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MSSM

Master of Science in Smart Manufacturing

MSSM 5001
Additive Manufacturing Introduction
[3-0-0:3]
Exclusion(s)
SMMG 5500
Description
This course covers selected topics of current interest in additive manufacturing. Students will study the fundamentals of various additive manufacturing techniques, including fused deposition modeling (FDM), two-photon lithography, stereolithography (SLA), etc. The additive manufacturing process (FDM or SLA as an example) will be illustrated by actual model design, system setup and fabrication of parts.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Understand the past development of additive manufacturing techniques.
- 2.
  Understand the working principles of additive manufacturing techniques.
- 3.
  Apply the methodologies and techniques to real problems in additive manufacturing.
- 4.
  Recognize the current research trend in additive manufacturing.
- 5.
  Gain practical skills of developing additive manufacturing systems.
MSSM 5002
Advanced Metal Additive Manufacturing
[3-0-0:3]
Exclusion(s)
SMMG 5900
Background
Mechanical design and college math. Basic fluid mechanics, and heat transfer knowledge is preferred.
Description
This course provides students with the latest knowledge and skills for metal additive manufacturing (AM) techniques and implications, as well as the fundamental understanding of process-structure-property relationships in material processing using AM.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Demonstrate comprehensive knowledge of the major metal AM processes and their advantages and limitations.
- 2.
  Demonstrate understanding of the implications of current metal AM techniques, the challenges in current metal AM processes, and the opportunities of metal AM in industry and academia.
- 3.
  Identify the physics and key processing parameters in current metal AM techniques.
- 4.
  Obtain systematic understanding of process-structure-property relationships across different length scales in metal AM processes.
- 5.
  Acquire the skills and confidence to design parts for AM or create innovative solutions using AM across a vast opportunity space.
- 6.
  Acquire a cutting-edge perspective on digital transformation of metals and metal matrix composites, and the future manufacturing.
MSSM 5003
Design for Manufacturing and Assembly
[3-0-0:3]
Description
This is a course in Design for Manufacturing and Assembly (DFMA) that focuses on the principles and techniques involved in designing products for efficient and cost-effective manufacturing and assembly processes. This course aims to equip students with the knowledge and skills necessary to optimize the design of products, considering factors such as ease of manufacturing, assembly, and overall product quality.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Demonstrate a solid understanding of the principles and concepts behind Design for Manufacturing and Assembly (DFMA), including the importance of designing products for efficient manufacturing and assembly.
- 2.
  Analyze and evaluate product designs from the perspective of manufacturability and assembly.
- 3.
  Optimize product designs for efficient manufacturing and assembly processes.
- 4.
  Demonstrate proficiency in using relevant software and tools, such as Computer-Aided Design (CAD) software and simulation tools.
MSSM 5004
Engineering Data Analytics and Statistical Learning for Smart Manufacturing
[3-0-0:3]
Description
This course focuses on the sensing and data analytics techniques for modeling, monitoring, and optimization of advanced manufacturing processes. The techniques introduced in this course can find wide applications in manufacturing industries such as ship/fuselage assembly process. This course will provide the students with understanding of the fundamental and advanced data analytics and statistical learning methodologies, and the ability of formulating and solving real problems with the appropriate modeling strategies and statistical principles.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Be equipped with the fundamental knowledge of engineering data analytics and statistical learning concepts, problems, and techniques.
- 2.
  Integrate data analytics and statistical learning techniques with industrial and systems engineering domain knowledge to appropriately formulate problem and facilitate decision making.
- 3.
  Implement software programming skills to transform from data-rich to decision-smart, which will satisfy practical needs and solve application-oriented issues in real manufacturing industries.
- 4.
  Master real problem-solving skills via conducting industrial data analytics projects.
MSSM 5005
Manufacturing System Modeling and Analysis
[3-0-0:3]
Background
Prior knowledge in statistics is required.
Description
This course will introduce the students to an in-depth modeling and analysis of the workflow dynamics that shape the operation and the performance of contemporary production systems. It will develop systematic and rigorous models for the study of the considered environments. It aims to fill the need for an accessible but comprehensive presentation of the analytical approaches for modeling and analyzing models of manufacturing and production systems.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Describe different manufacturing systems.
- 2.
  Analyze and improve the performance of single-product factories.
- 3.
  Analyze and improve the performance of multi-product factories.
- 4.
  Select and use proper simulation tools for performance analysis.
- 5.
  Apply stochastic modeling and analysis to practical problems and applications.
MSSM 5007
Sustainable Manufacturing
[3-0-0:3]
Description
The course discusses the principles of sustainability with manufacturing processes. It covers from the social to technological impact of sustainable manufacturing. The evaluation system and tools used for sustainable manufacturing will be introduced. It also contains a business case study of sustainable manufacturing. Students will learn how to manage manufacturing systems that minimize environmental impact while maintaining economic viability and ensuring social responsibility.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Develop the knowledge about ESG and sustainable manufacturing.
- 2.
  Conduct the Life-Cycle Assessment (LCA) of a manufacturing process.
- 3.
  Understand the materials and energy management in sustainable manufacturing.
MSSM 5008
Immersive Technologies in Manufacturing
[3-0-0:3]
Background
Familiarity with at least one programming language (preferably C# or Python)
Description
This course covers the technical and experiential design foundation required for the implementation of immersive environments in current and future virtual, augmented, and mixed reality platforms. It also highlights the applications of these technologies under the manufacturing environment. The curriculum covers a wide range of literature and practice starting from the human-computer interface concepts following the evolution of all supporting technologies including visual displays for VR, AR and MR, motion tracking, interactive 3D graphics, multimodal sensory integration, immersive audio, user interfaces, IoT, games and experience design, focusing on manufacturing-related scenarios.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Describe the principles of VR, AR and MR.
- 2.
  Compare different input, output and accessory devices in VR, AR and MR.
- 3.
  Select and implement best practices in VR, AR and MR.
- 4.
  Evaluate VR, AR and MR tools for manufacturing applications.
- 5.
  Develop VR, AR or MR tools for manufacturing applications.
MSSM 5009
Fundamental Theories and Algorithms of CAD/CAM
[3-0-0:3]
Exclusion(s)
SMMG 5600
Background
Basic knowledge in calculus, elementary geometry, and linear algebra.
Description
This course covers topics such as curves and surfaces, geometric modeling basics, data structures in CAD/CAM, optimization, numerical control technology, numerical control machining, and projects. In addition to lectures, a 3-hour lab in SolidWorks and MATLAB programming will be offered.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Have a thorough understanding of the fundamental mathematical theories and computer algorithms underlying today’s CAD/CAM technologies.
- 2.
  Design and implement computer programs of moderate complexity for CAD/CAM tasks.
MSSM 5010
Numerical Methods for Engineers
[3-0-0:3]
Background
Basic knowledge in calculus, linear algebra, and computer programming.
Description
This course is intended for teaching numerical methods for engineering students at the postgraduate level. The course will have three important objectives: (1) to teach the basic theories and fundamentals of numerical methods; (2) to help the students to acquire skills to implement these methods for computer solution; and finally (3) to provide an environment where the students can familiarize themselves with many today’s popular commercial software systems and their use in the solution of engineering problems.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Have a thorough understanding of the fundamental mathematical theories and algorithms underlying modern numerical methods.
- 2.
  Efficiently use the MATLAB system to implement representative numerical algorithms to solve practical engineering problems, individually or as a team.
MSSM 5011
Computerized Numerical Control Technology
[3-0-0:3]
Background
General knowledge of manufacturing process and equipment.
Description
This course covers the contents of the principle and applications of Computerized Numerical Control (CNC), like the fundamental technologies of numerical control (including interpreter, interpolator, control of acceleration and deceleration, and position control system), and the characteristics and industrial applications of typical CNC controllers and CNC machine tool.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Recognize the state-of-the-art computerized numerical control technologies.
- 2.
  Understand the electromechanical and automation theory in numerical controller.
- 3.
  Solve practical issues related to position, velocity, and torque control of manufacturing equipment.
- 4.
  Apply advanced theories and methods related to the topics of numerical control.
MSSM 5012
Introduction to Microelectromechanical Systems (MEMS): Fabrication and Application
[3-0-0:3]
Exclusion(s)
SMMG 5100
Description
In this course, students will delve into the intricate world of microfabrication technologies, including key processes such as photolithography, etching, deposition, and more. These techniques, used in integrated circuit (IC) fabrication, are adapted and extended to address the unique challenges posed by Microelectromechanical Systems (MEMS) design and manufacturing. The processes are explored both theoretically and practically, enabling students to develop the skills necessary for research-level prototyping and industry-scale production of MEMS. Furthermore, this course delves into the integration of MEMS and ICs, discussing the advantages and exploring different levels of integration. These discussions are complemented by detailed case studies of several MEMS devices, revealing their real-world applications and the associated micro-fabrication processes.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Gain foundational and extensive knowledge in microfabrication.
- 2.
  Show capability for original research in MEMS fields.
- 3.
  Develop critical and analytical thinking skills for practical cleanroom processing tasks.
- 4.
  Comprehend the essential design considerations and constraints in manufacturing microdevices.
- 5.
  Create process flows and fabricate diverse miniaturized sensors for applications in environmental monitoring, automobiles, smartphones, medical devices, and more.
MSSM 5013
Introduction to Precision Engineering
[3-0-0:3]
Description
This course provides an in-depth understanding of the principles and techniques used in precision engineering, including tool materials, mechanics of cutting, ultra-precision machine elements, MEMS and nanoscale additive manufacturing. Based on these accumulations, this course also covers topics such as the industry growth, global state and the future of precision engineering.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Recognize the history and current research in precision engineering.
- 2.
  Explain the fundamental principles of precision engineering, including tool materials, mechanics, bearings, etc.
- 3.
  Explain the fundamental principles of micro-electro-mechanical systems (MEMS).
- 4.
  Explain the fundamental principles of precision measurement, including mechanical, optical, electrical measurement, etc.
- 5.
  Apply and combine interdisciplinary precision engineering techniques to real problems in the chosen topics.
MSSM 5014
Robotics Manufacturing
[3-0-0:3]
Description
This course introduces students to wide fundamental concepts, techniques, and technologies in robotics-enabled manufacturing automation and optimization. The course covers wide topics including robot kinematic and dynamic modeling, GPU-based solid modeling, control system design, sensors and perception, motion planning, and process control. Students will explore integrating robotic techniques into the manufacturing process to enable design automation and optimization for smart manufacturing.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Demonstrate a comprehensive understanding of robotics technologies, including robotic components, kinematics, sensors, actuators, and end-effectors commonly used in manufacturing applications.
- 2.
  Explain how robotics are integrated into manufacturing systems, including the programming, control, and coordination of robots with other machinery, conveyors, and automated processes.
- 3.
  Program industrial robots, understand their operating principles, and effectively deploy them to perform specific manufacturing tasks.
- 4.
  Analyze and design control systems for robotics manufacturing, including the selection and integration of sensors, actuators, and feedback mechanisms to optimize robot performance and manufacturing processes.
- 5.
  Apply their knowledge to program, operate, and troubleshoot industrial robots in simulated manufacturing scenarios, identifying and resolving common operational challenges.
MSSM 6000
Independent Project
[4 credits]
Description
An independent research project related to Smart Manufacturing carried out under the supervision of faculty members. Grade PP, P or F.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Demonstrate mastery of the knowledge and skills in the selected topics related to smart manufacturing.
- 2.
  Apply an interdisciplinary approach in examining the selected topics.
- 3.
  Critically evaluate different aspects of the selected topics.
- 4.
  Communicate findings effectively in written reports.
MSSM 6001
Industry Internship Project I
[4 credits]
Description
The Industry Internship Project provides students with the opportunity to apply their theoretical knowledge and academic training to real-world manufacturing environments, allowing them to gain practical experience and witness the application of smart manufacturing concepts in action. Students are required to complete an industry internship with a duration of 6 months. The internship consists of two parts. In MSSM 6001, students are required to submit a mid-term progress report for review by the academic and industry supervisors. Graded PP, P or F.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Apply theoretical knowledge and skills to real-world projects and challenges in the industry.
- 2.
  Gain hands-on experience in a professional work environment to navigate real-world scenarios and challenges.
- 3.
  Enhance important professional skills such as communication, problem-solving, time management, and teamwork.
- 4.
  Build professional relationships and expand professional networks within the industry.
- 5.
  Gain a better understanding of potential career paths and opportunities within a specific industry, and clarify professional goals and aspirations.
MSSM 6002
Industry Internship Project II
[4 credits]
Description
The Industry Internship Project provides students with the opportunity to apply their theoretical knowledge and academic training to real-world manufacturing environments, allowing them to gain practical experience and witness the application of smart manufacturing concepts in action. Students are required to complete an industry internship with a duration of 6 months. The internship consists of two parts. In MSSM 6002, students are required to submit a final internship report for review by a committee consisting of the academic and industrial supervisors, and the Program Director. Graded P or F.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Apply theoretical knowledge and skills to real-world projects and challenges in the industry.
- 2.
  Gain hands-on experience in a professional work environment to navigate real-world scenarios and challenges.
- 3.
  Enhance important professional skills such as communication, problem-solving, time management, and teamwork.
- 4.
  Build professional relationships and expand professional networks within the industry.
- 5.
  Gain a better understanding of potential career paths and opportunities within a specific industry, and clarify professional goals and aspirations.
MSSM 6003
Capstone Project
[6 credits]
Description
Students are required to undertake a capstone project in the last term of the program. The capstone project should generally be combined with the industry internship training and coursework study, with a duration of a regular term. By the end of the term, students need to finish and submit a project report and give a defense presentation. Graded P or F.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Conduct independent research, gather and analyze data, and draw meaningful conclusions in the selected topics related to smart manufacturing.
- 2.
  Apply critical thinking skills to evaluate and address complex problems or questions within the field of smart manufacturing.
- 3.
  Effectively communicate research findings, project outcomes, and recommendations through written reports and presentations.

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