NASA Technical Memorandum 101633 

THE POTENTIAL APPLICATION OF THE BLACKBOARD MODEL OF 

PROBLEM SOLVING TO MULTIDISCIPLINARY DESIGN 

James L. Rogers 

[HASA-T8-10M33) THE POTENTIAL APPLICATXOI H09-28314 . OF THE BLACKBOaaD HODEL OF PROBLEX SOLY116 

TO MULTIDISCIPLIlAfP DESIGN 

Research Center) 12 p CSCL 09B Unclas 

(MASA. , Langley 

G3/6 1 0224591 

July 1989 

National Aeronautics and 

Space Administration 

Langley Research Center 

Hampton, Virginia 23665-5225 
THE POTENTIAL APPLICATION OF THE BLACKBOARD MODEL 

OF PROBLEM SOLVING TO MULTIDISCIPLINARY DESIGN 

* 

J. L. Rogers 

NASA Langley Research Center 

Hampton, VA 

Abstract 

This paper discusses the potential application of the 

blackboard model of probleni solving IO multidisciplinary 

design. Multidisciplinary design problems are complex, illstructured, and lack a predetermined decision path from the 

initial staning point to the final solution. The final solution is 

achieved using data from different engineering disciplines. 

Ideally, for the final solution to be the optimum solution, there 

must he a significant amount of communication among the 

different disciplines plus intradisciplinary and interdisciplinary 

optimization. In reality, this is not what happens in today's 

sequential approach to multidisciplinary design. Therefore it 

is highly unlikely that the final solution is the true optimum 

solution from an interdisciplinary optimization standpoint. A 

multilevel decomposition approach has been suggested as a 

technique to overcome the problems associated with the 

sequential approach. but no tool currently exists with which to 

fully implement this technique. A system based on the 

blackboard model of problem solving ;ippe;irs to be ;in ideal 

tool for implementing this technique because it offers an 

increnient;il problem solving approach that requires no ;I priori 

deterniined reiisoning path. Thus it has the potentiid of finding 

;I iiiore optinium solution for the iiiultidisciplinnry design 

prohleinh found in tcxlay 's nerospace industries. 

1. Prohlem Backermind 

During the design process. the desigii probleni can be 

decomposed into subprohlenis, eiich pen;iining to a differtiit 

discipliiie. Idenlly, for the finiil solution to be tlie optiniutii 

solutioti, there tiiust be ;I significant iitiiount of coniniunicntion 

iit1iong the different disciplines plus ;I significant amount of 

hth iiitr~tclisciplinnry and ititerdisciplinary optimization. 

In reality, the optimum solution is seldom found in 

today's multidisciplinary design process bec;iuse the m:ijority 

of the design decisions are made in ;I sequence such as the one 

!or aircraft design shown in figure 1. 

typically follows these steps. First, the aerodynmiic enginesrs 

take the initial model. analyze it, perform sonie optii1iiz;itioii. 

and p;iss a model that hiis been nerodyn;iniic;illy constrained 

on to the structural engineers. The structur;iI engineers t;ike 

this constriiined model. milyze it, perform soiiie optimizntion. 

and pass a funher constrained niodel on to the next group of 

engineers for analysis and optimization in their particular 

discipline. This sequenti;il ;ippro;ich to niirltidiscipliii;ity 

design implies that iter;itions iire to be performed until ;in 

optiiiiuni solution is obtiiined. However. kc:iuse of budget 

and hie constr;iints. very few (if any) iterations with 

interdisciplinary optimiz;ition are perfomied. Since rliere is 

little or no interdisciphiry optimization feedback. en2' "ineers 

seldom get ;I ch;ince to an;ilyze md optimize their discipliric 

after changes have been iii;ide by other discipliiies dowistrc:un 

in the design process. Thus, iipplying the discipliiics in simc 

sequcriti;il order and freezing their rcspcctive v;iri;ihlss withoti1 

ariy iiiterdisciplinwy optimiz;ttioii does not neccss:irily yicld 

the glob;illy optimitiii solution. 

1 The design sequence 

The g!oh;illy optimurii solution is 1101 ;ilu;iys ohi;iiried by [lis 

sequenti;il :ipproach to niultidisciplin~iry design hcc;iiise of 1111: 

following pmdox posed by tlie iipproiich. Par;idos: ;IS more 

arid more time is spent on the design, the kriowlcdgc incrc;iscs 

nbout the object being designed. hut the freedoin ahout wliicli 

design decisions can be iiiiitle decre;iscs (see Fig. 2). I 'I'liis is ;I 

result of coi1str;iiiits hcirig iiiiposed by tlie dil'fcrcnt disciplines 

in he drsigii process. Thus ;I lorge percentage OF he crucial 

design decisions thiit iire iii;iile during the early p1i;isc.s of thc 

design process litnit the design I'recdoiii during thc 1:itcr 

ph;l\es. 

,. Io ove:~'cotiie tlie p:ir;iilos ;issociatctl with the scqitciiii;t I 

By nature. iiiir1tidisciplin;iry design prohlcriis ;ire 

;ippro;icli, Sohieski developed ;I niultilevel dccompohitioti 

approxh 

cniiiplex, ill-defined, ill-structured and kick ;I predetermined 

decision path from the initial st;irting point to the t'in;tl 

solution. In this approach, ;I liirgc problem is hrokLn down 

into a hierarchy of smaller. self-contained subprohmis which 

I 

I 
are simple, well-defined, and well-structured (see Fig. 2). 1 lie 

links among these subproblems is preserved. The linking 

information is small relative to the vast amount of information 

that must be processed internally for each subproblem. The 

solution efforts are guided and controlled by a hierarchy of 

goals and suhgoals IO yield a more optimum solution. 

The multilevel decomposition approach proved to be only 

feasible when a problem could be decomposed into a strictly 

top-down hierarchy. Some design problems do not fall into 

this category because there may be a link between two or more 

subproblems at the Same level. To address these other types of 

design problems, Sobieski introduced "a new method based on 

sensitivity analysis of a complex, coupled system which yields 

derivatives of the system behavior with respect to design 

variables fully accounting for the interactions among the 9arts 

3 of the systems and the disciplines that govern its design."- 

This approach is referred to as non-hierarchic decomposition. 

As the aerospace industry moves into the IY"s, new design 

tools are needed to implement both the hierarchic 

deconiposition approach iind the non-hierarchic approach 

coupled with sensitivity analysis to allow the knowledge about 

the object being designed to significantly increase without a 

significant reduction in design freedom. Since both 

approaches brcak a problem down into smaller subproblems, 

the kcy to this solution is to be able to simultaneously consider 

contributions from all the subproblems and handle the tradeoffs up front. Another important research issue remaining for 

implementing this appro;ich is how to incorporiite human 

judgment, control. and creativity into the system. The 

bl;ickbo;ird modcl proposed in this paper appears to be ii 

potenti;il tool for combining the human elements with either 

multilevel decomposition approach to solve niultidisciplin;iry 

design prohlems. 

Newcll said the fnllowing about h1;ickbo:irds: 

"Met;iphoriciilly we can think of D set ot'workers. ;ill looking 

at the same bl;icktxxird: each is able to read everything th;it is 

on it. and to judge when he hiis sonicthiiig worthwhile io ;idd 

to it. This conception is jtist that of Scll'ridgcs' I';iiideriioiiitini: 

;I set of deiiions, c;ich Innking ;it the tot:iI situ;ition ;itid 

shrieking in proportion to wli;it they see tits their n;itures ... ,,? 

i3l;ickho;ird niodcls have ken around lor wvcral ye;irs. 

Nii Ilils written ;in excellent overview of the evolution of 

hl;rckho;ird niodels and the descripti~2s of sonic of the key 

:ipplicntions of bl;ickho;ird systems.' ' 

hrief introduction to the hliickboiird approach to problem 

solving. the three major components of the bl;ickboard model 

(the knowledge sources. the hliickboard dat;i structure, and i!v 

control niech;inisni), and the steps in tlie probleni solving 

This section provides a 

szquence5'6'7 Examples of the components with respect to 

design are given in Section IV. 

h to Problem Solvins 

The blackboard approach to problem solving is composed 

of several steps. First, the problem is divided into loosely 

linked subproblems where these subproblenis correspond to 

areas of specialization. Second, the solution space is divided 

into different levels of abstraction of the problem and 

maintained on a global data base called the blackboard. 

Finally, the knowledge and procedures required to solve the 

problem an divided into specialized knowledge sources to 

solve the subproblems. 

Nii explains the blackboard approdch to problem solving 

in term of putting together ajigsaw puzzles For this 

hypothetical example, picture a mni with ;I large blackboard 

and several people each holding some pieces of it jigs;rw 

puzzle. A few of the people volunteer to put their niost 

promising pieces on the blackbaud. Each person then looks ;it 

their pieces of the puzzle to see if they tit me of the pieces on 

the blackboard. Those that have pieces that fit in the currriit 

state of the puzzle add them to the hl;ick.khoard. Now the group 

examines the current state of the puzzle and their puzzle pieces 

and add the pieces that fit the current st;ite of the puzzle to the 

blackboard. This continues until the puzzle is complete. The 

puzzle can be completed without any comniunic;ition iirliong 

the people in the room. Ewh person is "self-;tctivoting" wid 

adds pieces to the bl;ickboard whenever there is on opportuniry 

to do so. There is no it priori order for placing pieces on the 

blackhoard bec;iuse the order is deterniinrd by the st;ite ot' the 

solution. Thus the solution to the puzzle is completed 

increnient;illy and opportuiiisric;illy instend of systemiiticnlly. 

To add some control to this ;in;ilogy. ;in ;iisle is ;iddc.d to 

the rooni so th;it only one ptrson is ;illowed to go to the 

blacktmrd at a time. Everyone examines the ctirrr'nt st;ite ot' 

the puzzle illid detcnnines whether or not they c;in ni;ike ;I 

contribution to the solution. A innnitor is needed to detcnnine 

who gets to go to the bl;ickho;ird. Everyone who can miikc ;I 

contribution to the solution raises ;I hiid. The monitor LISCS 

some criteria for ni;iking ;I selection hiised on some strategy 

selected for conipleting the puzzle. After th;it piece is ;itltletl. 

others who c;tn possihly ii\;ike ii contrihution r;risc their h;rnds. 

This process continues until the prnhlcm is solved. (l'liis 

serial form of the blackho;ird inotlel works wcll for 

uniprocessor computers, hut much resc;irch reniiiins to he done 

on concurrent problem-solving methods. Nii gives ;I more 

elaborate example of the blackboiird method of probleni 

solving to explain the organizntion of the bl;ickboard ;I d tlie 

partitioning of the knowledge into knowlcdge sources.' This 

level of detail is beyond the scope of this paper.) 

9 
ORIGINAL PAGE IS 

OF POOR QUALITY 

The KnowledPe Sou rces 

The knowledge about the problem to be solved is divided 

into knowledge sources which are kept separate and 

independent. Each knowledge source can viewed as one large 

rule with two parts, a condition and an action. If the condition 

is met, then the action is executed. Therefore, knowledge 

sources are event-triggered because only knowledge sources 

with conditions evaluated to true can have their actions 

executed. The action part of the knowledge source may be 

composed of rules and/or procedures which can execute 

application programs. The action part of the knowledge 

source retrieves the appropriate data defining the current state 

of the problem from the blackboard and applies it to provide 

new information to the blackboard. 

Output from the knowledge sources updates the current 

state of the problem solution on the blackboard and should 

eventually lead to a solution of the problem. Knowledge 

sources do not directly communicate with one mother. All 

communication among knowledge sources is done through the 

blackboard. Only the knowledge sources are allowed to 

modify the entries on the blackboard. By communicating only 

through the blackboard, the knowledge sources can only 

indirectly influence one another when the output from an 

action of one knowledge source produces an entry on the 

blackboard which satisfies or partially satisfies the condition 

of another knowledge source. 

The Blackboard Dntn Structure 

The purpose of the blackboard is to provide ii nie3;ins of 

storing data that is common to more than one knowledge 

source, simplify communication and coordination among the 

knowledge sources, and insure that the solutions generated 

during the design process remain consistent. The blitckbonrd 

acts ;IS an intermediary for the coniniunicntions and 

interactions miong the knowledge sources by storing entries 

generated and needed by the knowledge sources during the 

problem solving process. One way of storing these entries on 

the blackboard is in the form of ohjecrs. Stefik and Bobrow 

define objects ;is entities that combine the properties of 

procedures and data since they perfonn computations and save 

local state. Ench object ciin store and process inforni:irion, 

create new information, and communicate with other objects 

through niesstrges. Messages sent between objects result in an 

action being taken. An object receives ii message which 

specifies some type of operation to be performed. The object 

responds to the message by using its own procedures to 

perform the operation. In other words, message sending is 

similar to an indirect procedure cnll where the message tells 

the object what needs to be done without s:iying how to do it. 

8 

The solutions and partial solutions of the problem being 

solved can be organized into horizontal and/or vertical 

partitions. The horizontal partition of the solution space 

represents distinct partial solutions (or alternative solutions) to 

the problem. These partial solutions may overlap. They 

reflect different groupings of the partial solutions, such as 

temporal, spatial, or conceptual. 

The vertical partition of the solution space (a hierarchy) 

distinguishes objects at different levels of abstraction and 

groups them as classes which are descriptions of one or more 

similar objects. The class objects contain information such as 

super class, class variables, instance variables. The .viper 

class indicates which class or classes a particular class is 

below in the hierarchy. A class inherits v,ariables from its 

super classes which reduces redundancy. An insrnricr of a 

class is an object described by ;I particuku class. Variables in 

objects are used for storing the state of the solution and can be 

given a default value. For exaniple, Car may be a class. 

within the super class Vehicles, with ;in instance Model-T. 

Class variables contain information shared by :dl instances of 

a cliiss. Instance variables (sometimes called slots) ;ire 

variables local to a particular instance. In the c;u exmpk, ;I 

class variable might be nurnber-of-wheels, while an instance 

variable might be CarOwner. All instances of the class car 

will inherit the number of wheels from the class v:uiable w4iile 

having an individual owner. Lids are used to denote the 

relationships among the objects. A Model-T is-a car ;ind car is 

a-kind-of vehicle ;ire ex;iiiipIes of links. By using the links. 

objects c;in be collected into ii group of interconnected objects 

called a coniposife ol>jejcct. A car can be thouglit of ;IS ;I 

composite object because it is composed of ;I body, power 

system, and electrical system. 

of ;I hood. doors, chassis, etc. The door is composed of ;I 

window, lock. etc. Thus the lock is a-part-of the door which 

is a-part-of the body which is a-part-of the c;ir. In ;idditiwi, 

objects c;in be parts of more than one object such as ;\I\ object 

son being a p;ut of both the object mother arid the ohject 

father. A composite object can then be formed into ;I 

perspecrive. Perspectives ;\re defined ;IS different views of the 

same conceptual entity. For ex;imple, depending on the 

perspective the smie woiiun may be viewed ;is ;I niother. ;I 

daughter. ;I sister, ;in employee, or ;I supervisor. 

8 The body, in turn. is composed 

Mcrliotfs ;ire other pieces of infomi:ition ;ire stored in 

classes arid ciin be inherited from super classes. A cl;iss 

specifies the behavior of its instances in teniis of thcir 

response to ;I message which is composed of ;I selector ;tiid 

argunients. A method is chosen by rniltching the selector with 

the list of methods. The methods decl;ir;itions n;imes 

procedures (functions) for implementing the riicthods. As an 

example. suppose the chss c:ir tins ;I method c;illed Display. 

Display.Car is :I function that implements the inethod Display 

for instance of the class Car by displ;iying the instance of the 

car on the screen. The methods used ;ire dependent upon the 

pcrspective ;I knowledge source h;is about a particiilar object. 

Entries at lower levels of abstraction may support or elaborate 

3 
on entries at higher levels. The properties of the objects at one 

level of abstraction serve as input to a set of the knowledge 

sources. The actions of these knowledge sources place new 

information (change the properties) of the objects at the same 

or different levels of abstraction. Thus the knowledge sour\"t i 

transform entries from one level of abstraction to another. 

The Control Mechanism 

Different knowledge sources may have their conditions 

satisfied simultaneously during the problem solving process. 

If this happens, a control mechanism is required to determine 

which knowledge source should execute next. The control 

mechanism consists of a set of control modules which monitor 

changes in the blackboard. It applies its own knowledge base 

about the problem being solved and the repertoire of avail;\ble 

knowledge sources to determine the best step to take next. 

This approach can apply different solution strategies to 

build the solution one step at a time. One strategy might be to 

proceed bottom-up through the different levels of abstraction. 

This is done by first applying only those knowledge sources 

that generate entries at the lowest level of abstraction. Once 

these are exhausted, only the knowledge sources generuting 

entries at the next higher level ;ire applied, and so on until ;I 

solution is obtained. Other strategies include top-down, a 

combination of top-down and bottom-up, or an arbitrary 

application of knowledge sources. 

The strategy for arbitrary application of knowledge 

sources appears to be very flexible. At each stage of the 

problem solving process, any type of reasoning step might be 

chosen. The step might be data driven (bottom-up), goal 

driven (top-down), or model driven (combination). It might be 

determined by focusing attention on n particular aspect of the 

solution. The focus of attention may be which knowledge 

source to activate next, which blackbo;ird objects ;ippe;ir 

promising to pursue, or some combination (which knowledge 

sources to apply to which objects). As ;I result, the sequence 

of applying knowledge sources which iinplies the sequence of 

steps to solve the problem is dytimic and opportunistic rather 

than fixed and predetennined. 

The Seuirence of Problem Solvitir! Steps 

The steps taken by the blackboard system to solve ;I 

problem occur in the following iterative seqiience: 

(I) 'The iiction part of ;I knowledge source makes ii ch;inge(s) 

to iiti object(s) on tlie blackbard. 

(2) The condition parts of the knowledge sources ;ire esamined 

to determine which knowledge sources can make ;I 

contribution to the solution of the problem. 

4 

(3; The control mechanism selects the focus of attention. 

(4) If the focus of attention is a knowledge source, then a 

blackboard object(s) is chosen on which to process the 

knowledge source. This is called knowledge scheduling. If the 

focus of attention is a blackboard object, then a knowledge 

source is chosen to process the contents of that object. This is 

called event scheduling. If both a knowledge source and a 

blackboard object are chosen as the focus of attention, then the 

knowledge source processes the information in that object. 

(5) One of the knowledge sources determines whether or not 

the problem solving process has been completed. If it has then 

the process terminates, otherwise the process is repeated 

beginning at step one. 

111. A Candidate for the Blackbosrd Model? 

Much work has been done in applying Artitici:il 

Intelligence tools and te ques to problems in different 

engineering disciplines. Even the application of the 

blackboard approach to engineering problems is tiot ;I new 

concept. For example, Srirani hiis applied it to smlctural 

design and st~yc\IUrq$design integrated with 

construction. 

or not the blnckbonrd model can be coupled with Sohieski's 

tnultilevel decomposition approaches to yield ;in ;ippropri;ittt 

tool so that when it is applied to ;I niitItidiscipliti;iry design 

problem such ;is the one found in the aerospace industry it will 

result in ;I more optimum design in less time and at less cost. 

sytj 

9 -, ~ But, the ~~uestion reniains ;IS to whether 

To determine whether or not ;I problem is ;I candidate for 

the bliickhard approach requi e\ ;in rxnniinotioii of the 

characteristics of the problem.' is the problem complex ;itid illstructured? Sitiion defines ;I complex problem ;IS one imde L p 

of ;I large tiiinibcr of parts that interact in ;I nonsiniple way. 

111 such problems, the whole is greater than the siim of the 

parts where given tlie properties of the parts ;ind tlie laws of 

their interactions, it is tiot ;I trivial tilatter to infer tlie properties 

of the whole. In iidditioti, he defines ill-structitred problems ;IS 

those characterized by poorly defined go;iIs and ;in iibsencc of 

;L predetennined decision piIIh from the initial state to the goal 

st;ite. and often ii lack of well-defined criteria for detemiining 

whether or not a solution is acceptable. Other charxteristics 

include ;I large solution space, the need for independent (or 

semi-independent) pieces of knowledge to cooperate in 

foniiiiig ;I solution, the integration of diverse infoniiation from 

a vxicty of input, and the need of an evolutionnry solution 

requiring no ;I priori determined rensoning pnth c;iusing the 

selsction of what to do next to be mode while the prohlem is 

king solved. 

5 .' 

11 

Since the above are ;ill chmcteristics of the multilevel 

approach to solving multidisciplinary design problems. then 
the blackboard's incremental and opportunistic problemsolving approach appears to be an ideal tool for 

implementation. The blackboard system proposed in the next 

section as an implementation tool does not yet exist. It is 

meant to serve as a guide for showing the potential advantages 

that might be obtained from applying such a system. 

IV, Imolementation in the Blackboard Mode 1 

The blackboard model offers the design manager a method for 

keeping track of the design options and incomplete design 

ideas. This can be especially useful as the design progresses 

through a series of transitions from one design state to another. 

The states are adjusted based on changes that have just 

occurred. Since there are many different paths that may be 

taken. it is necessary to keep a history of the design decisions 

in case the design manager needs to bncktrack because f 

some problem encountered on the current design path. 

Keeping track of the knowledge of incomplete design ideas is 

important because design is a dynamic and ever changing 

process where an alternative that is valid at one state may be 

invalid at another and vice-versa. The blackboard model can 

also keep track of the reasoning behind the design decisions 

and of the general evolution of the design process. This 

reasoning can be captu7g as design experience and applied to 

improve future designs. 

savings since estimates are that YO% or more of the things that 

are devyed are actually redesigns of something that already 

exists. 

19 

This could result in significant 

To implement the multilevel decomposition approach in ;I 

. blackboard model. the problem must first be decomposed into 

design subproblems. This *em be done with tools such ;IS the 

one developed by Ropers. This is import;int because the 

design m;innger must know how to group the modules into 

subproblems and how to assign the subproblems to design 

teiiiiis so that changes in one subproblem will have predictable 

effects on other subproblems. The decomposition of ;I generic 

design problem is shown in figures 4 and 5. Figure 4 displays 

the group of modules before decomposition. The modtiles are 

represented by boxes ;ilong the di;tgond. A horizontol line 

from the box indicates ;in output from the module, while a 

vertiail line indicittes ;in input to the module. A vertic;il line 

entering the module from below implies it feedbiick link. The 

sni;ill circles intlicnte ;I link betweeii two niodules wtitre the 

output froin one tiioritile is ;in input to :inother module. The 

links among the modules consist of design vari;tbles. hchavior 

vuri;ililes, and constr;iints. At this point, there is very little 

informiition itbout the links ;inlong the modules th;it might be 

of benefit to ;i design man;iger. Figure 5, on the other tiand, 

displays the s;ime group of modules ;Iller they liiive heen 

reordered ;itid decomposed into subproblenis by Rogers' 

decomposition tool. The purpose of this tool is to limit the 

number of feedback links thereby decrexing the cost of 

ohtnining a solution by partitioning the modules of a pro!yk-!i 

Ik 

into circuits which represent subproblems. All feedback links 

are contained within the circuits indicating that an iteration is 

required. Circuits are connected to each other only by 

feedforward links, therefore there is no iteration among 

circuits and they can be ordered into a multilevel hierarchy 

(fig. 6) which should result in some information about how the 

knowledge sources will interact with the levels of abstraction 

on the blackboard. 

The Knowledce Sources 

For the blackhoard model, each one of these decomposed 

subproblems (circuits) and its associated modules are assigned 

as a disciplinary knowledge source. The knowledge sources 

can be on the same or different computers. They are triggered 

when the conditional part of their rule is satisfied. The 

conditional part knows whitt objects on the bl;rckboard a 

specific knowledge source is interested in, when those objects 

change, and detemiines if it cnn contribute some data to update 

those objects. The action part of the knowledge soitrce may be 

a knowledge base, or an application program (;inAysis ;id 

intradisciplinnry optimization), a database system. or some 

combination. The action pan should also have some sort of 

user and gmphics interface. The action part of these 

knowledge sources provide data from the different disciplines 

to the blackboard. They know which objects on the 

blackboard they can update and how to update them. Each 

disciplinary knowledge source views the global model from its 

own perspective and may have rules and d;itn nbout thiit 

perspective local to the knowledge source. An exaniple of ;I 

structures knowledge source is show in figure 7. 

In addition to the disciplinary knowledge sources. orhcr 

type of knowledge hources could prove to be u~cl'ul. Tlirx 

knowledge sources include knowledge ahout interdiscipliiiary 

optimization, strategy. iiiter;iction constraints, sensitivity 

;in;ilysis, and resources. The interdisciplin;i~y-optimization 

knowledge source. when triggered into action, would use 

design variables atid constraints from all disciplines to provide 

;in optimum design from ;I globd perspective. This will 

probably c;iuse ch;iiiges in certain objects monitored by 

disciplinary knowledge sources ;itid trigger them into iiction. 

The strategy knowledge source keeps track of the current st;tte 

of the solution ;itid USCS its knowledge base to move to the 

next st;ite in the solution process. The ititer;ictioii-co1istr;~iiits 

knowledge source increiiscs cnniriiunic;ition. coordin:ition, ;ind 

coc>per;ttion among the various disciplines by resolving the 

conflicts that arise among their constraint interf;ices. Tlie 

sensitivity-;iiinlysis knowledge sourct: aids in deciding how to 

modify ;I design by deterniining which design v;iri;ibles ;ire the 

most inlluentinl nnd whether their influence is positive or 

negative. And finally, the resources knowledge source 

conteins the corporate knowledge about old designs ;~nd 

design decisions that can be used to guide and control the 

solution process. 
The Blackboard and Control Mechanism 

The blackboard may have more than one partition, but for 

this application it is assumed that only one partition. the 

solution panition, is to be created. The multilevel 

decomposition scheme decomposes the problem into a 

hierarchy of subproblems which can be mapped into levels of 

abstraction on the blackboard. A knowledge source may 

receive a signal for its conditional pan from an object at one 

level and issue a change to an object at another level. 

The boxes in figure 3 represent one way to decompose a 

problem into composite objects. As mentioned before, the 

objects contain information such as super class. class 

variables, instance variables, and methods. In the example, 

wing is a super class of ailerons. The two classes are linked 

together by ailerons are a-part-of the wing. Class variables in 

objects are used for storing the state of the solution and can be 

given a default value which would be useful for providing an 

initial design. Classes are made of specific instances. For the 

infomiation about a specific instance of a class, such as design 

variables affecting that particular instance. A class specifies 

the behavior of its instances in terms of their response to 

messages. An example of a method that might be in the class 

wing is Oprimize Strtrcnire.lVing which would invoke ;1 

knowledge source to optimize the wing from a structures 

perspective and return a change in the design variables which 

would be inherited by each instance of the wing class. The 

methods used are dependent upon the perspective il knowledge 

source has about a particular object. For ex;iniple, the 

structures discipline views a wing from ;I different perspective 

than the controls discipline. 

.ISS .. wing, an instance is Iefr-wing. Instance variables contain 

Control of the whole process is handled by the inferelicing 

mechanism of choice. The inferencing mechiinism m:iy be 

developed in-house or purchased from ii vendor. This 

mechanism keeps track of all entries on the blnckbo;ird and 

determines ;I priority for executing the knowledge sources that 

have their condition pans satisfied at any one point in time. 

From these facts, it uses its knowledge b;ise to detennine the 

focus of attention. It then determines which bl;ickho;ird ob,ject 

;tiid knowledge source will be used to move to the next 

solution state based on the coniputed priorities. Figure 8 

displays the proposed bl;ickbo;ird imp1enient;ition. 

V. Summary 

New softwwe tools need to be developed for 

multidisciplinary design to improve productivity by achieving 

a more optim;il design at less cost in less time. This paper 

presents the problems of today's sequential approach to 

niultidiscipliniiry design ;ind offers the blnckboard model ;IS a 

potential tool for implenienting the multilevel decomposition 

approach to overcome those problems. The blackboard model 

serves as a global database for the solution with each 

discipline acting as a knowledge source for updating the 

solution. This approach applies opportunistic problem solving 

which requires no a priori determined reasoning path. 

Selection of which knowledge source to apply to move to a 

new problem state is achieved by examining the current state 

of the problem and choosing the best step from several 

possibilities. By using this approach it is possible that 

engineers can improve the coordination, communication, and 

cooperation in the conceptual design process allowing them to 

examine more alternatives, capture the design decisions for 

future reference, and achieve a more optimal design from an 

interdisciplinary viewpoint. 

VI. Acknowledzments 

The author wishes to thank Jean-Francois hZ. B:irthelemy for 

his suggestions on the engineering aspects of this paper. ;ind 

Kathy H. Abbott for her suggestions on the blnckbo;ird 

aspects. 

V11. References 

1. Sobieszcz;inski-Sobieski, J.; B;utheleriiy. J-F. M.: and 

Giles, G. L.: Aerospace Engineering Design by Systeiixitic 

Decomposition ond Multilevel Optimization. NASA TM 

85813, June 1984. 

2. Sobieszcz;inski-Sobieski. J.: "Sensitivity Aniilysis and 

Miiltiilisciplinary Optimization for Aircraft Design: Keceiit 

Adv;inces ;uid Results." NASA Thl 100630. July I9SS. 

3. Sohieszczanski-Sobieski, J.: "Optimization by 

Decomposition: A Step from Hier;irchic to Non-liicr;irctiic 

Systeiiis." Proceedings of the Symposium on Recent 

Adviinces in Multidisciplinary An;ilysis ;in11 0ptimiz;itioii. 

Hainpton, VA, September 28-30.1988. NASA CP-303 I. Ikt 

1, pp. 5 1-78. 

4. Newell, A.: "Sonie Prohlenis of Basic Orguiimtion in 

Problem Solving Progr;inis." Proceedings of the Conference 

on Sclf-Organizing Systems. W;ishington, DC. 1962, pp. 393- 

423. 

5. Nii, 1-1. P.: "Bl;ickho;ird Systems: The 13l;ickho;ird Model of 

Prohlrni Solving and the Evolution of Blackbo;ird 

Architectures - Part I." AI M;ig;izine, Simmer 1986. pp. 38- 

53. 

6. Nii. tl. P.: "Blackbo;trd Systems. Blackboard Applic;ition 

Systems, Blackboard Systems from it Knowledge Enginerring 

Perspective." AI M;ig;izine, August 1986, pp. 82-106. 

7. Hayes-Roth, B.: "A Blackhnrd Architecture for Control." 

Artificial Intelligence, Vol. 26, 1985, pp.251-321. 

h 
8. Stefi, M.; and Bobrow, D.: "Object-Oriented 

Programming: Themes and Variations." The AI Magazine, 

Vol. Winter, PP. 40-62, 1985. 

9. Sriram, D.: A Bibliography of Knowledge-based Expert 

Systems in Engineering. SIGART Newsletter, No. 89, July 

, 

1984. pp. 131-136. 

10. Sriram, D.; and Joobbani. R.: Special Issues, AI in 

Engineering. SIGART Newsletter, No. 92, April 1985, pp. 38- 

144. 

11. Sriram, D.: "DESTINY: A Model for Integrated Structural 

Design." International Journal for AI in Engineering, October 

1986. 

12. Sriram, D.: Knowledge-Based Approaches for Structural 

Design. CM Publications, UK, 1987. 

13. Sriram, D.; Logcher, R.; and Groleau, N.: "A Framework 

for a Computer Integrated Design and Construction System.'' 

Proceedings of the International Conference on Computational 

Engineering Science, April 10-14, 1988, Atlanta, GA, Vol. 2. 

pp. 62.i. 1 -62.i-4. 

14. Simon, H. A,: The Sciences of the Artificial. MIT Press, 

1969. 

15. Kaliiy, Y. E.; Swerdloff, L. M.; nnd Harfmann, A. C.: "A 

Knowledge-based Computable Model of Design." 

Proceedings of the IFlP WG 5.2 Working Conference on 

Expert Systems in Computer Aided Design, Sydney Australia, 

February 1987, pp. 203-227. 

16. Milher, M. L.; and Zhao, F.: "Using Experience to Plan the 

Synthesis of New Designs." Proceedings of the lFlP WG S.2 

Working Conference on Expert Systems in Computer Aided 

Design, Sydney Australia, Februiiry 19x7, pp. 330-373. 

17. Dietterich. T. G.; and Ullni:in, D. G.: "FOKLOG: A Logicbased Architecture for Design." Proceedings of the IFlP WG 

5.2 Working Conference on Expert Systetns in Computer 

Aided Design, Sydney Australin. February 19x7, pp. 1-24. 

18. Rogers, J. I..: " A Knowledge-based Tool for Multilevel 

Decomposition of ;I Complex Design Problem." NASA TP 

2903, January 1989. 

7 
inlerdiscipiinary 

ilerations 

1 

Aerodynamics Slruclures Aeroelaslicily 

lnlradiscipllnar y 

llernlions 

Fig. I Sequential decision making in the design process 

lreezes out subsequent design freedom. 

100% 

0% 

Time inlo the design process 

Fig. 2 Paradox of the conventional sequential decision making in design. 

Landing Gear Wing Fuse I age Empennage 

Slrucl. BOX Ailerons Flaps 

/ \ / 

Landing Gear Wing Fuse I age Empennage 

Fig. 3 Typical decomposition of a design problem. 

8 
1 

"ig. 4 Nondecomposed problem. 

I. __ 1 

1:ig. S Modules and circuits. 

Level 1 

Level 2 

Level 3 

Level 4 

Fig. 6 Decomposed problem. 

9 
b 

Structural 

Analysis 

4 

Fig. 7 Sample structures knowledge sourcc. 

Optimization 

+ 

I Binckboard Knowledge Source!, 

Optlmlzatlon 

Fig. X Blackboard implementation of the multilevel decomposition approach. 

10 
1. Report No. 2. Government Accession No. 

NASA TM-101633 

4. Title and Subtitle 

The Potential Application of the Blackboard Model of 

Problem Solving to Mu1 tidiscipl inary Design 

7. Authorb) 

James L. Rogers 

3. Reclpiant's Catalog No. 

5. Report Date b 

July 1989 

6. Perfmmg Organization Code , 

I 

I 

I 

8. Performing Organization Report No. 

I 

lli 10. Work Unit No. 

9. Performing Organization Name and Address 

NASA Langley Research Center 

Hampton, VA 23665-5225 

I 505-63-01-07 

11. Contract or Grant No. 

13. Type of Report and Period Covered 

12. Sponsoring Agency Name and Address Technical Memorandum National Aeronautics and Space Administration 

Washington, DC 20546-0001 14. Sponsoring Pgency Code 

19. Security Classif. (of this report) . 20. Security Classif. (of this page) 21. No. of pages 

Unclassified Unclassified 11 

15. Supplementary Notes 

To be presented at the AIAA Computers in Aerospace VI1 Conference, Monterey, CAY 

October 3-5, 1989. (AIAA Paper No. 89-3071) I 

22. Price 

A0 3 

16. Abstract 

This paper discusses the potential application of the blackborad model of problem 

solving to multidisciplinary design. 

ill structured, and lack a predetermined decision path from the initial starting 

point to the final solution. The final solution is achieved using data from 

different engineering disciplines. Ideally, for the final solution to be the 

optimum solution, there must be a significant amount of communication among the ' 

different disciplines plus intradiscipl inary and interdisciplinary optimization. I 

In reality, this is not what happens in today's sequential approach to multi- I 

disciplinary design. Therefore it is highly unlikely that the final solution is thq 

true optimum solution from an interdisciplinary optimization standpoint. A multi- 1 

problems associated with the sequential approach, but no tool currently exists with 1 

which to fully implement this technique. A system based on the blackboard model of 

problem solving appears to be an ideal tool for implementing this technique because it offers an incremental problem solving approach that requires no a priori 1 

I determined reasoning path. Thus it has the potential of finding a more optimum 

solution for the mu1 tidiscipl inary 

Mu1 tidiscipl inary design problems are complex , 

level decomposition approach has been suggested as a technique to overcome the I 

.. . . 17. Key Words (Suggested by Author(s)) industries. n;~~;iof;;;;~-ii *we , 

mu1 tidiscipl inary design 

B1 ackboard Model 

Decomposition 

Uncl assif ied - Unl imi ted 

Subject Category 61