MING ZHOU
ASSOCIATE PROFESSOR
Dr. Ming Zhou received a Ph.D. in Systems and Industrial
Engineering from the The University of Arizona. Currently he is an associate
professor in the IMT department, and taught courses in computer graphics,
reliability and failure analysis, statistics for experimental research,
advanced computer aided design, graphical analysis calculus, experimental
design and process analysis, etc. Dr. Zhou has also taught courses in
engineering statistics, industrial engineering methods, CAD/CAM, computer
programming before he join the faculty of ISU. He has also given workshop
lectures on design of experiment (DOE) and computer aided design/modeling.
Dr. Zhou is actively conducting applied research in several areas (see
description below). He is a member of IIE and INFORMS.
CURRICULUM DEVELOPMENT
- Dr. Ming Zhou has proposed the following courses for undergraduate or
graduate studies:
- Graduate students and senior undergraduates are also welcome to
take independent study course with Dr. Zhou, and may select a topic
from, but not limited to, the following areas: computer integrated
manufacturing (CIM), CAD (geometric modeling, graphics, analysis),
computer simulation, design/analysis of production/manufacturing
systems, statistical quality control (SPC), design of experiment (DOE),
industrial application of artificial intelligence (e.g., expert
systems), production planning and inventory control, project management
and scheduling, applied optimization, fuzzy-logic and neural network
modeling, decision-making analysis, integrated design and analysis of
distribution packaging.
CURRENT RESEARCH INTERESTS/ACTIVITIES
- Decision models and optimization in computer-aided process planning (CAPP)
- Fuzzy logic and optimization models for the QFD implementations in
design and quality planning/improvement
- Network flow models/heuristics in planning QC operations in general
manufacturing systems
- Neural network models for package performance prediction and package
design
- Data mining and rule formation with neural networks, knowledge
extraction from massive data/database
- Modeling and analysis of engineering design process/methodology
- Artificial Intelligence (AI) in the design and control of engineering
systems
- Simulation modeling/analysis of discrete production/manufacturing
systems
- AI and knowledge-based system for design and optimization of food
extrusion process
- Combining GIS and GPS technology with operations research in
production and distribution planning
GRANTS/PROPOSALS
- Research grant from University Research Council (URC), $2350, 1996. Process
Selection and Tolerance Allocation for Rotational Surfaces.
- Research grant from URC, $2800, 1997. A Fuzzy Set Theory Based
Methodology for Target Value Problem in Quality Improvement.
- 1997 PIF Award from Indiana State University, $4160. Integrated
Design, Modeling and Analysis in Distribution Packaging.
- Research grant from Kellogg Institute, Inc., $58,740. April, 1999. AI
and Knowledge-based System for Design and Optimization of Food Extrusion
Process.
- Lilly Faculty Fellowship, $5000, May, 1999. Investigation and
Development of Data Mining Models for Analyzing First-Year Student
Profile Data.
SELECTED PUBLICATIONS
- "Integrated Operations Planning and Manufacturing Cell
Formation", Proceedings, ORSA Technical Session On Manufacturing
Management, June, 1994, pp. 96-103.
- "Formation of General GT Cells: An Operation-based
Approach", International Journal of Computers and Industrial
Engineering, Vol. 34, No. 1, pp. 147-157, 1998.
- "Formation of Independent Flow-line Cells based on Operations
Requirement and Machine Capability", IIE Transactions, Vol.
30, pp.319-329, 1998. This paper received "Best
Paper Award" from IIE Transactions.
- "A Parallel Station Heuristic For The Mixed-Model Production Line
Balancing Problem", International Journal of Production
Research, Vol. 35, No. 11, 1997, pp. 3095-3105.
- "Process Selection and Tolerance Allocation for Rotational
Surfaces", Proceedings, 6th Industrial Engineeing Research
Conference, May, 1997, pp. 942-947.
- "Fuzzy Logic Based Models for Quality Planning and
Improvement", Intelligent Engineering Systems Through Artificial
Neural Networks, Volume 7, 1997, pp. 311-316.
- "A Fuzzy Set Theory Based Approach for Target Improvement Problem
in Design and Quality Planning", International Journal of
Industrial Engineering, Vol. 5, No. 4, 1998, pp. 278-287.
NEW COURSES
- Reliability
and Failure Analysis____ Introduce the concept and principles
of reliability, failure modes and mechanisms, with emphasis on the
applied techniques to determine time-to-failure, failure rate, and
reliability of conponents/systems, including probability distribution
models, construction of reliability bath-tube curve (RBTC), failure mode
and effect analysis (FMEA), fault tree analysis (FTA), etc. This course
is designed for both undergraduate and graduate students (Master) as
well as engineers/managers in service.
- Experimental
Design and Process Analysis ____ Introduction to the design
and analysis of engineering experiments for industrial applications.
Topics include single factor models, blocking design, factorial design
and regression analysis. Emphasis is given to the modeling of industrial
application problems. Computer aided modeling and analysis is also
introduced. The course is designed for graduate students (particularly
QSS major) as well as engineers/managers in service.
- Reliability,
Maintainability and Serviceability____ This course is
designed for graduate students, particularly doctoral students in
Quality Systems Specialization (QSS). It emphasizes the methodology used
in analyzing manufacturing and other production systems based on
reliability, maintainability and serviceability concepts and principles.
CONTACT INFORMATION
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