Manufacturing and automation systems techniques and technologies part 1 of 5 three pillars of manufacturing technology ( TQL)

CONTRIBUTORS TO THIS VOLUME JAMES S ALBUS DONALD S BLOMQUIST HOWARD P BLOOM GARY P CARVER RICHARD H F JACKSON ALBERTJONES PHILIP Ν ANZETTA JOHN A SIMPSON DENNIS A SWYT CONTROL AND DYNAMIC SYSTEMS ADVANCES IN THEORY A N D APPLICATIONS Volume Editor Edited by RICHARD H F JACKSON C T LEONDES Manufacturing Engineering Laboratory National Institute of Standards & Technology Gaithersburg, Maryland School of Engineering and Applied Science University of California, Los Angeles Los Angeles, California and College of Engineering University of Washington Seattle, Washington V O L U M E : MANUFACTURING AND AUTOMATION SYSTEMS: TECHNIQUES AND TECHNOLOGIES Part of Three Pillars of Manufacturing Technology ACADEMIC PRESS, INC Harcourt Brace Jovanovich, Publishers San Diego New York Boston London Sydney Tokyo Toronto ACADEMIC PRESS RAPID MANUSCRIPT REPRODUCTION The articles in this work are U.S government works in the public domain This book is printed on acid-free paper @ Copyright © 1992 by ACADEMIC PRESS, INC All Rights Reserved No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher Academic Press, Inc 1250 Sixth Avenue, San Diego, California 92101 United Kingdom Edition published by Academic Press Limited 24-28 Oval Road, London NW1 7DX Library of Congress Catalog Number: 64-8027 International Standard Book Number: 0-12-012745-8 PRINTED IN THE UNITED STATES OF AMERICA 92 93 94 95 96 97 BC CONTRIBUTORS Numbers in parentheses indicate the pages on which the authors* contributions begin James S Albus (197), Robot Systems Division, Manufacturing Engineering Laboratory, National Institute of Standards and Technology, Gaithersburg, Maryland 20899 Donald S Blomquist (163), Automated Production Technology Division, Manufacturing Engineering Laboratory, National Institute of Standards and Technology, Gaithersburg, Maryland 20899 Howard P Bloom (31), Factory Automation Systems Division, Manufacturing Engineering Laboratory, National Institute of Standards and Technology, Gaithersburg, Maryland 20899 Gary P Carver (31), Factory Automation Systems Division, Manufacturing Engineering Laboratory, National Institute of Standards and Technology, Gaithersburg, Maryland 20899 Richard H F Jackson (1), Manufacturing Engineering Laboratory, National Institute of Standards and Technology, Gaithersburg, Maryland 20899 Albert Jones (249), Manufacturing Engineering Laboratory, National Institute of Standards and Technology, Gaithersburg, Maryland 20899 Philip Nanzetta (307), Office of Manufacturing Programs, Manufacturing Engineering Laboratory, National Institute of Standards and Technology, Gaithersburg, Maryland 20899 John A Simpson (17,333), Manufacturing Engineering Laboratory, National Institute of Standards and Technology, Gaithersburg, Maryland 20809 Dennis A Swyt (111), Precision Engineering Division, National Institute of Standards and Technology, Gaithersburg, Maryland 20899 vii PREFACE At the start of this century, national economies on the international scene were, to a large extent, agriculturally based This was, perhaps, the dominant reason for the protraction, on the international scene, of the Great Depression, which began with the Wall Street stock market crash of October 1929 In any event, after World War II the trend away from agriculturally based economies and toward industrially based economies continued and strengthened Indeed, today, in the United States, approximately only 1% of the population is involved in the agriculture industry Yet, this small segment largely provides for the agriculture requirements of the United States, and, in fact, provides significant agriculture exports This, of course, is made possible by the greatly improved techniques and technologies utilized-in the agriculture industry The trend toward industrially based economies after World War II was, in turn, followed by a trend toward service-based economies; and, in fact, in the United States today roughly 70% of the employment is involved with service industries, and this percentage continues to increase Nevertheless, of course, manufacturing retains its historic importance in the economy of the United States and in other economies, and in the United States the manufacturing industries account for the lion's share of exports and imports Just as in the case of the agriculture industries, more is continually expected from a constantly shrinking percentage of the population Also, just as in the case of the agriculture industries, this can only be possible through the utilization of constantly improving techniques and technologies in the manufacturing industries in what is now popularly referred to as the second Industrial Revolution As a result, this is a particularly appropriate time to treat the issue of manufacturing and automation systems in this international series Thus, this is Part of afive-partset of volumes devoted to the most timely theme of "Manufacturing and Automation Systems: Techniques and Technologies." "Three Pillars of Manufacturing Technology" is the title of this volume It is edited by Richard H F Jackson, and its coauthors are Dr Jackson and his colleagues at the National Institute of Standards and Technology (NIST) Manufacturing Engineering Laboratory, a unique organization on the international scene ix χ PREFACE Ordinarily, in this Academic Press series, the series editor provides the overview of the contents of the respective volumes in the Preface However, in the case of this unique volume, this, among other things, is provided by Dr Jackson in the first chapter of this volume Therefore, suffice it to say here that Dr Jackson and his colleagues are all to be most highly commended for their efforts in producing a most substantively important volume that will be of great and lasting significance on the international scene C T Leondes ACKNOWLEDGMENT There are many who contributed to the production of this book whose names not appear on title pages Principal among these are Barbara Horner and Donna Rusyniak, and their participation bears special mention Their editorial and organizational skills were invaluable in this effort, and their untiring and cheerful manner throughout made it all possible Richard H F Jackson xi MANUFACTURING TECHNOLOGY: THE THREE PILLARS RICHARD H.F JACKSON Manufacturing Engineering Laboratory National Institute of Standards and Technology Gaithersburg,MD 20899 I INTRODUCTION In their simplest form, the three pillars of manufacturing technology are: robots, computers, and production equipment (or, in the case of mechanical manufacturing: machine tools) Since the mid-twentieth century and the onslaught of the second industrial revolution, these three pillars have formed the foundation upon which all new techniques and advances in the technology of factory floor systems have been built This is of course not to deny the importance of advances in non-technology areas such as lean production, quality management, continuous improvement, and workforce training On the contrary, improvements in these areas can provide significant gains in industrial productivity and competitiveness Nevertheless, in the area of manufacturing systems the three pillars are just that: the foundation Because of their importance to the manufacturing systems of today, and because they will also be critical to the development of the advanced manufacturing systems of tomorrow, they are the theme of this volume Further, these pillars form the foundation of the advanced manufacturing research at the Manufacturing Engineering Laboratory (MEL) of the National Institute of Standards and Technology (NIST), and since that work is at the center of the U.S government's programs in advanced manufacturing research and development, it CONTROL AND DYNAMIC SYSTEMS, VOL 45 RICHARD H F JACKSON is featured here The chapters were produced by staff of MEL and can be considered a profile of a successful research and development effort in manufacturing technology, which profile is aimed at providing guidance for those who would expand on it II A VISION OF MANUFACTURING IN THE TWENTYFIRST CENTURY To thrive in the twenty-first century, a manufacturing enterprise must be globally competitive, produce the highest quality product, be a low cost, efficient producer, and be responsive to the market and to the customer In short, the next century's successful manufacturing firms will be "World Class Manufacturers" who make world class products for world class customers; i.e, customers who know precisely what they want and are satisfied only with world-class products There are many perspectives from which one can view a world class manufacturing firm It can be viewed from the perspective of the shop floor and its interplay of the hardware and software of production It can be viewed from the perspective of the legal environment in which it operates, both nationally and internationally It can be viewed from the standpoint of the business environment, with its complex of tax and capital formation policies that affect long- and shortterm planning It can be viewed from the perspective of its corporate structure and embedded management techniques, which may facilitate or impede progress toward a manufacturing system of the twenty-first century It may be viewed through the eyes of its employees, and the way it incorporates their ideas for improving the manufacturing process, the way it seeks to train them and upgrade their skills, and the way it strives to integrate them with the intelligent machines of production It may be viewed from the perspective of its policies for performing, understanding, incorporating and transferring state-of-the-art research in advanced manufacturing technology A world class manufacturer may be viewed from these and many other perspectives, but, as depicted in Figure 1, the essential issue of importance for a successful twenty-first century manufacturing enterprise is to learn how to operate smoothly and efficiently within each of these regimes and to combine them into a smoothly functioning, well-oiled engine of production Such an engine takes as input the classical categories of labor, capital, and material, and produces world class products for world class customers *See the Appendix to this Introduction for a brief description of the Manufacturing Engineering Laboratory and its programs M A N U F A C T U R I N G TECHNOLOGY: THE THREE PILLARS 21ST CENTURY MANUFACTURING Figure Twenty-First Century Manufacturing While each of these perspectives is certainly important in its own right, and the interplay with the other factors is critical, in this book we concentrate on two of the gears of the well-oiled machine: manufacturing technology research and development, and technology deployment We concentrate on these because these are the only appropriate areas for a scientific and engineering laboratory like NIST to address In fact, NIST is the only federal research laboratory with a specific mission to support U.S industry by providing the measurements, calibrations, quality assurance techniques, and generic technology required by U.S industry to support commerce and technological progress III THE THREE PILLARS OF MANUFACTURING TECHNOLOGY We have organized this book and our programs at NIST around the three basic components of any successful mechanical manufacturing system: machine tools and basic precision metrology, intelligent machines and robotics, and computing and information technology, all overlaid on a background of standards and measurement technology, as shown in Figure These are the three pillars of manufacturing technology research and development because they have been, are, and will be for some time to come, the quintessential components of factory M A N U F A C T U R I N G IN THE TWENTY-FIRST CENTURY: A VISION 339 D Staffing and Management Although we have considered the hardware and software of the factory of the twenty-first century, and only by implication the human staff and its management, it cannot be overlooked that the demands of the SMP will result in changes in staffing patterns and human resources management equally profound The development of the FMP resulted in a continual "deskilling" of humans on the factory floor With the SMP, this process is being reversed The concept of Fredrick Taylor [7] that there exist one best way of doing every task and management must enforce this procedure will fall by the wayside Management will increasingly become aware that, in the words of Nancy L Badore of Ford Motors, that involvement and empowerment of the employee is the modern paradigm for management success [8] The concept of continuous process improvement, propounded by Genichi Taguchi and now widely adopted, assumes on the factory floor a degree of analytical ability and a knowledge of the fundamentals of the processes in use that has been missing from manufacturing since before 1855 These mental, intellectual skills will replace almost entirely the manual effort of the FMP If the job can be done by "brute strength and ignorance" it will be done by a robot Since 1900 the percentage of the work force directly engaged in production has decreased and those engaged in management and administration, and scientific technical has increased [9] There is little reason to believe this trend will not continue until the latter two groups almost completely dominate the manufacturing workforce At the higher levels of a much flatter and more open management hierarchy, profound changes in "lifestyle" will occur Increasingly, design and planning will be done by teams These teams will use ever more sophisticated management tools and performance metrics [10] To be successful, such teams will require of their members much greater interpersonal and communication skills and a shift away from individual to team responsibility and reward Our university engineering and business schools will have adjusted their curricula to provide their graduates with these new necessary skills Increased emphasis on design technology will be common in engineering courses both undergraduate and graduate [11] All the necessary changes can be brought about only partly by vocational training and professional education Improved in education, math, and science starting before entering the work force will be necessary, along with cultural changes The introduction of the FMP brought about profound societal changes, such as the rise of the industrial proletariate, in all nations There is every reason to believe the changes in society brought about will be as great IV CONCLUSIONS The next 20 to 50 years will see profound changes in manufacturing as the Second Manufacturing Paradigm matures Thosefirmsthat stay at the forefront will prosper as World-Class Producers Those firms that not adapt will fail 340 JOHN A S I M P S O N There is much work at the research and development level to be done in the United States by industry, government and academia if U.S Industry is to regain its world class status Perhaps, most importantly, the industrial culture must change, Taylorism must vanish, internal barriers must fall and management must be as flexible as the means of production An era will have passed REFERENCES M.J Boskin and L.J Lau, "Capital Formation and Economic Growth," Technology & Economics, National Academy Press, Washington, DC (1991) J.D Power & Associates Initial Quality Survey, quoted in Manufacturing Competitiveness Frontiers, February 1991 K Gabriel, J Jarvis, and W Trimmer, "Small Machines, Large Opportunities," Report on Workshop on Microelectromechanical Systems, January 1988, National Science Foundation, Washington, DC (1989) G Taguchi and D Clausing, "Robust Quality," Harvard Business Review, January-February 1990 Ministry of Industrial Science and Technology, "National R&D Project, Flexible Manufacturing System Complex with Laser," Japan (1980) G Heaton, R Reppetto and R Sobine, "Transforming Technology: An Agenda for Environmentally Sustainable Growth in the 21st Century," World Resources Institute, Washington, DC (1991) J Gies, "Automating the Worker," American Heritage of Invention and Technology, American Heritage, New York, NY, Winter 1991 N.L Badore, "Involvement and Empowerment: The Modern Paradigm for Management Success," Symposium on Foundations of World-Class Manufacturing Systems, National Academy of Engineering, June 19,1991 D.A Swyt, "The Workforce of U.S Manufacturing in the Post-Industrial Era," Journal of Technological Forecasting and Social Change, Vol 24 (1988) 10 K.R Baudin, "Manufacturing System Analysis," Youdon Press, Englewood Cliffs, NY (1990) 11 Manufacturing Studies Board, "Improving Engineering Design," National Academy Press, Washington, DC (1991) INDEX NIST engineering paradigm, 78-80 Part Model Files, 84-85 system specification, 80-82 development of, 25-28 (IMDAS) Integrated Manufacturing Data Administration System, 85-86 integration research by background, 249-250 communications issues, 289-301 common memory, 295-299 network architecture, 291-293 network layering, 299-301 technology issues, 294 topology, 294-295 types of communication, 290-291 data management issues, 268-289 architecture and, 269-274 heterogeneous system management, 268 IMDAS system, 274-287 real-time operations, 268-269 data preparation, 253-254 production management, 249-268 shopfloorcontrol, 254-265 architectural considerations, 254-256 distributed decision-making, 258-260 future trends, 265, 268 generic controllers, 257-258 integrated decision-making and control, 260-265 intelligent system architecture, 200-202 NIST research and development, 7-8 technology transfer applications models, 317-319 automation programs, 310-311 background, 307-308 company size, 327-328 future directions, 329-330 hierarchical control architecture, 319-321 A Abbe error, coordinate-position measurement, 136 Abbe, Ernst, measurement theory, 20 Accuracy dimensional measurements error characterization, 126-127 manufacturers' statements, 128 standards-imposed limits, 123-125 error summary and analysis, hierarchy of, 153 Acoustic ranging, intelligent system architectures, 230 Actuators, intelligent systems, 198 Additive-multiplicative representation dimensional measurements, 127-128 error summary and analysis, 154 Advanced Technology Program (ATP), 323 Air Force (U S.) Enterprise Integration Framework Program, 97 Next Generation Control, 321 Albus, J., 27 Alignment errors displacement interferometry, 134-135 distance errors, 139 ALPS representation system, 254 Ambient air index, errors in, 133 Ambler, E., 22 AMICE consortium, 97-98 AMPLE program, process-intermittent error compensation, 182 AMRF (Automated Manufacturing Research Facility) communications system, 295-301 common memory, 295-299 networking, 299-301 concurrent engineering and, 77-85 engineering applications, 83-85 information management technology, 82-83 341 342 INDEX AMRF (Automated Manufacturing Research Facility) (continued) internal programs, 326-327 models for, 311-315 National Automated Manufacturing Laboratory, 309-310 Naval applications, 328-329 Navy Centers of Excellence, 317 NBS history and, 308-309 Omnibus Trade and Competitiveness Act (1988), 323-326 RAMP program, 316-317 software error correction, 319-321 standards models, 321-322 AND/OR graphs integration research, 254 intelligent system architectures, 210-211 ANSI standards, concurrent engineering and, 60-62 Apparel Design Research System, concurrent engineering, 85 Application protocols AMRF communications network, 301-303 concurrent engineering and commercialization of, 65 PDES/STEP advisory group, 62-63 STEP program, 68-71 Application prototyping AMRF technology transfer and, 317-319 NIST national testbed, 90-92 Application systems, concurrent engineering and, 75-76 Arbitrary boundary location, extension measurement errors, 151 Artifact standards, dimensional measurements, 125 Artificial intelligence, automated manufacturing and,27 ASN (Abstract Syntax Notation) standard, 278 Assembly models, concurrent engineering and, 47 Assessment functions, shopfloorcontrol, 260-263 Attention mechanisms, intelligent system architectures, 237-238 Automated manufacturing concurrent engineering and, 53-55 intelligent systems, 197-198 Axiom-type matrix analysis, 154-156 Β Basic Service Executive (BSE), BDAS system, 279 "Batch-of-one" manufacturing concepts, 27-29 BDAS (Basic Data Administration System), 274, 277-279 Behavior, in intelligent system architectures, 208-209 Behavior generating (BG) module hierarchical control systems, 201-202 vs horizontal control systems, 202-204 intelligent system architectures, 211-214 attention mechanisms, 237-238 EX(J) executor submodule, 213-214 JA (job assignment) submodule, 212 PL(j) planner subievel submodule, 213 timing diagram, 205-206 Behavior generating system defined, 210-211 hierarchical levels, 204 intelligent system architecture, 201 "Best estimate prediction," 235-236 Bottom-up processing, intelligent system architectures, 230-231 Boundary-location errors, 140-142 average-material-boundary location, 151-152 extension measurement errors, 151 Business alliances, concurrent engineering and, 50-52 C Calibration process, automation of, 22 CALS (Computer-aided Acquisition and Logic) program concurrent engineering and, 97 PDES/STEP project, 57-58 Canonical architectures, data administration and, 271-272 Career growth, concurrent engineering and, 40 Carnap, R., 21 Carriage Abbe tilt, position measurement errors, 148 Carriage motion, errors in, 136 Cell-level decision-making, shopfloorcontrol, 259 Center for Manufacturing Engineering and Process Technology (CMEPT), 25-28 Centralized data and control architecture, 271 "Chunking," intelligent system architectures hierarchical levels, 204-205 sensory processing hierarchy, 238-241 Colt, Samuel, 19 Command translation, BDAS system, 278 Command trees, intelligent system architecture, 203-204 INDEX Commercialization methods, STEP program and, 74-75 Communications issues BDAS system, 274, 278 hierarchical control systems, 202 integration techniques and, 289-301 AMRF network, 299-301 common memory, 295-299 communication categories, 290-291 network architecture, 291-293 technology, 294 topology, 294-295 Company size, AMRF technology transfer and, 327-328 Comparison functions, intelligent system architectures, 233-234 Compensated boundary location, extension measurement errors, 151 Compensated standard air index, errors in, 133 Competitiveness concurrent engineering and, 32 cultural aspects, 49-50 vs choice, 40 manufacturing technology and, 9-10 Computer Controlled Measurement Machine (CCMM), 23-24 Computer Numerical Control (CNC), measurement theory and, 21 Computer-aided design (CAD) concurrent engineering and, 73-75 interface problems, 26 quality control, post-process inspection, 189 Computer-aided engineering (CAE), concurrent engineering and conceptual design, 45 Computer-Aided Manufacturing (CAM), 26 Computer-integrated manufacturing (CIM), 95, 97-100 Computers concurrent engineering and, 48-52 manufacturing technology background, research and development, 3-9 Conceptual design, concurrent engineering and, 45 Concurrent engineering product data standards automation and, 52-55 background, 31-34 cultural compatibility and, 48-52 definitions, 36-40 design criteria, 42-48 Enterprise Integration Framework, 95, 97-100 NIST role in, 77-85 343 National PDES testbed, 85, 87-95 PDES/STEP effort, 55-66 shared databases, 55 team work-in-effect concept, 34-41 technical limitations of STEP and, 67-77 Confidence factors, intelligent system architectures, 236-237 Configuration management concurrent engineering and, 76-77 NIST national testbed, 87, 92, 95-96 Conformance testing concurrent engineering and, 77 NIST national testbed, 88-90 Consensus building, concurrent engineering and, 56 Control architectures automated manufacturing, 26-27 data administration and, 271-274 Confrol cycles, intelligent system architectures, 207 Control theory, intelligent systems, 197-198 Coordinate measurement system coordinate axes, errors in, 139 dimensional measurements, 121 limits, 124 misalignment, error-budget example, 147-149 Coordinate measuring machine (CMM) accuracy enhancement, 23-24 AMRF technology transfer and, 319-321 dimensional measurements, 121-122 measurement theory and, 21-22 quality control, post-process inspection, 187-188 Quality in Automation (QIA) program, 164 Coordinate-position measurement error sources, 135-137 misalignment errors, 158-159 Cost analysis, concurrent engineering and design criteria and, 47 reduction with, 53 Cross referencing techniques, intelligent system architectures, 226-227 Cultural factors, concurrent engineering and, 48-52 Customer awareness, concurrent engineering and, 53 Cyclic replanning, intelligent system architectures, 206-207 D DARPA, concurrent engineering, 97 344 INDEX Data administration, data management integration and, 270-274 Data analysis, pre-process machine characterization, 172-178 Data Assembly Service (DAS), DDAS system, 282-283 Data delivery, data management integration and, 269 Data Director Service (DDS), DDAS system, 282 Data management BDAS system, 274-278 concurrent engineering and information management technology, 82-83 STEP program, 69, 72-73 integration issues, 268-274 architecture for, 269-274 data administration, 270-274 data modeling, 269-270 database design, 270 communications issues, 289-290 data delivery and job scheduling, 269 heterogeneous system environment, 268 IMDAS system, 274-289 BDAS system, 274-279 DDAS system, 279-283 MDAS system, 283-285 performance evaluation, 285-289 real-time operations, 268-269 Data manipulation, data administration and, 271 Data Manipulation Language Service (DMLS), DDAS system, 279, 281 Data modeling, 269-270 Data sharing, concurrent engineering and, 68 Data translation, BDAS system, 278 Database design, data management integration and, 270 Database sharing, concurrent engineering and, 55 DDAS (Distributed Data Administration System), 279-283 Dead path errors compensation, 146 index of refraction, 134 Decision-making distributed, 258-260 integration with control, 260-265 Design criteria concurrent engineering and, 42-48 conceptual design, 45 detailed design, 45-46 manufacturing system and process design, 46 representation of intent, 47-48 uniqueness and product life cycle, 42-46 Detailed design, concurrent engineering and, 45-46 Detection intelligent system architectures, 230-231 thresholds, 234-235 Deterministic manufacturing metrology, 24-25 quality control and, 164-167 Dimensional gauging routines, 183-184 Dimensional measurements See Precision dimensional measurement Direct Numerical Control (DNC), measurement theory and, 21 Dispatch Manager (DM), shop floor control, 258 Displacement dimensional measurements ,114-115 error sources error-budget example, 143, 145-147 misalignment errors, 158 position measurement errors, 147-148 Displacement interferometry dimensional measurements limits, 123-124 metric transfer, 119-120 error sources in, 132-135 alignment errors, 134-135 fringe-fractioning, 134-135 index of refraction of medium n, 133 vacuum wavelength, 132-133 Displacement scales, errors in, 135-136 Distance measurement dimensional measurements, 115-116 error-budget example, 149-150 error sources, 138-140, 159 metric transfer, 121-122 Distributed data and control architectures, 271 Distributed decision-making, shopfloorcontrol, 258-260 Distributed Service Executive (DSE), DDAS system, 279 DMIS (dimensional measuring interface specifications) limitations, 191-192 parts programs, 190-191 post-process inspection, 187-192 Drafting, historical background, 18 "Drill Up" acoustic sensor, 24 Ε EDIF standard, concurrent engineering and, 66 Egospheres, intelligent system architectures, 221-225 object coordinates, 222 world coordinates, 222 INDEX Eisenhart, C , 20-21 Electronic subdivision, errors in, 134 Emotions, intelligent system architectures and, 243-244 Engineering applications, concurrent engineering and,83 Engineering Design Laboratory (AMRF), 85 Engineering environment, concurrent engineering and, 82-83 Engineering technology, concurrent engineering and,83 Enterprise Integration Framework, concurrent engineering, 95, 97-100 Enterprise modeling, data management integration and, 269-270 "Enterprise networking" concept, 291-293 Entities, in intelligent system architectures, 225-226 database hierarchy, 227-228 mapping and, 226-227 sensory processing hierarchy, 240-241 Equipment-level decision-making, shop floor control, 260 Error-budget example, 143-157 displacement errors, 143,145-147 fringe-fraction error, 145 index-of-refraction error, 145-146 interferometer-axis alignment error, 146 sum of displacement-specific errors, 146 total displacement error, 147 vacuum-wavelength error, 147 distance measurement errors, 149-150 extension measurement, 150-152 position measurement errors, 147-149 misalignment of coordinate and displacement, 147-148 Error characterization cascading nature of, 142-143 dimensional measurements additive-multiplicative representation, 127-128 axiomatic terms, 130-132 formal-theoretical characterization, 128-132 matrix of errors, 130 precision-vs.-accuracy, 126-127 summary and analysis, 152-157 Error sources, 132-143 boundary location, 140-142 compounding error in measurement types, 142-143 coordinate-position measurement, 135-137 displacement interferometry, 132-135 distance measurement, 138-139 345 system element misalignments, 158-160 European Strategic Program for Research on Information Technology (ESPRIT), 97-98 Events, intelligent system architectures, 228-229 Execution function, shopfloorcontrol, 265-266 Extension dimensional measurements, 122-123 error summary and analysis, 157 error-budget example, 150-152 F Facility-level decision-making, 258-259 Factory engineering models, 47-48 Feature probing, distance errors, 139 Flexible Manufacturing Systems (FMS), 25-26 Fly wheeling, intelligent system architectures, 242 Focus-based optical probes, 230 Fringe-fraction errors, 134 error-budget example, 145 G Gage-block, manufacturing paradigm, 19 Game theory, intelligent systems, 197-198 Gauging data, process-intermittent error compensation, 184-186 Generic controller, shopfloorcontrol, 257-258,261 Generic data models, concurrent engineering and, 72-73 Generic Enterprise Data Model (GEDM), concurrent engineering and, 72 Generic entities, intelligent system architectures, 225-226 Generic Product Data Model (GPDM), concurrent engineering and, 72 Geometric-thermal (G-T) model data acquisition, 172-178 pre-process machine characterization, 171-178 data acquisition, 172 Geometry concurrent engineering and, 72 NIST specifications, 80-82 displacement and, 114 distance and, 115 extension and, 116 346 INDEX Geometry (continued) intelligent system architectures, 223-224 position, in dimensional measurements, 113 reference-frame, errors in, 136-137 Gestalt effects, intelligent system architectures, 241-242 Global query processor, 271, 273-274 GM MAP protocol, automated manufacturing, 26-27 Group characteristics, 241 H "Hard automation," manufacturing paradigms and, 19 Harmonization process, concurrent engineering and, 65-66 Heterodyne principle, dimensional measurements, 120 Heterogeneous systems, data management integration in, 268 Hierarchical Control System Emulator, 320-321 Hierarchical control systems, 319-321 horizontal control systems, 202-204 intelligent system architecture, 201-202 levels in, 204-208 Homogeneous coordinate representation, 168 Horizontal control systems, vs hierarchical control systems, 202-204 Hybrid architectures, 271, 273-274 Hypothesized correspondence, intelligent system architectures, 239-240 Hysteresis, intelligent system architectures, 242 I IEEE 802 standards, AMRF communications network, 299 IF/THEN rules, intelligent system architectures, 218 IGES (Initial Graphics Exchange Specification) AMRF technology transfer and, 316-317 computer-aided design (CAD) and, 26 concurrent engineering and data sharing, 68 IGES/PDES organization, 59-60 STEP and, 66 limits of, 28-29 quality control, 187-192 Illusion, intelligent system architectures, 242 Image flow, intelligent system architectures, 230 IMDAS (Integrated Manufacturing Data Administration System), 27 concurrent engineering and, 85-86 data management integration, 274-289 BDAS system, 274-279 DDAS system, 279-283 MDAS system, 283-285 performance evaluation, 285-289 Index-of-refraction error, 133 error-budget example, 145-146 Individualism, concurrent engineering and, 51-52 Information management technology, concurrent engineering and, 82-83 Information models, concurrent engineering and, 72 Information Resource Dictionary System (IRDS), 80-82 Information technology, research and development, 4-5 "In-Process" gaging, flexible manufacturing systems (FMS), 25-26 Integration techniques AMRF programs background, 249-250 communication programs, 289-301 data management issues, 268-289 architecture for, 269-274 heterogeneous system environment, 268 IMDAS system, 277-289 real-time operation, 268-269 production management, 250-268 future evolution, 265, 268 manufacturing data preparation, 253-254 shopfloorcontrol, 254-265 concurrent engineering and, 32-34 Intelligent machines concurrent engineering and, 48 research and development, 4-9 theory of, 197-198 See also Computers; Robotics Intelligent systems actuators, 198 architecture behavior generation (BG) modules, 207-214 hierarchical levels, 204-208 vs horizontal, 202-204 task decomposition, 214-215 sensors, 198 sensory processing, 198, 229-241 attention mechanisms, 237-238 fly wheeling, hysteresis and illusion, 242 Gestalt effects, 241-242 hierarchy, 238-241 INDEX perceptual context, 231-232 recognition detection, 230-231 SP modules, 232-236 surface measurements, 229-230 world model updates, 236-237 system architecture, 200-215 task decomposition, 200 value judgments, 243-245 value state-variable map overlays, 245 VJ modules, 244-245 value systems, 199 world model, 198-199, 216-229 entities, 225-226 entity database hierarchy, 227-228 events, 228-229 knowledge representation, 218 map-entity relationship, 226-227 maps, 219 overlays, 219-220 pixel frames, 220-221 resolution, 221 space, 219 updates, 236-237 WM and KD modules, 216-218 Interface standards, concurrent engineering and, 33-34 Interferometer-axis alignment error, 146 Interferometer-optics thermal drift, 146 International Standards Organization/Open System Interface (ISO/OSI), 26-27 TCI84/SC4, 60 8473 Connectionless Network Service Protocol, 299-300 Internet gateways, AMRF communications network, 299-300 Interoperability testing, NIST national testbed, 90-92 Interprocess communication, BDAS system, 274 IPC standard, concurrent engineering and, 66 J Japan, concurrent engineering and, 50-52 Job scheduling, data management integration and, 269 Johansson, Carl Edward, 19 Κ KD module, intelligent system architectures, 216-218 "Keiretsu," research and development, 347 Kinematic model, pre-process machine characterization, 167-168 Knowledge representation, intelligent system architectures, 218 L Laser interferometry, 23-24 Laser ranging, intelligent system architectures, 230 Life cycle of product, concurrent engineering and, 42-45 Line entities, intelligent system architectures, 241 M Machine-path atmosphere, index-of-refraction error, 145-146 Machine tools vs measuring machine, 156-157 pre-process machine characterization kinematic models, 168-171 metrology, 172 research and development, STEP program and, 74 Machine-tool controller (MTC), 178-179 Macro-scale, dimensional measurements, 112 "Mailbox" systems, 296-297 Management concepts, concurrent engineering and, 40 Manufacturing Automation Protocol (MAP), 291-293 Manufacturing Data Interface Standards Program, 87 Manufacturing Data Preparation (MDP) project integration research, 253-254 shopfloorcontrol, assessment function, 262 Manufacturing Engineering Laboratory (MEL) AMRF technology transfer and, 309-310 Automated Production Technology Division, 15 Fabrication Technology Division, 16 Factory Automation Systems Division, 15 manufacturing technology and, 1-2 overview, 13-16 Precision Engineering Division, 13-14 Robot Systems Division, 14 Manufacturing information systems, 54-55 Manufacturing systems AMRF Integration Project, 85-86 concurrent engineering and design criteria and, 46 models for, 47 348 INDEX Manufacturing technology commercialization of, 9-10 historical context, 9-10 world class standards for, 2-3 Manufacturing Technology Centers (MTCs), 323-326 Mapping techniques, intelligent system architectures, 218-219 egospheres and, 221-225 map transformations, 222-224 map-entity relationships, 226-227 overlays, 219-220 value state and, 245 pixel frames, 220-221 resolution, 221 Mass production efficiency, measurement theory and,20-21 Master Data Administration System (MDAS), 283-285 Master Service Executive (MSE), MDAS system and, 283-285 Mathematical modeling manufacturing paradigms and, 20-21 pre-process machine characterization, 168 Maudslay, Henry, 18 Measurement Assurance Programs (MAP), 21 Measurement technology displacement and, 115 distance and, 115-116 extension and, 116-117 fundamental axioms, 128-130 manufacturing technology, 3-9 position and, 114-115 theory of, 20-21 See also Precision dimensional measurement Measuring machines, error summary and analysis, 156-157 Mechanical drawing automation of, 28-29 concurrent engineering and, 101 historical background, 18 Mechanical measurement background, 17 future trends in, 29 manufacturing history and, 17-19 drafting history, 18 English system, 18 manufacturing paradigms early development of, 19 science and mathematics in, 20-21 second paradigm, 21-29 National Bureau of Standards and, 22-23 Memorandum of Understanding (MOU), concurrent engineering and, 57-58 Memory communications systems AMRF system, 295-299 distributed memory, 296, 298 shared memory, 296-297 intelligent system architectures, 243-244 Meter, in dimensional measurements derived nature of, 118 formal definition, 118 operational realization, 118-119 realization limits, 123 Metrology, research and development, Michelson interferometer, 119-120 Micro-scale, dimensional measurements, 112-113 Mid-scale, dimensional measurements, 112 Milling operations, error summary and analysis, 157 Mirror translation, misalignment in, 135-136 Misalignment errors, dimensional measurements, 157-160 Modeling techniques, AMRF technology transfer and, 311-315 "Molecular Measuring Machine," 124 Monge, Gaspard, 101 Monitoring function, shopfloorcontrol, 265, 267 Multi-enterprise concurrent engineering, 32-34, 101-102 Multiple Autonomous Undersea Vehicle (MAUV) project, 200 Ν Nano-scale, dimensional measurements, 113 NASA Standard Reference Model (NASREM), 28 AMRF technology transfer and, 320-321 National Automated Manufacturing Laboratory, 309-310 National Bureau of Standards (NBS) AMRF technology transfer and, 308-309 Atomic Physics Program, 22-23 Center for Manufacturing Engineering and Process Technology (CMEPT), 25-28 Hierarchical Control Architecture, 27-28 measurement theory and, 22 Naval applications, AMRF technology transfer and, 328-329 Navy Centers of Excellence, 317 Navy Manufacturing Technology program, 311 Network communication BDAS system, 274, 278 integration issues, 291-293 Network Interface Process (NIP), 296-297 Neuroscience, intelligent machines and, 197-198 INDEX NIST (National Institute of Standards and Technology) AMRF programs, integration issues, 249-250 concurrent engineering and, 77-85 manufacturing technology and, 1-2 National PDES Testbed, 85, 87-95 Quality in Automation (QIA) program, 163-164 post-process inspection, 188-192 Non Uniform Rational B-Spline (NURBS) surfaces, 80 Numerical control (NC) machine tools, 21 measurement theory and, 21 part-program segmentation, 183 Ο Object-axis/probe-path alignment, distance measurement errors, 149 Object coordinates, intelligent system architectures, 222 Object-distance error sources, 159 Object environment, errors in, 139 Object point definition, distance measurement errors, 150 Object thermal expansion, distance measurement errors, 149 Objects, observed vs predicted surfaces, 241 Omnibus Trade and Competitiveness Act of 1988, 323-326 Open system standards, concurrent engineering and, 33-34 Open Systems Architecture (OSA), concurrent engineering, 97 Open Systems Interconnection (OSI), Reference Model, 290-291 Operations research, intelligent systems, 197-198 Optimization functions, shopfloorcontrol, 262, 264-265 Ρ Part program modification, 186-187 Partition problems, data management integration and, 270 Parts inspection, quality control, 189-190 Parts on Demand (POD) system (NBS), 316-317 Patents, AMRF technology transfer and, 313 PDES (Product Data Exchange using STEP) concurrent engineering and commercialization of STEP and, 63-65 harmonization of product standards, 65-66 IGES/PDES organization, 59-60 349 institutional aspects of, 59-63 production data standardization, 55-66 U S Government needs and, 56-59 integration research, 253-254 Manufacturing Data Preparation (MDP) project, 253-254 NIST national testbed, 85, 87-95 Perception, intelligent system architectures, 231-232 Performance evaluation, IMDAS system, 285-289 editing time, 289 execution time, 289 propagation time, 286 response times, 286, 288 transaction analysis time, 286 Photogrammetry, intelligent system architectures, 230 Physical networks, integration techniques and, 289-290 Physics displacement and, 114-115 distance and, 115 extension and, 116 position, in dimensional measurements, 113-114 Planning horizons, intelligent system architectures, 207 Point entities, intelligent system architectures, 240-241 Polarization mixing, errors in, 134 Position dimensional measurements, 113-114 error-budget example, 147-149 measurement concept of, 114 probes, 137 "Post-box" memory systems, 27-28 Post-process control loop, quality control architecture, 166 Post-process inspection, quality control, 187-192 Pre-process machine characterization machine tool models, 168-171 geometric-thermal model, 171-178 data acquisition and metrology, 172 data analysis, 172-178 quality control programs, 165,167-178 kinematic model, 167-168 Precision dimensional measurement assessment, 125-132 formal-theoretical error characterization, 128-132 statistical error characterization, 126-128 background, 111-112 basis of*, 118-125 accuracy limits, 123-125 350 INDEX Precision dimensional measurement assessment (continued) artifact standard limits, 125 coordinate measurement system, 121 limits, 124 displacement interferometry, 119-120 limits, 123-124 distance characteristics of objects, 121-122 extension characteristics of objects, 122-123 meter realization limits, 123 transfer of metric, 119-123 unit of length, 118-119 visible light of known wavelength, 119 error-budget example, 143-157 displacement errors, 143,145-147 distance measurement errors, 149-150 extension measurement, 150-152 position measurement errors, 147-149 summary and analysis, 152-157 error sources, 126, 132-143 boundary location, 140-142 compounding error in measurement types, 142-143 coordinate-position measurement, 135-137 displacement interferometry, 132-135 distance measurement, 138-139 system element misalignments, 158-160 quanitity and characteristics table, 117 scope of, 112-117 macro-scale, 112 micro-scale, 112-113 mid-scale, 112 nano-scale, 113 range, 112-113 types of, 113-117 displacement, 114-115 distance, 115-116 extension, 116-117 position, 113-114 Prediction algorithms, intelligent system architectures, 205 Priorities, intelligent system architectures, 243-244 Probes errors probe-as-measuring-machine, 137 probe-as-sensor, 137 settings, position measurement errors, 148 Process control, intelligent systems, 197-198 Process models, concurrent engineering and, 47 Process-intermittent control loop quality control architecture, 166 error compensation, 181-187 implementation, 182-187 methodology for, 182 Product data exchange technology NIST national testbed, 87, 92, 94 research and development, 5-6 Product data standards automation and, 52-55 background, 31-34 Enterprise Integration Framework, 95, 97-100 NIST and, 77-85 National PDES testbed, 85, 87-95 PDES/STEP effort, 55-66 STEP challenges and, 67-77 Product diversity, concurrent engineering and, 40 Product life cycle, 42-45 Production equipment background, research and development, 3-9 Production management, integration research, 250-268 communications issues, 289-290 future evolution, 265, 268 manufacturing data preparation, 253-254 shopfloorcontrol, 254-265 Production Manager (PM), shopfloorcontrol, 257 Production time, concurrent engineering and, 53 Programmable machine tools, measurement theory and, 21 "Proper" measurement theory, 21 Proprioceptive sensors, 229-230 Prototype applications, concurrent engineering and,74 Q Quality control architecture schematic, 165 automated manufacturing DMIS and IGES and, 187-192 overview, 163-167 pre-process machine characterization, 167-178 geometric-thermal (G-T) model, 171-178 kinematic model, 167-171 process-intermittent error compensation, 181-187 dimensional gauging routines, 183-184 NC part-program segmentation, 183 part program modification, 186-187 real-time error corrector, 178-180 manufacturing paradigms and, 20-21 Quality controller (QC), 182 Quality Database, quality control programs, 167 Quality in Automation (QIA) program, 163-164 INDEX Quality Monitor, quality control programs, 167 Query Mapping Service (QMS) DDAS system, 281 MDAS system and, 283-285 Query processing, data administration and, 270-271 Queue Manager (QM), shopfloorcontrol, 257-258 R Range of dimensional measurements, 112 Rank-order operator, dimensional measurements, 129 Rapid Acquisition of Manufactured Parts (RAMP), 316-317 Real-time Control System (RCS) intelligent system architecture, 200-202 quality control architecture, 165 Real-time Error Corrector (RTEC) quality control with, 178-180 architecture, 165-166 transparent mode, 179-180 Real-time operations data management integration and, 268-269 intelligent system architectures, 205-207 Recognition intelligent system architectures, 230-231 thresholds, 234-235 Reference-frame geometry, 136-137 Replication problems, data management integration and, 270 Research and development, manufacturing and research technology, 3-9 Resource data models, concurrent engineering and,72 Robotics control architectures for, standardization of, 27-28 manufacturing technology background, research and development, 3-9 S SARTICS program, AMRF technology transfer and, 321 Scale dimensional measurements, 129 displacement interferometry, 120 error of, 131-132 summary and analysis, 156 351 factor, pre-process machine characterization, 168 Science, manufacturing paradigms and, 20-21 Scientific management, manufacturing paradigms and,19 "Self Conscious Machine" concept, 24 Semantic Association Model (SAM), 274-275 Sensors, intelligent systems, 198 Sensory processing intelligent system architectures, 198, 201, 229-241 attention mechanisms, 237-238 fly wheeling, hysteresis and illusion, 242 Gestalt effects, 241-242 hierarchy, 238-241 perceptual context, 231-232 recognition and detection, 230-231 SP modules, 232-236 surface measurements, 229-230 world model update, 236-237 Sensory processing (SP) module hierarchical control systems, 201-202 levels, 204 intelligent system architectures, 232-236 attention mechanisms, 237-238 comparison sublevel, 233-234 recognition/detection threshold, 234-235 spatial integration, 234 temporal integration module, 234 timing diagram, 205-206 Shewhart, W., 20 Shopfloorcontrol integration research, 251-252, 254-265 architecture, 254-256 distributed decision-making, 258-260 generic controller, 257-258 hierarchical levels, 255-256 integrated decision-making and control, 260-265 maps, 221 Shop-level decision-making, 259 Software error correction, 319-321 Solid modeling systems, concurrent engineering and, 73-75 Space, intelligent system architectures, 219 Spatial aggregation, sensory processing and, 204 Spatial integration, intelligent system architectures, 234 Spatial resolution behavioral generation and, 204 intelligent system architectures, 221 Specific entities, intelligent system architectures, 225-226 Specifications, concurrent engineering and, 74 352 INDEX Standards AMRF technology transfer and, 321-322 concurrent engineering and, 33-34, 38 manufacturing technology, 3-9 validation, NIST national testbed, 88-90 State Technology Extension Program, 323 Statistical Process Control (SPC), 20, 24-25 quality control architecture, 165 Statistical Quality Control, 20 STEP (Standard for the Exchange of Product Model Data) AMRF technology transfer and, 323-326 commercialization of, 63-65 concurrent engineering and application protocols, 68-71 application systems, 75-76 configuration management, 76-77 conformance testing, 77 data representation, 69, 72-73 data sharing, 68 Information Resource Dictionary System (IRDS), 80-82 Product Data Exchange using (PDES), 55-66 technical challenges, 67-77 verification and validation, 75 development of, 28-29 integration research, 253-254 NIST national testbed, 87 Production Cell, 90-92 quality control, 191-192 Stereo vision, intelligent system architectures, 230 Structured light, intelligent system architectures, 230 Subsystems AMRF technology transfer and, 314 integration techniques and, 289-290 Sum of displacement-specific errors, 146 Sum of distance-specific errors, 150 Sum of extension-specific errors, 152 Sum of position-specific errors, 148 "Super Redundant" algorithms, measurement theory and, 23-24 Supplier-vendor cooperation, concurrent engineering and, 53 Surface measurements intelligent system architectures observed vs predicted surfaces, 241 sensory processing and, 229-230 System architecture, intelligent machines, 200-215 behavior generation (BG) modules, 208-214 hierarchical levels, 204-208 vs horizontal, 202-204 task decomposition hierarchy, 214-215 Τ Task analysis, intelligent system architectures, 208-209 Task decomposition, 200 hierarchy, 214-215 Task frame, intelligent system architectures, 208-209 Taylor, Frederick, 19 Teamwork, concurrent engineering and, 32-34, 34-41 definitions, 36-40 human team approach, 35-36 parallel processing and, 36, 39 sequential information, 36 Technical Office Protocols (TOP), 291-293 Technology, communications and, 294 Temporal aggregation, sensory processing and, 204 Temporal integration, intelligent system architectures, 234 Temporal resolution, behavioral generation and, 204 Testing techniques, concurrent engineering and, 74 Thermal drift errors in, 134 index-of-refraction error, 146 Thermal-expansion from object, errors in, 139 Timing diagrams, intelligent system architectures, 205-206 Top-down processing, intelligent system architectures, 230-231 Topology communications and, integration issues, 294-295 concurrent engineering and, geometry and, 80-82 Total displacement errors, error-budget example, 147 Total distance error, 150 Total extension error, 152 Total position error, 148-149 Touch probes, intelligent system architectures, 229-230 Trade balance, U.S.-Japan, concurrent engineering and, 50-52 Transaction Manager (TM) data administration and, 271 DDAS system, 281-282 Transformation matrix, 168-171 Transport protocols, AMRF communications network, 300 Type-axiom error matrix, 156-157 INDEX U U S Government, concurrent engineering and, 56-59 Uncertainty, dimensional measurements and, 127 Unit of measure, dimensional measurements, 118-119, 129 error of, 131 summary and analysis, 155-157 V Vacuum-wavelength error, error-budget example, 147 Validation procedures concurrent engineering and, 67-77 STEP program and, 75 NIST national testbed, 87 Validation Testing System, NIST national testbed, 88-90 Value judgment (VJ) module hierarchical control systems, 201-202 intelligent system architectures, 243-245 Value state-variable map overlays, 245 Value systems, intelligent machines, 199 Verification procedures, concurrent engineering and,75 VHDL standards, concurrent engineering and, 66 Visible light of known wavelength, 119 W Wavelength in vacuum, errors in, 132-133 Whitney, Eli, 18 Working groups, concurrent engineering and, 60 353 Workstation-level decision-making, 259-260 World coordinates, intelligent system architectures, 222 World model, intelligent system architectures, 198-199,216-229 entities, 225-227 database hierarchy, 227-228 events, 228-229 knowledge representation, 218 maps, 219 egospheres and, 221-225 map-entity relationships, 226-227 overlays, 219-220 pixel frames, 220-221 resolution, 221 sensory processing and, 235-237 space, 219 WM and KD modules, 216-218 World model (WM) module hierarchical levels, 204 control systems, 201-202 intelligent system architectures, 216-218 sensory processing and, 231 Y Youden, W J., 20-21 Ζ Ζ displacement errors, 174-178 Zero, dimensional measurements, 129 error of, 131 summary and analysis, 154-155 ... interchange of process and product information THREE PILLARS OF MANUFACTURING TECHNOLOGY RESEARCH AND DEVELOPMENT Machine Tools Computers 11 1 STANDARDS AND MEASUREMENTS Figure Three Pillars of Manufacturing. .. theme of "Manufacturing and Automation Systems: Techniques and Technologies. " "Three Pillars of Manufacturing Technology" is the title of this volume It is edited by Richard H F Jackson, and its... Washington Seattle, Washington V O L U M E : MANUFACTURING AND AUTOMATION SYSTEMS: TECHNIQUES AND TECHNOLOGIES Part of Three Pillars of Manufacturing Technology ACADEMIC PRESS, INC Harcourt Brace