Industrial, Manufacturing, and Systems Engineering

Bryan Mesmer from the Department of Industrial and Systems Engineering and Engineering Management at the University of Alabama in Huntsville will present at the Seminar on Friday April 27 at 1:15pm in Room 105 of Nedderman Hall. Dr. Mesmer’s presentation title, abstract, and biographical sketch are below.

Title: Reimagining Systems Engineering Through Preferences and the Arts
Author: Bryan Mesmer
Location: Nedderman Hall (NH) Room 105
Date: Friday, April 27
Time: 1:15pm – 2:15pm

Abstract: This seminar will discuss the pursuit of creative and novel research in the foundations of systems engineering to enable a reimagining of systems engineering. A reimagining is needed due to the growing challenges in costs, schedules, etc. that systems engineering is facing as systems become ever more complex. Specifically two research topics will be discussed: decision making in systems engineering and the art of systems engineering. Decision making is researched in order to reduce inconsistencies in systems engineering by advancing the state of observing, communicating, and representing preferences. Inconsistencies in decision making typically lead to designs that are non-optimal due to stakeholders disagreeing on what is best. Utility and game theories are the primary tools used in this research. The arts are researched to identify approaches that could aid in understanding and performing systems engineering and to infuse those artistic approaches into systems engineering. The arts research that will be discussed in this seminar are gaming, storytelling, and theatre. In particular, the need for a surrogate of complex systems due to the high costs, long durations, and limited accessibility of common complex systems will be discussed, with theatre proposed as a surrogate. The findings of the research demonstrate that systems engineering can be improved, but a fundamental transformation of systems engineering may need to occur for those improvements to be fully realized.

Biography: Dr. Bryan Mesmer is an Assistant Professor in the Department of Industrial and Systems Engineering and Engineering Management at the University of Alabama in Huntsville. Dr. Mesmer was previously a Postdoctoral Research Associate in the Department of Aerospace Engineering at Iowa State University. He completed his Ph.D. in August 2012 at the State University of New York at Buffalo in Mechanical Engineering. Also at the University at Buffalo, he completed his M.S. in Mechanical Engineering (2010) and a dual B.S. in Mechanical and Aerospace Engineering (2007). His research has focused on improving the systems engineering process, particularly for large-scale complex systems. He uses his background in decision analysis, multidisciplinary design analysis and optimization, system/subsystem modeling, design theory, and value-based design to perform research on topics including: interactions in systems and design; incorporation of end-user models and simulations in design; preference representation and communication; the arts in systems engineering; and integration of new system and design processes in government and industry practice. He is currently the University Lead of the NASA Systems Engineering Research Consortium, leading efforts on the development of systems engineering principles and the integration of modelling techniques.

 

 

UTA IMSE alumnus Scott Wiederhold from American Airlines will present at the IMSE Seminar on Monday April 23 at 1:15pm in Room 105 of Nedderman Hall. Mr. Wiederhold’s presentation title, abstract, and biographical sketch are below.

Title: From Mainframes to Machine Learning: Advanced Analytics at American Airlines
Author: Scott Wiederhold
Location: Nedderman Hall (NH) Room 105
Date: Monday, April 23
Time: 1:15pm – 2:15pm

Abstract: Every day at American Airlines over 6,500 flights depart carrying over 500,000 passengers. Planning for every single flight starts almost a year in advance, and requires the input of multiple departments. The Operations Research Team at American Airlines plays a critical role in the models, systems, and analytics that departments across the airline rely on to do their jobs on a daily basis. This talk gives insight into the entire flight and passenger journey – from building a schedule, pricing and selling tickets, airport layouts, and post-travel items. We’ll also discuss how the Operations Research team supports departments across the airline, and how a new team dedicated to Machine Learning and Data Science is advancing the thinking of Artificial Intelligence across the organization.

Biographical sketch: Scott Wiederhold has been with American Airlines for over 17 years. He manages a new team of OR Consultants responsible for workforce analytics and Human Resources. Prior to working in Operations Research he held positions in Airports, Maintenance, Operations Centers, and Headquarters. Scott received his undergraduate degree from the University of California, San Diego, and his MS in Industrial Engineering from the University of Texas at Arlington.

 

-Posted by Jay Rosenberger

Dr. Megan Olsen from Loyola University Maryland will present at the Seminar Friday April 13 at 1:15pm in Room 121 of Science Hall (SH). Dr. Olsen’s presentation title, abstract, and biographical sketch are below.

 

Title: Metamorphic Testing for Simulation Validation

Author: Dr. Megan Olsen
Location: Science Hall (SH https://www.uta.edu/maps/?building=SH) Room 121
Date: Friday, April 13
Time: 1:15pm – 2:15pm

 

Abstract: A simulation model must be validated, i.e. demonstrated to accurately represent the system it studies, for its results to be reliable. However, simulation validation is a challenging task.  One of the primary sources of this challenge is the absence of an oracle to test its validity, as without an oracle one cannot determine if the result of a program is correct. This oracle problem has long been studied in software engineering. Metamorphic Testing has been found to be an effective technique to test software without an oracle by creating pairs of test cases that act as pseudo-oracles. We provide guidelines on applying a modified version of metamorphic testing to increase confidence in the validity of simulation models. In this technique, pseudo-oracles are developed based on metamorphic relations between parameters and behaviors within an executable simulation model. These relations represent an understood property of the system being studied, which can be used to check the validity of the simulation without knowing the correct answer. In this talk we will explain metamorphic testing and how it applies to simulation model validation, including a demonstration of its effectiveness via a case study on a gossip propagation model.

 

Biographical Sketch: Dr. Megan Olsen is an Associate Professor of Computer Science at Loyola University Maryland. She earned her M.S. (2009) and Ph.D. (2011) in computer science from University of Massachusetts Amherst, and her B.S. in computer science from Virginia Tech (2005). Dr. Olsen’s research currently focuses on improving simulation approaches and validation. Recent work includes quantifying the level of validation achieved on a simulation model, guidelines for using metamorphic testing for simulation validation, and utilizing reinforcement learning within agent-based predator-prey models. Recent work has been published in Summer Sim, Winter Sim, Spring Sim, and the International Conference on Computational Science.

 

IMSE is hosting a panel with Jaime Cantu, Kelsey Medeiros, and Janice Tolk for the Seminar Monday April 9 at 1:15pm in Room 105 of Nedderman Hall (NH). The title, summary, and biographical sketches of the panelists are below.

Title: Panel on Decision Making Under Uncertainty
Panelists: Dr. Jaime Cantu, Dr. Kelsey Medeiros, and Dr. Janice Tolk
Location: Nedderman Hall (NH) Room 105
Date: Monday, April 9
Time: 1:15pm – 2:15pm

Panel Summary: Join us for panel discussion on the 5 Hallmarks of High Reliability Organizations, importance of culture, and High Reliability Systems. Dr. Jaime Cantu, Assistant Professor of Industrial, Manufacturing, and System Engineering. Dr. Kelsey Medeiros, Assistant Professor of Psychology.  Her research focuses on complex problem solving in organizations, and she has worked with several national and international organizations on HR-related issues including Hogan Assessment Systems and NBC Universal. Dr. Janice Tolk, Windswept Plains Consulting and Adjunct Assistant Professor of Industrial and Systems Engineering at the University of Tennessee.  Windswept helps companies implement HRO structures into their organizations.

 
Dr. Kelsey Medeiros, Ph.D., is an Assistant Professor of Industrial and Organizational (I-O) Psychology at the University of Texas at Arlington. She earned her PhD in I-O psychology with a minor in quantitative psychology from the University of Oklahoma (OU) in May 2016. She also holds a Master’s degree in I-O psychology from OU and a Bachelor’s degree in psychology from Penn State University. Kelsey has published over 25 articles and book chapters on creativity, leadership, and organizational ethics.

 

Dr. Janice N. Tolk, Ph.D., is an Adjunct Assistant Professor in the Industrial and Systems Engineering Department at the University of Tennessee Space Institute and the Managing Partner of Windswept Plains Consulting, LLC.  She is on the Board of Directors of High Reliability Summits, LLC. She consults with a variety of industries on High Reliability Organization (HRO) theory and practice.  She retired from the Pantex Plant in Amarillo, Texas where she served in a variety of management and leadership positions and in multiple organizations, thus gaining a wide range of experience in facility engineering and construction; maintenance management; safeguards and security; high explosives manufacturing, research and development; and special nuclear materials development and testing.

 

Dr. Jaime Cantu, Ph.D. is an Assistant Professor in Industrial, Manufacturing, and Systems Engineering Department at the University of Texas at Arlington. He received his Ph.D. in Systems & Engineering Management from Texas Tech University. Jaime’s Postdoctoral work was funded by Department of Energy to work with the CNS Pantex plant on using system dynamics in High Reliability Organizations. His research incorporates economic decision analysis, organizational performance measurements, and system modeling; so that engineers, technical managers, and researchers will have better decision analysis tools.

-Posted by Jay Rosenberger

Dr. Yifei Lou from the University of Texas Dallas will present at the Seminar Monday March 26 at 1:15pm in Room 105 of Nedderman Hall (NH). Dr. Lou’s presentation title, abstract, and biographical sketch are below.

 

Title: Nonconvex Approaches in Data Science

Author: Yifei Lou

Location: Nedderman Hall (NH) Room 105

Date: Monday, March 26

Time: 1:15pm – 2:15pm

 

Abstract: Although “big data” is ubiquitous in data science, one often faces challenges of “small data,” as the amount of data that can be taken or transmitted is limited by technical or economic constraints. To retrieve useful information from the insufficient amount of data, additional assumptions on the signal of interest are required, e.g. sparsity (having only a few non-zero elements). Conventional methods favor incoherent systems, in which any two measurements are as little correlated as possible. In reality, however, many problems are coherent.  I will present a nonconvex approach that works particularly well in the coherent regime. I will address computational aspects in the nonconvex optimization. Various numerical experiments have demonstrated advantages of the proposed method over the state-of-the-art. Applications, ranging from super-resolution to low-rank approximation, will be discussed.

Biographical sketch: Yifei Lou has been an Assistant Professor in the Mathematical Sciences Department, University of Texas Dallas, since 2014. She received her Ph.D. in Applied Math from the University of California Los Angeles (UCLA) in 2010. After graduation, she was  a postdoctoral fellow at the School of Electrical and Computer Engineering Georgia Institute of Technology, followed by another postdoc training  at the Department of Mathematics, University of California Irvine from 2012-2014. Her research interests include compressive sensing and its applications, image analysis (medical imaging, hyperspectral, imaging through turbulence), and (nonconvex) optimization algorithms.

Dr. Li Wang from UT Arlington’s Math Department will present at the Seminar Monday February 26 at 1:15pm in Room 105 of Nedderman Hall.  Dr. Wang’s presentation title, abstract, and biographical sketch are below.

Title: Graph Structure Learning based on Reversed Graph Embedding
Author: Li Wang
Location: Nedderman Hall (NH) Room 105
Date: Monday, February 26
Time: 1:15pm – 2:15pm

Abstract:  Many scientific datasets are of high dimension, and the analysis usually requires retaining the most important structures of data. Many existing methods work only for data with structures that are mathematically formulated by curves, which is quite restrictive for real applications. To get more general graph structures, we develop a novel graph structure learning framework that captures the local information of the underlying graph structure based on reversed graph embedding. A new learning algorithm is developed that learns a set of principal points and a graph structure from data, simultaneously. Experimental results on various synthetic and real world datasets show that the proposed method can uncover the underlying structure correctly.

Biographical Sketch:  Dr. Li Wang is currently an assistant professor with Department of Mathematics, University of Texas at Arlington, Texas, USA. She worked as a research assistant professor with Department of Mathematics, Statistics, and Computer Science at University of Illinois at Chicago, Chicago, USA from 2015 to 2017. She worked as the Postdoctoral Fellow at University of Victoria, BC, Canada in 2015 and Brown University, USA, in 2014. She received her Ph.D. degree in Department of Mathematics at University of California, San Diego, USA, in 2014. She received the master degree in Computational Mathematics from Xi’an Jiaotong University, Shaanxi, China, in 2009 and the Bachelor degree in Information and Computing Science from China University of Mining and Technology, Jiangsu, China in 2006. Her research interests include data science, polynomial optimization and machine learning.

 

-Posted by Jay Rosenberger

Senior Vice President, Dr. Andrew Liou, from Foxconn will present at the DFW INFORMS Seminar on Thursday, February 15th, at 6:00 pm in Room 100, Nedderman Hall (NH).  Dr. Andrew Liou’s presentation title and biographical sketch are below.

DFW INFORMS will offer refreshments (pizza, soft drink & water). The room is open from 5:30 pm. All students and faculty are encouraged to attend.

Title: Transformation to an Industrial Internet Operation: A Foxconn Story
Author: Dr. Andrew Liou
Location: Nedderman Hall (NH) Room 100 (https://www.uta.edu/maps/?building=NH)
Date & Time: Thursday, February 15 @ 6:00 pm

Biographical Sketch:
Andrew Liou, Ph.D, P.E.
1979, Tunghai University, BS IE
1981-1986, Auburn University, MS IE and Ph.D
1986-2002, Cleveland State University, Assistant, Associate, Professor and Chairman of IE Department
Assistant Director, Advanced Manufacturing Center
Director, Productivity and Quality Center
1994-1996 (Sabbatical leave), Director of Quality, Black and Decker
2002-2008, CEO, Uniworld Consulting for more than 30 international companies
2008-2013, Vice President, Foxconn Industrial Engineering Academy
2013-current, Interim General Manager and Senior Vice President, Foxconn iPhone business group, for daily operations, automation and intelligent manufacturing

 

-Posted by Jay Rosenberger

Dr. Eli Olinick from Southern Methodist University will present at the Seminar Monday February 12 at 1:15pm in Room 105 of Nedderman Hall. Dr. Olinick’s presentation title, abstract, and biographical sketch are below.

Title: Compact Multicommodity Flow Formulation with Applications to Vehicle Routing, Concurrent Flow, and Social Network Analysis
Author: Eli Olinick
Location: Nedderman Hall (NH) Room 105
Date: Monday, February 12
Time: 1:15pm – 2:15pm

Abstract: We present a compact mixed integer program (MIP) for the vehicle routing problem with optional pickup and delivery in which a freight carrier seeks to generate revenue from an empty delivery vehicle’s backhaul trip from its last scheduled delivery to its depot by allowing it to deviate from the least expensive (or fastest) route to accept delivery requests between intermediate points as allowed by its capacity and required return time. The MIP is inspired by a novel representation of multicommodity flow, the triples formulation, that significantly reduces the size of the constraint matrix and the linear programming upper bound on optimal profit compared to a formulation based on the classical node-arc representation. This in turn leads to faster solution times when using a state-of-the-art MIP solver. In an empirical study of both formulations, problem instances with ten potential pickup/dropoff locations (including the vehicle’s current location and its depot) were solved three to twelve times faster with our formulation while instances with 20 locations were solved 90 to 2,000 times faster. The largest instances in the study had 40 locations and 1,482 delivery requests; these instances could not be solved with the node-arc-based formulation, but were solved within an average of 90 minutes of CPU time using our compact formulation. We present a similar study applying the triples formulation to the notoriously difficulty maximum concurrent flow problem (MCFP), an optimization problem concerning the equitable use of resources in congested networks. In this study we found that the CPLEX linear programming solvers solved 89% of the MCFP instances in our computational study faster with the triples formulation than it did with the other two formulations, typically two to four times faster than the node-edge formulation when available computer memory allowed both to be solved. The triples formulation appears to be particularly well suited for problem instances defined on dense graphs; on average, CPLEX solved these types of problems in our study 10 times faster with the triples formulation. Finally, we propose a new clustering algorithm based on hierarchical maximum concurrent flow (HMCF) and its duality relation to the sequence of sparsest cuts, and discuss theoretical properties which make it more accurate and often more robust than many popular algorithms in the literature. We present a new measure of node centrality, determined from the HMCF, called flowthrough centrality, and empirical results comparing its improved stability relative to currently used centrality measurements employed in social network analysis when knowledge of the network topology is incomplete or in transition.

Biographical Sketch: Eli V. Olinick is an Associate Professor in the Department of Engineering Management, Information, and Systems at SMU’s Bobby B. Lyle School of Engineering. He completed his B.S. in Applied Mathematics (1989) at Brown University and earned his M.S. (1994) and Ph.D. (1999) in Industrial Engineering and Operations Research at the University of California at Berkeley. Professor Olinick’s research interests include applied optimization and network design problems. His research activities have been funded by multiple government and industry grants totaling over $1.6M, and he has published over 20 refereed research articles in prominent journals in operations research and network engineering. He is a past president of the INFORMS Technical Section on Telecommunications, the Dallas/Fort Worth INFORMS chapter, and an Associate Editor of Networks and Spatial Economics.

 

-Posted by Jay Rosenberger