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Updated: Jun 1, 2026

Atomic Scale Structural Studies of Macromolecular Assemblies by Solid-state Nuclear Magnetic Resonance Spectroscopy
Published on: September 17, 2017
A LEAN approach toward automated analysis and data processing of polymers using proton NMR spectroscopy
Hans de Brouwer1, Gerrit Stegeman
1SABIC Innovative Plastics, Global Analytical Technology, Bergen op Zoom, The Netherlands. hans.debrouwer@sabic-ip.com
Automating nuclear magnetic resonance (NMR) data processing significantly improved lab efficiency. This enhancement boosted sample throughput by 100% and reduced turnaround time, optimizing resource utilization.
Area of Science:
- Analytical Chemistry
- Laboratory Automation
- Process Improvement
Background:
- Expensive laboratory instruments require maximum utilization.
- Skilled human resources need effective deployment.
- Manual NMR data processing is time-consuming and prone to variability.
Purpose of the Study:
- To automate the entire data processing, calculation, and reporting chain for NMR data.
- To improve quality and reliability of NMR data analysis.
- To free up valuable human resources and increase laboratory productivity.
Main Methods:
- Applied LEAN process improvement tools to identify inefficiencies.
- Developed an in-house software package for automated data treatment.
- Implemented consistent data processing and uniform results administration.
Main Results:
- Reduced operator time by 35%.
- Doubled annual sample throughput from 1400 to 2800.
- Decreased turnaround time from 6 days to less than 2 days.
Conclusions:
- Automation of NMR data processing enhances quality and reliability.
- Significant improvements in productivity and resource utilization were achieved.
- The developed software provides a robust solution for NMR data analysis.
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