00100	The Computerized Factory
00200		Ray Doedecker, Asst Plant General Manager
00300			Systems Manuf Div, IBM, Poughkeepsie, NY
00400	
00500	Use of computerized automation at IBM.  
00600		Design automation for electronic circuits
00700			check components specs
00800			lists of components
00900			logic diagrams
01000		manufacturing instructions
01100			automatic or hand wire-wrap
01200			pc cards
01300			in-process tests
01400			control assembly machine for discrete wiring
01500			record data on work completed
01600			holes in pc cards
01700		manufacturing computer enclosures
     

00100		COST ESTIMATES
00200	
00300	QUANTITIES OF 1, IGNORE ENGINEERING COSTS
00400	Q1000	INCLUDE ENG COST; ESTIMATES ARE JUDGED CONSERVATIVE BY SCHEINMAN
00500	
00600	
00700	DEVICE		1973		1978
00800	
00900	TV (BW)		$300
01000		Q1000	$200
01100	
01200	MONITOR		$150
01300		Q1000	$70
01400	
01500	CAMERA,SOLID STATE
01600	 COLOR,256x256		Q1000	$1000	HOPE FOR BETTER(PICTUREPHONE IMPETUS)
01700	
01800	PAN/TILT	$700
01900		Q1000	$350
02000	
02010	TV INTERFACE	$1000
02020		Q1000	$300
02030	
02100	FOCUS/ZOOM	$500
02200		Q1000	$300
02300	
02400	LASER		$250
02500		Q1000	$175
02600	
02700	LASER DEFL	$400
02800		Q1000	$250
02900	
03000	
03100	ARM		$3500		WITH 2 FINGER PGRAM HAND
03200		Q1000	$1000
03300	
03400	TOUCH&FORCE	$1200
03500		Q1000	$600
03600	
03700	HAND		$1500
03800	 3 FINGER,ARTIC $750		TOMOVIC HAND $2500 IN UNITS OF 1
03900	
04000	
04100	COMPUTER	$4000		TI 980A WITH MUL/DIV
04200		Q1000	$3000		$1000
04300	
04400	EXTRA MEMORY FOR VISION 8Kx16 BITS, 170x170 4 BITS
04500		Q1000	$1000
04600	
04700	
04800	
04900	SYSTEM COSTS Q1000
05000			MINI		MAXI
05100	TV ELEC				$470
05200	TV MECH				$650
05300	LASER				$425
05400	2 ARMS		$2000		$2000
05500	TOUCH&FORCE	$600		$600
05600	COMPUTER	$3000		$3000
05700	EXTRA MEM			$1000
05800	
05900	
06000	TOTALS		$5600		$8200
06100	
06200	SELLING PRICE	$12000		$17000
06300	
06400	INCREMENTAL COST ADDED TO UNIMATE (Q1000, ASSUME $25K UNIMATE)
06500	TOUCH&FORCE	$600	PRICE $1200	5%
06600	VISION W/MEM	$2200	PRICE $4400	16%
06700	
06800	A widely quoted capital cost for economically replacing one-shift
06900	assembly line worker in the automobile industry is $20k-$22k.  For
07000	isolated assembly stations, the economic cost-benefit analysis
07100	is quite simple; one merely compare cost vs man-shifts.  Almost always,
07200	there will be interactions, which we cannot predict.  Maintenance, at
07300	one man for twenty manipulators, is not more than equivalent supervisory
07400	staff for workers.  Design interactions can raise the cost, but this
07500	is not uniformly true.  In many cases, subsidiary improvements can be
07600	made in the interfacing process, which result in additional savings.
     

00100	GNP
00200		$217 BILLION	30.2%   1970
00300	PRODUCTION WORKERS
00400		MOTOR VEHICLES	580,000	VALUE ADDED	$14.5 BILLION
00500		METAL PRODUCTS	575,000			$11.5 BILLION
00600		INSTRUMENTS	385,000			$10.1 BILLION
00700		ELECTRICAL	623,100			$13.4 BILLION
00800		
00900	50% OF PRODUCTION IS BY FIRMS WITH GREATER THAN 5000 EMPLOYMENT
01000	
01100	ESTIMATE OF SAVINGS IN DOD WITH PROGRAMMABLE AUTOMATION
01200		2.2 BILLION OUT OF 13.3 BILLION 16%
01300	
01400	ESTIMATE IN MANUFACTURING SAVINGS WITH PROGRAMMABLE AUTOMATION
01500		$27.6 BILLION OUT OF 492. BILLION	5%
     

00100	applications of robotics research
00200		automated assembly
00300		computerization of industry
00400			group technology
00500			scheduling and routing
00600	
00700	
00800	
00900	
01000	benefits of robotics research
01100		productivity increases
01200		social need for productivity
01300			social service needs
01400			more leisure
01500			unmet material needs: housing,public transit, poverty
01600	
01700	areas of robotics most likely to have short term payoff:
01800		manipulation w/ touch
01900		representation of shape and space
02000		perceptual systems-integrated systems
02100	
02200	necessity for programmibility in robotics
02300	
02400	structure of models
02500	
02600	knowability of things
02700		permanence
02800		contiguity
02900		computational requirements
03000		separability of objects
03100		independence of variables
03200			interactions separately described
03300		classification:objects cluster  can be classified into similarity classes
03400		structure		part/whole
03500		form=function
03600	
03700	mechanistic interpretation of affective behavior
03800			eg force someone to do something
03900	symbolic models
04000	
04100	
04200	information science in production
04300		systematizing control of production
04400		modularization and commonality of parts and operations
04500		description of parts and objects
04600		design automation
04700		analysis of tasks
04800		communication and file storage
04900		scheduling
05000		routing
05100		sensing, monitoring
     

00100	REPRESENTATION OF SHAPE
00200	
00300	what tasks required of a representation
00400		choice of parts
00500		manipulation
00600		avoidance
00700		display
00800		recognition
00900		visual feedback
01000		perceptual strategies
01100		learning
01200		3-d cues
01300	
01400	what operations required
01500		display-2 dim proximity
01600		manipulation-center of gravity,center of rotation,length, thickness
01700		avoidance-3 dim proximity, find free space
01800		visual memory-encode shape into memory reference descriptors
01900		recognition-features,visual memory,hypotheses,prediction,verification
02000			geometric relations among parts
02100		
02200		simplicity criteria for cross section function
02300			constant
02400			monotonic
02500			continuous
02600			number of maxima
02700	
02800		curve representation is topologically inadequate in 2d
02900		surface representation is topologically inadequate in 3d
03000			a)curve is one-dimensional
03100			  surface is two-dimensional
03200			b)when do we need higher dimensions-proximity
03300			  choice of parts
03400				volume-parts vs surface-parts
03500				area-parts vs curve-parts
03600			c)local realizability
03700			d)dimension arguments
03800	
03900		proximity
04000	
04100		fabrication operations
04200		form=function heuristics
04300		ease man-machine communication		technology transfer
04400			input devices -3d
04500			symbolic input
04600			high-level manipulation
04700		predictive results for perception
04800		initial organization
04900		
05000		level of representation
05100		symbolic descriptions--iconic descriptions
05200		example of gravity discussed at coffee
05300		what are we going to do with descriptions
05400		descriptions relative to what we are going to do with them
05500	
05600		important properties are not in 2d image: 3d interpretation
05700		
05800		system should be a programming language
05900			modular
06000			heterarchical
06100			redundancy, consistency, inconsistency
06200			problem-solving system
06300			approximation of decision trees by statistical estimates
06400	
06500		desiderata for representation
06600			generative
06700			levels of detail
06800			3d interpretation
06900			high level
07000			mechanism for similarity
07100			part/whole segmentation structured description
07200	
07300		schema, additions, deletions, transformations
07400	
07500		volume representation
07600		similarity as a paradigm problem
07700		choice of paradigms
07800		principle of redundancy, hypothesis and verification
07900	
08000		significance of shape representation
08100			fabrication operations
08200			form=function
08300				basis for extending Winston's learning paradigm
08400			ease of man-machine communication
08500				input 3d
08600				display
08700				primitives for programming
08800				common vocabulary
08900			useful in initial organization stages
09000			useful for monocular vision
09100	
09200			group technology and overall computer control of production
09300				analysis of assembly tasks
09400				description of parts and objects
09500				modularization of process
09600				commonality
09700				automated parts description
09800				task programming for robots
09900				machining descriptions,selective accuracy and monitoring
10000			graphics
10100			visual feedback
10200			
10300	
10400		partial knowledge--backs of objects invisible in single scene
10500	
10600		visual memory
10700	
10800		3d representation valuable since accurate predictions can always
10900			be made; not true with 2d representation
11000	
11100		for man-machine communication, machine should have same
11200			concepts as man
11300			understands objects in terms of pieces joined
11400			or in terms of fabrication operations (lathe,drill)
11500			pasting
11600		relationships
11700			near
11800			touch
11900			inside
12000			join
12100			cross
12200			overlap
12300			parallel
12400			corresponding
12500			adjacent
12600			above
12700			left,right,in front,behind
12800	
12900		see many problems as AI problems
13000			graphics
13100			computer languages
13200	
13300		experimentation and learning
13400		three models for learning
13500			statistical inference
13600			deductive/inductive
13700			experimental paradigm of construction of models
13800				independence of variables, specified interactions
13900	
14000		depth information as a way of building up the map
14100	
14200		bilateral symmetry
14300	
14400		three-dimensional cues
14500			
14600		joints
14700			sleeves
14800			parallel joints-flat
14900			conservation at joints
15000		intersections as cues to shape
15100		depth measurement techniques
15200			laser
15300			stereo
15400			phase modulation
15500			time of flight
     

00100	description
00200		computational aspects
     

00100	Vision as a description process, not vision as a data reduction process.
00200	Not what to forget, but what is worth remembering?  In what form is
00300	it worth remembering?  Only that which can be made sense of is worth
00400	saving.  I.E., descriptions, some images (for motion parallax).  Most
00500	images have no worth for later times, since they will not reappear
00600	in just that way, although parts of them might and may be saved as such.
     

00100	Waltz
00200		edge labels
00300			convex
00400			concave
00500			obscuring
00600			shadow (planar)
00700			crack  (planar)
00800		illumination labels
00900			illuminated
01000			shadowed
01100			self-shadowed (facing away from the light source)
01200	
01300		consistency conditions
01400			a line must have the same label from vertices at both
01500			ends.  Thus, the possible labels for a line are the
01600			intersections of the labels for vertices at both ends.
01700			The possible labels for a vertex are the interpretations
01800			which have consistent line labels for all lines.  Possible
01900			interpretations for a cycle of vertices around a region
02000			assign consistent line assignments and illumination
02100			assignments.
02200	
     

00100	Guzman
00200		Roberts used concavities and T's to guess unobscured and obscured
00300		faces of polyhedra in order to fit template models to line-drawing
00400		data. [TOB note: he could have done better by fitting lines than
00500		by fitting points].
00600		Guzman departed from template fitting to separate objects in some
00700		reasonably complex scenes of polyhedra.  He used local evidence
00800		from some vertices to link regions.  Doubly linked regions were
00900		joined as objects, and any regions linked twice to these objects
01000		were joined, iteratively.  Double linking eliminated some errors
01100		in joining, but had to be followed by a joining of regions linked
01200		by a weak and strong link, or single regions linked only to the
01300		body.
01400		The primary links were given by three-line-vertices which were
01500		not a T (indicating obscuration), between regions which had no
01600		concavity (it also inhibited links depending on the background).
01700	 A refinement inhibited links if either region was
01800		concave or had an angle of pi at the next vertex along the common
01900		line.  Thus the system really depended on concavity,
02000		and on knowledge of the background (given from outside).
02050		We could phrase that condition that a line should be terminated
02075		properly at either end, where terminated properly has the meaning
02087		of each region is strictly convex (less than pi) at the vertex.
02100			Links
02200				Y
02300				Arrow
02400				X 
02500				Peak
02600				matching T's
02700			Local Links
02800				Legs
02900				Triangles
03000	
03100			SMB links
03200			
03300		When did it do badly?	Holes and other non-convex features,
03400		accidental alignment, buried vertices.
03500	Objections
03600		did not work very well
03700		was not extendable despite a lot of work
03800		was a cookbook; gave no semantics
03900		required being told background
     

00100	ROBERTS
00200		3-D SCENES
00300		COMPLETE SYSTEM
00400		USED 3-D MODELS WITH PART/WHOLE SEGMENTATION
00500		BASED ON MATCHING, NOT ON SEGMENTATION BASED ON DEPTH CUES
00600		ASSUMED PERFECT LINE DRAWING
00700		SEPARATION OF HIGH LEVEL AND LOW LEVEL
00800		LINE FINDER AND ORGANIZER PASS-ORIENTED
00900			SUCCESSIVELY MORE GLOBAL
01000			FAIRLY WELL DONE
01100		SOME CAPABILITY WITH OBSCURED OBJECTS
01200	
01300	
01400	
01500	OBTAIN LINES
01600		GRADIENT THRESHOLDED, MAX SAMPLE ON A 4X4 NBHD
01700			T=IMAX/10
01800		CORRELATE WITH LOCAL LINES IN 4 DIRECTIONS
01900			REQUIRE BEST/WORST>3
02000		CONNECT LINE FRAGMENTS
02100			ADJACENT 4X4 NBHDS
02200			LINE WITHIN 23 DEGREES OF BOTH FRAGMENTS
02300		ELIMINATE UNCONNECTED FRAGMENTS
02400		REDUCE LOOPS OF 3 AND 4 FRAGMENTS
02500		LONGER CONNECTIONS-SINGLY CONNECTED
02600		SEQUENTIAL EXTENSION WITH LEAST SQUARES TO DETERMINE CORNERS
02700			RMS ERROR TEST, BACKUP
02800			EXTEND IN OTHER DIRECTION
02900		LINE MERGING AND GAP BRIDGING
03000	
03100	POLYGON PROCESSING
03200		LINES
03300		LINK TOGETHER NEARBY END POINTS, ORDERED BY ANGLE
03400		INTERIOR AND EXTERIOR (SUM OF ANGLES)
03500			CONCAVITIES
03600			T'S
03700		SELECT "COMPLETE POLYGONS", W/O CONCAVITIES, W/O STEMS OF T'S
03800			MODELS HAVE 3,4,6 SIDED POLYGONS
03900	
04000	MODEL MATCHING
04100		POINT BOUNDED BY COMPLETE POLYGONS	N3,N4,N6 ORDERED LIST
04200		LINE BOUNDED BY TWO COMPLETE POLYGONS
04300		COMPLETE POLYGON W/ EXTRA LINE
04400		POINT W/ 3 LINES
04500	
04600		DETERMINE THE BEST TRANSFORMATION FROM THE MODEL TO THE
04700		DATA POINTS, MEASURED BY AN RMS ERROR, AND SUCH THAT NO MODEL
04800		POINTS LIE OUTSIDE THE BOUNDARIES OF THE OBJECT, SINCE THEY
04900		WOULD GIVE RISE TO NEW LINES.
05000	
05100			DESCRIBES OBJECTS BY SUCCESSIVELY RECOGNIZING PARTS
05200			WHICH ARE AMONG HIS MODELS AND DESCRIBING WHAT IS
05300			LEFT.  HIS MODELS ARE RIGHT PRISMS OF 3,4,6 FACES,
05400			IE, BLOCKS, WEDGES, AND HEXAGONAL PRISMS.
05500	
05600		TO RELATE A MODEL TO IMAGE PTS, FIND A MATRIX H
05700		AND A DIAGONAL MATRIX D SUCH THAT FOR MODEL PTS A
05800		AND IMAGE PTS B
05900			AH=DB
06000			A=(A11,A12,A13,A14)  ROW VECTOR OF FIRST MODEL POINT
06100			  (A21,A22,A23,A24)  ROW VECTOR OF SECOND MODEL POINT
06200			  ................
06300	
06400			H=(H11,H12,H13)
06500			  (H21,H22,H23)
06600			  (H31,H32,H33)
06700			  (H41,H42,H43)
06800	
06900			B=(B11,B12,B13)  ROW VECTOR OF FIRST POINT
07000			  (B21,B22,B23)	 ROW VECTOR OF SECOND IMAGE POINT
07100			  ...........
07200	
07300		NOTE THAT HE USES POSTMULTIPLICATION AND ROW VECTORS.
07400	
07500		THE MATRIX H IS RESTRICTED SOMEWHAT IN AN AD HOC FASHION.
07600		DETERMINE A MATRIX R WHICH IS SUCH THAT
07700			H=RP	WHERE P IS A PROJECTION
07800		THEN  	R=H*INV(P) WHERE INV(P) IS INVERSE OF P.
07900		R IS A 4X4 MATRIX WHICH HAS 15 DEGREES OF FREEDOM
08000		WE WANT TO ALLOW TRANSLATION, ROTATION, AND SCALING
08100		ALONG 3 AXES; NINE DEGREES OF FREEDOM.  THE OTHER
08200		SIX DEGREES OF FREEDOM CORRESPOND TO SKEW (CUBE TO PARALLELIPIPED)
08300		AND PERSPECTIVE (COMPRESSION OF ONE END OF MODEL).  WE
08400		IGNORE SKEW AND PERSPECTIVE.  WE REQUIRE THE PERSPECTIVE COLUMN
08500		OF THE TRANSFORM R TO BE ZERO, AND INCORPORATE ALL PERSPECTIVE IN
08600		A SINGLE PERSPECTIVE TRANSFORM P.
08700		REQUIRING ZERO SKEW IS EQUIVALENT TO REQUIRING THAT THE 3X3 SUBMATRIX
08800		BE ORTHOGONAL (IE A ROTATION).  
08900	SUPPORT
09000		THE ANGLES OF PLANES IS KNOWN.  EACH PLANE TESTED:
09100			NOT VISIBLE
09200			DOWNWARD Z DIRECTION
09300			APPROXIMATELY HRIZONTAL
09400		CHOOSE BEST PLANE FOR EACH OBJECT.  SHOULD BE SAME ORIENTATION
09500		FOR ALL OBJECTS IN PICTURE.
09600	
     

00100	Minsky and Papert	AI Memo 252
00200	
00300	"blocks world" robotics environment and children's stories better suited
00400		to these studies than puzzle, game, and theorem-proving environments
00500	Thinking is based on the use of SYMBOLIC DESCRIPTIONS and description-
00600	manipulating processes to represent a variety of kinds of KNOWLEDGE--
00700	about facts, about processes, about problem-solving, and about computation
00800	itself, in  ways that are subject to HETERARCHICAL CONTROL STRUCTURES--
00900	systems in which control of the problem-solving programs is affected by
01000	heuristics which depend on the meanings of events.
01100	
01200	The ability to solve new problems ultimately requires the intelligent
01300	agent to conceive, debug, and execute new procedures.  Such an agent
01400	must know to a greater or lesser extent how to plan, produce, test,
01500	modify, and adapt procedures; in short, it must know a lot about
01600	computational processes.  We are not saying that an intelligent machine,
01700	or person, must have such knowledge available at the level of overt
01800	statements or consciousness, but we maintain that the equivalent of such
01900	knowledge must be represented in an effective way somewhere in the
02000	system.
02100	
02200	REASONING BY ANALOGY
02300		
02400		Make up a description D(A) for figure A
02500		Make up a description D(C) for figure C
02600		Change D(A) so that it describes figure B, ie T(D(A))=D(B)
02700			Make a description for the way that D(A) was changed to D(B)
02800		Use D(T) to change D(C)
02900	
03000	children use schematic descriptions to represent geometric information
03100		folded-out cube drawing vs perspective drawing
03200	children's drawings are nearer to internal representation
03300		face is a square
03400		each face meets four others
03500		all plane angles are right angles
03600		each vertex meets 3 faces
03700		opposite edges on faces are parallel
03800	perspective drawings are nearer to external world
03900	We might observe that the child's drawings are closer to the internal
04000	representation, the adult's to the raw image.  The adult's has utility
04100	in being able to go through the perceptual mechanism to communicate
04200	to the internal representation.
04300		this is a good way of communicating with the interior representation
04400		by way of simulating the external world
04500	
04600	LEARNING STRUCTURAL MODELS
04700	discussion of the pass-oriented model of human visual perception
04800		not entirely wrong, or useless
04900		introduces HETERARCHY
05000	leads in from Gestalt; what is not a sum of its parts?
05100	computational theory Perceptrons
05200	
05300	Guzman
05400	Rattner
05500	Learning
05600		primary question what to remember
05700		learning is not separate from other intelligent activity
05800	
05900	do not attempt unsound approaches to learning:
06000		learning based not on bookkeeping, but exploring structure
06100	learning to learn requires describing processes and manipulating
06200		such descriptions
06300	
06400	Piaget's conservation experiments
06500		model for the performance of the non-conservation child
06600	
06700		A scenario for considering descriptions for the child in
06800		the egg experiment.  
06900			QUANTITATIVE
07000				SPATIAL
07100					EXTENT means more
07200					SPARSENESS means less
07300				NUMERICAL
07400					counting
07500					one-one correspondence
07600			HISTORICAL
07700				IDENTITY  none added or taken away
07800				REVERSIBILITY  spreading out is reversible
07900	
08000		quantitative seems inconsistent, HISTORICAL SEEMS CONSISTENT
08100		
08200	[ASIDE, I suppose that the maturing is actually in coming up with
08300	these sophisticated descriptions]
08400	
08500		the secret of learning often lies in the discovery of descriptions 
08600		that emphasize the "essential" aspects of things or events, and omit
08700		or subjugate the "accidental" features.
08800	
08900	parameter modification
09000		severe limits on class of things learnable in this way
09100		end up only with coefficients, not a symbolic analysis
09200			which another program might use.
09300		alternative for game-playing
09400			instead of returning a low numerical value for a position,
09500			return a description of why the position is bad.
09600			Then the plausible-move generator can look for moves
09700			which defend that square or pin attackers.
09800			Or return a description of why the move is good to look
09900			for enemy replies.
10000		misconception about the significance of trial and error
10100			many small qualitative changes to procedures
10200		[I doubt whether multi-layer devices are interesting without
10300		modularity]
10400	Winston
10500		network of objects, relations, and relations between relations
10600		specially chosen examples and counter-examples
10700		if counter-example     "near-miss"
10800			note the difference
10900			amend description to reject an addition
11000				or require a deletion
11100		if example
11200			note the difference
11300			amend description to allow the difference
11400				if substitution then generalize to smallest class
11500					containing both
11600	
11700		relations between relations are included
11800		grouping
11900			
     

00100	robots will force planning and organization of the manufacturing process
00200	to establish modularity
     

00100	Lindbom, Unimation, 2nd Int Symp on Indust Robots, p129
00200	short runs, manual labor
00300	long runs, special-purpose automation
00400	programmibility for short to medium production runs
00500	memory size-a few hundred steps
00600	branching and control
00700	find less expensive to have extra degree of freedom than to make special
00800		purpose device, or move production machinery
00900	accuracy .050".  greater accuracy possible using slides and guides
01000	
01100	advantages of robots in automation
01200	
01300	a)  direct sensor input from tools in modes not natural for humans
01400	b)  high data rate from sensors to control to effectors
01500		Humans are
01600		faster when information can be input to their visual or
01700		auditory systems which are highly parallel, but much information
01800		cannot be directly input.
01900	To bring about a transfer of technology from the laboratory to pilot
02000	production, several concurrent phases are necessary:
02100		systematize hardware (cost conscious)
02200			Scheinman arm
02300			sensor study
02400			standard interface and pan/tilt for visual devices
02500			adopt commercial visual hardware
02600		systematize software and interaction
02700			hand/eye system
02800			drawing program
02900			experience with low/cost graphics
03000		ease of problem specification
03100			visual representation
03200			geometric editor
03300			visual input
03400			perceptual strategies
03500		standardize economical computer configuration
03600			alternative is de facto standards at lower level
03700			powerful force for guiding manufacturers of minis
03800		provide powerful modules to broaden engineering choices
03900		design inherent reliability.
04000			continuous self-calibration
04100			disaster detection and contingency planning
04200			wide latitude in tolerances
04300			low incremental cost in quality control
04400			continuous monitoring of function and product quality
04500	
04600	A plant would normally have a central time-sharing system which would
04700	monitor and schedule operations of machines and subsystems.  That
04800	provides a natural subdivision of abilities between the small computers
04900	which would control one or more machines, and the central system which
05000	would provide file storage and software support for large programs.
05100	Thus, we would find that the central computer would support:
05200		interactive job specification
05300			mechanical computer-aided design (CAMD)
05400		strategies
05500		complex vision for recovery (interrupt basis from minis)
05600	while the small machines would have, in addition to the arm control
05700	and contingency planning described above:
05800		visual feedback prediction and verification (Gill)
05900		edge and line finder (Hueckel)
06000		corner finder (Gill)
06100		region finder (Baumgart)
06200		color regions
06300		2-D template matching of shape
06400		access to large machine for contingency
06500	overall significance of information sciences in industry
06600		batch production
06700		control of scheduling, resource allocation, flow routing
06800		commonality of design
06900			find common fabrication and assembly operations
07000			find more common components
07100		increased understandibility and communication
07200			availibility of information
07300				keep track of delayed effects of design decisions
07400				cuts cost of preparation and transmission
07500				increased accessibility of information