Date of Award

5-3-2024

Publication Type

Dissertation

Degree Name

Ph.D.

Department

Mechanical, Automotive, and Materials Engineering

Keywords

Automation;Fabric Materials;Handling Systems;Mold Geometry Analysis;Simulation;Soft Robotic

Supervisor

Jill Urbanic

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

Fiber composite materials renowned for their exceptional specific stiffness and strength and have become integral in various industries, including automotive, aviation, and consumer goods, driven by the pursuit of reducing vehicle mass through light-weighting strategies. However, the adoption of these materials presents challenges related to high production volume and handling automation. Current practices rely on multi-stage manual operations for hand layups, causing fabric material handling to be a bottleneck in the production process. Conventional handling methods currently in use often face various drawbacks, spanning from causing damage to the fabric, being prohibitively expensive, consuming high amounts of energy, lacking flexibility, to being overly sophisticated. Additionally, soft robotics solutions, as found in existing literature, are predominantly either tendon-driven or pneumatic, exhibiting limitations in adaptability during operation and controllability. They often fall short in achieving synchronous multi-arm pick-and-place motion and tend to be complex and challenging to build and operate. This research explores the development of automated pick and place processes for fabric materials, utilizing soft grippers, additive manufacturing, and dual arm collaborative robots to address the challenges associated with traditional methods. The study begins with investigating soft grippers for basic material pick and place tasks. Through a series of experiments, the study assesses gripper characteristics, thread damage and slippage under varying gripping forces and motion speeds. The dissertation then delves into conducting different novel dual arm pick and place strategies to explore and evaluate performance of pick-and-place operations. The research incorporates Finite Element (FE) modeling via standardized testing and characterization to validate the effectiveness of conducted handling solutions. The FE model, exhibiting a high correlation with select dual arm pick-and-place tests, used as a tool to explore the impact of mold surface geometry and fabric’s aspect ratio on placement performance. Addressing the challenges of handling limp fabric materials, particularly in complex mold surface geometries, the dissertation proposes a component-based approach that establishes a design framework to seamlessly associate facet-based surface geometry analysis with specialty gripper design parameters. The study introduces specialty robotic grippers, including Origami-inspired designs and flexible segments like living hinges. The findings show that the use of soft grippers significantly reduces damage, slippage, and wrinkling in most conditions. It is also revealed that convex surfaces and longitudinal pick-and-place operations outweigh concave and transverse handling processes, respectively. Robotic system integration of specialty grippers-mold surface associative design with different fabric materials and mold variations proved effectiveness of the proposed geometry analysis technique and functionality of regulated design guidelines. The findings of the research pave the way for rapid, efficient, mechanically simple, cost-effective, and secure integration of soft robotics in fabric composite manufacturing settings.

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