, and providing command and control. To achieve these objectives, the organization prioritizes the health and safety of its personnel and the integrity of its supply chain, while continually adapting to evolving regulations and emerging challenges.

Business Challenges

The client faced significant challenges in extracting data fields from Material Safety Data Sheets (SDS) due to a manual process that required extensive human input. This manual extraction not only consumed a considerable amount of time but also necessitated a large team to manage the workload. Given the complexity of SDS extraction, which is a common issue for chemical-handling companies worldwide, the client sought an AI-driven solution to automate the process. This would reduce dependencies and streamline operations with a centralized system.

Manual labor work

Data extraction complexity

Lack of analytics

Need for a centralized system to address all issues

Inadequate tracking of ingredient sourcing.

Our Solution

To address the challenges, we used computer vision and machine learning models to automate SDS data extraction and visualization.

Utilization of Computer Vision and Machine Learning Models

Employed advanced technologies to automate the extraction of data from SDS.

Implementation of Novel Algorithms for Key-Value Extraction

Developed and implemented advanced algorithms to extract, segment, and classify text from SDS to accurately fetch key-value pairs for precise data retrieval.

Data Breakdown and Presentation on the Front End

Processed and displayed extracted data clearly and efficiently on the user interface.

Introduction of Graphs and Charts for Data Visualization

Added graphical representations to enhance the analysis and utilization of SDS data points.

Business Outcome

Driving Efficiency with a Centralized, User-Friendly System

Following implementation, the client's analysts experienced improved operational efficiency with seamless access to a centralized system, enhancing workflow flexibility and reducing manual workload significantly.
  • Increased operational efficiency by 40%.
  • Client satisfaction ratings improved by 30%.
  • Enabled remote access and operation from any location.
  • Reduced manual workload by 50%.
  • Enhanced system usability, resulting in a 25% increase in user adoption.
Python
Angular
Java Script
HTML 5
SQL Server Mgmt Studio
Disclaimer:

In the interest of confidentiality and respecting our client partnerships, we refrain from disclosing specific client names within our case studies.

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