Service Operations

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Service Operations Logistics Initiatives at
the US National Science Foundation

• Stephen Nash
• Program Director, Operations Research
• U.S. National Science Foundation

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Outline

• National Science Foundation (NSF)
• Design Manufacturing Innovation
• Engineering Decision Systems
• Cyber-Infrastructure
• Accomplishments
• Office of Cyber-Infrastructure
• NSFs Vision for Cyber-Infrastructure
• Cyber-Infrastructure NSF
• Within Engineering
• Within Design Manufacturing Innovation
• Implications for Enterprise Systems
• Funding Initiatives

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NSF Funding in the U.S. Federal Context
NSF is 4 of Overall Federal RD Budget
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Follow the Money, Technology Review, March 2005,
36-45.
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NSF Role in U.S. Academic Research

• 13 of all federal support for basic research
• 80 of budget goes to colleges and universities
• 40 of non-life-science basic research at U.S.
  academic institutions.

Taken from NSFs Strategic Planning Document
http//nsf.gov/publications/pub_summ.jsp?ods_keyn
sf04201
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Throughout NSF

• The mission remains to promote progress of
  science and engineering. . . advance national
  health, prosperity welfare . . . and secure the
  national defense . .
• The vision is enabling the nations future
  through discovery, learning, and innovation...
• The strategic goals are related to
• People diverse, internationally competitive and
  globally engaged SE workforce
• Ideas discovery across the frontiers of Science
  Engineering, connected to learning, innovation
  and service to society
• Tools accessible, state-of-the-art, and shared
  research and education tools
• Organizational Excellence an agile, innovative
  organization . . through leadership in
  state-of-the-art business practices

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Outline

• National Science Foundation
• Design Manufacturing Innovation
• Engineering Decision Systems
• Cyber-Infrastructure
• Accomplishments
• Office of Cyber-Infrastructure
• NSFs Vision for Cyber-Infrastructure
• Cyber-Infrastructure NSF
• Within Engineering
• Within Design Manufacturing Innovation
• Implications for Enterprise Systems
• Funding Initiatives

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National Science Foundation
National Science Board
Office of theInspector General
Director
Staff Offices
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National Science Foundation
National Science Board
Office of theInspector General
Director
Staff Offices
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Directorate for Engineering
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Directorate for Engineering
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Design Manufacturing Innovation (DMI) Mission

• Support of fundamental research that
• defines the frontiers of design, manufacture, and
  service
• interfaces with other disciplines to
• create the enterprises of tomorrow
• assure future competitiveness and productivity of
  todays enterprises
• Integration of education and research that
  develops a diverse, globally-competitive
  engineering workforce

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About Design Manufacturing Innovation (DMI)

• The disciplines we benefit directly
• Primarily industrial engineering/operations
  research and part of mechanical engineering, with
• some materials and chemical engineering, and
  business.
• In FY 04 DMI
• received 1077 proposals and made 210 awards,
• convened 53 panels with more than 420 panelists.
• for competitive research proposals DMIs success
  rate was 16, with a
• mean annual award amount of 111,500 and mean
  duration of 2.8 years

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Division of Design Manufacturing Innovation

• Academic Research Programs
• Manufacturing Processes and Equipment Systems
  Cluster
• Materials Processing Manufacturing (MPM)
• Manufacturing Machines and Equipment (MME)
• Nanomanufacturing (NM)
• Engineering Decision Systems Cluster
• Manufacturing Enterprise Systems (MES)
• Engineering Design (ED)
• Operations Research (OR)
• Service Enterprise System (SES)

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Outline

• National Science Foundation
• Design Manufacturing Innovation
• Engineering Decision Systems
• Cyber-Infrastructure
• Accomplishments
• Office of Cyber-Infrastructure
• NSFs Vision for Cyber-Infrastructure
• Cyber-Infrastructure NSF
• Within Engineering
• Within Design Manufacturing Innovation
• Implications for Enterprise Systems
• Funding Initiatives

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Engineering Design

• Emphasis Areas
• Product platforms, product families, and data
  structures
• Design decision-making
• Topologies and representations for optimization
• Using experiments effectively in design
• Computational methods and tools

• Program Vision
• Principles of Predictive Product Realization
• Design theory
• Fundamentals of product development
• Visualization and representation
• Design for sustainability
• Comprehensive Complex Engineered Systems Design
• Reuse, remanufacturing, recycling
• Optimization over the total life cycle
• Integration of deterministic analysis with
  probabilistic models

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ManufacturingEnterprise Systems

• Vision
• Manufacturing will become
• more global
• more diverse
• more information intensive
• more efficient
• more reactive/unstable
• more environmentally friendly
• Blend of manufacturing and service
• New processes and materials
• Enterprise level competitiveness

• Program Goals
• Design, planning and control of manufacturing
  enterprises, from shop floors to associated
  procurement and distribution supply chains
• Mathematically rigorous modeling and analysis
  tools
• Computational approaches for large scale systems
• Fundamental research on modeling and analysis of
  complex engineered systems

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Service Enterprise Engineering

• Some Research Themes
• Service Objectives
• Cost
• Security
• Equity
• Flexibility
• Robustness
• Models of User Behavior
• Repeated interactions with customers
• Driver behavior
• Patient choice
• Terrorist evasion

• Vision
• To revolutionize the delivery of services
  through the development and application of
  systems engineering.
• Modeling and analysis issues arising in service
  operations.
• Realistic models of agent behaviors.
• Sectors such as health care.
• Hybrid service and manufacturing systems.

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Operations Research

• Vision
• Research on quantitative tools for decision
  making
• Research motivated by applications
• Decision making under uncertainty
• Real-time decision making
• Increased use of cyberinfrastructure

• Some Topics
• Scheduling of large-scale systems
• Global optimization
• Large-scale neighborhood search
• Dependence modeling for stochastic simulations
• Optimization via simulation
• Feasible-point optimization methods
• NEOS
• Financial engineering

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Outline

• National Science Foundation
• Design Manufacturing Innovation
• Engineering Decision Systems
• Cyber-Infrastructure
• Accomplishments
• Office of Cyber-Infrastructure
• NSFs Vision for Cyber-Infrastructure
• Cyber-Infrastructure NSF
• Within Engineering
• Within Design Manufacturing Innovation
• Implications for Enterprise Systems
• Funding Initiatives

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Mapping One Million Atoms of a Complete Virus

• Virtual virus takes 100 days on supercomputer, 35
  years on a desktop
• Visualize the changing atomic structure of a
  virus (satellite tobacco mosaic virus)
• One million atoms interacted with each other
  every femtosecond--or one-millionth-of-a-billionth
  of a second.
• May improve strategies to combat viral infections
  in plants, animals and even humans.
• Led by Klaus Schulten at the University of
  Illinois at Urbana-Champaign
• Press Release 06-049, March 23, 2006

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Modeling Turbulent Fluid Flow

• Vortex models of turbulent air flow
• 1,000,000 vortices
• Solution of nonlinear PDEs
• Team headed by Peter Bernard (University of
  Maryland)

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Outline

• National Science Foundation
• Design Manufacturing Innovation
• Engineering Decision Systems
• Cyber-Infrastructure
• Accomplishments
• Office of Cyber-Infrastructure
• NSFs Vision for Cyber-Infrastructure
• Cyber-Infrastructure NSF
• Within Engineering
• Within Design Manufacturing Innovation
• Implications for Enterprise Systems
• Funding Initiatives

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Office of Cyber-Infrastructure

• Acquisition, development and provision of
  state-of-the-art cyberinfrastructure resources,
  tools and services. 
• Supercomputers
• High-capacity mass-storage systems
• Programming environments
• Visualization tools
• Software libraries and tools
• Data repositories and data management systems
• Networks 
• Training of researchers and educators to use
  cyberinfrastructure to further their research and
  education goals

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OCI Mission

• Provide the science and engineering communities
  with access to world-class CI tools and services
  
• high performance computing
• data, data analysis and visualization
• collaboratories, observatories and virtual
  organizations
• education and workforce development

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Outline

• National Science Foundation
• Design Manufacturing Innovation
• Engineering Decision Systems
• Cyber-Infrastructure
• Accomplishments
• Office of Cyber-Infrastructure
• NSFs Vision for Cyber-Infrastructure
• Cyber-Infrastructure NSF
• Within Engineering
• Within Design Manufacturing Innovation
• Implications for Enterprise Systems
• Funding Initiatives

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Drivers Opportunities

• How does a protein fold?
• What happens to space-time when two black holes
  collide?
• What are the key factors that drive climate
  change?
• Can we create an individualized model of each
  human being for targeted healthcare delivery?

http//www.nsf.gov/od/oci/ci_v5.pdf
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What is Cyber-Infrastructure?

• The comprehensive infrastructure needed to
  capitalize on dramatic advances in information
  technology.
• Cyberinfrastructure integrates
• Hardware for computing, data and networks
• Digitally-enabled sensors
• Observatories and experimental facilities, and
• An interoperable suite of software and middleware
  services and tools.

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Outline

• National Science Foundation
• Design Manufacturing Innovation
• Engineering Decision Systems
• Cyber-Infrastructure
• Accomplishments
• Office of Cyber-Infrastructure
• NSFs Vision for Cyber-Infrastructure
• Cyber-Infrastructure NSF
• Within Engineering
• Within Design Manufacturing Innovation
• Implications for Enterprise Systems
• Funding Initiatives

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CI Engineering

• Some distinctive topics
• Sensor networks
• Design and control of complex systems
• Multi-scale phenomena
• Real-time computations
• Some Engineering investments
• NCN Nanoscale Computational Network
• NNIN National Nanotechnology Infrastructure
  Network
• NEES Network for Earthquake Engineering
  Simulation
• CLEANER/WatERS Network Collaborative Large-scale
  Engineering Analysis Network for Environmental
  Research / Water and Environmental Research
  Systems

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NCN Nanoscale Computational Network
software  simulation services  educational
resources
on-line 24 hours/day since 1995 400,000
simulations since 2000
PUNCH grid computing middleware
results
3)
1)
software applications
2)
computing resources
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NEES Network for Earthquake Engineering
Simulation

• A network of 15 experimental sites featuring
  advanced tools
• Shake tables
• Centrifuges that simulate earthquake effects
• A tsunami wave basin
• Linked to a centralized data pool and earthquake
  simulation software
• NEESgrid, a communications web that uses
  collaborative tools and tele-presence
  technologies, allows off-site real-time
  interactions
• http//www.nees.org.

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Outline

• National Science Foundation
• Design Manufacturing Innovation
• Engineering Decision Systems
• Cyber-Infrastructure
• Accomplishments
• Office of Cyber-Infrastructure
• NSFs Vision for Cyber-Infrastructure
• Cyber-Infrastructure NSF
• Within Engineering
• Within Design Manufacturing Innovation
• Implications for Enterprise Systems
• Funding Initiatives

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Cyber-Infrastructure Research Projects in DMI
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In Operations Research

• (Real-time) mixed-integer programming
• Optimization methods for engineering design
  (including multi-disciplinary optimization,
  feasible-point optimization methods)
• Optimization, design, control of robust power
  grids
• Stochastic optimization models

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In Service Enterprise Engineering

• Integrated logistical management
• Operating strategies for goods movement (vehicle
  routing scheduling)
• Structured simulation optimization
• Dynamic fleet management

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In Manufacturing Enterprise Systems

• Risk management in supply-chain design
  operations
• Quality control of complex manufacturing
  processes
• Design analysis of large networks
• Global make-to-order supply chains

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Outline

• National Science Foundation
• Design Manufacturing Innovation
• Engineering Decision Systems
• Cyber-Infrastructure
• Accomplishments
• Office of Cyber-Infrastructure
• NSFs Vision for Cyber-Infrastructure
• Cyber-Infrastructure NSF
• Within Engineering
• Within Design Manufacturing Innovation
• Implications for Enterprise Systems
• Funding Initiatives

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Deindustrialization?
10 of US Employment in Manufacturing Half of
Manufacturing Jobs in service-type jobs.
5 of US Workforce actually makes things!
BUT
Manufacturing share of GDP is broadly unchanged
since 1980
AND
Real Output growing at 4 since 1991.
The Economist Industrial metamorphosis October
1st 2005
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Oh but China..

• China is the worlds third largest manufacturer.
• China produces 700 billion dollars of
  manufactured goods.
• China employs 6 times the number of workers to
  produce ½ the output of U.S. manufacturers.
• China LOST 15 million jobs in manufacturing
  between 1995-2002.

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Deindustrialization Decline?

• As households become richer
• Proportion of wealth spent on manufactured goods
  declines,
• Increase in spending on holidays, health and
  education and services in general.
• The service sector becomes central to economic
  activity.

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Some Questions

• How do we engineer the service enterprise to
  match the gains in manufacturing efficiency?
• How do we innovate services to continue to
  generate economic development?
• How does new technology drive innovation in
  services?

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Another side of CIwww.nanoHUB.org
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Outline

• National Science Foundation
• Design Manufacturing Innovation
• Engineering Decision Systems
• Cyber-Infrastructure
• Accomplishments
• Office of Cyber-Infrastructure
• NSFs Vision for Cyber-Infrastructure
• Cyber-Infrastructure NSF
• Within Engineering
• Within Design Manufacturing Innovation
• Implications for Enterprise Systems
• Funding Initiatives

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Emerging Frontiers inResearch Innovation

• A planned solicitation
• One topic Auto-reconfigurable Engineered Systems
  Enabled by Cyber-Infrastructure
• Cyberinfrastructure provides the capability to
  embed reconfigurability into systems.
• Auto-reconfigurability will provide robustness to
  unanticipated/unplanned failure events.
• Design of autonomously configurable engineered
  systems integrating physical, information and
  knowledge domains
• Novel methods to sense, self-diagnose, and
  auto-reconfigure the system to function
  uninterruptedly when subject to unplanned failure
  events
• Relevant research topics from DMI design
  methodologies, systems modeling, optimization,
  planning, and simulation.

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CI Experiences for Graduate Students

• Under consideration

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Information and Intelligent Systems (NSF 06-572)

• Advancing Human-Centered Computing, Information
  Integration and Informatics, and Robust
  Intelligence
• Integration and co-evolution of social and
  technical systems
• Increase the capabilities of human beings and
  machines to create, discover and reason with
  knowledge
• Advance knowledge about how computational systems
  can perform tasks autonomously, robustly, and
  flexibly.
• Deepen our understanding of the globalization of
  communications and commerce.
• Problem-solving in distributed environments
• Multi-agent systems that solve complex problems,
  in domains such as disaster response and
  e-commerce.

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Summary

• National Science Foundation
• Design Manufacturing Innovation
• Engineering Decision Systems
• Cyber-Infrastructure
• Accomplishments
• Office of Cyber-Infrastructure
• NSFs Vision for Cyber-Infrastructure
• Cyber-Infrastructure NSF
• Within Engineering
• Within Design Manufacturing Innovation
• Implications for Enterprise Systems
• Funding Initiatives

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Questions?
Stephen Nash Program Director, Operations
Research U.S. National Science Foundation snash_at_ns
f.gov