Informs 2015

311 / 552

INFORMS Philadelphia – 2015
309
4 - Wake Effect Characterization in Wind Power Systems
Mingdi You, PhD Candidate, University of Michigan, 1205 Beal
Avenue, IOE 1773, Ann Arbor, MI, 48109, United States of
America, Eunshin Byon,
Jionghua (judy) Jin
The rapid growth of wind power underscores the need to understand the
dynamic characteristics of wind turbine operations. Wind turbines in a wind farm
exhibit heterogeneous power generations due to the wake effect. This study
provides a computational framework for characterizing the wake effects via a
data-driven approach by extending the Gaussian Markov Random field
framework. The computational results show that this approach improves the
prediction capability over other methods.
TB74
74-Room 204A, CC
System and Process Informatics in Additive
Manufacturing (II)
Sponsor: Quality, Statistics and Reliability
Sponsored Session
Chair: Linkan Bian, Assistant Professor, Mississippi State University,
260 McCain Building, Mississippi State, Starkville, MS, 39762,
United States of America,
1 - Accelerated Bi-objective Process Optimization for Laser-based
Additive Manufacturing (LBAM)
Amir M. Aboutaleb, Mississippi State University, 260 McCain
Building, Mississippi State, MS, 39762, United States of America,
Alaa Elwany, Scott M. Thompson,
Linkan Bian, Nima Shamsaei, Mohammad Marufuzzaman
Material properties of fabricated parts via LBAM have demonstrated to either be
correlated, interdependent or inconsistent with process parameters. In many cases
the goal is optimize the LBAM process considering several material properties of
interest as a multi-objective problem. We propose a novel methodology for
leveraging current experimental data to guide and accelerate the bi-objective
Design-of-Experiment process for Pareto Front approximation by the minimum
number of experiments.
2 - Spatial Gaussian Process Models for Porosity Prediction in
Selective Laser Melting
Alaa Elwany, Texas A&M University, 3131 TAMU, College
Station, TX, United States of America, ,
Gustavo Tapia, Huiyan Sang
We develop a Gaussian process-based predictive model for predicting the porosity
in metallic parts produced using Selective Laser Melting (SLM – a laser-based AM
process). A case study is conducted to validate this predictive framework through
predicting the porosity of 17-4 PH stainless steel manufacturing on a commercial
SLM system.
3 - Automatic Feature Priority Assignment for Automated
Production Processes
Ola Harryson, Professor, North Carolina State University,
400 Daniels Hall, 111 Lampe Dr, Raleigh, NC, 27606,
United States of America, Richard Wysk,
Sidharth Chaturvedi, Harshad Srinivasan
This work describes a system for the prioritization of features at the near-net
production stage in order to minimize the effort required for any subsequent
finish machining. Heuristics are used to assign weights to features based on value
and produceability. A graph of feature relationships is is used to modify the
assigned weights based on design and tolerancing principles. An implementation
of this system for use with the AIMS hybrid process is described and
demonstrated with sample parts.
4 - Additive Manufacturing of Biomedical Implants:
Feasibility Assessment via Supply-chain Cost Analysis
Adindu Emelogu, Mississippi State University, 260 McCain
Building, Mississippi State, MS, 39762, United States of America,
Linkan Bian,
Mohammad Marufuzzaman
We investigate the economic feasibility of fabricating biomedical implants close to
hospitals by additive manufacturing (AM) instead of traditional manufacturers
(TM) located far from point-of-use. We develop a stochastic mixed-integer
programming model which helps to decide the location of AM centers and
volume of product flows that minimize supply chain cost. A case study of
hospitals in Mississippi, USA recommends AM only when the production cost of
AM to TM ratio (ATR) reduces to 3 or less.
TB75
75-Room 204B, CC
IBM Research Best Student Paper Award II
Sponsor: Service Science
Sponsored Session
Chair: Ming-Hui Huang, National Taiwan University, Taiwan - ROC,
1 - Best Student Paper Competitive Presentation
Ming-Hui Huang, National Taiwan University, Taiwan - ROC,
Finalists of the IBM Research Best Student Paper Award present their research
findings in front of a panel of judges. The judging panel will decide the order of
winners, which will be announced during the business meeting of the Service
Science Section at the Annual Conference.
2 - Online Network Revenue Management using Thompson
Sampling
He Wang, MIT, Cambridge, MA, United States of America,
Kris Johnson Ferreira, David Simchi-Levi
Mobile apps have great potential to provide promising services to improve
consumers’ engagement and behaviors. Focusing on healthy eating, this study
shows that an image-based professional support greatly improves consumer
engagement and eating behaviors, while social media and a heuristic approach of
self-management might have negative effects in some occasions. Mobile apps
have great potential to provide promising services to improve consumers’
engagement and behaviors. Focusing on healthy eating, this study shows that an
image-based professional support greatly improves consumer engagement and
eating behaviors, while social media and a heuristic approach of self-management
might have negative effects in some occasions.
3 - How Environmental Certification Can Affect Performance in the
Service Industry: Evidence from the Adoption of LEED Standards
in the U.S. Hotel Industry
Matthew Walsman,Cornell University, Ithaca, NY United States
of America, , Suresh Muthulingam,
Rohit Verma
This study uses a mixed method approach (difference-in-differences and multi-
level modeling) to measure the impact of environmental certification (i.e. LEED
certification) on financial performance in the US hospitality industry. We find
that certification does contribute to higher revenue for the certifying hotel,
relative to its competitors.
4 - Optimal Coinsurance Rates for a Heterogeneous Population
under Inequality and Resource Constraints
Greggory J. Schell, Center for Naval Analyses, 3003 Washington
Blvd, Arlington, VA, United States of America, ,
Rodney A. Hayward, Mariel Lavieri, Jeremy B. Sussman
We derive prescription coinsurance rates which maximize the health of a hetero-
geneous patient population. We analyze the problem as a bilevel optimization
model where the lower level is a Markov decision process and the upper level is
a resource allocation problem with constraints on expenditures and coinsurance
inequality.
5 - Managing Rentals with Usage-Based Loss
Vincent Slaugh, Penn State University, Univeristy Park, PA,
United States of America, Bahar Biller,
Sridhar Tayur
We study the operation of a discrete-time stochastic rental system over a single
selling season in which rental units may be purchased or damaged by customers.
We provide structural results related to the expected profit function and the
optimal policy for allocating rental units to meet customer demand. In an
industrial use case motivated by a high-fashion dress rental business, we show
significant value to accounting for inventory loss and using the optimal inventory
recirculation rule.
TB75