FixtureBased usefulness measure for hybrid process planning

1
Fixture-Based usefulness measure for hybrid
process planning

• Jeon sang min

2
Abstract

• Hybrid process planning approach
• Identify existing design and process planning
  (fixture that can hold the new design)
• Traditional geometric similarity measures are
  inadequate ? new fixture-based usefulness measure

3
introduction

• Developing generative process planners for
  complex machined part is a difficult challenge
• GPP ? less successful selecting the fixture
  needed to complete the PP
• Developing new hybrid approach to PP

4
introduction

• The Fixture planning approach must identify
  designs and process plans that have fixtures that
  can hold the new design
• Developing an approach for defining a usefulness
  measure that explicitly reflects fixture
  usefulness

5
Introduction

• Background describes previous work
• Describes our hybrid process planning approach
• Defines the fixture planning problem
• Solve this problem
• Example
• Summarize

6
Background

• Variant techniques are the tools of choice they
  currently support almost all practical
  implementations of CAPP
• GPP attempts to synthesize a process plan
  directly for new design
• HPP approaches attempt to exploit knowledge in
  exist plans

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Background

• VPP based on the use of the GT coding system
  (DCLSSS, MICLASS, OPITZ)
• 1. captures a new products critical design and
  manufacturing attribute (GT code)
• 2. group products with similar GT code in to
  product families

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Background

• Variant approach proceeds as follows
• 1. design D ? determines GT code
• 2. index into DB (P/D ? P/D)
• 3. engineer modifies P
• 4. produce P

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Background

• Classifying designs (solid, CAD model)
• 1. SUN95 described a similarity measure for
  solids based on properties of a boundary
  representation. ? not incorporate manufacturing
  considerations
• 2. Herr97, Sing97 developed plan-based design
  similarity measures

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Background

• Generative approach
• Mant89,Kamb93, Gupt94a, Yue94
• Difficulties arise form interaction (workpiece
  fixturing, process selection, process sequencing)
• Part system Geel95 marketed commercially ?
  not really achieved significant industrial use

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Background

• Hybrid process planning
• Variant hybrid
• Park93 acquiring knowledge (GPP) and storing
  knowledge (Schema)
• Mare94 capture the plan knowledge
• Lu98 case-based approach

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Background

• Existing hybrid approaches have limited
  capabilities
• Robust hybrid approach must consider
• - feature interaction
• - precedence constraints
• - tolerances
• - other critical design information
• Must consider how store, classify, and retrieve
  useful design and PP information

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Background

• Fixture planning is an important issue in
  small-batch manufacturing
• Flexibility of modular fixture
• Identifying a good fixture for a given operation
  is a difficult task ? many different types of
  fixtures and fixture element
• Fixture has to satisfy stability, location,
  restraint, accessibility, cost

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Background

• Process planning and fixture planning are two
  problems
• Automatic fixture design
• Integration of fixture planning and process
  planning
• Research has focused on mathematical solution and
  holding a part and on expert systems and CAFP

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Hybrid process planning

• Combine the best characteristics of both variant
  and GPP ? avoid the worst limitations of each
• Generative planner is a better approach for
  creating a preliminary process plan
• Variant approach is very useful technique for
  completing the process plan and adding the
  necessary details

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Hybrid process planning
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Hybrid process planning

• Extends the generative approach
• Using generative approach for process selection
• Variant procedure select fixtures, complete the
  process plan

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Hybrid process planning

• Machining feature
• Represent a design as a collection of machining
  feature
• Feature extractor Regli
• Identify the volumetric machining features
• These feature represent different possible
  machining operation
• Feature-based representation

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Hybrid process planning

• Generate a promising FBM from the feature set
• Generate promising operation plan for the FBM
• Estimate the achievable machining accuracy of
  operation plan
• Design fixture search the existing design and
  process ? used for the new design ? modify the
  retrieved fixture

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Hybrid process planning

• No promising operation plans were found
• Exit with failure
• Returning the operation plan best tradeoff
  among quality, cost, time

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Fixture selection

• Fixture planning step design a fixture for each
  setup
• Setup is a set of consecutive operations
• Calculating each fixtures feasibility and
  modification for infeasible fixture ? too much
  effort ? search quickly ? database designs
  process plan, machining operation, fixture

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Fixture selection

• For each setup
• Identify an existing setup
• The old fixture modify ? if necessary
• Verify the fixture
• - geometrically location
• - constrain workpiece ? cutting force
• - contact (fixture tool)

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Fixture selection
P
GPP
S
S
D
VPP
d
D
S
p
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Approach
characteristic
Fixture
Define fixture usefulness measure
attribute
Setup
Vector function
Define mapping
Usefulness measure
Define usefulness measure
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Example
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Example

• Fixture has three clamp
• c1, c2, c3 vector describe
• k1, k2, k3 clamping force

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Example
Maximum cutting force
width
height
length
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Example
Without modifying Locating clamping point,
clamping force
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Example
Without modifying Locating clamping point,
increase clamping force
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Example
Modify Locating clamping point, By maximum
distance
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Example
f(F4,Sh) (2, 0.1?f)
f(F5,Sh) (3, 2?p)
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Example
The overall size of the fixture depends upon the
size of the workpiece
Fixture clamping forces have to be create enough
to withstand the cutting forces
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Example
Sh has the same size workpiece as setup Sk And
experiences no greater cutting forces
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Example
Sh has the same size workpiece as setup Sk and
the maximum cutting force experienced during Sk
is ?f greater than the maximum cutting force
experienced during Sh
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Example
Workpiece dimensions are different and the
maximum diffenence between the workpiece
demension is ?p
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Example
f(S1,S0) (1, 0)
f(S2,S0) (2, ?f)
f(S3,S0) (3,?p)
f(S4,S0) (2, 0.1?f)
f(S5,S0) (3, 2?p)
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Example
H
W
X
-X
Y
-Y
L
Z
-Z
L
H
W
f(S1,S0) (1, 0)
f(S2,S0) (3, 3)
S0 more useful for S0 then S2
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Summary and conclusions

• Hybrid variant-generative process planning
  approach
• Includes sophisticated feature recognition and
  plan-based design evaluation
• Based on theoretical foundations ? soundness,
  completeness, efficiency, and robustness

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Summary and conclusions

• Describes an approach for defining a usefulness
  measure
• Usefulness approach could be applied to fixture
  planning in other domains
• Address the related issue of design
  representation, process plan generation and
  evaluation
• Fixture planning