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    ABSTRACT 'zhis paper  presents an  automatic assembly planning  system which takw
    the  CAD description of a product as  input and  automatidy gene" an
    assembly plan subject to  the  resoma constraint of a given assembly cell.
    The system improves  both  the flexibility  and productivi@ of  flexible
    manufacturing systems. and  is composed of  five modules: world datab.
    simulated world  model.  knowledge  acquisition mechanism,  p-g
    knowledge base,  and  assembly planner.  The world database contluns  the
    information  from a designer  which provides  the  information about the  p
    duct and the assembly  cell.  The knowledge quisition mechanism  acqb
    knowledge  neccssBty  for  assembly  planning  that  is,  the  pnecedence
    knowledge among assembly tasks,  the  fix-  specification  for  the  assem-
    bly,  and  the tool requirement  for the  assembly  tasks. The  acqllired
    knowledge  forms mC  planning knowledge  base.  The  simulated world
    model keeps  lrack of the  current state of the  assembly world.  In the  initial
    state,  all the  components  are  xpamted, while in the  final state, all  the  com-
    ponents are  assembled together. The  assembly planner is made up of a set
    of  production rules which models the  effects of rcal assembly tasks. By
    repeatedly applying  these poduction rules  to  the  simulated world ~Eate,  the
    pbna  transfams  the initial state  into the final  state.  The  set of  rules
    applied during this  transformation  pmcess  forms the  assembly plan to  actu-
    ally  assemble the  product  in the  given Bssembly cell. Examples are  given to
    illustrate  the  concepts in these  five modules.8427
    1.  Introduction
    Due to  the  inherent complexity in the  assembly process  planning.  it is
    usually carried out  in a hienrrchical fashion [la] for robotic assembly ceU
    There are  four planning levels in this  hierarchy:  assembly-level planning.
    task-level planning, manipulator-level planning, and  pint-level  planning.
    Extensive work has  been  done from the  joint-level  planning up to  the  task-
    level planning [2,7, 12,131, but relatively few literatures have talked about
    the automatic generation  of assembly  plans.  Bourjault  [31  proposed an
    algorithmic method of  generating  all the  assembly tank  sequences  from  a set
    of precedence  relationships among  assembly mating  tasks. Here an  assem-
    bly mating task  refers to  an  operation or  proms of putting two subassem-
    blies  toghr. The precedence  relationship are  obtained by interactively
    answering  two  sets  of  st"d  questions  about  the mating tasks.  The
    number of these questions  is exponential with respect to  the  number of mat-
    ing  tasks.  De Fazio and Whimey  [5l improved Boujault's  method  by
    reducing the number  of  questions to twice the number of mating  tasks.
    Wolter [16] proposed a so-called "constraint graph"  to  implicitly represent
    the precedence relationships among the  movements of components  in an
    assembly.  Feasible assembly sequences can  be  generated by  solving this
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