Overview
The Department of Mechanical and Industrial Engineering (MIE) offers the Master of Science in Advanced and Intelligent Manufacturing (MS in AIM) to meet the growing demand for engineers, researchers, and scientists trained in advanced manufacturing and Industry 4.0 technologies. This degree program offers students an opportunity to either train for industry jobs with coursework and co-op experience or prepare for a doctoral program through coursework and research experience. MIE department offers both core courses and elective courses required to complete the program. Students can take MS Project or MS Thesis under any MIE faculty. This program is designed for engineering and science students planning to pursue careers in advanced and smart manufacturing. The key sectors that require manufacturing professionals include automotive, aerospace, defense, appliances, computing machines, smartphones, and communication equipment. The MS in AIM program helps students acquire knowledge and skills to:
- Build digital (CAD) models of parts and products to support manual and computer-aided manufacturing
- Design, develop, and analyze traditional and advanced manufacturing processes
- Utilize additive manufacturing to produce complex parts with ease and efficiency
- Select manufacturing processes to fabricate parts and products for quality and cost
- Configure and analyze manufacturing systems for efficiency, responsiveness, and high throughput
- Understand the characteristics and challenges of nanomanufacturing processes
- Leverage Industry 4.0 technologies including internet of things, cloud computing, sensor analytics for advanced manufacturing
- Adopt condition-based maintenance strategies to achieve high resource utilization
- Apply automation, robotics, and artificial intelligence to make manufacturing smart and self-operational
- Use human-machine interaction tools such as augmented reality and virtual realty
- Analyze human performance in sociotechnical systems such as supply chains
- Apply data analytics methods to gain insights from design and manufacturing data
In the context of this program, the traditional manufacturing covers metal removal, forming, casting, and particulate processes. The additive manufacturing covers topics such as 3D-printed parts using different approaches. The nanomanufacturing covers fabrication as well as printing of micro and nano devices and design and creation of multifunctional materials. Intelligent manufacturing focuses on factory automation, prognostics and health management, dynamic scheduling, cloud-enabled manufacturing, and industrial internet of things for manufacturing performance assurance. It also leverages real-time data analytics and control systems, advanced high-fidelity models, networked data, and computation for seamless interoperation of cyber and physical assets in manufacturing facilities.
General Degree Requirements
To be eligible for admission to any of the MS degree programs, a prospective student must hold a Bachelor of Science degree in engineering, science, mathematics, statistics, or an equivalent field. Students in all master’s degree programs must complete a minimum of 32 semester hours of approved coursework (exclusive of any preparatory courses) with a minimum grade-point average (GPA) of 3.000. Students can complete a master's degree by pursuing any of one of the three tracks: coursework option, project option, and thesis option. Specific degree requirements for each of these tracks can be found under the Program Requirements tab. Students may pursue any program either on a full-time or part-time basis; however, certain restrictions may apply.
Specific Degree Requirements
Core courses for the Master of Science in Advanced and Intelligent Manufacturing provide students with a foundation in traditional and advanced materials processing, additive manufacturing, intelligent manufacturing, and digital manufacturing. Students can select electives from a wide range of fields including mechanical engineering, industrial engineering, operations research, and engineering management. Alternatively, students can also take courses outside the MIE department by seeking a prior approval from their faculty advisor or MS thesis advisor. The course curriculum is designed to prepare students for industry jobs as well as for pursuing a doctoral program in manufacturing, mechanical engineering, and industrial engineering.
Academic and Research Advisors
All nonthesis students are advised by the faculty advisor designated for their respective concentration or program. Students willing to pursue the thesis option must first find a research advisor within their first year of study. The research advisor will guide the students' thesis work, and thesis reader(s) may be assigned at the discretion of their research advisor. The research advisor must be a full-time or jointly appointed faculty in the MIE department. If the research advisor is outside the MIE department, before the thesis option can be approved, a faculty member with 51 percent or more appointments in the MIE department must be chosen as co-advisor, and a petition must be filed and approved by the co-advisor and the MIE Graduate Affairs Committee. Thesis option students are advised by the faculty advisor of their concentration before they select their research advisor(s). The research advisor and co-advisor must serve as thesis readers.
Plan of Study and Course Selection
It is recommended that all new students attend orientation sessions held by the MIE department and the Graduate School of Engineering to acquaint themselves with the coursework requirements and research activities of the department as well as with the general policies, procedures, and expectations.
In order to receive proper guidance with their coursework needs, all MS students are strongly encouraged to complete and submit a fully signed Plan of Study (PS) to the department before enrolling in second-semester courses. This form not only helps the students manage their coursework but it also helps the department to plan for requested course offerings. The PS form may be modified at any time as the students progress in their degree programs.
Students pursuing study or research under the guidance of a faculty member can choose project option by taking Master’s Project (IE 7945) or Master’s Project (ME 7945). An MS project must be petitioned to the MIE Graduate Affairs Committee and approved by both the faculty member (instructor for Master's Project) and the student's academic advisor. The petition must clearly state the reason for taking the project course; a brief description of the goals; as well as the expected outcomes, deliverables, and grading scheme.
Students pursuing coursework option may petition the MIE Graduate Affairs Committee to substitute Independent Study (IE 7978) or (ME 7978) up to 4 semester hours. An independent study must be approved by the instructor and the academic advisor. The petition must clearly state the instructor; the reason for taking the course; a brief description of the goals; as well as the expected outcomes, deliverables, and grading scheme. Students in other options (i.e., thesis or project) are not eligible to take independent study. When taking thesis or project options, the independent study course cannot be taken.
Options for MS Students (coursework only, project, or thesis)
Students accepted into any of the MS programs in the MIE department can choose one of the three options: coursework only, project, or thesis. Please see the Program Requirements tab on the top menu of this page for more information. MS students who want to pursue project or thesis options must find, within the first year of their study, a faculty member or a research advisor who will be willing to direct and supervise a mutually agreed research project or MS thesis. Moreover, students who receive financial support from the university in the form of a research, teaching, or tuition assistantship must complete 8 semester hours of thesis. Students are strongly encouraged to complete their 8 semester hours of Thesis (IE 7990) or Thesis (ME 7990) over two consecutive semesters.
Students who complete the thesis option must make a presentation of their thesis before approval by the department. The MS thesis presentation shall be publicly advertised at least one week in advance and all faculty members and students may attend and participate. If deemed appropriate by the research advisor, other faculty members may be invited to serve as thesis readers to provide technical opinions and judge the quality of the thesis and presentation.
Change of Program/Concentration
Students enrolled in any of the MIE department programs or concentrations may change their current program or concentration no sooner than the beginning of their second full-time semester of study. In order for the program or concentration change request to be considered by the MIE Graduate Affairs Committee, the student must not be in the first semester of their current program, must have a 3.300 GPA, and have completed at least 8 semester hours of required coursework in their sought program at Northeastern.
Graduate Certificate Options
Students enrolled in a graduate degree program in the College of Engineering are eligible to pursue an engineering graduate certificate in addition to or in combination with the MS degree. For more information please refer to Graduate Certificate Programs.
Complete all courses and requirements listed below unless otherwise indicated.
Core Requirements
Code | Title | Hours |
---|---|---|
IE 6300 | Manufacturing Methods and Processes | 4 |
IE 7270 | Intelligent Manufacturing | 4 |
ME 5240 | Computer Aided Design and Manufacturing | 4 |
ME 5640 | Additive Manufacturing | 4 |
Restricted Elective Courses
Code | Title | Hours |
---|---|---|
Complete 4 semester hours from the following: | 4 | |
Human Performance | ||
Special Topics in Mechanical Engineering (Nano and Microscale Manufacturing) |
Options
Complete one of the following options:
Coursework Option
Code | Title | Hours |
---|---|---|
Complete 12 semester hours from the Elective Course List below. | 12 |
Project Option
Code | Title | Hours |
---|---|---|
IE 7945 | Master’s Project | 4 |
Complete 8 semester hours from the Elective Course List below. | 8 |
Thesis Option
Code | Title | Hours |
---|---|---|
IE 7990 | Thesis | 8 |
Complete 4 semester hours from the Elective Course List below. | 4 |
Elective Course List
Code | Title | Hours |
---|---|---|
Industrial Engineering | ||
Lean Concepts and Applications | ||
Engineering Probability and Statistics | ||
Supply Chain Engineering | ||
Simulation Analysis | ||
Intelligent Manufacturing | ||
Data Mining in Engineering | ||
Statistical Methods in Engineering | ||
Statistical Quality Control | ||
Reliability Analysis and Risk Assessment | ||
Human Factors Engineering | ||
Special Topics in Industrial Engineering | ||
Neural Networks and Deep Learning | ||
Master’s Project | ||
Independent Study | ||
Thesis | ||
Thesis Continuation - Half-Time | ||
Operations Research | ||
Probabilistic Operation Research | ||
Inventory Theory | ||
Integer and Nonlinear Optimization | ||
Network Analysis and Advanced Optimization | ||
Logistics, Warehousing, and Scheduling | ||
Materials Engineering | ||
Principles, Devices, and Materials for Energy Storage and Energy Harvesting | ||
Structure, Properties, and Processing of Polymeric Materials | ||
Properties and Processing of Electronic Materials | ||
Mechanical Engineering | ||
Mechatronic Systems | ||
Robot Mechanics and Control | ||
Environmental Issues in Manufacturing and Product Use | ||
Advanced Mechanics of Materials | ||
Control Systems Engineering | ||
Advanced Control Engineering | ||
Engineering Management | ||
Engineering Project Management | ||
Economic Decision Making | ||
Financial Management for Engineers |
Program Credit/GPA Requirements
32 total semester hours required
Minimum 3.000 GPA required
- 1
A thesis is required for all students who receive financial support from the university in the form of a research, teaching, or tuition assistantship. The thesis topic should cover one or more of the areas from statistics, mathematics, optimization, data mining, machine learning, database design, big data, visualization tools, or forecasting methods. The thesis should train students for research in data and operations analytics and/or prepare them for a doctoral program.