2016 INFORMS Annual Meeting Program

SA67

INFORMS Nashville – 2016

SA68 Mockingbird 4- Omni

2 - Online Adaptive Sampling And Estimation For Clustered Anomaly Detection Hao Yan, Georgia Institute of Technology, yanhaopku@gmail.com In point-based sampling and sensing system, adaptive exploration in complex sampling space can dramatically reduce the sampling time. Most of the existing techniques focus on reducing the overall fitting error for the entire sampling space. However, in many application, such as anomaly detection, only sparse clustered anomalous regions are important. In this paper we develop two adaptive sampling strategies together with estimation methods to recover the clustered region and discuss their properties to balance the space filling property and focus sampling near the anomalous region. Finally, the proposed methodology is validated by simulation study and real datasets in Guided Wave Experiment. 3 - A Penalized (log)-Location-Scale Tensor Regression Model For Residual Useful Lifetime Prediction Xiaolei Fang, Georgia Institute of Technology, xfang33@gatech.edu Kamran Paynabar, Nagi Gebraeel We develop a penalized prognostic model whose covariates are tensor-based degradation signals. To address the ultrahigh dimensionality challenge, the coefficient tensor is decomposed as a product of some basis matrices (CP decomposition) or a product of a core tensor and some factor matrices (Tucker decomposition) . Instead of estimating the coefficient tensor itself, we estimate these basis matrices or core tensor and factor matrices, which have far much smaller dimensionalities. Two algorithms with global convergence property are developed for model estimation. The effectiveness of our models is validated using a simulation study and an infrared image-based degradation signal dataset. 4 - Multivariate Profile Monitoring Based On Sparse Multichannel Functional Principle Component Analysis Chen Zhang, National University of Singapore, zhangchen@u.nus.edu, Hao Yan, Jianjun Shi This paper presents a new monitoring framework for multi-channel profile data. In particular, we first propose a sparse multichannel functional principle component analysis (SMFPCA) to model multiple profiles, SMFPCA on one hand can capture the auto-correlation structure of profile data well, and on the other can allow flexible cross-correlations of multiple or even high-dimensional profiles with different features. Then using SMFPCA scores, we further propose a monitoring scheme that can detect sparse out-of-control changes efficiently. Numerical studies together with a real example in the semiconductor manufacturing demonstrate the application and effectiveness of our methods. SA67 Mockingbird 3- Omni Journal of Quality Technology Invited Session Sponsored: Quality, Statistics and Reliability Sponsored Session Chair: Fugee Tsung, HKUST, Hong Kong, season@ust.hk 1 - Bayesian Life Test Planning For Log-Location-Scale Family Of Distributions Yili Hong, Virginia Polytechnic Institute, yilihong@vt.edu This paper describes Bayesian methods for life test planning with censored data from a log-location-scale distribution. We use a Bayesian criterion based on the estimation precision of a distribution quantile. A large-sample normal approximation gives a simplified, easy-to-interpret, yet valid approach to this planning problem, where in general no closed-form solutions are available. We present numerical investigations using the Weibull distribution with type II censoring. We also assess the effects of prior distribution. A simulation approach of the same Bayesian problem is also presented. 2 - Multivariate Exponentially Weighted Moving-average Chart For Monitoring Poisson Observations Nan Chen, National University of Singapore, isecn@nus.edu.sg In this talk, we develop a feasible multivariate monitoring procedure based on the general multivariate exponentially weighted moving average (MEWMA) to monitor the multivariate count data. The multivariate count data is modeled using Poisson log-normal distribution to characterize their interrelations. We systematically investigate the effects of different charting parameters and propose an optimization procedure to identify the optimal charting parameters. To further improve the efficiency, we integrate the variable sampling intervals (VSI) in the monitoring scheme. We use simulation studies and an example to elicit the application of the proposed scheme.

QSR Refereed Research Session Sponsored: Quality, Statistics and Reliability Sponsored Session Chair: Hui Yang, Pennsylvania State University, University Park, PA, United States, huy25@psu.edu 1 - An Optimum Design Of Laser-based Additive Manufacturing Experiments by Leveraging Analogous Prior Data Amir Massoud Aboutaleb, Mississippi State University, 139 A, Park Circle, Starkville, MS, 39759, United States, aa1869@msstate.edu Linkan Bian Most of Lase-Based Additive Manufacturing studies do not use a systematic approach for optimizing process parameters for desired part properties. Existing design-of-experiment methods require two stages of experiments: a large batch of initial experiments and multiple smaller batches of sequential experiments. Our method directly utilizes experimental data from previous studies to guide the sequential optimization experiments of the current study. 2 - Model Transfer via Equivalent Effects Of Lurking Variables Arman Sabbaghi, Purdue University, West Lafayette, IN, 47907, United States, sabbaghi@purdue.edu Qiang Huang The transfer of a model across different settings of lurking variables is addressed with a novel framework that fuses the Rubin causal model with the effect equivalence concept. A Bayesian methodology for model transfer is developed and applied to transfer deformation models across additive manufacturing environments 3 - Residual Useful Lifetime Prediction Using a Degradation Image Stream Xiaolei Fang, Georgia Institute of Technology, 1546 Woodlake Dr NE, Apt F, Atlanta, GA, 30329, United States, xfang33@gatech.edu, Kamran Paynabar, Nagi Gebraeel This paper proposes a new methodology for RUL prediction of a system using a sequence of degradation images. The methodology integrates tensor linear algebra with traditional location-scale regression widely used in reliability and prognosis. Two optimization algorithms with a global convergence property are developed for model estimation. 4 - Statistical Modeling For Spatio-Temporal Degradation Data Xiao Liu, IBM, 1101 Kitchwan Road, Room 29-252, Yorktown Heights, NY, 10598, United States, liuxiao@us.ibm.com Kyongmin Yeo, Jayant Kalagnanam This paper investigates the modeling of an important class of degradation data, which are collected not only over time but also from a spatial domain. Like many traditional degradation models which rely on stochastic processes, a space-time random field is constructed, through a novel approach, for modeling the spatio- temporal degradation process. 2016 Edelman Finalists Reprise – I Sponsored: CPMS, The Practice Section Sponsored Session Chair: Michael A Trick, Carnegie Mellon University, Pittsburgh, PA, United States, trick@cmu.edu 1 - Operations Research Transforms The Scheduling Of Chilean Soccer Leagues And South American World Cup Qualifiers Andres P Weintraub, Universidad de Chile, Dept De Ingenieria Industrial, Republica 701 Casilla 86-D, Santiago, Chile, aweintra@dii.uchile.cl, Fernando Alarcon, Guillermo Duran, Luis Ramirez, Hugo Munoz, Mario Ramirez, Denis R. Saure, Sebastian Souyris, Rodrigo Wolf-Yadlin, Gonzalo Zamorano, Matias Siebert, Jaime Miranda, Mario Guajardo For the past 12 years, we have applied OR techniques to schedule soccer leagues in Chile. Using integer programming-based methods, it is decided which matches are played in each round, taking into account various objectives. We have scheduled more than 50 tournaments using this approach, resulting in an estimated economic impact of about $59 million. Because of the high portability of these techniques, we have used them successfully to schedule sports leagues in other countries and the South American qualifiers for the 2018 Soccer World Cup. Furthermore, the methods used in this application have been disseminated widely, helping to promote OR as an effective tool for addressing practical problems. SA69 Old Hickory- Omni

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