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Undergraduate<\/strong> Courses<\/strong><\/p>\n <\/p>\n VM455\/ME4550J: Introduction to Data-driven Engineering Design \u6570\u636e\u9a71\u52a8\u5de5\u7a0b\u8bbe\u8ba1\u5bfc\u8bba <\/strong><\/p>\n <\/p>\n DESCRIPTION:<\/p>\n <\/p>\n Introduction to the fundamental theories and techniques of data-driven engineering design, extracting insights from large datasets to support decision-making in product\/system design, quantitative methods for customer preference modeling, discrete choice analysis, data analysis and visualization, text mining, supervised\/unsupervised learning, deep\/reinforcement learning, network analysis; model evaluation, validation and improvement.<\/p>\n <\/p>\n PREREQUISITES: Vg100, Vg101, Vm250<\/p>\n <\/p>\n CREDIT: 3<\/p>\n <\/p>\n Offered terms: Fall semesters<\/p> <\/p>\n VM250\/ME2500J: Design and Manufacturing I \u8bbe\u8ba1\u4e0e\u5236\u9020 I<\/strong><\/p>\n <\/p>\n DESCRIPTION:<\/p>\n <\/p>\n Introduce students the complexity of engineering practice and to follow the development of an idea from its conception to the construction of a prototype; Develop the technical skills necessary to generate an engineering drawing with appropriate dimensions, tolerances, and specifications, and an engineering assembly, using free-hand sketching and a modern CAD system; Introduce basic mechanical elements and materials and learn the practice and limitations of basic prototyping and manufacturing tools.<\/p>\n <\/p>\n PREREQUISITES: VV156 or VV186, VG100, VM010 or VM020<\/p>\n <\/p>\n CREDIT: 4<\/p>\n <\/p>\n Offered terms: Summer semesters<\/p>\n\n <\/p>\n <\/p>\n <\/p>\n VG100\/ENGR1000J: Introduction to Engineering \u5de5\u7a0b\u5bfc\u8bba<\/strong><\/p>\n <\/p>\n DESCRIPTION:<\/p>\n <\/p>\n ENGR1000J is a collaborative combination of two components: a technical component (Tech) that teaches how to design and construct an engineering project in multiple stages; and a technical communication component (TC) that teaches how to effectively propose, describe, and explain that project to an external audience. In detail, some of the skills this course aims to introduce include:\n(1)\tthe application of mathematics and science to an engineering project (Tech)\n(2)\tconceptualization of need, feasibility assessment, decision to proceed, project organization, plan of work, ability to design and conduct experiments, as well as to analyze and interpret data (Technical \/ Communication)\n(3)\tthe ability to identify and solve problems, through systems and process design (Technical \/ Communication)\n(4)\tan understanding of professional and ethical responsibility (Tech)\n(5)\tan understanding of engineering in relation to numerous social contexts (Technical \/ Communication)\n<\/p>\n <\/p>\n PREREQUISITES: NA<\/p>\n <\/p>\n CREDIT: 4<\/p>\n <\/p>\n Offered terms: Fall semesters<\/p>\n\n <\/p>\n Graduate Courses<\/strong><\/p>\n <\/p>\n VM583\/ME6801J: <\/b>Manufacturing Processes and Systems<\/b> \u5236\u9020\u8fc7\u7a0b\u4e0e\u7cfb\u7edf <\/b><\/p>\n <\/p>\n DESCRIPTION:<\/p>\n <\/p>\n This course aims to introduce students the modeling and analysis methods in modern manufacturing processes and systems as well as the fundamental concepts and technologies in smart manufacturing. Topics covered include:<\/p>\n <\/p>\n (1) Modeling & analysis of manufacturing processes, including solidification, deformation (elastic & plastic), material removal and joining, and additive manufacturing.<\/p>\n (2) Modeling & analysis of manufacturing systems, including building blocks of manufacturing systems, quality control, economic models and optimization of manufacturing systems, lean manufacturing.<\/p>\n (3) Fundamentals of smart manufacturing system, including Internet of Things (IOT), Cyber-Physical Systems (CPS), predictive maintenance, digital twins, cloud manufacturing, smart factory.<\/p>\n <\/p>\n PREREQUISITES: Courses related to Statistical Methods<\/p>\n <\/p>\n CREDIT: 3<\/p>\n <\/p>\n Offered terms: Fall semesters<\/p>\n <\/p>","protected":false},"excerpt":{"rendered":" Undergraduate Courses VM455\/ME4550J: Introduction to Data-driven Engineering Design \u6570\u636e\u9a71\u52a8\u5de5\u7a0b\u8bbe\u8ba1\u5bfc\u8bba DESCRIPTION: Introduction to the fundamental theories and techniques of data-driven engineering design, extracting insights from large datasets to support decision-making in product\/system design, quantitative methods for customer preference modeling, discrete choice analysis, data analysis and visualization, text mining, supervised\/unsupervised learning, deep\/reinforcement learning, network analysis; model evaluation, validation […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-13","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/sites.gc.sjtu.edu.cn\/youyibi\/wp-json\/wp\/v2\/pages\/13","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sites.gc.sjtu.edu.cn\/youyibi\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/sites.gc.sjtu.edu.cn\/youyibi\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/sites.gc.sjtu.edu.cn\/youyibi\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.gc.sjtu.edu.cn\/youyibi\/wp-json\/wp\/v2\/comments?post=13"}],"version-history":[{"count":25,"href":"https:\/\/sites.gc.sjtu.edu.cn\/youyibi\/wp-json\/wp\/v2\/pages\/13\/revisions"}],"predecessor-version":[{"id":579,"href":"https:\/\/sites.gc.sjtu.edu.cn\/youyibi\/wp-json\/wp\/v2\/pages\/13\/revisions\/579"}],"wp:attachment":[{"href":"https:\/\/sites.gc.sjtu.edu.cn\/youyibi\/wp-json\/wp\/v2\/media?parent=13"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
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