The development of an integrated and intelligent CAD CAPP CAFP environment using logic-based reasoning.pdf

computww8dlte it may force a designer to work on the low levels of details and specifications at the early design stage most feature recognition research applied to csg or b rep solid models uses the method of syntactic pat tern recognition to find machinable features without an integrated and intelligent cadgappkafp environment j y h fuh et al addressing the issues of features relationships or non geometric information existing on 2d engineering drawings this information however is important to designing and planning the manufacturing processes manufacturing process planning is traditionally based on engineers experience a great deal of research work has been carried out on computer assisted process planning capp since the middle of the 1970s al though a great number of capp systems have been developed only a few systems have actually been used by the industry the lack of a scientifically vigorous base for process planning is the major problem in current capp research lo a review of the current re search on capp and cafp indicates that separation of fixture planning from process planning and insufficient study of process and fixture planning practice in indus try are among the major problems which hamper the development of an automatic process planning system research on cafp has been concentrated basically on two areas to search for a mathematical solution for locating and holding a part1 15 and to reduce fixture planning into computer routines fixture planning with rule based expert system is discussed in references 16 20 a review of the current cafp research was recently made by change21 indicating that 1 although being a part of process planning fixture planning has been undesirably separated from process planning in the cafp research 2 some of the factors that have a significant effect on fixture planning such as position and orienta tion tolerances and the form irregularity of the initial workpiece or raw material have been ne glected overview of our approach our system has three basic application models namely feature analyser process planner and fixture planner built on the top of the cadlog system a distin guished feature of our system is the integration of process planning with fixture planning most existing capp systems for machining processes do not consider the fixturing requirements since a machining opera tion can be performed only when the stock material or the intermediate workpiece is located and clamped properly a process plan generated without considering fixturing can be hardly workable in most cases the feature analyser module serves as a cap to c 4m figure i bridge which extracts the geometric informa tion from the cad model and interprets the manufac turing information contained in the 2d engineering drawings based on the information obtained the process planner module determines the required ma chining operations their sequence and the machines and toolings to be used according to the design infor mation and the process plan generated by the process planner the fixture planner module selects the modu lar fixture components and determines the fixture con figuration or layout such that the workpiece can be properly located and held during machining potential cadlog is the ucla intelligent cali system constructed by interfac ing cajmm system with ibm vm prolog to allow interpretation of 2d and 3d cad entities see reference 22 218 1 cad cam figure 1 the relation and information flow among the three major modules tooling problems can be identified and fed back to the design workstation for improving the part design and its manufacturability as well as to the process planner to ensure that a workable process plan can be ob tained cad interface c 4dlog system cadlog was originally developed at ucla computer aided design laboratory to provide the foundation for extracting and reasoning about cad drawings from a commercial cad cam system in this case cadam it provides a graphical environment to extract a 2d or 3d drawing directly from a cad system and performs reasoning operations on its geometric features the reasoning operations are carried out through logical inferences provided by the underlying computer lan guage prolog figure 2 shows the mechanism used in cadlog system to translate drawing entities into prolog facts for reasoning applications the use of cadlog system allows for 1 easy geo metric reasoning from a cad system without interpret ing its cad database in details 2 an interactive graph ical environment to display execution results of the application programs from the screen and 3 the capabilities for working in both prolog mode and cadam design mode with the aid of the cadlog system this integrated system can be built as a graphics oriented one this graphic feature provides unique advantage previous applications developed by our group using this approach include automatic 2d to 3d model construc tion23 design chec king for productibility automatic dimensioning for 2d drawings process plan generator for prismatic machined parts24 and nc program gen erator for machining certain manufacturing features25 logic based reasoning using prolog our system adopts a logic based approach by using the principle representing and specifying the problem in figure l cad to prolog model translation22 an integrated and intelligent cad cwp gafp environment j y h fuh et a logic axioms on which the reasoning processes can be performed prolog programming in logic is a com puter language used for solving problems that involve objects and the relationships between objectsz it has been chosen by many programmers for applications of symbolic computation including relational database mathematical logic problem solving natural language processing design automation rule based expert sys tems and many areas of artificial intelligence the behaviour where prolog interpreter will repeat edly attempt to satisfy and re satisfy goals in a conjunc tion is called bucktrucking this unique feature creates fast and natural pattern matching and inferencing in a large database in our application prolog becomes an efficient tool to perform geometric reasoning based on the large amount of drawing primitives created by the cadlog system design and manufacturing principles can be easily formulated into prolog rules that can be modified added or deleted from the knowledge base without major changes in the program knowledge representation the core of an intelligent system is its inference engine or reasoning mechanism in this system manufacturing knowledge provided by experienced manufacturing process planners is represented as a collection of rules and facts for making decisions these rules and facts are formalised as predicate logic and implemented as rules in prolog language there are three classes of knowledge stored in our system 1 procedural knowledge which is often rep resented as if conditions then actions rules 2 declarative knowledge which consists of the data that define specific facts such as part design machine and tooling resources and 3 control knowledge which determines the sequence in which rules are applied and facts are searched figure 3 shows the relationship among the three classes of knowledge reasoning is performed through symbolic manipulation based on the defined production rules manufacturing knowledge is symbolically expressed in the form of prolog terms facts and clauses rules these facts and rules together with the control knowledge constitute the inference engine and are symbolic manipulation declmiie knowledge procedure knowledge figure 3 the relationship among the three classes of knowledge stored in a temporal workspace or memory for rea soning and analysis there are various kinds of rules built into our system which are developed based upon the principles of machining they include rules to create machining processes machine and tooling selection rules constraint rules to obtain the feature precedence relationships fixturing rules or work holding principles and execution control rules to guide the problem solv ing when multiple rules are included in a knowledge base a certain number of rules must be used as controz knowledge these rules different from the task specific production rules control the sequence in which other rules are applied thus the efficiency of prob lem solving can be dramatically increased these kinds of control rules can be viewed as meta rules meta knowledge has been used extensively in many systems for controlling the activation of rule bases in our system machining rules are classified as groups and are searched sequentially until certain conditions are met during process reasoning once the rule bases become large the controlling schemes of meta rules should be implemented one of the strategies that specifies the sequence for executing rules can be de scribed by the followingz7 if certain conditions true then order rule 1 rule 2 rule 3 rules n the order states that rule 1 is applied first from the list of the eligible rules and rule 2 is applied in case rule 1 fails etc each rule is represented as a functional term goal that needs to be satisfied one after another under the prolog environment since rules contain information about their contents the rules to be satisfied can be dynamically allocated with out searching through the entire rule base blackboard architecture many expert systems have been developed from the use of blackboard architecture 28 29 for solving complex problems the blackboard is a good means of commu nication between different knowledge sources it serves as a manufacturing ad converting the geometrical and textual informa tion into prolog assertions recognition of machinable features with the aid of predefined algorithms and rules identifying spatial relationships among features through geometric reasoning interpretation of features through pattern search ing and matching attaching the manufacturing attributes to the ex tracted features outputting machinable features together with their relations and dependencies geometric information from the 3d model the 3d geometric model of a part contains the infor mation regarding the part geometry and topology that can be used to define machinable or manufacturing features since our system is designed for planning the machining process features extracted are machinable ones such as holes counter bores pockets slots grooves etc each feature is defined according to its geometric characteristics the definition for various features can be very ambiguous this results in difficulty in feature extraction generic recognition rules are then defined to uniquely identify a machinable feature the geometry and topology information required for defining features is extracted from a 3d enhanced wire frame model a model is initially created as a wire frame model in the cadam system it is then converted by a routine into a quasi surface model containing the information regarding the connectivity of geometric entities and the surface normals the 3d and 2d cad drawings are defined by formatted prolog assertions generated by the cadlog system see references 22 and 301 geometric and topological reasoning is per formed through predicates or goals defined in prolog table 1 gives the prolog assertions or descriptions of a part which are generated based on the information contained in the cadam database each geometry en tity such as line circle or face is treated as a separate element and has a unique identification num ber through the cadlog interface the geometric model of a part can be extracted from the cadam database and then translated into assertions which contain the parameters defining the geometric ele ments toplogy information defining the connectivity of the geometric elements can also be obtained see table 2 and figure 5 the feature analyser identifies a machinable feature according to the feature recognition rules and the relationships among geometric entities that constitute the feature the feature recognition rules should first be defined in words unambiguously then computer routines can be designed accordingly to perform the identification task for example to identify the feature of a through slot figure 51 the following feature recogniture rule written in the vm prolog31 format is used find slot i share pl p4 0 2 a minimum number of part setups 3 feature dependencies or feature con strains and 4 the dimension and tolerance require ments the process planning routine in our system follows a rule based approach and generates multiple process plans which satis the built in rules of constraints derived from machining practice by taking dimension and tolerance requirements into account this method allows the creation of multiple process plans without exhaustively searching the entire problem space for the possible choices fixturing requirements or locating and clamping conditions are determined after a pre liminary process plan is created thereby potential tooling problems can be identified at the initial stage of planning such a concept is adopted in the fixture planner module not only to select fixture components and to determine fixture configurations but also to optimise the operation sequence through reducing part setup changes consequently an optimised process plan can be generated figure 6 shows the flow chart of the process planning routine a graphical interface routine has also been developed to display the interme diate shapes of a workpiece sequencing of identified machinable features precedence relationship of features there are two types of feature precedence relationship to be considered for the determination of operation sequence one is prior which specifies that a feature should be machined before another and the other is together which indicates that two or more features can be made with the same fixture in the same setup position the cad model of a finished part is first decomposed into a set of features to be machined the built in constraint rules which are formulated on the basis of general machining principles are then used to define precedence relations among these features the relationship that feature fi should be machined before feature fi can be expressed as l fi or in prolog assertion ptior l fi 221 an integrated and intelligent cadicappkafp environment j y h fuh et al table 1 prolog assertions created by cadlog for representing the geometry of a 3d model drawing idkxd demol partl wno o elname 1619 cdt3dcxcenibr 4 49997330 0 502999902 endl 4 43887520 i 04959488 0 31999993 1 io 319999933 end2 4 06260300 0 836477220 0 319999933 1 begin angle 1 57079506 end angle 2 37884712 1 majorradius 0 549999535 1 minor radius 0 549999535 veci orl 0 546595573 vec tor2 0 061097499 3 0 0610975623 0 0 1 0 546595037 0 0 1 line type o color 0 drawing id cad demol part l vuno ol elname 16191 ati rib numalx 58i at 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0111 circle or arc drawing id cad demol part 1 wnch o elname 1619i groupnamh 11 f line drawing id cad demol part wncx o elname 26091 cdt3duendr 4 49997044 0 346997261 0 0 1 end2 4 49997234 0 0470002294 0 0 line type ol coior 0 1 drawing id cad demol part vuno o elname 2609 altrib numatii 177 ats 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 drawing id cad demol part 1 vungf o groupnama 11 attrib numatii l ats 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 319999933 1 00000000 0 0 0 0 i drawing id cad demol part 1 wng o elname 1619 groupnamh 22 planar surface drawing id cad demol part vuncx o groupnamh 221 attrii3 numatli 22 ats 0 i 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5029999b2 0 549999893 0 319999933 4 4999733b 1 000 and jk can be written as fff fk or in prolog assertion and fi c f4 where nil is a null feature the possible sequence of machining these features can be f f2 f3 f4 f5 ef6 or together fi fi fk suppose that the following features precedence rela tionships exist for features fj i 1 2 6 therefore process plans that satisfy the precedence relationships given above can be generated table 2 prolog predicates used to represent the connectivity of the gometric elements in a cad model maxvohfaces minvol faces vmem facel volumel share facelface2 edgell memberof edgel facel phface id flag cylinder or hole face id vol piane or cylinder normal direction or axis edge id pointl point2 line or circle maximum volume bounded by faces minimum volume bounded by faces face1 is a member of a volume 1 face1 and face2 share edge 1 edge 1 is a member of face11 the face is a cylinder or a hole based on a flag identification of a face normal direction of a face end points of a line or a circular arc point 1 f p fixture planner figure 7 feature dependency resulting from dimension and toler ance requirements note d dependency j face feature an integrated and intelligent cadkappkafp environment j y h fuh et al the ith dependency for the feature fj can be ex pressed as follows d i f d tol toll for dimensional tolerance or d i f spec tol toll for form or orientational tolerance where f the datum for the ith dependency d the dimension of feature fi specified with respect to datum f spec the tolerance type and tol and to1 upper and lower bounds of the tolerance for example three dependencies d l d 2 and d 3 are defined for the whole feature f4 figure 7 df4 1 f 5 500 0 005 o oos df4 2 f2 4 000 0 005 o ooo df4 3 f3 perpendicularity 0 005 0 0001 since features fr f2 and f3 determine the position and orientation of the feature f4 the following feature precedence relations result generation of alternative process plans using process decision graph after the precedence relations among features have been determined the process decision graph pdg as shown in figure 8 is used to determine the logical ways of machining a part the graph makes it possible for the system to find all the operations sequences that conform with the constraint rules hence flexibility of production scheduling and control can be obtained the pdg is generated through fonvurdplunning 34