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Displaying 51 - 75 of 272

Summary of the Symposium on Data Analytics for Advanced Manufacturing

April 13, 2017
Author(s)
Anantha Narayanan Narayanan, Ronay Ak, Yung-Tsun Lee, Rumi Ghosh, Sudarsan Rachuri
The Symposium on Data Analytics for Advanced Manufacturing was held in conjunction with the 2016 IEEE International Conference on Big Data in Washington D.C. on December 6-7, 2016. The Symposium's goal was to address manufacturing industries' issues, needs

GAUSSIAN PROCESS REGRESSION (GPR) REPRESENTATION IN PREDICTIVE MODEL MARKUP LANGUAGE (PMML)

March 29, 2017
Author(s)
Jinkyoo Park, David Lechevalier, Ronay Ak, Max K. Ferguson, Kincho H. Law, Yung-Tsun Lee, Sudarsan Rachuri
This paper describes a Predictive Model Markup Language (PMML) representation of Gaussian Process Regression (GPR) models. PMML is an XML-based standard language used to represent data mining and predictive analytic models, as well as pre- and post

A Classification Scheme for Smart Manufacturing Systems Performance Metrics

February 28, 2017
Author(s)
Yung-Tsun T. Lee, Senthilkumaran Kumaraguru, Sanjay jain, Qais Hatim, Stefanie Robinson, Moneer M. Helu, Sudarsan Rachuri, Soundar Kumara, Christopher Saldana, David Dornfeld
This paper proposes a classification framework for performance metrics for smart manufacturing systems. The discussion focuses on agility, asset utilization, and sustainability, and we discuss classification themes for each of these areas that lead to the

Model-based engineering for the integration of manufacturing systems with advanced analytics

July 10, 2016
Author(s)
David Lechevalier, Anantha Narayanan Narayanan, Sudarsan Rachuri, Sebti Foufou, Yung-Tsun Lee
To employ data analytics effectively and efficiently on manufacturing systems, engineers and data scientists need to collaborate closely to bring their domain knowledge together. In this paper, we introduce a domain-specific modeling approach to integrate

A Neural Network Meta-Model and its Application for Manufacturing

October 29, 2015
Author(s)
David J. Lechevalier, Ronay Ak, Steven Hudak, Yung-Tsun T. Lee, Sebti Foufou
Manufacturing generates a vast amount of data both from operations and simulation. Extracting appropriate information from this data can provide insights to increase a manufacturer's competitive advantage through improved sustainability, productivity, and

A "Smart Component" Data Model in PLM

October 28, 2015
Author(s)
Yunpeng Li, Utpal Roy, Seungjun Shin, Yung-Tsun Lee
Today's physical products are becoming smarter not only because of their increasingly complex functionalities, but also for their superior capabilities of adaptation to dynamic working environment based on embedded software and real-time information

INTEGRATING RULE-BASED SYSTEMS AND DATA ANALYTICS TOOLS USING OPEN STANDARD PMML

August 3, 2015
Author(s)
Yunpeng Li, Utpal Roy, Yung-Tsun Lee, Sudarsan Rachuri
Rule-based expert systems such as CLIPS (C Language Integrated Production System) are 1) based on inductive (if-then) rules to elicit domain knowledge and 2) designed to reason new knowledge based on existing knowledge and given inputs. Recently, data

SIMULATION-BASED DESIGN CONCEPT EVALUATION FOR AMBULANCE PATIENT COMPARTMENTS

July 14, 2015
Author(s)
Deogratias Kibira, Yung-Tsun T. Lee, Jennifer L. Marshall, Allison Barnard Feeney, Larry Avery, Allie Jacobs
To address the inadequacy of existing standards regarding interior layout design, the Department of Homeland Security (DHS) Science and Technology Directorate, the National Institute of Standards and Technology (NIST), the National Institute for

Building Analytical Support for Homeland Security

February 2, 2015
Author(s)
Sanjay Jain, Charles W. Hutchings, Yung-Tsun Lee
This chapter discusses modeling and simulation as a significant means for providing analytical support for homeland security problem solving and decision making that involves what can be considered a complex and dynamic system of systems - the current
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