HomeAgendaPeopleProjectsPublicationsLab ResourcesClassesIEM Home

Research Thrusts

Theoretical Foundations of Sensor-based Modeling (presentation file)

1. Suboptimal multiscale representation and denoising of contaminated chaotic signals

2. Sensor-based reconstruction of n-SDE formal models

3. Recurrence based piecewise eigen representation

Applications to Quality Monitoring in Machining and Other Manufacturing Machine Operations

Sponsors: NSF, Zumberge Fellowship, SC2 Foundation, HP, National Instruments, ONR-MURI, Powell Foundation, OSU Startup Grant

1. Experimental characterization of machining process dynamics

2. Sensor-based modeling and control of machining dynamics and chatter

3. On-line continuous tool wear estimation using fractal analysis

4. Nonlinear analysis and microdynamic modeling of acoustic emission

5. Model-based tampering for improved performance of aerospace precision grinding processes

 

RFID and RF Sensor network applications

Sponsors: ONR, NSF, OK-DoT

1. Damage monitoring of connected plate structures

2. Nonlinear Intrusion Detection in TCP/IP networks

3. Container Integrity monitoring using RFID Sensors

 

Applications to Large Distributed Systems

Adaptive Interactive Modeling Systems Technology (with S.C-Y. Lu)) 

Sponsors: USC, Ford

1. Backward mapping methodology for design synthesis

2. Ontological extension of axiomatic design

 

Control of Distributed Transportation Systems (with M. Dessouky)

Sponsors: METRANS, NSF

1. Coordination of dynamic resource allocation in trucking operations

2. Multiagent negotiations for transit system control

 

Funded Research Activity

Current Research Projects

1.      SST: Collaborative Project: Self-sustainable sensor networks for infrastructural integrity monitoring

PI (with S.R.T. Kumara-Penn State, S-G. Kim-MIT and X. Zhang-Berkeley),

NSF, $774,000 (OSU allocation $198,000), 2004-2007

This collaborative project brings together the complementary expertise of the investigators in piezoelectric power generation (MIT), miniature high efficiency RF units (Berkeley), wireless signal analysis (OSU) and survivability of large sensor networks (Penn State). The two main objectives of the project are to (a) design and fabricate self-supporting miniature wireless sensors (currently for vibration and temperature measurement) capable of harvesting energy from the host-environment and therefore do not need batteries, and (b) derive principles to harness information from these sensors for quality and integrity monitoring of large scale infrastructure systems. These systems include underground utility pipeline networks. Eight journal papers and 3 conferences papers have been accepted or published, and 10 manuscripts have been submitted for review based on the research conducted under this grant. This project has been the basis for 2 MS and 1 PhD theses.

 

2.      Nonlinear Continuous Flow Modeling for Real-Time Performance Prediction of Automotive Assembly Operations

PI

GM, $76,500, 2005-07

Manufacturing enterprises are investing in a variety of sensors and IT infrastructure to increase plant floor systems visibility. This offers an unprecedented opportu­nity to track performance of a manufacturing system from a dynamic, as opposed to a static sense. Conventional static models are inadequate for predicting performance variables in real-time from these large data sources. Dynamic models are necessary to compactly capture information from vast data sources for real-time performance prediction.  Among the relevant approaches, flow modeling offers an effective balance between accuracy and speed. This approach treats the part movement in a manufacturing system as a fluid flow and models the dynam­ics in the form of differential equations. However the presence of finite capacity buffers and machine breakdowns make the models discontinuous, thereby rendering the simulations slow and less accurate. We have investigated the use of hybrid continuous-discrete modeling approach. The results show that the model speeds are comparable to those of commonly used discrete event simulations, and the model estimates are with 10% of actual line observations. We are currently in the process of further enhancing the model speed through the use of sigmoidal function theory and degradation dynamics.

 

3.      RF Sensor Application for Container Integrity Monitoring

Co-PI (with V. Sarangan)

OK-DoT, $60,000, 2005-07 (OSU-IEM allocation $14,500)

Global supply chain operations use hundreds of thousands of container trucks to transport valuable goods within and across continents. The vibration patterns of a container and its contents can reveal significant information related to its integrity during transport, handling and storage. The patterns of container vibrations are sensitive to the following four major factors that define the operating condition of a container:  terrain type, speed of the vehicle, weight of the container and dimensions of the container. The primary purpose of this project is to establish quantitative relationships between the vibration patterns and the operating conditions of a moving container truck and the stability of contents therein through a series of experiments involving the use of a model container truck and a wireless (T-mote) sensor capable of discerning vibrations at 200Hz sampling rates. The idea is to classify the operating conditions by analyzing the complex dynamics underlying vibration signals. Using nonlinear analysis, we find that the the Lyapunov exponents are in the range of 0.01-0.02 for dynamics underlying signals from Stage 1 and 0.005 for those from Stage 2, implying that the dynamics may be nonlinear and chaotic. The statistical and nonlinear dynamic features together are successfully mapped using a neural network to classify between the different operating conditions. The neural networks were able to accurately identify the operating conditions from the vibration sensor features about 90% of the times. In real life, the research results can be applied to accurately capture the environmental condition in which the vehicle is moving and thus proactively address possible serious integrity losses. One manuscript has been submitted for review, and the student team that works on this project has won multiple awards (in the OSU-ECE Design Day and OSU Research Week) for their efforts. This research has been the basis for one ongoing PhD thesis and one MS thesis.

 

4.      Technological and Economic Analysis of RFID and RF Sensors for Tinker AFB operations

PI

CASI-Tinker AFB, $50,000, 2006-07.

The project aims to survey and evaluate alternative Automatic Identification Technologies (AITs) that complement and/or integrate with the current WiFi systems for improving the real-time tracking of assets in Tinker AFB ramp operations. We are investigating the technological and economic viabilities of passive RFID and sensor-integrated wireless sensor networks (e.g., Motes) along with other alternative AITs. This project will lead to the development of design and operational guidelines of a modified AIT system that fuses information from multiple AITs (including WiFi) for effective asset tracking.

 

5.      Heterogeneous wireless sensor based modeling of chemical mechanical planarization process

Co-PI (with R. Komanduri and Z. Hou)

NSF, $394,000, 2007-10.

The semiconductor industry is rapidly moving towards ultra-large scale integration (ULSI) of microelectronic circuits. Planar surfaces are necessary to enhance wafer yield and reduce stack heights. Chemical mechanical planarization (CMP) has become the process of choice for this application. Material removal rate (MRR) and within wafer nonuniformity (WIWNU), among other performance variables, should be optimized for improved productivity and reduced costs. Interestingly, PIs’ recent studies showed that the dominant process parameters for determining MRR are not so significant for WIWNU and vice versa. Also, the process-machine interactions play an important role with the CMP process dynamics likely to be nonlinear and stochastic. Research to-date has not addressed the physical bases for such behaviors. This is a critical scientific and technological barrier for effective quality monitoring and control of CMP.  This recently approved project will yield deeper insight into various chemo-mechanical interactions in CMP and will integrate a heterogeneous sensor network into CMP operations to improve productivity and IC quality.

 

6.       Experimentation test-bed for evaluation of RFID and RFID sensing technologies

PI

CELDi (NSF/IUCRC), $30,000, 2005

This project was aimed at creating a laboratory infrastructure to conduct research in RFID systems, evaluate and benchmark performance of various RFID and high throughput RF sensor systems. A laboratory to conduct research in Sensor Networks and Complex Systems Monitoring (COMMSENS) has been established in Fall 2004. It now houses various components of RFID systems, sensors, data acquisition systems procured from multiple commercial vendors as well as a new architecture for high throughput wireless sensing of large scale infrastructure. This project has also led to an approach for statistical design of RFID system, a statistical model for predicting performance of RFID systems in various environments as well as a method to overcome current technological barriers in reading RFID sensors in highly metallic environments. This research has been the basis for one MS thesis and two patent disclosures.

 

7.       RFID business case study

PI

FAA, $42,800, 2005-06

This study had focused on evaluating the technological and economic feasibility of using RFID and 2-D barcodes for identification and tracking of assets in FAA logistics center operations. A spreadsheet framework to perform the economic analysis was developed. One of the research assistants involved in this project was subsequently hired as a summer intern to follow-up on the research results and to customize the framework to FAA operations. A Phase 2 of this project is currently being considered.

 

 

Prior Research Funding 

1. Co-PI (with B. Khoshnevis) for "Free-form fabrication of advanced ceramic components using contour

    crafting," Office of Naval Research (Sub-contracted from Rutgers), $105,000, 2000-02

2. PI for “Dynamic modeling of Contour Crafting,” Powell Foundation Fellowship, USC, $50,000, 2001-

    2002

3. Co-PI (with M. Dessouky and R. Leachman) for “Real-time dispatching and routing in urban rail

    networks,” National Science Foundation (approved for funding), $149,800, 2002-2004

4. Co-PI (with S.C. Lu) for “Adaptive Interactive Modeling System,” Ford Motor Company, $10,000, 1997-

    98

5. PI for “Implementation of nonlinear real-time chatter control in machining,” Zumberge Grant, USC,

    $24,977, 1998-1999

6. PI for “Academic Grants Program: Development of instrumentation for the Manufacturing and Controls

    Lab,” National Instruments, received $12,000 worth of instrumentation and software, 2000

7. PI for “Virtual machine tool laboratory to meet local manufacturing needs,” SC2 Grant, USC, $6,000,

    1999-00

8. PI for “HP Foundation Program: Development of Computer Network for Manufacturing and Controls

    Lab,” Received $30,000 worth of computing equipment through HP Foundation Grant, 1999

9. Co-PI (with S.C. Lu) for "USA-China Workshop on Advanced Machine Tool Research," NSF, $60,500,

    1998-00

10.PI for “Dynamic coordination of resource allocation in trucking operations," METRANS Center, $20,000,

     2000

11.PI (with M.M. Dessouky) for "Multiagent coordination of transit operations," METRANS Center,     

     $47,000, 2000-01

 

  Contact Us                                                                                                   Oklahoma State University