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faculty
Wenzhen Huang, PhD
Professor
Contact
508-910-6568
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Science & Engineering 116C
Education
| 2004 | University of Wisconsin | PhD in Industrial Engineering |
| 1987 | Shanghai Jiatong University | PhD |
| 1984 | Julin University | MS |
| 1982 | Julin University | BS |
Teaching
Programs
Programs
- Advanced Manufacturing
- Energy
- Engineering and Applied Science PhD
- Mechanical Engineering BS, BS/MS
- Mechanical Engineering MS
Teaching
Courses
Discussion and comparison of manufacturing processes for economy of production; and modifications to proposed designs to suit existing equipment. Material selection to suit production and service requirements is covered along with economics of automation and inventory control. Basic principles of the statistics and probability theory as applied to quality control of manufacturing process are discussed. Machining operations using conventional and modern machine tools are covered in addition to other manufacturing demonstrations.
Discussion and comparison of manufacturing processes for economy of production; and modifications to proposed designs to suit existing equipment. Material selection to suit production and service requirements is covered along with economics of automation and inventory control. Basic principles of the statistics and probability theory as applied to quality control of manufacturing process are discussed. Machining operations using conventional and modern machine tools are covered in addition to other manufacturing demonstrations.
Discussion and comparison of manufacturing processes for economy of production; and modifications to proposed designs to suit existing equipment. Material selection to suit production and service requirements is covered along with economics of automation and inventory control. Basic principles of the statistics and probability theory as applied to quality control of manufacturing process are discussed. Machining operations using conventional and modern machine tools are covered in addition to other manufacturing demonstrations.
Discussion and comparison of manufacturing processes for economy of production; and modifications to proposed designs to suit existing equipment. Material selection to suit production and service requirements is covered along with economics of automation and inventory control. Basic principles of the statistics and probability theory as applied to quality control of manufacturing process are discussed. Machining operations using conventional and modern machine tools are covered in addition to other manufacturing demonstrations.
Discussion and comparison of manufacturing processes for economy of production; and modifications to proposed designs to suit existing equipment. Material selection to suit production and service requirements is covered along with economics of automation and inventory control. Basic principles of the statistics and probability theory as applied to quality control of manufacturing process are discussed. Machining operations using conventional and modern machine tools are covered in addition to other manufacturing demonstrations.
Honors enrichment course supplementing a required junior level course in the Mechanical Engineering curriculum. This course is open to honors students who are enrolled in the affiliated required course in the mechanical engineering curriculum. The course provides coverage of more advanced topics and more in-depth analysis of concepts than are covered in the basic class. The course may include lecture and laboratory components at the instructor's discretion.
Principles and procedures necessary to control processes and quality of manufactured products. Topics include: product quality, quality assurance, destructive and non-destructive tests, statistical methods in quality control, acceptance sampling, rectifying inspection, sensors, automated inspection, control charts, total quality control, quality circle, quality philosophy of Deming, Taguchi, and others.
The need and subject matter of research. Laws, truths, analogy and hypothesis. Identifying and clustering parameters. Use of models. Experimental setup. Induction, deduction, statistics, and conclusions. Presentation and use of finding.
Fundamentals and procedures in developing efficient layouts for production and service facilities and material handling systems. Manual procedures and microcomputer-based layout algorithms. Review of material handling equipment used in warehousing and manufacturing. Algorithms to design and analyze discrete parts material storage and flow systems such as Automated Storage/Retrieval Systems, order picking, conveyors, automated guided vehicle systems and carousels.
Research
Research awards
- $ 31,911 awarded by University of Delaware for National Institute for Innovation in Manufacturing Biopharmaceuticals
Research
Research interests
- Computer Aided Tolerance Analysis and Optimization (NSF & UMASSD Chancellor's Fund)
- Diagnostics in Manufacturing (ATP/NIST)
- MEMS and NANOManufacturing
- Modeling, Simulation, and Optimization of Manufacturing Systems (ATP/NIST)
- Quality Engineering and Applied Statistics
Select publications
- W. Huang, B. R. Konda, Z. Kong (2010).
"Geometric Tolerance Simulation Model for Rectangular and Circular Planar Features"
Trans. NAMRI/SME - W. Huang, Z. Kong, A. Chennamaraju (2010).
"Fixture Robust Design by Sequential Space Filling Methods in Multi-Station Manufacturing Systems"
ASME Trans. Journal of Computing & Information Science in Engineering (JCISE) - W. Huang, Z. Kong (2009).
"Process Capability Sensitivity Analysis for Design Evaluation of Multi-Station Assembly Systems"
IEEE Trans., Special Issue on Advances in Automation Science and Engineering for Automotive Manufacturing
Wenzhen Huang obtained his Ph.D. in Industrial Engineering from The University of Wisconsin-Madison in 2004 and worked as postdoctoral research fellow at UW-Madison. He also worked as a professor of Mechanical Engineering at Shanghai Jiaotong University, China, for about 5 years.
Professor Huang's interests are in product and manufacturing process modeling, simulation, design analysis and optimization, and diagnosis for variation reduction and quality improvement. Specific topics in his recent and current research include streams of variation modeling and analysis (SOVA) in multi-stage manufacturing systems, compliant assembly process, GD&T modeling and simulation, statistical tolerance analysis and synthesis, probabilistic design and optimization, metrology and sensor system, and statistical signal processing for diagnosis and quality control. The application area covers automotive, fuel cell, MEMS,aerospace, shipbuilding, power industries, and general mechanical products and manufacturing systems design. His research has been and is supported by ATP/NIST, NSF, and UMASSD Chancellor's Fund.