Adapting Ant Colony for Topology Optimization of Compliant Mechanisms With Variable Material Density

Swarm intelligence optimization techniques are widely used in topology optimization of compliant mechanisms. The Ant Colony Optimization has been implemented in various forms to account for material density distribution inside a design domain. In this paper, the Ant Colony Optimization technique is applied in a unique manner to make it feasible to optimize for the beam elements’ cross-section and material density simultaneously. The optimum material distribution algorithm is governed by two various techniques. The first technique treats the material density as an independent design variable while the second technique correlates the material density with the pheromone intensity level. Both algorithms are tested for a micro displacement amplifier and the resulting optimized topologies are benchmarked against reported literature. The proposed techniques culminated in high performance and effective designs that surpass those presented in previous work.

Design and Additive Manufacturing of Lower Limb Prosthetic Socket

Additive Manufacturing (AM) is not only an innovative approach of fabrication but it fosters a new paradigm to design products. The possibility to confer inhomogeneous properties to the product provides an important design key. This paper concerns the design and manufacture of medical devices that require a high level of customization. We focus the attention on lower limb prosthesis and in particular on the prosthetic socket. The proposed method is centered on the virtual modeling of patient’s residual limb and the virtual process is highly integrated and the data flow is as fluid as possible. Three main phases can be identified: design, validation and manufacture of the socket. Firstly, the technician uses the Socket Modeling Assistant (SMA) tool to design the socket shape. Then, a numerical simulation is run to check pressure distribution and validate the socket shape. Finally, a multi-material 3D printer is used to build the socket. Preliminary results are presented and conclusions are drawn concerning the challenge of multi-material 3D printing of the socket.

A Proposal of a New Product Development Methodology: The CS-TG Method “Causality Search T-Method With Graphical Modeling”

In 2015, our team proposed a new development methodology, which we named the Causality Search T-Method (CS-T Method). This method makes it possible to solve the intrinsic limitation of target characteristics-based Parameter Design. Specifically, target characteristics-based Parameter Design is in essence a black-box method, which makes it difficult to obtain information on the mechanisms of quality improvement. The first aim of the CS-T Method is to determine the causal relationships between the target characteristics and multiple candidate “Effective-Explanation Factors” (EEF) such as physical properties, sensing data. The second aim is to improve the efficiency. Through a case study, our team demonstrated that it is possible to determine the causal relationships with significantly fewer experiments. We propose an extension of the CS-T Method, one which incorporates Graphical Modeling (GM), which we have named the CS-TG Method. Unlike conventional GM, which performs the analysis on the entire pool of candidate EEFs, CS-TG method allows the GM analysis to focus on the limited set of factors that were identified by the original CS-T as having a causal relationship with the target characteristics. In doing so, the new method is able to establish the causal relationships between each of the individual EEFs with fewer experiments.

A Generalization of the Heuristic Gradient Projection for 2D and 3D Frame Optimization

This paper introduces a generalization of the heuristic gradient projection (HGP) method for solving 2D and 3D frames. The main objective is to minimize the frame weight by means of size, topology and shape optimization considering stress constraint activation. HGP can give a specific iterative equation for each element cross section and loading type and consequently reach the optimum solution in a relatively smaller number of iterations compared to general heuristic recursive equations. However, the solution of frames with combined loads applied on the elements might converge slowly or oscillate around the constrained optimum value. Many approaches were investigated for the generalization of the HGP. However, the emphasis was always directed towards axial and bending loads. Although other types of loads may have an effect on the problem, like shear and torsion stresses in shafts or 3D frames. These types of loads are introduced into the optimization problem with more general algorithm. Weighting factors are utilized to give a weight to each stress type applied on each element. This factor is used to change the power of the HGP iterative formula for each element in the frame, which changes the power of the recursive formula according to the contribution of each loading type applied on the element. The proposed technique shows more accurate results in activating the stress constraints than previously developed HGP when dealing with combined loads, and keeps the advantage of the HGP in finding the optimum solution in a relatively small number of structural analyses. In the case studies several sample applications were solved to highlight the robustness of the proposed method.

Modular Design of Data-Driven Analytics Models in Smart-Product Development

Data-driven analytics models have been built as critical components of a smart product to enable product autonomy and intelligence. Due in part to the dynamic nature of the machine-learning algorithms used in data-driven analytics models, the configuration of a smart product is frequently refined, often in a real-time context. Hence, a smart product requires a continuous evolution of its architecture. This paper proposes a systematic method to facilitate the modularization of an analytics model architecture, so that a modular smart-product architecture can be achieved. Productizing an analytics model transforms conventional task-oriented data analytics activities into a data product development process. Issues related to the standardization of analytics models, the modular design approaches, the modularity quantification, and their impacts on the overall smart product design, are discussed. The proposed method is applied to an unmanned aircraft system (UAS) design so that a modular UAS architecture can be configured for various mission applications.

The Plant Kingdom in Engineering Design: Learning to Design From Trees

A tree may be the earliest multifunctional structure, and wood is the oldest known engineering material. Yet, trees have no place in engineering education. If we view a tree from merely a mechanical or civil engineering perspective, engineering mechanics can be learned from the tree’s example. Trees have survived by adapting to the most difficult circumstances: heavy winds, rains, floods, droughts, earthquakes, mammal damage, human intervention, etc. The root system must be strong and flexible enough to support the tree’s entire structure from varying load conditions and to provide food storage and nutrient transfer. The stem system provides structural support for the tree’s above-the-ground parts and transfers water and nutrients from the roots through the network of thick-walled cells to other parts of the tree. Leaves produce food and form the surface area surrounding the tree. Leaves come in a variety of shapes and sizes. The tree’s crown, comprising branches, leaves, and reproductive elements, help the tree to catch more sunlight. It moves upward and outward to expose more of its leaves to direct sunlight for photosynthesis while maintaining physical balance on the earth. A tree’s lifecycle can span hundreds of years, despite its vulnerability to constantly changing loads throughout the day and throughout its life. In monsoon and windy seasons, trees endure extremely difficult fatigue-loading. Various parts of the tree and its stem are subjected to combined loading conditions: tension, compression, shear, bending, and torsion. Trees develop and adapt stress management strategies by adjusting their shapes to the type or level of stress they endure: they add more mass where more strength is needed, allows material to easily break off (or physiologically inactive) from locations where it is not necessary, design optimum shapes, and create variable notch radii for reducing stress concentration. But a tree is much more than a structural member. It provides food and shelter for wildlife. It absorbs atmospheric carbon dioxide and produces oxygen. It lowers air temperature and facilitates the water cycle. Structural analysis of a tree can benefit engineering students and practicing engineers alike. Furthermore, a deeper understanding of trees can help us to create multifunctional designs that are in a symbiotic relationship with other members in the system. In short, studying tree mechanics can help us to become better engineers. This paper presents our efforts to integrate trees into engineering curricula to teach mechanics ranging from equilibrium study to stress analysis. Students of statics, dynamics, the strength of materials, stress analysis, material science, design, etc., can benefit from learning about trees. This approach enables students to understand the complexities of real-world living systems, appreciate the genius of nature’s design, and develop methods for creating sustainable designs.

Ride Comfort Evaluation Using Brain Activity in the Prefrontal Cortex Induced by Discomfort During Horizontal Vibration

In this study, we measured brain activity using near-infrared spectroscopy (NIRS) when a person was feeling discomfort caused by vibrations. We used the variance in oxygenated hemoglobin (oxy-Hb) levels as an evaluation index. Correlation coefficients were derived from the results of brain function measurements and sensibility evaluation of discomfort using a questionnaire. As a result, a high negative correlation was observed between discomfort and both vibration and brain activation around the medial prefrontal cortex, and a high positive correlation was observed between discomfort and both vibration and brain activation around the lateral prefrontal cortex. This suggests the possibility of evaluating discomfort on the basis of brain activation.

Utilizing the Generic Design Analysis (GDA) Process Model Within an Extended Set of Design Analysis Contexts

In most industrial product development projects, computer-based design analysis, or simply design analysis, is frequently utilized. Several design analysis process models exist in the literature for the planning, execution and follow-up of such design analysis tasks. Most of these process models deal explicitly with design analysis tasks within two specific contexts: the context of design evaluation, and the context of design optimization. There are, however, several more contexts within which design analysis tasks are executed. Originating from industrial practice, four contexts were found to represent a significant part of all design analysis tasks in industry. These are: 1. Explorative analysis, aiming at the determination of important design parameters associated with an existing or predefined design solution (of which design optimization is a part). 2. Evaluation, aiming at giving quantitative information on specific design parameters in support of further design decisions. 3. Physical testing, aiming at validating design analysis models through physical testing, that is, determining the degree to which models are accurate representations of the real world from the perspective of the intended uses of the models. 4. Method development, that is the development, verification and validation of specific guidelines, procedures or templates for the design analyst and/or the engineering designer to follow when performing a design analysis task. A design analysis process model needs to be able to deal with at least these four. In this work, a process model named the generic design analysis (GDA) process model, is applied to these four contexts. The principles for the adaptation of the GDA process model to different contexts are described. The use of the GDA process model in these contexts is exemplified with industrial cases: explorative analysis of design parameters of a bumper beam system, the final physical acceptance tests of a device transportation system (collision test, drop test, vibration test), and the method development of a template for analyzing a valve in a combustion engine. The “Evaluation” context is not exemplified as it is the most common one in industry. The GDA process model has been successfully used for the four contexts. Using the adaptation principles and industrial cases, the adaptation of the GDA process model to additional contexts is also possible.

Development of an Automatic Thermal, Electrical, and Mechanical Test Platform for Polymer-Derived Ceramics

Polymer-derived ceramics (PDC), prepared through thermal decomposition of polymeric precursors, are piezo-resistive, high-temperature resistant, and corrosion resistant material. Due to their excellent thermomechanical and electromechanical (piezo-resistive) behavior with very large gauge factors, they have great potential in being used as sensing materials in harsh environment, and thus has received extensive attentions in recent years. A better understanding of their holistic thermomechanical and electromechanical properties is crucial to the improvement of both the material and corresponding sensor designs. However, there has been a lack of customized, low-cost, and automatic machine that allows researchers to study the complex properties of PDCs. In this paper, an automated platform is designed to study the electromechanical and thermomechanical properties of newly developed PDCs. Featured with automatic temperature control and pressure control capabilities, the platform is able to apply load smoothly from 0 N to 220 N, and add heat from 0 to 250°C.