Workshops & Tutorials

All workshops and tutorials will be held Sunday, August 25th and have limited capacities.

Description: The practice of design is rapidly changing. The increasingly digital footprint of design and the growing prevalence of high-powered computing introduces new opportunities for making use of advanced computation. Simultaneously, the rise of complicated cyberphysical systems presents designers with challenges that are unprecedented in terms of scale, multi-disciplinarity, and complexity. In this way, human-AI teaming is not only an exciting opportunity for engineering design, but it is also quickly becoming a necessity. This workshop brings together leading researchers in AI/ML, formal methods, design science, human-computer interaction, and other fields to discuss emerging trends and future opportunities in human-AI teaming for engineering and design.

 

Description: Participants will learn the principles of advanced gear design and simulation and will interact with state-of-the-art computational tools for the virtual generation of gear drives and the application of tooth contact and finite element analysis (TCA & FEA) to evaluate their mechanical performance. Topics covered in this tutorial include the application of micro-geometry modifications to avoid edge contacts and absorb errors of alignment, the free-form design of gear tooth surfaces, the evaluation of the loaded functions of transmission errors and mesh stiffness as root-cause of noise and vibration, the compensation of errors of alignment caused by shaft deflections, and the advanced design of spiral bevel gear drives.

 

Description: Generative AI relies heavily on substantial and high-quality datasets to address domain-specific challenges. However, acquiring hand-crafted design knowledge proves challenging, particularly due to the time constraints faced by designers. Designers often hesitate to invest additional time in documenting and organizing explicit design knowledge, such as sketches, models, and inspirational images. Additionally, tacit knowledge, such as trade-offs and prioritization, is typically shared informally among designers working on the same project, lacking proper documentation.

1. Sorting Challenge: Sorting design documents becomes a formidable task due to the varied and abstract design workflows, shaped by individual designers with diverse perspectives.


2. Processing Challenge: Handling car design documentation proves to be intricate, given the complex nature of the product comprising over 20,000 parts and employing diverse data formats throughout various developmental stages.


3. Collecting Challenge: The imperative of confidentiality and the preservation of originality in car design results in a decentralized and somewhat closed design process, presenting difficulties in gathering comprehensive and openly accessible documentation.

The process of designing products is influenced by a range of factors, spanning from clear specifications to personal experiences. Assuming a structured design process, we can categorize these factors impacting the workflow and outcomes.

This workshop aims to explore innovative interaction methods and techniques to address the difficulty of collecting design knowledge. Using a practical case study focused on designing a new car, the workshop will delve into various dimensions of design knowledge, such as metacognition (Lawrie, Hay, & Wodehouse, 2022), tacit and explicit (Tsoukas, 2012; Grandinetti, 2014), scientific and emotional Bratianu (2014), confidential and public (Ahmad, Bosua, & Scheepers 2014).

Description: This workshop will introduce attendees to a new computational and physical prototyping framework for innovating and inventing mechanical motions using a web-based motion design software tool and a home-grown hardware kit to support the needs of students in classes, such as Freshman Design, Kinematics of Machinery, Mechatronics, and Robotics. While the hardware serves as a reference hardware, the software also allows exporting robot part geometry for laser-cutting or 3D printing.

 

Description: The advanced manufacturing (AM) paradigm is to create products using innovative technologies, but the technology adopted often fails to achieve the desired result. Digital twins (DTs), employing advanced data analytics and simulations, have the potential to break this logjam. For example, artificial intelligence algorithms can enable a DT to “understand” the spatial relationships needed to control an AM process. The DT technology can help address issues at each stage of the product development lifecycle, including design, manufacturing planning, process control, and product qualification.

However, the development of DTs requires large amounts of trustworthy and secure data and an advanced integration infrastructure for combining digital information from multiple sources. Additionally, statistical tools and machine learning models are needed to ensure data quality and consistency efficiently and effectively. Thus, a data management infrastructure is critical to help realize DTs for AM.

This workshop contains three main topics:
1. Overview of the digital twin concept and its role in AM
2. Data management infrastructure for DTs in AM
3. Relevant standards for DT implementations and AM cyber security

Who should attend:
The workshop is intended for students, engineers, and enthusiasts interested in AM, data management, and digital twin technologies wishing to learn more about state-of-the-art frameworks and software tools. A hands-on tutorial will showcase a NIST-developed software toolkit and a sample dataset for metal-based laser powder bed fusion additive manufacturing.

 

Description: From design conceptualization to production perfection, the Design for Manufacturing (DFM) workshop will guide participants through the entire manufacturing lifecycle, equipping them with the tools needed to navigate the complexities of modern engineering. The workshop is a set of principles and it is the culmination of years of hands-on engineering experience and educational expertise. The workshop is a scenario-based learning workshop, where participants will explore two scenarios for each topic: one where the engineer lacks knowledge of DFM principles and another where they are well-versed in DFM. Through practical exercises, participants will gain a comprehensive understanding of DFM concepts and their practical applications in real-world engineering scenarios. The sessions will cover DFM role in various phases of manufacturing a part from design to production/assembly to quality control.

 

Description: D2D workshop is a full-day event that will bring together professionals and academics to discuss the latest trends, challenges, and opportunities in the field of data-driven engineering design. The workshop will feature invited speakers from both industry and academia who will share their experiences, insights, and best practices in using cutting-edge data-driven machine learning methods to drive engineering design topics. Attendees will also have the opportunity to engage in discussions about the challenges and opportunities associated with data-driven engineering design and to network with other professionals and academics in the field. Additionally, the workshop will include a half-day hands-on activity, allowing participants to gain practical experience working with real-world data sets and engineering design problems. By the end of the workshop, attendees will have a comprehensive understanding of the latest trends and best practices in data-driven engineering design, as well as practical experience applying these concepts. The workshop promises to be a valuable opportunity for professionals and academics in the field to learn from each other, collaborate, and drive innovation forward.

 

Description: Embark on the essentials of autonomous driving in this 4-hour workshop, immersing yourself in the fundamentals of perception, motion planning, control theory, and applied machine learning. With a core focus on the F1TENTH and AutoDRIVE Ecosystem, this workshop offers practical insights to start your engines and get going.

With a vibrant community comprising 60+ universities, F1TENTH offers a dynamic environment for learning and racing 1/10th scaled autonomous vehicles. AutoDRIVE Ecosystem expands the opportunities for digital-twinning thereby streamlining the hardware-software co-development, and effectively bridging the gap between simulation and reality. It further offers Nigel, a 1/14th scaled autonomous vehicle with independent all-wheel drive and independent all-wheel steering architecture, which can be a useful platform for tackling the "autonomy challenge" from a mechanical engineering lens.

This workshop serves as a scaffolded framework, enhancing the understanding of engineering and computer science students in deploying real-time end-to-end autonomous systems. Covering fundamental aspects of autonomous driving (and racing), the workshop delves into the pivotal roles of perception, planning, and control components, emphasizing state-of-the-art methods for each. It also motivates the need for an integrated autonomy deployment framework and elucidates its efficacy through the deployment of on-road as well as off-road autonomy algorithms across diverse vehicular platforms.

 

Description: Multi-axis hybrid manufacturing stands as a transformative force poised to revolutionize current manufacturing processes across diverse industries. The integration of additive and subtractive processes in a single machine platform offers a myriad of technical advantages, making it a compelling choice for manufacturers seeking enhanced efficiency, precision, and versatility.

The adoption of multi-axis hybrid manufacturing can represent a paradigm shift in the industry, offering a holistic approach to production that marries the best aspects of additive and subtractive technologies. Its impact spans across industries, from aerospace and automotive to medical and beyond, promising enhanced efficiency, cost-effectiveness, design freedom, and quality in manufacturing processes. As manufacturers strive for competitiveness and innovation, the integration of multi-axis hybrid manufacturing is poised to be a cornerstone of the future manufacturing landscape.

 

Description: Recent developments in the 2D sketcher capabilities of modern CAD systems allow the creation of dynamic or moveable constrained geometry. Dynamic geometry is a new tool for the design of planar linkages and provides the opportunity for new synthesis methods. One method exploiting the advantages of this is Pole and Rotation angle Constraints (PRC). It has the intuitive, visual advantages of graphical methods and the fast and accurate advantages of analytical methods. PRC provides a single approach for every planar four bar linkage synthesis problem that is not overconstrained. Since CAD tools are commonplace in academia and industry there is direct carryover from education to industrial practice. Learn this breakthrough method to solve linkage synthesis problems faster and minimize trial and error since you can easily see thousands of possible solutions. The class will focus on the exact synthesis of linkages for rigid body guidance, point path, function generation and any combination of these tasks.

 

Description: This workshop uses the interactive Racism Untaught toolkit and is focused on methods for understanding and dismantling racialized and oppressive design. It starts with an exercise on power and privilege in a variety of systemic oppression. We then move to the first step in the toolkit, Context, where participants are given the cards that outline over 150 different elements of racism, sexism, ableism, and capitalism. This allows participants to analyze an artifact, system, or experience and learn how we perpetuate racism and oppression in our everyday lives and then how to break down racialized design. Then, participants further examine a system, artifact, or experience with step two, Define, used to understanding theories and methods that define the oppressive societal problem further. Lastly, participants move to step three, Ideate, walk away from this workshop with ideas on re-imagining a form of racialized and oppressive design specific to their field.

 

Description: The purpose of this workshop is to disseminate the findings of NSF CMMI funded research on "Theory-Grounded Guidelines for Solver-Aware System Architecting (SASA)" through an information session and a collaborative multi-player educational game.

Systems engineering aims to architect complex systems such that subtasks can be completed efficiently in parallel, and later integrated to form a system that delivers value. Traditionally, complex system development programs assume that interdisciplinary nature of these problems require expertise with domain specific knowledge. Hence the goal is to formulate the best technical architecture given operational needs, without considering who is solving different parts of the design problem and how they are engaging in the design process. Then, resulting subproblems are assigned to experts within traditional organizations (e.g., NASA, Lockheed, Ford). This view constrains the potential trajectory of design activities while simultaneously overlooking the potential benefits of engaging non-expert solvers. Consequently, complex system development processes are notoriously over budget and schedule; while technical innovations are constrained within the boundary of subsystems.

However, improvements in sharing platforms, the rise of "gig" work and broader adoption of open innovation tools call into question the efficacy of traditional approaches to architecting. In fact, the joint consideration of problem decomposition and solver assignment decisions could simultaneously improve design process outcomes in terms of performance, cost, and schedule; while enabling opportunities for novel solutions to be identified and realized.

The purpose of this workshop is to illustrate the fundamentals of SASA, along with the heuristics and design strategies enabled by this perspective, through an information session that is supported by a collaborative multiplayer educational game. The multiplayer game will first illustrate these concepts in a simple golf setting; then demonstrate how these ideas apply to an interdisciplinary robotics design problem. By the end of this workshop, the participants will have an improved understanding of SASA principles, along with heuristics and strategies to leverage SASA for tackling complex real-world design problems. The workshop promises a fun and engaging opportunity for industry professionals and academics to better utilize the human capital at their disposal, innovate, and gain the competitive edge in complex system development.

Description: Recent advances in design tools have transformed CAD models – and the processes by which they are created – into rich data troves for researchers investigating collaborative design processes and developing the next generation of AI driven design tools. This workshop will feature presentations from researchers from a few different fields doing informatics research with CAD data, as well as a panel discussion about the future of design tools.

The hands-on portion of the workshop will allow participants to work in focus groups to explore a few shared CAD data sets, brainstorming research questions and analysis methods that could provide insight into design processes or inform the next generation of CAD tools. Participants will walk away with an understanding of how to acquire CAD data from models and processes, as well as ideas for future research projects and collaborations.

Attendees are encouraged to bring a laptop to participate fully in the hands-on portion.

 

Description: As AI tools gain popularity, designers are actively integrating them into diverse design workflows, including user research, idea generation, and design variations. Despite their widespread use, there's a lack of awareness regarding biases in outputs, such as demographic and cultural biases, and potential harm could arise when these biases are incorporated into designs without careful consideration. Especially with generative AI tools such as ChatGPT and Midjourney being rapidly integrated not only into professional design practice but also education, there is a pressing need to raise awareness about bias risks and establish guidelines to evaluate and mitigate their impact in the use of the tools in design. This workshop aims to foster discussions on identifying, measuring, and mitigating biases in generative AI tools. After introducing existing biases found in the outputs from the tools, participants will engage in structured activities to experience the design process using the tools. Through reflective discussions, they will brainstorm a framework to measure bias impact and strategies to mitigate them. Based on the outcomes, we will collaboratively develop guidelines on how to use generative AI tools for design with an awareness of bias.