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Research Papers: Design Theory and Methodology

J. Mech. Des. 2018;140(7):071101-071101-12. doi:10.1115/1.4040165.

Identifying relevant stimuli that help generate solutions of desired novelty and quality is challenging in analogical design. To quell this challenge, the multifaceted effects of using stimuli which are located at various analogical distances to the design problem on the novelty and quality of concepts generated using the stimuli are studied in this research. Data from a design project involving 105 student designers, individually generating 226 concepts of spherical rolling robots, are collected. From these data, 138 concepts generated with patents as stimuli and the patents used are analyzed. Analogical distance of a patent is measured in terms of knowledge similarity between technology classes constituting the patent and design problem domain of spherical rolling robots. The key observations are (a) technology classes in closer than farther distances from the design problem are used more frequently to generate concepts, (b) as analogical distance increases the novelty of concepts increases, and (c) as analogical distance decreases the quality of concepts increases.

Topics: Design , Patents
Commentary by Dr. Valentin Fuster
J. Mech. Des. 2018;140(7):071102-071102-14. doi:10.1115/1.4039768.

Consumers often use a product's visual design as a mental shortcut to judge its unobservable attributes. Mental associations between visual design and unobservable attributes aid consumers in their judgments, and hypothetically reduce consumers' mental load. This paper describes a study that shows the possibility of quickly creating an association in subjects' minds between a holistic visual cue of a product—its body shape—and the general idea of “environmentally friendly” versus “not environmentally friendly,” a typically unobservable attribute. In this study, products' actual environmental friendliness was not measured. Subjects completed an association-building task, in which they developed mental associations between a product's visual cues and its “environmental friendliness” rating, an arbitrarily predetermined rating the authors supplied. The body shape was successfully used as a cue to subliminally communicate to subjects the product's “environmental friendliness.” As a comparison, an individual feature of the product was also used to cue; however, that was unsuccessful. An eye-tracking device was used to identify where subjects were focusing their eyes and for how long. In both the association-building task and a testing task that followed, subjects spent a greater percentage of time looking at the product's cued areas (the body and the selected feature). But during the testing task, subjects spent an even higher percentage of their time looking at the cued areas than they did during the association-building task. This indicates that mental associations, or cues, work to distribute mental load more efficiently.

Topics: Design , Testing , Bicycles , Shapes
Commentary by Dr. Valentin Fuster

Research Papers: Design Automation

J. Mech. Des. 2018;140(7):071401-071401-12. doi:10.1115/1.4039589.

Reliability analysis involving high-dimensional, computationally expensive, highly nonlinear performance functions is a notoriously challenging problem in simulation-based design under uncertainty. In this paper, we tackle this problem by proposing a new method, high-dimensional reliability analysis (HDRA), in which a surrogate model is built to approximate a performance function that is high dimensional, computationally expensive, implicit, and unknown to the user. HDRA first employs the adaptive univariate dimension reduction (AUDR) method to construct a global surrogate model by adaptively tracking the important dimensions or regions. Then, the sequential exploration–exploitation with dynamic trade-off (SEEDT) method is utilized to locally refine the surrogate model by identifying additional sample points that are close to the critical region (i.e., the limit-state function (LSF)) with high prediction uncertainty. The HDRA method has three advantages: (i) alleviating the curse of dimensionality and adaptively detecting important dimensions; (ii) capturing the interactive effects among variables on the performance function; and (iii) flexibility in choosing the locations of sample points. The performance of the proposed method is tested through three mathematical examples and a real world problem, the results of which suggest that the method can achieve an accurate and computationally efficient estimation of reliability even when the performance function exhibits high dimensionality, high nonlinearity, and strong interactions among variables.

Commentary by Dr. Valentin Fuster

Research Papers: Design for Manufacture and the Life Cycle

J. Mech. Des. 2018;140(7):071701-071701-10. doi:10.1115/1.4040164.

Highly organized, porous architectures leverage the true potential of additive manufacturing (AM) as they can simply not be manufactured by any other means. However, their mainstream usage is being hindered by the traditional methodologies of design which are heavily mathematically orientated and do not allow ease of controlling geometrical attributes. In this study, we aim to address these limitations through a more design-driven approach and demonstrate how complex mathematical surfaces, such as triply periodic structures, can be used to generate unit cells and be applied to design scaffold structures in both regular and irregular volumes in addition to hybrid formats. We examine the conversion of several triply periodic mathematical surfaces into unit cell structures and use these to design scaffolds, which are subsequently manufactured using fused filament fabrication (FFF) additive manufacturing. We present techniques to convert these functions from a two-dimensional surface to three-dimensional (3D) unit cell, fine tune the porosity and surface area, and examine the nuances behind conversion into a scaffold structure suitable for 3D printing. It was found that there are constraints in the final size of unit cell that can be suitably translated through a wider structure while still allowing for repeatable printing, which ultimately restricts the attainable porosities and smallest printed feature size. We found this limit to be approximately three times the stated precision of the 3D printer used this study. Ultimately, this work provides guidance to designers/engineers creating porous structures, and findings could be useful in applications such as tissue engineering and product light-weighting.

Commentary by Dr. Valentin Fuster

Research Papers: Design of Mechanisms and Robotic Systems

J. Mech. Des. 2018;140(7):072301-072301-8. doi:10.1115/1.4040167.

Recently, the wedge self-locking nut, a special anti-loosening product, is receiving more attention because of its excellent reliability in preventing loosening failure under vibration conditions. The key characteristic of a wedge self-locking nut is the special wedge ramp at the root of the thread. In this work, the effect of ramp angle on the anti-loosening ability of wedge self-locking nuts was studied systematically based on numerical simulations and experiments. Wedge self-locking nuts with nine ramp angles (10 deg, 15 deg, 20 deg, 25 deg, 30 deg, 35 deg, 40 deg, 45 deg, and 50 deg) were modeled using a finite element (FE) method, and manufactured using commercial production technology. Their anti-loosening abilities under transversal vibration conditions were analyzed based on numerical and experimental results. It was found that there is a threshold value of the initial preload below which the wedge self-locking nuts would lose their anti-loosening ability. This threshold value of initial preload was then proposed for use as a criterion to evaluate the anti-loosening ability of wedge self-locking nuts quantitatively and to determine the optimal ramp angle. Based on this criterion, it was demonstrated, numerically and experimentally, that a 30 deg wedge ramp resulted in the best anti-loosening ability among nine ramp angles studied. The significance of this study is that it provides an effective method to evaluate the anti-loosening ability of wedge self-locking nuts quantitatively, and determined the optimal ramp angle in terms of anti-loosening ability. The proposed method can also be used to optimize other parameters, such as the material properties and other dimensions, to guarantee the best anti-loosening ability of wedge self-locking nuts.

Topics: Vibration , Wedges , Thread
Commentary by Dr. Valentin Fuster

Design Innovation Paper: Design Innovation Papers

J. Mech. Des. 2018;140(7):075001-075001-10. doi:10.1115/1.4039853.

In this paper, a microsystem with prescribed functional capabilities is designed and simulated. In particular, the development of a straight line path generator micro electro mechanical system (MEMS) device is presented. A new procedure is suggested for avoiding branch or circuit problems in the kinematic synthesis problem. Then, Ball's point detection is used to validate the obtained pseudo-rigid body model (PRBM). A compliant MEMS device is obtained from the PRBM through the rigid-body replacement method by making use of conjugate surfaces flexure hinges (CSFHs). Finally, the functional capability of the device is investigated by means of finite element analysis (FEA) simulations and experimental testing at the macroscale.

Commentary by Dr. Valentin Fuster

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