Informs 2015

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INFORMS Philadelphia – 2015
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74-Room 204A, CC
Reliability II
Contributed Session
Chair: Yin Shu, University of Houston, E206 Engineering Bldg.2,
Houston, TX, 77204, United States of America,
1 - Detecting Entropy Increase in Categorical Data using Maximum
Entropy Distribution
Devashish Das, Research Assistant, University of Wisconsin,
Madis, 124 North Breeze Terrace Apt. E, Madison, WI, 53726,
United States of America, , Shiyu Zhou
In work, we propose a statistical monitoring method to detect the increase of
entropy in categorical data. First, we propose a distribution estimation method to
approximate the probability distribution of the observed categorical data. Then we
use this procedure to estimate the non-parametric, maximum entropy
distribution of an observed data sample and use it for statistical monitoring.
2 - A Conditioned-Based Maintenance Policy for a
Two-Component System
Ameneh Forouzandeh Shahraki, NDSU, 1220, 10th St. N, #101,
Fargo, ND, United States of America,
, Om Yadav
This paper proposes an optimal conditioned-based maintenance policy for a two-
unit deteriorating system with economic dependency. Each unit is monitored by
remaining useful life based-inspection policy and is maintained by corrective,
perfect or imperfect maintenance propose a general maintenance
decision framework to select optimal maintenance actions and to optimize the
grouping of maintenance actions for both components at the same time.
3 - Optimal Decision Making for Systems with
Mulifunctional Components
Yiwen Xu, University of Arizona, RM111, 1127 E. James E.
Rogers Way, Tucson, AZ, United States of America,
, Haitao Liao
We studied systems with multifunctional components. The goal is to make an
optimal decision to maximize the system reliability when a failure occurs.
Properties and numerical studies are included.
4 - Non-Gaussian Ornstein-Uhlenbeck Processes in
Degradation-based Reliability Analysis
Yin Shu, University of Houston, E206 Engineering Bldg.2,
Houston, TX, 77204, United States of America,
, Qianmei Feng, Hao Liu, Edward Kao
We use non-Gaussian Ornstein-Uhlenbeck (OU) processes to model the evolution
of degradation with random jumps. The superiority of our models stems from
their flexibility in modeling stylized features of degradation data series such as
nonlinearity, jumps fluctuation, asymmetry, and heavy tails. Based on Fokker-
Planck equations, we derive explicit results for reliability characteristics
represented by Levy measures. Our models are applicable for analyzing a great
deal of degradation phenomenon.
5 - A Flexible Random Effects Zero-inflated Model for the Study of
Copper Hillocks Growth
Guilin LI, National University of Singapore, #07-17 Blk E1,
Engineering Drive 2, NUS, Singapore, 117576, Singapore,
Szu Hui Ng, Daniel Chua, Royston Tan
An experiment was conducted to measure the metal layer shorts in integrated
circuits caused by copper hillocks to improve the process. Two features of the
collected short counts are identified: excessive zeros and multi-level variations. A
zero-inflated model with flexible random effects was proposed. Statistical
inference procedures are also developed.
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76-Room 204C, CC
Simulation III
Contributed Session
Chair: Ni Xia, School of Management, Huazhong University of Science
and Technology, No.1037, LuoYu Road, Hongshan District, Wuhan,
430074, China,
1 - Exact Efficient Simulation of Stochastic Differential Equations
Apaar Sadhwani, PhD Student, Stanford University, 212L,
Huang Engineering Center, 475 Via Ortega, Stanford, Ca, 94305,
United States of America, Kay Giesecke
We present practical techniques to improve the efficiency of exact simulation of
SDEs. Our proposed acceptance-rejection algorithm is an order of magnitude
faster than existing methods and alleviates the problem of sample paths hitting
unreachable boundaries. To achieve this speedup, we develop a novel method for
simulating hitting time of Brownian Meander to a fixed boundary. Numerical
experiments show that our method performs 10-15x faster than current
methods.
2 - Modeling and Simulation of Automotive Assembly Line
Ahad Ali, Associate Professor, Lawrence Technological University,
21000 West Ten Mile Road, Canton, MI, 48188,
United States of America, Don Reimer
This paper provides methods to create a valid representation of a automotive
assembly using modeling and simulation. Various performance analysis are
presented with statistical validation. The use of the mean steady state 90%
confidence interval was used to measure job per hour for the simulation model to
the current system. DOE and RSM will be used and analyzed.
3 - Promoting Loose Coupling in Simulation Models:
The Service Broker Approach
Sunil Kothari, Researcher, Hewlett-Packard, 1501 Page Mill
Road, Bldg 2U, Palo Alto, CA, 94304, United States of America,
Jun Zeng, Gary Dispoto, Francisco Oblea
Many simulation models are not designed for reuse since the development of
reusable models can take significant investment in time and effort since they
have to be abstracted over all possible use cases. We illustrate the service broker
architecture in the context of industrial printing domain. The service broker
architecture ensures that the resources are loosely coupled to demand. We
highlight two case studies to show our approach.
4 - Maximal On-time Delivery by Soft-pegging in Wafer Fab under
Consideration of Hierarchical Mes
Joon Young Lee, ASU ME, 850 S. McAllister Ave., Tempe, AZ,
85287, United States of America,
Under given hierarchical production planning and control of the MES,
assignment policy (soft-pegging) is considered in order to maximize customer
service level in semiconductor wafer fabrication processes. A wafer fab is modeled
and several input scenarios were experimented to see the effects of the policy.
On-time delivery is maximized in equilibrium state at a diversification point by
proper assignment policy.
5 - Knowledge Evolution in a Dynamic R&d Team from the
Perspective of Task Performance
Ni Xia, Mr., School of Management, Huazhong University of
Science and Technology, No.1037, LuoYu Road, Hongshan
District, Wuhan, 430074, China,
We leverage learning by doing to establish a model of knowledge evolution in a
R&D team,and simulate the effects of strength of team dynamics,task load,task
complexity.Simulation results indicate that dynamic strength has greater damage
to group knowledge than individual not only destroys group
knowledge,but also benefit knowledge also find low task load
benefits knowledge restore but harms knowledge increase, while task complexity
cannot take significant effects.
WC77
77-Room 300, CC
Supply Chain Competition I
Contributed Session
Chair: Ziteng Wang, Department of Industrial and Systems
Engineering, North Carolina State University, 111 Lampe Dr., Daniels
443, Raleigh, NC, 27695, United States of America,
1 - Price and Quantity Competition in Mixed Market with a
Common Retailer
Jian Liu, Dr., Hohai University, Focheng West Road No.8,
Business School, Hohai University, Nanjing, JS, 211100, China,
Sun Li, Huimin Wang
This paper investigates the public supplier and the private supplier’s equilibrium
pricing and quantity decisions in mixed market. Through comparing these
equilibrium results under different game, we find that under Cournot
competition, the whole market is in prison’s dilemma. Under Bertrand
competition, the market equilibrium exists when the product differentiation is
lower, where the public supplier is leader and the private one is follower.
2 - Real-time Demand Forecasting in a 3-stage Fast-fashion Retail
Supply Chain
Sanchoy Das, Professor, New Jersey Institute of Technology,
University Heights, Newark, NJ, 07102, United States of America,
, Jingran Zhang
Demand forecasting is a critical issue as a premise of supply positioning in a fast
fashion supply chain. This paper is focused on a fast fashion retailer that sells a
single product in a finite selling season, with demand uncertainty and stage
switching. Products are sold in three sequential stages, regular, clearance and
outlet. We derive the demand forecast by a modified exponential-weighted
moving average.
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