Fangzhou Xia

@inproceedings{2023AIM,

title = {Multi-axis Active Vibration Suppression for Wafer Transfer Systems},

author = {Jiajie Qiu^ and Hongjin Kim^ and Fangzhou Xia* and Kamal Youcef-Toumi},

url = {https://ieeexplore.ieee.org/document/10196218},

year  = {2023},

date = {2023-06-27},

urldate = {2023-06-27},

booktitle = {IEEE/ASME Advanced Intelligent Mechatronics},

abstract = {Vibration suppression is critical in precision mechatronic systems for nanofabrication. For automated wafer handling in semiconductor plants, Overhead Hoist Transport (OHT) vehicles transport wafers carried in Front Opening Unified Pods (FOUPs); while the wafers are transported in a FOUP, semiconductor chips are at risk of damage by excited small particles due to mechanical vibration. Active suppression of the FOUP vibrations has been proposed to improve the production yield. However, there are two main challenges that make it a non-trivial problem. First, moving FOUPs carried by the OHT vehicles have no external anchoring point as a momentum source for control efforts. Second, no sensor attachment is permitted on mass-production FOUPs, which makes feedback control more challenging without measurement. Since the goal is to suppress the large FOUP acceleration peaks instead of eliminating all vibration, an inertia-based counterbalancing system is designed to address these challenges. To validate this idea, a custom testbed is designed for multi-axis vibration generation and suppression. A Disturbance Observer-Based Controller (DOBC) is developed and implemented on the hardware. During the experiment, 38 percent of the OHT hand unit vibration (and 42 percent of FOUP vibration) suppression is achieved in the OHT travel direction. Moreover, multi-axis FOUP-level acceleration-peak reduction is achieved to verify the effectiveness of the proposed method. },

keywords = {Actuator, Automation, Design, Experimentation, Instrumentation, Mechatronics, Modeling & Simulation, Motion Control, Theory},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{2023ASEE,

title = {Project-based Learning Course Co-designed with Regional Enterprises},

author = {Lufan Wang and Rouying Chu and Fangzhou Xia and Zhuoxuan Li* and Yan Wei and Yiming Rong},

url = {https://peer.asee.org/board-49-project-based-learning-course-co-designed-with-regional-enterprises},

year  = {2023},

date = {2023-06-25},

urldate = {2023-06-25},

booktitle = {ASEE 2023 Annual Exposition & Conference},

publisher = {American Society for Engineering Education},

abstract = {Project-based learning (PBL) courses in higher education require the instructor team to be highly resourceful, multi-disciplined, and inspiring. It also needs student teams to be proactive, collaborative, and good at inquiries. Designing and implementing PBL in a classroom can be challenging due to teaching staff shortage and insufficient knowledge of instructors. To address these challenges, we proposed a novel PBL course design methodology to involve local enterprises and entrepreneurs as course co-instructors, thereby compensating for the lack of industry participation in the current PBL course development efforts. The methodology consists of five main pillars: (1) inquiry-based problem solving using practical real-world problems; (2) active knowledge construction through a multidisciplinary team; (3) situated learning through meaningful social interaction with a community of practice; (4) guided investigation with scaffolded instructions on research methodology and technology; and (5) prototype demonstration with expert feedback. To test the effectiveness of the PBL course design methodology, we performed two experiments at Southern University of Science and Technology, a top research university in Shenzhen, China, in a form of a three-week summer school. Two-year data was collected including archival course data, interview data of students, faculty and industry partners, as well as student feedback surveys. We found that the proposed PBL curriculum involving industry mentors can significantly improve students’ engineering design skills and effectiveness of learning.

},

keywords = {Design, Education},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{2023ICRA,

title = {Robotic Method and Instrument to Efficiently Synthesize Faulty Conditions and Mass-Produce Faulty-Conditioned Data for Rotary Machines},

author = {Yip Fun Yeung* and Fangzhou Xia and Juliana Covarrubias and Mikio Furokawa and Takayuki Hirano and Kamal Youcef-Toumi},

url = {https://ieeexplore.ieee.org/document/10161055},

year  = {2023},

date = {2023-05-29},

urldate = {2023-05-29},

booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},

abstract = {Condition synthesis is vital for generating data for fault detection and diagnosis studies. Traditional methods rely heavily on human labor. This study proposes a robotic method and its instrument to efficiently synthesize faulty conditions and mass-produce data to develop fault detection and diagnosis algorithms. The first contribution is the formalization of a new approach called Robotic Condition Synthesis, which shifts the traditionally labor-intensive task of condition synthesis to a robot-based force control task. The second contribution is developing a new robotic manipulator, which is more effective than current lab-grade robots for the tasks involved in the Robotic Condition Synthesis. The third contribution is empirical evidence of the superiority of this new robot in performing the Robotic Condition Synthesis tasks. This study also explores the potential of the new robot by conducting a three-dimensional system identification of a rotordynamic plant, which lays the foundation for more advanced Robotic Condition Synthesis policies in the future.},

keywords = {Actuator, Automation, Design, Experimentation, Instrumentation, Intelligence, Mechatronics, Motion Control, Theory},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{2022IEEEAIM,

title = {Physical Intelligence in the Metaverse: Mixed Reality Scale Models for Twistronics and Atomic Force Microscopy},

author = {Fangzhou Xia* and Morgan P Mayborne and Qiong Ma and Kamal Youcef-Toumi},

url = {https://ieeexplore.ieee.org/document/9863383},

doi = {10.1109/AIM52237.2022.9863383},

year  = {2022},

date = {2022-01-01},

urldate = {2022-01-01},

booktitle = {2022 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM)},

pages = {1722-1729},

abstract = {Physical intelligence (PI) is an emerging research field using new multi-functional smart materials in mechatronic designs. On the microscopic scale, PI principles give rise to unconventional transducers, which are especially useful for micro/nano-robot design with size and resource constrains. Since it is not easy to directly observe nanoscale multi-physics phenomenon, understanding their principles can be challenging. In this work, we bring PI principles into the metaverse to bridge this gap by developing two mixed reality scale models. The first example is a virtual reality (VR) 2D material twistronics visualizer to demonstrate the novel intelligent 2D materials with tunable properties as a rising field in condensed matter physics. Users can interactively control the cross-coupling multi-physics phenomena and observe the visualized material responses. The second example is centered around an Atomic Force Microscope (AFM) to illustrate its imaging and probe principles. For interaction, users can control the twist angle using atomic lattice models and feel the AFM cantilever force using custom haptic devices. We believe these tools can help precision mechatronic engineers understand and make better use of physical intelligence building blocks to design micro-electromechanical systems.},

keywords = {Actuator, Atomic Force Microscopy, Design, Education, Experimentation, Instrumentation, Intelligence, Material Science, Mechatronics, MEMS, Modeling & Simulation, Nanorobotics, Sensor},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{2019ACC_2,

title = {Design and Control of a Multi-Actuated Nanopositioning Stage with Stacked Structure},

author = {Chen Yang* and Fangzhou Xia and Yi Wang and Stephen Truncale and Kamal Youcef-Toumi},

url = {https://ieeexplore.ieee.org/document/8815299},

year  = {2019},

date = {2019-01-01},

urldate = {2019-01-01},

booktitle = {IEEE American Control Conference (ACC)},

pages = {3782-3788},

abstract = {A novel multi-actuated nanopositioning stage with stacked structure has been developed. The aim is to achieve both high bandwidth and large motion range. Symmetric flexures are designed to obtain equal stiffness along any direction in the lateral plane. With this design, the lateral stiffness and corresponding bending mode resonance frequency can be optimized. Both analytical model and finite element analysis are employed to predict the dominant resonance frequency. Experimental results indicate that the dominant resonance of nanopositioner is at 28.2 kHz, with a motion range of 16.5J.1m. A disturbance-observer-based controller is implemented to suppress the hysteretic nonlinearity. The new design and control system enable high-bandwidth and high-precision nanopositioning up to 2 kHz.},

keywords = {Actuator, Atomic Force Microscopy, Design, Experimentation, Instrumentation, Mechatronics, Modeling & Simulation, Motion Control},

pubstate = {published},

tppubtype = {inproceedings}

}