Undergraduate Department of
Industrial and Manufacturing Engineering
FAMU—FSU College of Engineering
Website: https://www.eng.famu.fsu.edu/ime
Chair: Zeng; Professors: Awoniyi, Liang, Okoli, Zeng, M. Zhang; Associate Professors: Dickens, Park, Vanli, Wang, Yu; Assistant Professors: Li, Sun, Sweat; Research Faculty: Park; Teaching Faculty: Garcia, Georgiadis, Gross, Taylor, Tibi; Professor Emeritus: Braswell
The mission of the Department of Industrial and Manufacturing Engineering is to provide for students a solid industrial engineering curriculum coupled with a strong research program driven by the economic and technological development needs of society.
The Industrial Engineering degree provides a broad technical background with special emphasis on manufacturing systems, computer modeling, costs, quality, management, and human factors. Industrial engineering draws upon specialized knowledge and skills in the mathematical, physical, and social sciences, together with the principles and methods of engineering design and analysis, to specify, predict, and evaluate industrial systems.
The program of study includes engineering analysis for the optimization of industrial systems, design of man-machine systems, and the scientific management of activities. Specialized training is available in the use of modern engineering tools and techniques such as computer-aided design (CAD), computer integrated manufacturing (CIM), and ergonomic (human factors) engineering.
Industrial engineers pursue careers in manufacturing, service industries, and government. In addition, many industrial engineers are now being employed in nontraditional fields such as hospitals, banks, insurance, and information processing. The present and future demand for IE's appears to be very high. Industrial engineers are increasingly being called upon to act as productivity catalysts in manufacturing and service organizations in order to meet regional, national, and international demand and competition.
Program Educational Objectives
The Bachelor of Science in Industrial Engineering (BSIE) curriculum is accredited by the Engineering Accreditation Commission of ABET, 111 Market Place, Suite 1050, Baltimore, MD, 21202-4012, phone (410) 347-7700. The Bachelor of Science in Industrial Engineering (BSIE) curriculum is designed to comply with the ABET criteria for accrediting engineering programs. The educational objectives are that, within the first few years following their graduation, graduates should have:
- Been employed in industrial, service, or governmental organizations applying the industrial engineering skills in developing, designing, analyzing, implementing, or improving integrated systems that include people, materials, information, equipment, and energy
- Completed or enrolled in a graduate program
- Participated in a multicultural and diverse workplace
- Utilized teamwork, communication, and engineering management skills.
To achieve these objectives, all industrial engineering students must demonstrate or exhibit specific program outcomes. Students are instructed to contact their academic advisor or visit the departmental Website at https://www.eng.famu.fsu.edu/about/accreditation to obtain the current list of industrial engineering program outcomes.
Computer Skills Competency
All undergraduates at Florida State University must demonstrate basic computer skills competency prior to graduation. As necessary computer competency skills vary from discipline to discipline, each major determines the courses needed to satisfy this requirement. Undergraduate majors in industrial engineering satisfy this requirement by earning a grade of "C–" or higher in COP 3014 (preferred) or CGS 3406.
State of Florida Common Program Prerequisites for Industrial Engineering
The Florida Virtual Campus (FLVC) houses the statewide, internet-based catalog of distance learning courses, degree programs, and resources offered by Florida's public colleges and universities, and they have developed operational procedures and technical guidelines for the catalog that all institutions must follow. The statute governing this policy can be reviewed by visiting https://www.flsenate.gov/Laws/Statutes/2021/1006.73.
FLVC has identified common program prerequisites for the degree program in Industrial Engineering. To obtain the most up-to-date, state-approved prerequisites for this degree, visit: https://cpm.flvc.org/programs/368/283.
Specific prerequisites are required for admission into the upper-division program and must be completed by the student at either a community college or a state university prior to being admitted to this program. Students may be admitted into the University without completing the prerequisites but may not be admitted into the program.
Engineering Core Courses
COP 3014 Programming I (3)
EEL 3003 Introduction to Electrical Engineering (3)
EEL 3003L Introduction to Electrical Engineering Lab (1)
EGN 2123 Computer Graphics for Engineers (2)
EGN 3613 Principles of Engineering Economy (2)
EGM 3512 Engineering Mechanics (4)
EML 3100 Thermodynamics (2)
MAS 3105 Applied Linear Algebra I (4)
Requirements for a Major in Industrial Engineering
It is the policy of the Department of Industrial and Manufacturing Engineering that a student must receive satisfactory ("C–" or better) grades in all prerequisite courses prior to enrolling in an industrial engineering course. Concurrent registration in a course and its prerequisites is not allowed. All prerequisites to prerequisites must be completed. Failure to abide by this policy will result in the cancellation of enrollment in the course at any time during the semester and with no refund of fees. Corequisite courses must be taken concurrently or satisfactorily completed prior to enrolling in the course.
A candidate for the Bachelor of Science (BS) degree in industrial engineering is required to successfully complete the following courses, in addition to the other College of Engineering core requirements:
EGN 2123 Computer Graphics for Engineers (2)
EGN 3443 Statistical Topics in Industrial Engineering (3)
EGN 3613 Principles of Engineering Economy (2)
EIN 3104 Introduction to Engineering Management (3)
EIN 3010 Industrial and Manufacturing Engineering Tools (3)
EIN 3390C Engineering Materials and Manufacturing Processes I (3)
EIN 4394C Engineering Materials and Manufacturing Processes II (3)
EIN 4243 Ergonomics (3)
EIN 4333 Design of Integrated Production Systems and Facilities Layout (3)
EIN 4621 Manufacturing Systems Engineering (3)
EIN 4890 Industrial Engineering Senior Design Project I (3). - First of two semester sequence
EIN 4892 Industrial Engineering Senior Design Project II (3). - Second of two semester sequence
EIN 4936 Selected Topics in Industrial Engineering (3)
EIN 4940 Industrial and Manufacturing Engineering Practicum (2)
ESI 3312 Operations Research I: Deterministic (3)
ESI 3628 Computing Topics in Industrial Engineering (3)
ESI 4234 Quality Control and Reliability Engineering (3)
ESI 4313 Operation Research II: Nondeterministic (3)
ESI 4523 Simulation of Industrial Engineering Systems (3)
XXX XXXX Technical Elective (with advisor's approval) (3)
XXX XXXX Department Electives (3)
Industrial engineering majors are required to consult with their IE undergraduate advisor before enrolling for the next academic term. Students must obtain current IE degree requirements and course offering schedules from the IE department.
Honors in the Major
The Department of Industrial and Manufacturing Engineering offers an Honors in the Major program in Industrial Engineering to encourage talented juniors and seniors to undertake independent and original research as part of the undergraduate experience. For requirements and other information, see the "University Honors Office and Honor Societies" chapter of this General Bulletin, or visit https://honors.fsu.edu/honors-major.
Grade Requirements
In addition to University and college requirements regarding grades and grade point average (GPA), the Department of Industrial and Manufacturing Engineering requires that the IE major achieve a grade within the "C" range or higher for all required IE courses. In accordance with College of Engineering policy, a student may request that one course completed with a grade of "D+", "D", or "D–" be counted toward the BSIE degree. Recommendation by the IME undergraduate advisor(s) and approval by the department chairperson and the associate dean are required for the course to be counted toward graduation credit.
Definition of Prefixes
EEL—Engineering: Electrical
EGN—Engineering: General
EIN—Industrial Engineering
EMA—Materials Engineering
EOC—Ocean Engineering
ESI—Industrial/Systems Engineering
PRO—Prosthetics/Orthotics
Undergraduate Courses
EGN 1004L. First Year Engineering Laboratory (1). This laboratory includes an emphasis on student time management, a variety of products and processes, and computer-aided problem solving. Product/process involves sketching and drawing pertinent diagrams by hand, and learning the history and engineering concepts involved.
EGN 2123. Computer Graphics for Engineers (2). Corequisite: MAC 2311. This course covers principles of engineering graphics: visualization, spreadsheet applications, graphical calculus, and descriptive geometry. Also introduces the engineering design process and CAD systems.
EGN 3443. Statistical Topics in Engineering (3). Prerequisite: MAC 2312. This course explores basic statistical analysis, samples and populations, variability, hypothesis formulation, and data analysis. Use of computer software and interpretation of results.
EGN 3613. Principles of Engineering Economy (2). Prerequisite: MAC 2313 or equivalent. This course emphasizes discrete cash flow diagrams, cash flow equivalence factors, standard criteria for comparing project proposals, special cash flow topics, special analysis, and case studies.
EGN 4060. Big Data Analytics in Engineering (3). Prerequisite: EGN 3443. This course introduces fundamentals of big data analytics including data loading, cleaning, transformation, visualization, predictive analytics, and data-driven decision making. An emphasis is placed on computer implementation using state-of-the-art data analytics language.
EIN 3010. Industrial and Manufacturing Engineering Tools (3). Prerequisite: Major status. This course teaches, from an engineering viewpoint, fundamental topics that are important for the practicing industrial engineer, including technical writing, oral communication and presentation of technical topics, managerial and cost accounting for production organizations and databases and management information systems.
EIN 3104. Introduction to Engineering Management (3). Prerequisites: EGN 2123 and EGN 3613. This course focuses on topics such as the evolution, history, emergence, and ethics of engineering and industrial engineering. Emphasis is placed on the management of technology and on the engineering method for product conceptualization, design, development, and production. Fundamental sciences, engineering methods, information systems, economics, and behavior theory contained in engineering management principles and practices.
EIN 3390C. Engineering Materials and Manufacturing Processes I (3). Prerequisite: CHM 1045 and CHM 1045L. Corequisite: EGN 2123. This course is an introduction to industrial materials and their composition, properties, metallography, and heat treatment. Introduction to the manufacturing processes of machine industries including hot working, cold working, and metal removal.
EIN 3905r. Directed Independent Study (3). Prerequisite: Permission from the department chairperson. Topics vary and each case must be approved by the department chairperson. May be repeated to a maximum of six semester hours.
EIN 4214. Occupational Safety and Hazard Control (3). This course covers the history of safety, safety in the workplace, government regulations, methods of accident prevention, system safety, reliability, and fault tree analysis.
EIN 4243. Ergonomics (3). Prerequisites: EGM 3512, EGN 3443, and EIN 4394C. This course examines human characteristics and limitations in relation to physical work, mental work, and job design. This course utilizes case studies and design exercises to explore human physiological variables in relation to industrial work environments and product design.
EIN 4333. Design of Integrated Production Systems and Facilities Layout (3). Prerequisites: EGN 2123, EGN 3613, and ESI 3312C. This course explores basic functions: demand forecasting, process planning, master scheduling, expediting, and quality control. Inventory control. Formation of systems from those basic functions. Case studies and design exercises with computer implementation.
EIN 4394C. Engineering Materials and Manufacturing Processes II (3). Prerequisite: EIN 3390C. This course is an introduction to engineering materials used in industry from the perspectives of composition, microstructures, properties, and heat treatment, various traditional and non-traditional manufacturing processes, basic mathematical descriptions for selected processes, and the application of these concepts to process selection and planning.
EIN 4444. Technology Entrepreneurship and Commercialization (3). This course simulates, in an academic environment, the process of creating and analyzing business models and commercialization plans for technology-based products or services to meet a need or solve a problem.
EIN 4611. Industrial Automation and Robotics (3). Prerequisite: EIN 3390C. This course introduces modern manufacturing systems, with a special focus on the integration of manufacturing resources using computers. Featured subjects include design, planning, analysis, and control of computer-integrated manufacturing systems.
EIN 4621. Manufacturing Systems Engineering (3). Prerequisite: EIN 4934C. This course introduces modern manufacturing systems, with a special focus on the integration of manufacturing resources using computers. Featured subjects include design, planning, analysis, and control of computer-integrated manufacturing systems.
EIN 4890. Industrial Engineering Senior Design Project I (3). Prerequisite: Must be in final year of the degree program. This course is the first in a two-part course sequence, this capstone class represents the culmination of the industrial-engineering design sequence and draws upon student training from all previous courses. This course utilizes the six-sigma methodology to reduce variation and defects to deliver products and services that meet customer requirements.
EIN 4891. Industrial Engineering Senior Design Project (3). Prerequisite: Must be in final year of the degree program. This course expects students to complete a large-scale design project involving the full implementation of the IPPED process. Project includes a written report and requires the use of various techniques and methods. Two-semester sequence.
EIN 4892. Industrial Engineering Senior Design Project II (3). Prerequisite: EIN 4890, and must be in final year of the degree program. This course is the second in a two-part course sequence, this capstone class represents the culmination of the industrial-engineering design sequence and draws upon student training from all previous courses. This course utilizes the six-sigma methodology to reduce variation and defects in order to deliver products and services that meet customer requirements.
EIN 4934r. Honors Thesis (3). May be repeated to a maximum of six semester hours.
EIN 4936r. Selected Topics in Industrial Engineering (3). Topics are determined by a departmental committee on special topics, taking into consideration the needs of students who are about to graduate. May be repeated to a maximum of nine credit hours. May be repeated within the same term.
EIN 4940. Industrial and Manufacturing Engineering Practicum (2). Prerequisite: EIN 4621. This course illustrates the design principles required for industries to preserve a competitive enterprise.
ESI 3312C. Operations Research I: Deterministic (3). Prerequisite: MAS 3105. This course covers the following topics with emphasis on validation of algorithm linear programming, assignment problems, CPM, network flows, discrete optimization, and branch-and-bound solution method.
ESI 3628. Computing Topics in Industrial Engineering (3). Prerequisite: COP 3014. This course focuses on state of the art computing techniques for industrial engineers. Applications of structured programming, mathematical analysis software, and engineering databases. Use in engineering of GUI languages, Internet communication, and UNIX.
ESI 4234. Quality Control and Reliability Engineering (3). Prerequisite: EGN 3443. This course is an introduction to quality and reliability engineering. This course examines statistical quality control techniques, process capability analysis, design and analysis of experiments for quality and reliability improvement.
ESI 4313C. Operations Research II: Nondeterministic (3). Prerequisites: EGN 3443 and MAP 3305. This course focuses on the development and application of nondeterministic, analytic models including PERT/CPM, discrete and continuous time Markov chains, queuing models including queuing networks, inventory models, and decision analysis. Case studies and design exercises.
ESI 4523. Simulation of Industrial Engineering Systems (3). Prerequisite: ESI 4234. This course focuses on simulation modeling and computer solution of industrial engineering systems. Modeling strategies, probability considerations, simulation languages, simulation verification, and engineering case studies.
ESI 4626. Managing Supply Chains for Resilience (3). Prerequisite: ESI 3312C. This course covers key concepts, models, and analytical tools of supply chain management, including facility location, supply-chain network design, aggregate planning, inventory management, risk-pooling strategies, product-design strategies for supply-chain management, distribution strategies, the bullwhip effect, and distribution management.
ESI 4682. Introduction to Machine Learning (3). Prerequisites: EGN 3443, ESI 3312, and MAS 3105. This course is an introduction to machine learning geared toward advanced undergraduates or first-year graduate students.
ESI 4686. Deep Learning in Practice (3). Prerequisites: EGN 3443, ESI 3312C, and MAS 3105. This course introduces three main neural networks (ANN, CNN, and RNN) and the realization in Python. Students learn the basics such as forward propagation, backward propagation, and gradient descent algorithms, as well as up-to-date neural network projects like (YOLO, VGG19, Resnet50, etc.)
For listings relating to graduate coursework, consult the Graduate Bulletin.