The faculty in the Department of Industrial and Management Systems Engineering offer graduate programs leading to the M.S., the Master of Science in Engineering, and the Ph.D. degrees in Industrial Engineering.
The overall educational objective of graduate study in industrial engineering is to improve each student’s ability to understand, analyze, and resolve problems within complex organizations. Industrial engineers must develop qualitative and quantitative abilities to assist management in such diverse organizations as banks, government, hospitals, military, and manufacturing operations.
It is required that all students applying for one of the master’s or doctoral degree programs submit scores (verbal, quantitative, analytical) on the Graduate Record Examination, a statement of purpose, and three letters of recommendation.
MASTER OF SCIENCE
See “Master’s Degrees” for information on the M.S. degree.
MASTER OF SCIENCE IN ENGINEERING
Students applying for the program leading to the Master of Science in Engineering degree in Industrial Engineering may have a baccalaureate degree in a major or field other than industrial engineering, although engineering, mathematics, or science is recommended. The student’s qualifications are reviewed by the faculty.
A dual degree is available. It is designed to enable qualified graduate students to pursue the Master of Science in Engineering (M.S.E.) at ASU and a Master of International Management of Technology (M.I.M.O.T.) at the American Graduate School of International Management (Thunderbird). Thunderbird is an internationally recognized private graduate school located in the Phoenix metropolitan area, offering course work in international studies, modern languages, and world business. Details are available from the departmental office.
See “Master of Science in Engineering” for more information on the M.S.E. degree.
DOCTOR OF PHILOSOPHY
The Ph.D. degree in Industrial Engineering is conferred upon evidence of excellence in research that culminates in a dissertation representing a significant contribution to the field of industrial engineering.
See “Doctor of Philosophy” for general requirements.
Program of Study. The program of study should be developed early in the second semester of Ph.D. study or when the student has completed six semester hours of courses at ASU. Specific requirements may be obtained from the department.
Early Evaluation. Early in the second regular semester in residence, the student’s program of study and academic accomplishment to date serve as a basis for evaluation by the supervisory committee. The results of this evaluation are used to assist the student in improving or modifying the program of study, to encourage the continuance of Ph.D. studies or, if necessary, to discourage the student from continuing in the program.
Foreign Language Requirements. None.
Comprehensive Examinations. When the Ph.D. student has essentially completed the course work in the approved program of study and submitted a research proposal to the advisory committee, the student is given a written comprehensive examination relating to the research area. The written examination is followed by an oral exam.
Dissertation Committee. Upon successful completion of the comprehensive examinations, the student applies for candidacy. At this time a dissertation committee is selected to assist in and evaluate the research project and dissertation.
Dissertation Requirements. A dissertation based on original work demonstrating creativity in research and scholarly proficiency in the subject area is required.
Final Examinations. A final oral examination in defense of the dissertation is required.
RESEARCH ACTIVITY
The Industrial and Management Systems Engineering faculty are involved in a wide variety of research projects. Recent research includes: interrelationship of the working environment and productivity with emphasis on the human factors elements; creation and development of an Industrial Engineering design environment; proper uses of human factors information in the development of multimedia training systems for the manufacturing environment; evaluation and analysis of computerized product models for automated manufacturing, which includes CAD, CAM, and process planning; examination of the cost drivers in semiconductor material handling simulations which involves determining the factors responsible for the accuracy in the model and weighing them against the time necessary to include them in the model; modeling, analysis, and design of semiconductor manufacturing systems; SPC for short runs; transient models of queuing networks with inspection; multi-tasking of workers in just-in-time systems; hybrid push/pull manufacturing system design; logistics modeling of component redundancy with spares; assessing manufacturing using quality, time and cost; assessing statistical capability for complex manufactured parts; innovative methods for teaching statistics to engineering students; forecasting electric power demand; human factors with emphasis on visual perception; computer vision and imaging processing; best practices, maturity, and diffusion in new product development; creativity in engineering concept design; defining and measuring software quality; chaotic dynamics in vehicle traffic; development and analysis of stochastic environmental life cycle assessment inventory modeling; extensions to regression adjustment techniques in multivariate statistical process monitoring; statistical processing control with autocorrelated data; new hypothesis test for the characteristic value of the Weibull distribution; Bayes’ stopping rules for reliability testing; repairability features for use in reliability block diagram simulations; applications of the Burr distribution in reliability; scheduling of underground mining operations; modeling with first-order predicate linear formulas; measuring the business effects of utilizing state-of-the-market electronic commerce technology and business practices; effective employment of information technology as a strategic differentiator for a company; development of the next generation systems modeling tool kit, an object oriented package called left“FIDO” that allows function, information, dynamic and organizational modeling to be done in a common framework; development of a framework for a model-based enterprise, which is the integration of commercial off-the-shelf (COTS) technologies that allows a company to migrate into the 21st century with an analytical foundation; developing aids that assist in evaluating design performance with respect to environmental, health, and safety objectives; developing methodologies that significantly improve the productivity of software design, development and maintenance; developing systems concepts for configuration and change management; development of techniques for the rapid application development of client server and web systems; development of distance education concepts knowledge enterprises; development of management of technology methodologies for the allocation of technological resources in the virtual enterprise environment.
Omnibus Graduate Courses: See omnibus graduate courses that may be offered.
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