KDI: Networked Engineering A Joint Research Initiative of CMU-Drexel-USC William C. Regli Assistant Professor and Director Geometric and Intelligent Computing Laboratory Department of Mathematics and Computer Science Drexel University

KDI:NE Project Goals To develop, integrate and evaluate information systems for distributed and collaborative design and manufacturing.

Project Overview NSF Grant: CISE/IIS Drexel University Program: NSF Knowledge and Distributed Intelligence (KDI) Initiative Amount: $1.2M Duration: October October 2001 One of 40 projects selected in 1998 (of 697 proposed)

Principal Investigators Carnegie Mellon University –Pradeep Khosla –Ramayya Krishnan University of Southern California –Berok Khoshnevis –Stephen Lu Drexel University –Thomas Hewett –William Regli

Industry and Gov’t Partners AT&T Labs, Internet Platforms National Institute of Standards and Technology Structural Dynamics Research Corporation (SDRC) Delaware Valley Industrial Resource Center (DVIRC) Bridgeport Machine Tools Ford Motor Company

KDI: Networked Engineering Communication of Information –within an office –across virtual organizations –to suppliers and customers Access to Services –human expertise –software agents Collaboration & Negotiation –among different disciplines and departments Information Services Collaboration

KDI:NE Research Objectives Design Repositories –Engineering knowledge-bases to leverage legacy knowledge Composable Simulation –CAD enhanced with engineering analysis and behavior models Collaborative Negotiation –Conflict management strategies for design Usability Evaluation –Assess computational support for collaborative design Networked Engineering Studios –Integrate Internet, collaboration, and CAD tools

Design Repositories Goals: Record, archive and manage design information as it is created during distributed design activities. Approach: –Message model for distributed design –Process archival methodologies to populate design knowledge-bases –Retrieval strategies for design knowledge-bases Impact: –Enables variational design –Access and reuse of legacy data and information –Platform for networked collaboration on and knowledge sharing about design problems Related Project: NSF CAREER Award CISE/IIS

Repository Scenario

Engineering Digital Libraries … contain CAD models, assemblies, plans, revisions, S-B-F models, project information and workflows, design rationale...

Research Objectives Integrated engineering knowledge-bases and engineering digital libraries Intelligent decision support tools for design Techniques to leverage legacy knowledge Current Results and Accomplishments: Graph-based structures for knowledge modeling Geometric search algorithms Collaborative/Conceptual interfaces Internet-Based Design Repository

National Design Repository Enables national and international participation Links in related resources To be coupled with intelligent search and retrieve tools

Involved Drexel/GICL Research Personnel Dr. William C. Regli (MCS) Dr. Thomas Hewett (PSA) Dr. Wei Sun (Mech. Eng.) Dr. Jon Sevy (GICL Asoc. Dir.) Mr. Gaylord Holder GRAs –Vincent Cicirello (MS, 1999) –Xiaochun Hu (PhD) –Max Peysakhov (MS, 2000) –Xiaoli Qin (MS, 1999) –Vera Zaychik (MS, 2000) NSF REUs –Lisa Anthony –Dmitry Genzel –J. Elvis John –David McWherter –Yuriy Shapirshteyn –Joshua Wharton Part-Time & Workstudy –Binh Le –Victoria Charles

Current Status Deploying Repository site Initial implementation of –Conceptual query interface –Structure matcher Data acquisition –CAD data (w/ SDRC, PTC, NIST) –Process/Assembly Plans (w/ Bridgeport and CMU) Integrated with fabrication services –GICL’s Bridgeport 4-axis machining center

Future Work Integrate Repository with K-base system Approximation algorithms for –structure matching –distance measurement Enhanced design graph representation Experimentation and testing of conceptual design/query interface Adaptable query interface for Internet agents Integrated cost estimation, planning, and manufacturing network services

Composable Simulation Goals: Create simulations of mechatronic systems by composing mechanical CAD models, electrical models and information technology. Approach: –Automatically create product-level simulations –CAD enhanced with analysis and behavior models –Hierarchical distributed simulation architecture –CORBA-based implementation Impact: –Allow reuse of simulation models –Significantly reduce the time to build simulators –Increase fidelity of simulations

Scenario: Conceptual Design... Pitch Motor Mechanical System PID Coupling Yaw Motor Reference Yaw Pitch Control Signal Control Signal

… to Model Simulation Design conceptCAD and Virtual prototyping Model synthesis and refinement Automatically generate dynamic model and simulation software. Prototype refinement Dynamics Pitch motor Control Ref. Yaw motor

Component Models Component Models Simulation software architecture Simulation software architecture Simulation processes Simulation processes Information Agents Information Agents Linpack Odepack Matlab Dymola ACIS Conceptual Design Conceptual Design System Overview

Novel Features Creation of simulation software by combining individual simulation processes Inclusion of information agents in simulation process Provision of distributed environment Automatic model refinement

Component Models Object-Oriented Modeling Paradigm –reuse of models Design Repository used to select CAD components –incorporates ADAMS or DADS Information Agents –control system algorithms –environment definition

Software Architecture Analyze conceptual graph to create simulation processes –distributed objects –retrieve CAD information via ACIS Build simulator architecture –synchronization mechanisms –communication protocols Execute simulation

Simulation Output

Collaborative Negotiation Goal: Develop systematic methods to establish optimal strategies to guide design team interactions and to manage design conflicts raised from these interactions. Approach: –Game-theoretic modeling of collaborative design activities –Establishment of conflict management strategies for mechatronic design problems Impact: –Theoretical foundations for new software tools to support collaboration and negotiation activities –Techniques for trade-off analysis in mechatronic systems design Related Projects: –DARPA/CMU CODES –CMU DecisionNet

Outline The problem context –enterprise-wide decision support for military logistics planning The approach –use an e-commerce metaphor to create a virtual repository of decision support resources The research challenges –metadata (what kinds, representation..) –the search and discovery problem

Overview of DecisionNet Architecture –Providers/developers of decision support objects register with broker provide metadata –Broker(s) compiles metadata into a catalog supports search to respond to consumer queries with varying degrees sophistication returns executable plans (an ordered collection of services) –Users use broker to search and retrieve resources/computational plans use broker to execute resources to solve problem computational objects in the repository

Networked Engineering Studios Goal: Deploy testbed of Design Studios that integrate Internet technologies and collaboration/multimedia tools with proactive CAD systems and inter-networked engineering and fabrication services. Approach: –Leverage vBNS, COTS software and strong industry collaboration –Merge collaborative work tools with tools for design, manufacturing, negotiation and Product Data Management (PDM) Impact: –Interdisciplinary learning/work environment: CS/EE/ME/Psyc/CE/IE/HCI –New classroom for industry –Platform for evaluation

Initial Sites

vBNS Logical Network Map Last Updated 2/1/99 NOTE: Lines between institutions and aggregation points or NAPs represent the configured bandwidth of their connection to the vBNS. The bandwidth of the actual circuits may be greater than shown. 75 Operational Connections 19 Planned Connections MIT 13.8 Mbps Wayne State Milwaukee Purdue UMass Chicago Los Angeles Boston Texas Cal Poly Pomona Cal State San Bernardino New York City Perryman, MD Columbia NYU George Washington Georgetown SDSU Houston CalREN-2 South Cleveland ESnet iDREN ESnet DREN NREN ESnet DREN SREN APAN 35 Mbps CA*Net II DREN NREN iDREN ESnet DREN NI NREN FNAL ANL San Francisco Seattle PNW St. Louis Missouri MREN/ STARTAP CalREN-2 North NI Denver NASA AMES MAX MFS DC NAP Sprint NY NAP SoX Kentucky Atlanta Wake Forest Penn State UIUC Yale Boston U Brown Harvard Minnesota Chicago UIC Madison Northwestern Iowa Iowa State UC Boulder Utah NCAR Washingto n Ohio State PSC NCSA Oregon State UC Berkeley Stanford UC Davis UCSF UCSC Arizona UCSD CalTech UC Irvine UC Riverside UCSB USC USC ISI CMU Rutgers Highway 1 UMD Johns Hopkins UMBC VA Tech UVA ODU Vanderbilt Duke NC State NCSC UNC UT Austin Rice Baylor C. of Medicine Houston TAMU Houston Cornell Princeton Birmingham SDSC MiamiFSU Indiana UCLA Michigan Notre Dame GA Tech MCI Reston GA State Michigan State Merit UPenn UNM Florida Central Florida Rochester NYSERNET Syracuse Rensselaer SUNY Buffalo Washington DC NIH MCI - vBNS POP vBNS Approved Institution Planned vBNS Approved Institution vBNS Partner Institution Network of vBNS Partner Institutions Planned Network of vBNS Partner Institutions Aggregation Point Planned Aggregation Point DS3 OC3 OC12 UNH Dartmouth Drexel  1998

Evaluation & Human Factors Goal: Work with practicing engineers and engineering educators to improve support for design and to understand performance of designers in distributed and collaborative design environments. Approach: Assess computing system support for design and collaborative design through empirical examination of interaction effects among: –Hardware and Software characteristics –Identifiable sets of users Evaluation as part of computing system design process: –Provides feedback to designers –Enables users to contribute tool and system design ideas –Forces ongoing concern with goals and the criteria for meeting them –Evaluation will happen

Impact Improved tools for engineering design and collaboration Tools that designers will want to use Assessment techniques Collaborators: –DVIRC –Drexel ME –SDRC –Bridgeport –Ford –NIST

Assembly Structures

CUP: Conceptual Understanding and Prototyping Functional requirements “Enable back-of-the-envelope sketching” –capture basic 3D assembly structure –part relationships –function characteristics –behavior characteristics Collaborative environment Internet-Centric