Configuration design problems are common in everyday life as well as engineering, with examples ranging from the selection and arrangement of furniture for a living room to the type of problem-solving used by NASA engineers to return Apollo 13 safely to Earth. There are many theoretical approaches for solving configuration design problems but few studies have examined how humans naturally solve them. This work used data-mining techniques (specifically hidden Markov models) to study the behavioral patterns shown by humans solving two distinct configuration design problems. Mining this data revealed beneficial process heuristics that are potentially generalizable to the entire class of configuration design problems. The trained models indicate that designers proceed through four procedural states, beginning in a state dominated by topology design and progressing to a final state with a focus on parameter design. The mined models also indicate that high-performing designers opportunistically tune parameters early in the process, enabling a more effective and nuanced search for good solutions.
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Gwang Kim, Yunjung Kwon, Eun Suk Suh and Jaemyung Ahn
J. Mech. Des 138(7), 07140; doi: 10.1115/1.4033504
This paper proposes a framework to analyze the architectural complexity of systems developed with a product family. A product family is a set of products that are derived from common sets of parts, interfaces, and processes, known as the product platform. Through the use of product platforms, several variations of products can be developed in a short period of time with relatively low-engineering costs to capture market share in niche market segments as the demand arises. This work can be used in a variety of ways to guide product platform and variant architecture development during the initial concept generation stage. The effectiveness of the proposed framework is demonstrated through a case study of a train bogie platform.
The process starts with building the design structure matrix (DSM) model, which captures the structural architecture as well as mass, energy, and information flow, for the product platform and its variants. Using the DSMs created and the selected complexity metric, the architectural complexity, which includes the structural complexity and flow complexity values, is assessed. Based on the quantitative results obtained, the overall complexity for the product platform and the product family could be compared with other competing product platform architecture and product family concepts. Furthermore, this process also allows system architects and decision makers to manage overall complexity of an entire product family, either through complexity minimization or by designing the entire platform and product architecture to be less sensitive to engineering changes in terms of complexity fluctuation.
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Additive manufacturing (AM) techniques provide designers with greater freedom in creating customized products with complex shapes. When major design changes are made to a part, undesirable high cost increments may be incurred due to AM process setting adjustments, challenging designers to explore AM-enabled design freedom while controlling costs at the same time. In this research, we introduce the concept of a variable product platform and its associated AM process setting platform, based on which the design and process setting adjustments can be restricted within a bounded feasible space in order to limit cost increments. Fuzzy Time-Driven Activity-Based Costing (FTDABC) approach is introduced to predict AM production costs based on process settings. The process setting adjustment’s feasible space boundary is identified by solving a multiobjective optimization problem. Design parameter limitations are computed in a Mamdani-type expert system and then used as constraints in the design optimization to maximize customer perceived utility. Case studies on designing an R/C racing car family illustrate the proposed methodology and demonstrate that the optimized additive manufactured variable platforms can improve product performances at lower costs than conventional consistent platform based design.
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School of Engineering Design, Technology, and Professional Programs (SEDTAPP)
The Pennsylvania State University
213J Hammond Building, University Park, PA, 16802, U.S.A.
Design, Research, and Education for Additive Manufacturing Systems Laboratory,
413D Goodwin Hall, 635 Prices Fork Road, Blacksburg, VA, 24061, U.S.A.
The PolyJet material jetting additive manufacturing (AM) process is uniquely qualified to create complex, multi-material structures. However, key manufacturing constraints need to be explored and understood in order to guide designers in their use of the PolyJet process including 1) minimum manufacturable feature size, 2) removal of support material, 3) survivability of small features during cleaning, and 4) the self-supporting angle in the absence of support material. In this study, the authors used a series of experiments to identify statistically significant geometric and process parameters and how they impact part manufacturability. Support material removal was found to be limited by the cross-sectional area of small channels in the part; a minimum cross-sectional area approximately equal to the diameter of the cleaning water jet spray results in the highest percentage of support material removed from small channels (Figure 1). The process’s minimum resolvable feature size was shown to rely on surface finish and feature shape, as well as the interactions between surface finish and orientation, surface finish and feature direction, and orientation and feature direction. If a designer can account for the ideal configuration of these variables, then it is possible to manufacture features that are half the size of a more general “worst-case” scenario. Feature survivability during the cleaning process was tied to cross-sectional area (for rigid features) and feature connectivity (for flexible features), with flexible features requiring significantly larger feature diameters to survive when fixed at both ends. Finally, the self-supporting angle in the absence of support material was driven by the orientation of the surface with respect to the roller in the print head assembly, with y-dominated specimens offering better self-supporting angles. Experimental design studies such as these are crucial to provide designers with the knowledge to ensure that their proposed designs are manufacturable with the PolyJet process, whether designed manually or by an automated method, such as topology optimization.
Figure 1. Mean support material removed from channels of various areas
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Origami-Based Self-Folding Structure Design and Fabrication Using Projection Based Stereolithography
Authors: Dongping Deng; Yong Chen
J. Mech. Des.. 2015; 137(2):021701-021701-12
Self-folding structures are beneficial for a wide variety of applications including biomedical and electronics products. In this paper a novel fabrication approach based on a three-dimensional (3D) printing process is presented for fabricating self-folding structures that can be actuated in a heating environment. The designed and fabricated thermo-actuating structures are two-dimensional (2D) origami sheets that have multiple printed layers. The middle layer of an origami sheet is a pre-strained polystyrene film with large shrinkage ratios when heated. Both its top and bottom surfaces are covered with printed polymers with designed shapes. A foldable hinge is achieved by constraining the shrinkage of the film on one side while allowing the shrinkage of the film on another side when heated. Heuristic models of hinge folding angles are developed. Various experimental tests based on the developed 2D origami design and fabrication method are presented. Techniques on improving folding angle control are also discussed with possible applications.
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Authors: Tianyi Cai and Theodor Freiheit
J. Mech. Des. 136(10), 101701 (Jul 21, 2014) (12 pages)
Customers want good value when they buy products. However, the value perceived by a customer is affected in part by the benefits they get from the product and the cost of designing the product. This paper discusses how managers can better assign work-hours and other resources necessary to design products. Designers use these resources to create and improve upon the benefits the product delivers but at a cost that determines how the customer sees its value. Since the cost from the design process can be uncertain, for example because customer needs evolve and may not be fully understood, designers may have to repeat design activities to ensure the design is correct - Figure 1. A mathematical model is proposed that shows how resources are transformed into value. This model allows resources to be assigned to a design projects optimally to control costs. Examples of the model’s application demonstrate strategic and tactical resource assignment in scenarios developed from the computer industry and for design projects.
Figure 1 – Conceptual Model of Value Creation Cell
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This section includes brief descriptions of articles soon to be or recently published by the Journal of Mechanical Design. These featured articles highlight recent research developments and emerging trends in mechanical design. For Abstracts and Full Articles please see ASME's Digital Collection.