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Wojciech Matusik. Schulz, Adriana Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science 2018-09-17T14:52:03Z 2018-09-17T14:52:03Z 2018 2018 http://hdl.handle.net/1721.1/117844 1052124114 Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018. This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. Cataloged from student-submitted PDF version of thesis. Includes bibliographical references (pages 169-180). Over the next few decades, we are going to transition to a new economy where highly complex, customizable products are manufactured on demand by flexible robotic systems. In many fields, this shift has already begun. 3D printers are revolutionizing production of metal parts in the aerospace, automotive, and medical industries. Whole-garment knitting machines allow automated production of complex apparel and shoes. Manufacturing electronics on flexible substrates makes it possible to build a whole new range of products for consumer electronics and medical diagnostics. Collaborative robots, such as Baxter from Rethink Robotics, allow flexible and automated assembly of complex objects. Overall, these new machines enable batch-one manufacturing of products that have unprecedented complexity. In this thesis, I argue that the field of computational design is essential for the next revolution in manufacturing. To build increasingly functional, complex and integrated products, we need to create design tools that allow their users to efficiently explore high-dimensional design spaces by optimizing over a set of performance objectives that can be measured only by expensive computations. In this work discuss how to overcome these challenges by 1) developing data-driven methods for efficient exploration of these large spaces and 2) performance-driven algorithms for automated design optimization based on high-level functional specifications. I showcase how these two concepts are applied by developing new systems for designing robots, drones, and furniture. by Adriana Schulz. Ph.D. 180 pages eng Massachusetts Institute of Technology MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. http://dspace.mit.edu/handle/1721.1/7582 Electrical Engineering and Computer Science. Computational design for the next manufacturing revolution Thesis application/pdf false Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="d7cd73ef-5769-409d-897c-b3e1081d359c"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Computational design for the next manufacturing revolution</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2018</PublicationDate> <Authors> <Author> <DisplayName>Schulz, Adriana</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Electrical Engineering and Computer Science.</Keyword> <Abstract>Over the next few decades, we are going to transition to a new economy where highly complex, customizable products are manufactured on demand by flexible robotic systems. In many fields, this shift has already begun. 3D printers are revolutionizing production of metal parts in the aerospace, automotive, and medical industries. Whole-garment knitting machines allow automated production of complex apparel and shoes. Manufacturing electronics on flexible substrates makes it possible to build a whole new range of products for consumer electronics and medical diagnostics. Collaborative robots, such as Baxter from Rethink Robotics, allow flexible and automated assembly of complex objects. Overall, these new machines enable batch-one manufacturing of products that have unprecedented complexity. In this thesis, I argue that the field of computational design is essential for the next revolution in manufacturing. To build increasingly functional, complex and integrated products, we need to create design tools that allow their users to efficiently explore high-dimensional design spaces by optimizing over a set of performance objectives that can be measured only by expensive computations. In this work discuss how to overcome these challenges by 1) developing data-driven methods for efficient exploration of these large spaces and 2) performance-driven algorithms for automated design optimization based on high-level functional specifications. I showcase how these two concepts are applied by developing new systems for designing robots, drones, and furniture.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>