Date of Award

2026

Degree Type

Thesis

Degree Name

Master of Science in Systems Engineering

Department

Mechanical, Industrial and Systems Engineering

First Advisor

Valerie Maier-Speredelozzi

Abstract

Textile-based Healthcare Wearable Devices (tbHWDs) present a promising approach for non-intrusive physiological monitoring. However, standard-sized medical wearables often fail to maintain the consistent skin-to-sensor contact required for high-quality clinical data, while the mass apparel market suffers from massive material waste due to poor fit. This masters thesis introduces an end-to-end cyber-physical manufacturing framework that integrates 3D body scanning, parametric Computer-Aided Design (CAD), and robotic automation to fabricate personalized tbHWDs, using an upper-arm band for opioid withdrawal monitoring as a primary case study. Through a comparative evaluation of five 3D scanners, this work demonstrates that although metrology-grade active structured-light systems like the EinScan Pro HD achieve 0.2 mm precision, consumer-grade mobile photogrammetry applications (e.g., Polycam) offer a viable and accessible alternative.

Anthropometric data is extracted from the resulting meshes using MeasureMe, a purpose-built Blender add-on, and the values are appended to a spreadsheet database. These parameters drive a geometric model that unrolls the upper arm, approximated as a conical frustum, into a two-dimensional annular sector bounded by frequency-locked sinusoidal edges. Implemented as an iLogic-driven parametric assembly in Autodesk Inventor Professional, the model regenerates a wearer-specific pattern and circuit layout without manual CAD intervention. Physical realization is specified as a compact single-arm robotic workcell equipped with an automatic tool changer, a tacky heat-resistant conveyor, and an integrated heat press, sequencing laser cutting, thermoplastic polyurethane (TPU) lamination, direct ink writing of stretchable silver-flake conductors, pick-and-place sensor integration, laser curing, and bilayer encapsulation. By lowering the capital and skill barriers separating a body scan from a finished device, this framework offers a reproducible path toward localized, on-demand production of personalized tbHWDs, and more broadly toward fit-driven reduction of apparel waste.

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