Enhancing Part-to-Part Repeatability of Force-Sensing Resistors Using a Lean Six Sigma Approach

Area of Science:

• Materials Science
• Sensor Technology
• Industrial Engineering

Background:

• Polymer nanocomposites as force-sensing resistors (FSRs) are widely used in research.
• Inconsistent nanoparticle dispersion leads to variable FSR sensitivity, hindering industrial applications.
• Part-to-part repeatability is crucial for industrial adoption of FSRs.

Purpose of the Study:

• To reduce process variability in FSR sensitivity using the Six Sigma DMAIC methodology.
• To enhance the part-to-part repeatability of FSRs for industrial applications.
• To identify and implement mechanisms for consistent FSR performance.

Main Methods:

• Characterization of FSR sensitivity and physical modeling to understand variability.
• Deployment of the Define, Measure, Analyze, Improve, and Control (DMAIC) cycle.
• Exploration of two mechanisms: null force output voltage for sensor screening and input voltage trimming for sensitivity adjustment.

Main Results:

• Identified null force output voltage as a novel method to discard non-compliant sensors.
• Validated a method to trim FSR sensitivity by adjusting the input voltage.
• Significantly improved part-to-part repeatability of FSRs.

Conclusions:

• The Six Sigma DMAIC approach effectively reduces variability in FSR sensitivity.
• Novel methods for sensor screening and sensitivity trimming enable industrial-grade FSRs.
• Enhanced repeatability makes FSRs viable for demanding industrial applications.