A lattice-based approach for navigating design configuration spaces

Abstract Design configurations, such as Bills of Materials (BoMs), are indispensable parts of any product development process and integral to the design descriptions stored in proprietary Computer Aided Design and Product Lifecycle Management systems. Engineers use BoMs and other design configurations as lenses to repurpose design descriptions for specific purposes. For this reason, multiple BoMs typically occur in any given product development process. For example, an engineering BoM may be used to define a configuration that best supports a design activity whereas a manufacturing BoM may be used to define the configuration of parts that best supports a manufacturing process. Current practice for the definition of BoMs involves the use of indented parts lists and dendograms that are prone to error because it is easy to create discrepancies across BoMs that, in essence, are defined through collections of part identifiers such as names and part numbers. Such errors have a significant detrimental effect on the performance of product development processes by creating the need for rework, adding costs and increasing time to market. This paper introduces a design description capability that ensures consistency across BoMs for a given design. A boolean hypercube lattice is used to define a design configuration space that includes all possible configurations for a given design description. Valid operations within the space are governed by the mathematics of hypercube lattices. The design description capability is demonstrated through an early engineering design configuration software tool that offers significant benefits by ensuring consistency across the BoMs for a given design. The software uses and generates design descriptions that are exported from and imported to commercially available design systems through a standard (ISO 10303-214) interface format. In this way, potential for early impact on industry practice is high.

[1]  S. Zukowski Introduction to Lattice Theory , 1990 .

[3]  L. Beran,et al.  [Formal concept analysis]. , 1996, Casopis lekaru ceskych.

[4]  Bernhard Ganter,et al.  Formal Concept Analysis , 2013 .

[5]  Timothy W. Simpson,et al.  An Integrated Approach to Product Family Redesign Using Commonality and Variety Metrics , 2015, DAC 2015.

[6]  Hoda A. ElMaraghy,et al.  Product Design Retrieval by Matching Bills of Materials , 2014 .

[7]  Weiming Shen,et al.  A method for transformation of engineering bill of materials to maintenance bill of materials , 2014 .

[8]  Alison McKay,et al.  Exploiting lattice structures in shape grammar implementations , 2018, Artificial Intelligence for Engineering Design, Analysis and Manufacturing.

[9]  G. Grätzer,et al.  Lattice Theory: First Concepts and Distributive Lattices , 1971 .

[10]  Christoph Meier,et al.  Systematic module and interface definition using component design structure matrix , 2010 .

[11]  Chris McMahon,et al.  Annotation in product lifecycle management: a review of approaches , 2009 .

[12]  M. Fuge,et al.  Design Manifolds Capture the Intrinsic Complexity and Dimension of Design Spaces , 2017 .

[13]  Mark Robinson,et al.  Embedding Design Descriptions Using Lattice Structures: Technical Requirements, User Perspectives and Implementation , 2017 .

[14]  Sylvain Kubler,et al.  P2P Data synchronization for product lifecycle management , 2015, Comput. Ind..

[15]  G. Stiny The algebras of design , 1991 .

[16]  Lian Ding,et al.  Annotation of lightweight formats for long-term product representations , 2009, Int. J. Comput. Integr. Manuf..

[17]  Timothy Williamson,et al.  Parts. A Study in Ontology , 1990 .

[18]  Kai Li,et al.  Research on static service BOM transformation for complex products , 2018, Adv. Eng. Informatics.

[19]  Alison McKay,et al.  Using embedded design structures to unravel a complex decision in a product development system , 2017 .

[20]  Djordje Krstic From Shape Computations to Shape Decompositions , 2017 .

[21]  L. March,et al.  The Smallest Interesting World? , 1996 .

[22]  Lorin M. Hitt,et al.  Beyond the Productivity Paradox: Computers are the Catalyst for Bigger Changes , 1998 .

[23]  Chris A McMahon,et al.  Design Informatics: Supporting Engineering Design Processes with Information Technology , 2016 .

[24]  Lars Hvam,et al.  PROACTIVE MODELING OF MARKET, PRODUCT AND PRODUCTION ARCHITECTURES , 2011 .

[25]  Simon P. Frechette,et al.  Model Based Enterprise Technical Data Package Requirements , 2011 .

[26]  George Stiny,et al.  Shape: Talking about Seeing and Doing , 2006 .

[27]  Eswaran Subrahmanian,et al.  Managing and supporting product life cycle through engineering change management for a complex product , 2015 .

[28]  Yongsheng Ma,et al.  Parametric feature constraint modeling and mapping in product development , 2012, Adv. Eng. Informatics.

[29]  Dimitri N. Mavris,et al.  A digital thread approach to support manufacturing-influenced conceptual aircraft design , 2018 .