A Statistical Approach to Ranking Similarities of Three Function Structure Groups Using Directed Graphs

Prior efforts in the study of engineering design employed various approaches to decompose product design. Design engineers use functional representation, and more precisely function structures, to define a product’s functionality. However, significant barriers remain to objectively quantifying the similarity between two function structures, even for the same product when developed by multiple designers. For function-structure databases this means that function-structures are implicitly categorized leaving the possibility of incorrect categorization and reducing efficacy of returned analogous correlations. Improvements to efficacy in database organization and queries are possible by objectively quantifying the similarity between function structures. The proposed method exploits fundamental properties of function-structures and design taxonomies. We convert function-structures into directed graphs (digraphs) and equivalent adjacency matrices. The conversion maintains the directed (function → flow → function) progression inherent to function-structures and enables the transformation of the function-structure into a standardized graph. For design taxonomies (e.g. D-APPS), graph nodes represent flows in a consistent (but arbitrary) ordering. By exploiting the directional properties of function-structures and defining the flows as the graphical nodes, the objective and standardized comparison of two function-structures becomes feasible. We statistically quantify the association between digraphs using the Pearson Product Moment Correlation (PPMC) for both within-group and between-group comparisons. The method was tested on three product types (ball thrower, food processor, and an ice cream maker) with function-structures defined by various designers. The method suggested herein is provided as a proof-of-concept with suggested verification and validation approaches for further development.

Computer-Aided Gear Product Realization

To save time and resources, many are making the transition to developing their ideas virtually. Computer-aided gear production realization is becoming more and more desired in the industry. To produce gears with custom qualities, such as material, weight and shape, the trial and error approach has yielded the best results. However, trial and error is costly and time consuming. The computer-aided integrated design and manufacturing approach is intended to resolve these drawbacks. A simple one stage reduction spur gearbox is used as an example in a case study. First, the gear geometry is developed using computer aided design (CAD) modeling. Next, using MATLAB/Simulink, the gear assembly is connected virtually to other subsystems for system expectations and interaction analysis. Finally, using finite element analysis (FEA) tools such as ABAQUS, a dynamic FEA of the gear integration is completed to analyze the stress concentrations and gear tooth failures. Through this method of virtual gear design, customized dimensions and specifications of gears for satisfying system-level requirements can be developed, thereby saving time and manufacturing costs for any custom gear design request.

Differential Performance Signature Qualification for Additively Manufactured Parts

Additive Manufacturing (AM) technologies and associated processes, enable successive accretion of material to a domain, and permit manufacturing of highly complex objects which would otherwise be unrealizable. However, the material micro- and meso-structures generated by AM processes can differ remarkably from those arising from conventional manufacturing (CM) methods. Often, a consequence of this fact is the sub-standard functional performance of the produced parts that can limit the use of AM in some applications. In the present work, we propose a rapid functional qualification methodology for AM-produced parts based on a concept defined as differential Performance Signature Qualification (dPSQ). The concept of Performance Signature (PerSig) is introduced both as a vector of featured quantities of interest (QoIs), and a graphical representation in the form of radar or spider graph, representing the QoIs associated with the performance of relevant parts. The PerSigs are defined for both the prequalified CM parts and the AM-produced ones. Comparison measures are defined and enable the construction of differential PerSigs (dPerSig) in a manner that captures the differential performance of the AM part vs. the prequalified CM one. The dPerSigs enable AM part qualification based on how their PerSigs are different from those of prequalified CM parts. After defining the steps of the proposed methodology, we describe its application on a part of an aircraft landing gear assembly and demonstrate its feasibility.

Voice of the Customer Oriented New Product Synthesis Over Knowledge Graphs

The online shopping has been much easier and popular, and meanwhile brings new challenges and opportunities to the field of product design and marketing sale. On one hand, product manufacturers find it challenging to produce new popularly accepted products to meet the customers’ needs; on the other hand, end customers usually feel it difficult to buy ideal goods that they really want, even if navigating a huge amount of commodities. There are indeed a ‘communication gap’ between the customers and manufacturers. As an effort to partially resolve the issue, this paper proposes a novel product synthesis approach from ‘voice of the customer’ over product knowledge graphs. Here the voice of customers mainly refer to the buyers’ product reviews from online shopping platforms or blogs, while the product knowledge graph is constructed containing professional hierarchical product knowledge on its properties based on ontological models. Using the technologies of natural language processing, we first extract the customs’ polarities on each specific aspect of a product, which are then transited to design requirements on the product’s design components. Based on the requirement extractions, and the pre-built product knowledge, semantic web and reasoning techniques are utilized to synthesize a novel product that meets more customer needs. Typical case studies on mobile phones from raw online data demonstrate the proposed approach’s performance.

Categorization of Information Loss During the Dissemination of Design Ideas

Information is transferred through a process consisting of an information source, a transmitter, a channel, a receiver and its destination. Unfortunately, during different stages of the engineering design process, there is a risk of a design idea or solution being incorrectly interpreted due to the nonlinearity of engineering design. I.e., there are many ways to communicate a single design idea or solution. This paper provides a comprehensive review and categorization of the possible sources of information loss at different stages of the engineering design process. Next, the authors present an approach that seeks to minimize information loss during certain stages of the engineering design process. The paper i) explores design process and dissemination methods in engineering design; ii) reviews prior work pertaining to these stages of the engineering design process and iii) proposes an information entropy metric that designers can utilize in order to quantify information loss at different stages of the engineering design process. Knowledge gained from this work will aid designers in selecting a suitable dissemination solution needed to effectively achieve a design solution.

Trajectory Planning for Conformal 3D Printing Using Non-Planar Layers

Additive manufacturing (AM) technologies have been widely used to fabricate 3D objects quickly and cost-effectively. However, building parts consisting of complex geometries with multiple curvatures can be a challenging process for the traditional AM system whose capability is restricted to planar-layered printing. Using 6-DOF industrial robots for AM overcomes this limitation by allowing materials to deposit on non-planar surfaces with desired tool orientation. In this paper, we present collision-free trajectory planning for printing using non-planar deposition. Trajectory parameters subject to surface curvature are properly controlled to avoid any collision with printing surface. We have implemented our approach by using a 6-DOF robot arm. The complex 3D structures with various curvatures were successfully fabricated, while avoiding any failures in joint movement, holding comparable build time and completing with a satisfactory surface finish.

Overhanging Feature Analysis for the Additive Manufacturing of Topology Optimized Structures

This paper presents a methodology to find the optimum build orientation in the additive manufacturing of topologically optimized structural parts. The outlined methodology is based on applying a differential operator to the density distribution matrix of a topologically optimized design. The methodology is developed for 2D parts, where the profile of the geometry is constant. The 2D spatial difference operator effectively calculates the elemental density gradient vector, ultimately used to calculate the angles between i) overhanging surfaces of a topology optimized design, and ii) the build platform of a 3D printer. These angles, referred to as build angles, are used to estimate the relative amount of supporting structure required to print the design at a prescribed part orientation. This methodology can potentially be adopted to simulate the additive manufacturing surface quality of density based, structural topology optimization designs.

Optimization of the Case Depth of a Cylinder Made With 4340 Steel by a Control of the Laser Heat Treatment Parameters

This paper presents a numerical model able to control the temperature distribution along a 4340 steel cylinder heat-treated with Nd: YAG laser. The numerical model developed using the numerical finite element method, was based on a study of surface temperature variation and the adjustment of this temperature by a control of the heat treatment laser power. The proposed analytical approach was built gradually by (i) the development of a numerical model of laser heat treatment of the cylindrical workpiece, (ii) an analysis of the results of simulations and experimental tests, (iii) development of a laser power adjustment approach, and (iv) proposal of a laser power control predictor using neural networks. This approach was made possible by highlighting the influence of the fixed (non-variable) parameters of the laser heat treatment on the case depth, and has shown that it is possible by controlling the laser parameters to homogenize the distribution of the maximum temperature reached on the surface for a uniform case depth. The feasibility and effectiveness of the proposed approach leads to a reliable and accurate model able to guarantee a uniform surface temperature and a regular case depth for a cylindrical workpiece of a length of 50-mm and with a diameter of between 16-mm and 22-mm.

Multi-Component Topology Optimization for Powder Bed Additive Manufacturing (MTO-A)

This paper presents a gradient-based multi-component topology optimization (MTO) method for structures assembled from components made by powder bed additive manufacturing. It is built upon our previous work on the continuously-relaxed MTO framework utilizing the concept of fractional component membership. The previous attempt on the integration of the relaxed MTO framework with additive manufacturing constraints, however, suffered from numerical instability for larger size problems, limiting its application to 2D low-resolution examples. To overcome this difficulty, this paper proposes an improved MTO formulation based on a design field regularization and a nonlinear projection of component membership variables, with a focus on powder bed additive manufacturing. For each component, constraints on the maximum allowable build volume (i.e., length, width, and height), the elimination of enclosed voids, and the minimum printable feature size are imposed during the simultaneous optimization of the overall base topology and component partitioning. The scalability of the new MTO formulation is demonstrated by a few 2D examples with much higher resolution than previously reported, and the first reported 3D example of MTO.

Comparative Study of As-Built Geometric and Mechanical Properties of Additively Manufactured Ceramics

Additive Manufacturing (AM) encompasses a broad variety of fabrication techniques characterized by successive additions of mass and/or energy to a build domain. AM processes have been developed for a wide variety of feedstock materials, including metals, polymers, and ceramics. In the present work we study the AM of ceramics using the Direct Ink Writing (DIW) technique. We performed comparative studies between additively manufactured and conventionally manufactured test articles, in order to quantify the variations in output geometry and mechanical properties induced by the DIW process. Uniaxial tests are conducted using high-performance optical strain measurement techniques. In particular, it is shown that the DIW-produced specimens exhibit anisotropic shrinkage when fired, as well as a marked decrease in stiffness and ultimate strength. We conclude with a discussion of potential mechanisms which may be responsible for these property degradations, and introduce potential adaptations to the DIW AM process that may be effective in combating them.