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Complexity Metrics for Design

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The Designers' Sandpit. Assembly-oriented environment' written in C . ... Computer graphics and FEA. Topology. Feature recognition techniques, ... – PowerPoint PPT presentation

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Title: Complexity Metrics for Design


1
Complexity Metrics for Design Manufacturability
Analysis
(Shaping the Complexity of a Design)
  • Carlos Rodríguez-Toro
  • Cranfield University, UK

2
Outline of This Presentation
  • Designers Sandpit background.
  • Manufacturing cost analysis reasons for
    complexity measure.
  • Past studies survey review.
  • Complexity analyses.
  • Theoretical considerations.
  • Final discussion conclusions.
  • Ongoing work.
  • Questions and suggestions.

3
The Designers Sandpit
  • Assembly-oriented environment written in C.
  • Implements DFA as design evaluation tool.
  • Incorporates methods for generation and
    evaluation of concept design ideas, manufacturing
    analysis, assembly planning and design advice.
  • Website http//eng.hull.ac.uk/research/sandpit/

4
DFMA Analysis Steps
5
Manufacturing Cost Estimation
  • Most factors can be measured, but geometry and
    topology are still subjective,
  • Shape complexity affects manufacturing and
    assembly operations

6
How to Measure Complexity?
7
Past Studies Survey (1)
  • Definitions of complexity declare it as ...
  • Abstract estimation,
  • Context dependent,
  • Information management,
  • Associated with product flexibility and tendency
    to product mistakes.
  • Conceptual definitions design (geometry).
  • Quantitative representations and mathematical
    models manufacturing (systems complexity).

8
Past Studies Survey (2)
  • Geometry.
  • Computer graphics and FEA.
  • Topology.
  • Feature recognition techniques,
  • Group technology part codes.
  • Assembly analysis.
  • Assembly sequence,
  • Insertion trajectories,
  • Gripping configuration, etc.

9
Specific Complexity Measures
  • Axiomatic design (Nam Suh, 1999).
  • Time independent (imaginary and real complexity).
  • Time dependent (uncertainty of future events).
  • Systems complexity (Calinescu et al., 2000).
  • Entropic measures of information (amount of
    information required to predict state of the
    system).
  • Complexity and complicatedness. (Victor tang,
    2001).
  • Function of number of parts and their
    interactions.
  • Beneficial property, given reduction of
    complicatedness.

10
Evaluating Shape Complexity
  • 2D objects shape similarity for image
    retrieval.
  • Statistical methods.
  • Stochastic methods for part orientation yield the
    measure of shape complexity.

11
Complexity in the Sandpit
  • DFA methodology evaluation of manufacturing
    processes for each component.
  • Part count reduction minimises assembly
    operations, but increases component complexity
    (geometry).

12
Complexity Analysis Taxonomy
13
Component Complexity
  • Manufacturing complexity.
  • Geometric shape,
  • Counterbalance part count reduction.
  • Process complexity.
  • Difficulty associated with alignment, insertion
    and handling operations on individual parts.
  • DFA techniques provide a scoring system to
    evaluate these aspects.

14
Assembly Complexity
  • Structural complexity.
  • Structural breakdown implications in ease of
    assembly (critical paths).
  • Subassemblies increase product flexibility
    (parallel processing), but impact part tracking
    (mating conditions, storage and inspections).
  • Sequence complexity.
  • Number of insertion operations is proportional to
    the number of components.
  • Badly defined sequences incorporate unnecessary
    operations.

15
Theoretical Considerations
  • Complexity related to
  • Number of parts,
  • Complexity of each part,
  • Part count vs. Part complexity (efficiency?)
  • Overall complexity as the sum of component and
    assembly complexity.
  • Is there a threshold value for the overall
    complexity?
  • Spotted - Geometry as the common factor.

16
Overall Sandpit Requirements
  • Manufacturing cost estimation,
  • Establish precise definitions of each type of
    complexity,
  • Complexity metrics that can be used in
    conjunction with other metrics,
  • Shape similarity comparison (for reduction of
    variance or enhancement of product flexibility)

17
Conclusions (1)
  • Complexity is a problem of semantics and
    interpretations are only relevant within the same
    context,
  • Product design presents challenges for specific
    complexity metrics that need be comparable,

18
Conclusions (2)
  • The problem is the creation of methods and
    metrics for assessing the impact of design
    decisions on production (product design
    efficiency),
  • Shape/geometry is a common factor amongst the
    different types of complexity of a product and
    fundamental for the manufacturing analysis.

19
Ongoing Work
  • Definition of precise geometric reasoning
    methodology for manufacturability analysis
    (algorithms),
  • Definitions of units of measurement,
  • Identification of hidden dependencies and
    additional factors to the problem of complexity
    metrics.
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