Industrial Engineering Program At University of California Berkeley is a highly ranked program.
The undergraduate program is designed to prepare students for technical careers in production or service industries. It provides a strong foundation for those headed for engineering management positions or for those intending to go on to specialized graduate study in operations research, industrial engineering, or business administration.
The core of the program includes: basic science mathematics, including probability and statistics engineering optimization and stochastic models This forms the methodological foundation for upper division IEOR electives involving the analysis and design of production and service systems, information systems, and human work systems and organization, among others.
The paramount requirement of a doctoral degree is the successful completion of a thesis on a subject within the major field. Research areas may include the investigation of the mathematical foundations of and computational methods for optimization or stochastic models, including risk analysis. Research also may be undertaken to develop methodologies for the design, planning, and/or control of systems in a variety of application domains.
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Robert C. Leachman
Andrew Lim
Shmuel S. Oren
Christos Papadimitriou
Rhonda L. Righter (Chair)
Lee W. Schruben
Zuo-Jun "Max" Shen
Ikhlaq Sidhu
Candace Yano
Industrial Engineering and Operations Research
University of California @ Berkeley
Currently on industrial leave (starting 7/1/19)
Phil Kaminsky is the Earl J. Isaac Professor in the Science and Analysis of Decision Making in the Department of Industrial Engineering and Operations Research at UC Berkeley. He is currently on industrial leave at Amazon, as a Principal Research Scientist. Prior to his leave, he served as Executive Associate Dean and Associate Dean for Student Affairs in the UC Berkeley College of Engineering, and before that, faculty director of the Sutardja Center for Entrepreneurship and Technology, director of the Initiative for Research in Biopharmaceutical Operations, and department chair of Industrial Engineering and Operations Research.
Professor Kaminsky's research focuses primarily on the analysis and development of robust and efficient tools and techniques for design, operation, and risk management in logistics systems and supply chains. This encompasses operational issues including the modeling and analysis of production and control systems, as well as more tactical and strategic concerns, including the integration of production, distribution, and pricing strategies, and more broadly the analysis of issues that arise in integrated supply chain management.
Much of his current work is centered on two main themes: strategic, tactical, and operational issues that arise in the operation of biopharmaceutical firms; and collaborative, sustainable logistics. Other current projects focus on the development of novel flexible algorithms for supply chain optimization, container terminal operations, efficient operation of operating rooms, and quantitative modeling of behavior change for personalized healthcare. His research has been funded by the National Science Foundation, BioMarin, Bayer, Genentech, Navis, Project Production Institute, Material Handling Institute, Toyota, and FICO.
Professor Kaminsky received his BS in Chemical Engineering from Columbia University in 1989, and his MS and PhD in Industrial Engineering and Management Science from Northwestern University in 1997.
https://kaminsky.ieor.berkeley.edu/
Industrial Engineering and Operations Research Dept.
Ph.D. Northwestern University Industrial Engineering and Management Sciences
Research
Integrated Supply Chain Design and Management
Mechanism Design in Supply Chain Settings
Design and Analysis of Optimization Algorithms
E-mail: maxshen (at) berkeley.edu
https://ieor.berkeley.edu/people/zuo-jun-max-shen/
Updated on 9.8.2024, 22 September 2019, 29 March 2012
Original knol - http://knol.google.com/k/kvss/industrial-engineering-programs-at/ 1zb6eis38d7or/ 25
Department of Industrial Engineering and Operations Research
4141 Etcheverry Hall,
Mail Code 1777
University of California
Berkeley, CA 94720-1777
4141 Etcheverry Hall,
Mail Code 1777
University of California
Berkeley, CA 94720-1777
__________________________________________________________________________________
The Department of Industrial Engineering and Operations Research (IEOR) educates students to become highly skilled in:
the quantitative modeling and analysis of a broad array of systems-level decision problems concerned with economic efficiency, productivity and quality;
the quantitative modeling and analysis of a broad array of systems-level decision problems concerned with economic efficiency, productivity and quality;
An Important Contribution by University of California Berkeley Faculty.
Work Methods Design and Work Simplification
BY LOUIS E . DAVIS
College of Engineering. University of California
Berkeley. California
Advances in Food Research. (1953). United Kingdom: Elsevier Science. pp. 37-104.
https://www.google.com/books/edition/Advances_in_Food_Research/h6-yzgZaTOAC?hl=en
Industrial Engineering - Important Ideas and Principles - Work Methods Design and Work Simplification - LOUIS E . DAVIS
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2024 Fall Semester. Fall Semester Begins. Wednesday, August 21, 2024.
Undergraduate Program
The core of the program includes: basic science mathematics, including probability and statistics engineering optimization and stochastic models This forms the methodological foundation for upper division IEOR electives involving the analysis and design of production and service systems, information systems, and human work systems and organization, among others.
BS-IEOR worksheet 2023-2025
INTRODUCTION TO ENGINEERING - INTRODUCTION TO MODERN INDUSTRIAL ENGINEERING.
#IndustrialEngineering for #SocietyProsperity.
For the Academic Year 2024-25 - Bachelor in Industrial Engineering #BSIE. 9480+ Downloads for 2023-24.
Free Download from:
IEOR Courses
Upper Division Requirements
Course List
Code Title Units
IND ENG 120 Principles of Engineering Economics 3
IND ENG 160 Nonlinear and Discrete Optimization 3
IND ENG 162 Linear Programming and Network Flows 3
IND ENG 165 Engineering Statistics, Quality Control, and Forecasting 4
IND ENG 172 Probability and Risk Analysis for Engineers 2 4
or STAT 134 Concepts of Probability
or STAT C140 Probability for Data Science
or DATA C140 Probability for Data Science
IND ENG 173 Introduction to Stochastic Processes 3
IND ENG 174 Simulation for Enterprise-Scale Systems 3
IND ENG 180 Senior Project 4
IND ENG Electives: Select 6 courses from the following: 21
IND ENG 115 Industrial and Commercial Data Systems [3]
IND ENG 130 Methods of Manufacturing Improvement [3]
IND ENG 135 Applied Data Science with Venture Applications [3]
IND ENG 142A Introduction to Machine Learning and Data Analytics [4]
IND ENG 142B Machine Learning and Data Analytics II [4]
IND ENG 145 Fundamentals of Revenue Management [3]
IND ENG 150 Production Systems Analysis [3]
IND ENG 151 Service Operations Design and Analysis [3]
IND ENG 153 Logistics Network Design and Supply Chain Management [3]
IND ENG 156 Healthcare Analytics [3]
IND ENG 164 Introduction to Optimization Modeling [3]
IND ENG 166 Decision Analytics [3]
IND ENG 169 Integer Optimization [3]
IND ENG 170 Industrial Design and Human Factors [3]
Ethics Requirement: Select one course from the following: 3
BIO ENG 100 Ethics in Science and Engineering [3]
DATA C104/HISTORY C184D/STS C104D
Human Contexts and Ethics of Data - DATA/History/STS [4]
ENE,RES C100/PUB POL C184
Energy and Society [4]
ENE,RES W100/PUB POL W184
Energy and Society [4]
ENGIN 125 Ethics, Engineering, and Society [3]
ENGIN/IAS 157AC Engineering, The Environment, and Society [4]
IND ENG 171 Berkeley Changemaker: Ethical and Effective Entrepreneurship in High Tech [3]
UGBA 107 The Social, Political, and Ethical Environment of Business [3]
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Graduate Program
At the master's level, students may emphasize applied courses, preparing them for professional practice, or may follow a more theoretical program intended for those who will pursue doctoral studies.
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Research Program
The paramount requirement of a doctoral degree is the successful completion of a thesis on a subject within the major field. Research areas may include the investigation of the mathematical foundations of and computational methods for optimization or stochastic models, including risk analysis. Research also may be undertaken to develop methodologies for the design, planning, and/or control of systems in a variety of application domains.
_______________________________________________________________________________
Faculty:
 |
Andrew Lim
Shmuel S. Oren
Christos Papadimitriou
Rhonda L. Righter (Chair)
Lee W. Schruben
Zuo-Jun "Max" Shen
Ikhlaq Sidhu
Candace Yano
EMERITUS:
|
Richard E. Barlow Stuart Dreyfus Roger Glassey Robert M. Oliver Sheldon M. Ross (Now Chair at USC) J. George Shanthikumar Ronald W. Wolff |
Phil Kaminsky
Industrial Engineering and Operations Research
University of California @ Berkeley
Currently on industrial leave (starting 7/1/19)
Phil Kaminsky is the Earl J. Isaac Professor in the Science and Analysis of Decision Making in the Department of Industrial Engineering and Operations Research at UC Berkeley. He is currently on industrial leave at Amazon, as a Principal Research Scientist. Prior to his leave, he served as Executive Associate Dean and Associate Dean for Student Affairs in the UC Berkeley College of Engineering, and before that, faculty director of the Sutardja Center for Entrepreneurship and Technology, director of the Initiative for Research in Biopharmaceutical Operations, and department chair of Industrial Engineering and Operations Research.
Professor Kaminsky's research focuses primarily on the analysis and development of robust and efficient tools and techniques for design, operation, and risk management in logistics systems and supply chains. This encompasses operational issues including the modeling and analysis of production and control systems, as well as more tactical and strategic concerns, including the integration of production, distribution, and pricing strategies, and more broadly the analysis of issues that arise in integrated supply chain management.
Much of his current work is centered on two main themes: strategic, tactical, and operational issues that arise in the operation of biopharmaceutical firms; and collaborative, sustainable logistics. Other current projects focus on the development of novel flexible algorithms for supply chain optimization, container terminal operations, efficient operation of operating rooms, and quantitative modeling of behavior change for personalized healthcare. His research has been funded by the National Science Foundation, BioMarin, Bayer, Genentech, Navis, Project Production Institute, Material Handling Institute, Toyota, and FICO.
Professor Kaminsky received his BS in Chemical Engineering from Columbia University in 1989, and his MS and PhD in Industrial Engineering and Management Science from Northwestern University in 1997.
https://kaminsky.ieor.berkeley.edu/
Zuo-Jun “Max” Shen
Professor and ChairIndustrial Engineering and Operations Research Dept.
Ph.D. Northwestern University Industrial Engineering and Management Sciences
Research
Integrated Supply Chain Design and Management
Mechanism Design in Supply Chain Settings
Design and Analysis of Optimization Algorithms
E-mail: maxshen (at) berkeley.edu
https://ieor.berkeley.edu/people/zuo-jun-max-shen/
Updated on 9.8.2024, 22 September 2019, 29 March 2012
Original knol - http://knol.google.com/k/kvss/industrial-engineering-programs-at/ 1zb6eis38d7or/ 25
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