Review Article

J. Comput. Inf. Sci. Eng. 2018;18(4):040801-040801-16. doi:10.1115/1.4040131.

This review focuses on the design process of additively manufactured mesoscale lattice structures (MSLSs). They are arrays of three-dimensional (3D) printed trussed unit cells, whose dimensions span from 0.1 to 10.0 mm. This study intends to detail the phases of the MSLSs design process (with a particular focus on MSLSs whose unit cells are made up of a network of struts and nodes), proposing an integrated and holistic view of it, which is currently lacking in the literature. It aims at guiding designers' decisions with respect to the settled functional requirements and the manufacturing constraints. It also aims to provide an overview for software developers and researchers concerning the design approaches and strategies currently available. A further objective of this review is to stimulate researchers in exploring new MSLSs functionalities, consciously considering the impact of each design phase on the whole process, and on the manufactured product.

Commentary by Dr. Valentin Fuster
J. Comput. Inf. Sci. Eng. 2018;18(4):040802-040802-15. doi:10.1115/1.4040341.

Developments in digital technology and manufacturing processes have expanded the horizon of designer innovation in creating products. In addition to this, real-time collaborative platforms help designers shorten the product development cycle by enabling collaborations with domain experts from concept generation to product realization and after-market. These collaborations are extending beyond enterprise and national boundaries, contributing to a growing concern among designers regarding the security of their sensitive information such as intellectual property (IP) and trade secrets. The source of such sensitive information leaks could be external (e.g., hacker) or internal (e.g., disgruntled employee) to the collaboration. From a designer's perspective, this fear can inhibit participation in a collaboration even though it might result in better products or services. In this paper, we aim to contextualize this evolving security space by discussing various security practices in digital domains, such as encryption and secret sharing, as well as manufacturing domains, such as physically unclonable function (PUF) and physical part watermarking for anticounterfeiting and tamper evidence purposes. Further, we classify these practices with respect to their performance against different adversarial models for different stages in product development. Such a classification can help designers to make informed decisions regarding security practices during the product realization process.

Commentary by Dr. Valentin Fuster

Research Papers

J. Comput. Inf. Sci. Eng. 2018;18(4):041001-041001-14. doi:10.1115/1.4040461.

We hypothesize that by providing decision support for designers we can speed up the design process and facilitate the creation of quality cost-effective designs. One of the challenges in providing design decision support is that the decision workflows embody various degrees of complexity due to the inherent complexity embodied in engineering systems. To tackle this, we propose a knowledge-based Platform for Decision Support in the Design of Engineering Systems (PDSIDES). PDSIDES is built on our earlier works that are anchored in modeling decision-related knowledge with templates using ontologies to facilitate execution and reuse. In this paper, we extend the ontological decision templates to a computational platform that provides knowledge-based decision support for three types of users, namely, template creators, template editors, and template implementers, in original design, adaptive design, and variant design, respectively. The efficacy of PDSIDES is demonstrated using a hot rod rolling system (HRRS) design example.

Commentary by Dr. Valentin Fuster
J. Comput. Inf. Sci. Eng. 2018;18(4):041002-041002-16. doi:10.1115/1.4039683.

Functionally graded materials (FGM) have recently attracted a lot of research attention in the wake of the recent prominence of additive manufacturing (AM) technologies. The continuously varying spatial composition profile of two or more materials affords FGM to possess properties of multiple different materials simultaneously. Emerging AM technologies enable manufacturing complex shapes with customized multifunctional material properties in an additive fashion. In this paper, we focus on providing an overview of research at the intersection of AM techniques and FGM objects. We specifically discuss FGM modeling representation schemes and outline a classification system to classify existing FGM representation methods. We also highlight the key aspects such as the part orientation, slicing, and path planning processes that are essential for fabricating FGM object through the use of multimaterial AM techniques.

Commentary by Dr. Valentin Fuster
J. Comput. Inf. Sci. Eng. 2018;18(4):041003-041003-13. doi:10.1115/1.4040024.

Computer-aided design (CAD)/computer-aided manufacturing (CAM)/computer-aided engineering (CAE) integration offers designers, analysts, and manufacturers the opportunity to share data efficiently throughout the product development process. CAM for NC programing and tool design integrated with solid model data from CAD systems represents a large portion of the CAD/CAM/CAE domain. Sustained integration whereby successive changes to a CAD model are reintegrated with downstream applications is considered the most advanced and useful integration. Sustained integration is typically maintained when working in a homogeneous CAD/CAM environment. However, when working with applications that do not share a common environment (i.e., heterogeneous integration), sustained integration fails, and this lack of sustained integration can result in a loss of detailed information as a design progresses through the engineering design process. In the current paper, the authors discuss and demonstrate a novel approach to achieve sustained integration when working in heterogeneous CAD/CAM environments. After providing basic background information to establish a context, then discussing state-of-the-art and emerging solutions, the paper discusses virtual persistent identifiers as described via design change vectors (VPI/DCV). A series of three case studies shows sustained integration based on neutral formats like STEP working as well as that observed in homogeneous environments. This novel approach demonstrates success as a generic solution using common export formats from the current CAD systems and avoids the need to establish any new standards to achieve sustained integration. The paper finishes with a summary of observations learned from these case studies along with possible future research topics.

Commentary by Dr. Valentin Fuster
J. Comput. Inf. Sci. Eng. 2018;18(4):041004-041004-10. doi:10.1115/1.4040130.

In most city water distribution systems, a considerable amount of water is lost because of leaks occurring in pipes. Moreover, an unobservable fluid leakage fault that may occur in a hazardous industrial system, such as nuclear power plant cooling process or chemical waste disposal, can cause both environmental and economical disasters. This situation generates crucial interest for industry and academia due to the financial cost related with public health risks, environmental responsibility, and energy efficiency. In this paper, to find a reliable and economic solution for this problem, adaptive neuro fuzzy inference system (ANFIS) method which consists of backpropagation and least-squares learning algorithms is proposed for estimating leakage locations in a complex water distribution system. The hybrid algorithm is trained with acceleration, pressure, and flow rate data measured through the sensors located on some specific points of the complex water distribution system. The effectiveness of the proposed method is discussed comparing the results with the current methods popularly used in this area.

Commentary by Dr. Valentin Fuster
J. Comput. Inf. Sci. Eng. 2018;18(4):041005-041005-13. doi:10.1115/1.4040340.

During the last decade, as a result of their constant urge to retain sustainability, companies have shifted to the product-service system (PSS) business model, in an effort to gain competitive advantages. PSS providers have realized the importance of offering highly perceived solutions; thus, the necessity of monitoring the performance of PSSs and evaluating them has intensified. However, not much work has been conducted toward that direction, especially focusing on its practical application. In the current work, a holistic approach for PSS evaluation using key performance indicators (KPIs) is proposed, extending to all its lifecycle phases and covering aspects from both provider's and customer's perspectives. A software tool was developed to assist the decision maker in the selection of appropriate KPIs to monitor for PSS evaluation and additionally, to offer KPIs data collection, storage, processing, and visualization capabilities. The proposed methodology was applied in a real industrial case of the mold making area to validate its results.

Commentary by Dr. Valentin Fuster
J. Comput. Inf. Sci. Eng. 2018;18(4):041006-041006-12. doi:10.1115/1.4040606.

Intuitive use is a desirable feature in product and interface design. Until recently, however, there has been little research on the affective aspects of intuitive use. This paper contributes to the research in this area by proposing a systematic analytical method for assessing the affective aspect of intuitive use; the method uses an ontology of image schemas, computational semantics, and a sentiment analysis to determine the affect associated with interactions. The approach is evaluated through an empirical study involving 40 participants who completed a task with two products. The results show that the approach links the image schemas used for the completion of a task to the affective experiences of the users. The study has the potential to lead to improvements in design and the improved evaluation of intuitive use because it allows experiences to be linked directly to the specific image schemas employed in the design.

Commentary by Dr. Valentin Fuster
J. Comput. Inf. Sci. Eng. 2018;18(4):041007-041007-12. doi:10.1115/1.4040607.

Fixture locators are used to precisely locate and stably support a workpiece so that the desired position and orientation (pose) of the workpiece relative to the cutting tool can be maintained during machining or inspection process. It is believed that manufacturing errors of locators and locating datum surfaces are key factors for the pose error between the workpiece and the cutting tool. Optimizing the layout of locators is helpful to reduce the pose error so as to improve machining accuracy of the workpiece. In order to minimize the pose error, we introduced, for the first time, a singular value decomposition (SVD) technique for the location matrix to derive error amplification factors (EAF) in six degrees-of-freedom of the workpiece. The EAF principle defines the maximal singular value, the condition number, the product of all singular values and the manipulability as the maximal error amplification factor, the relative error amplification factor, the error ellipsoid volume and the location stability, respectively. The four defined indices taken as objective functions are optimized, by a nondominated sort genetic algorithm (NSGA-II), so that an optimal layout of locators is obtained due to the minimization of the pose error. Also, the feasibility of the proposed method was comprehensively validated by simulation and machining experiments.

Topics: Errors , Optimization
Commentary by Dr. Valentin Fuster
J. Comput. Inf. Sci. Eng. 2018;18(4):041008-041008-9. doi:10.1115/1.4040460.

Augmented reality (AR) has experienced a breakthrough in many areas of application thanks to cheaper hardware and a strong industry commitment. In the field of management of urban facilities, this technology allows virtual access and interaction with hidden underground elements. This paper presents a new approach to enable AR in mobile devices such as Google Tango, which has specific capabilities to be used outdoors. The first objective is to provide full functionality in the life-cycle management of subsoil infrastructures through this technology. This implies not only visualization, interaction, and free navigation, but also editing, deleting, and inserting elements ubiquitously. For this, a topological data model for three-dimensional (3D) data has been designed. Another important contribution of the paper is getting exact location and orientation performed in only a few minutes, using no additional markers or hardware. This accuracy in the initial positioning, together with the device sensing, avoids the usual errors during the navigation process in AR. Similar functionality has also been implemented in a nonubiquitous way to be supported by any other device through virtual reality (VR). The tests have been performed using real data of the city of Jaén (Spain).

Commentary by Dr. Valentin Fuster
J. Comput. Inf. Sci. Eng. 2018;18(4):041009-041009-12. doi:10.1115/1.4038821.

Mathematical tools underlie a method that has strong potential to lower the cost of fixture-setup when finishing large castings that have machined surfaces where other components are attached. One math tool, the kinematic transformation, is used for the first time to construct Tolerance-Map® (T-Map)® models of geometric and size tolerances that are applied to planar faces and to the axes of round shapes, such as pins or holes. For any polygonal planar shape, a generic T-Map primitive is constructed at each vertex of its convex hull, and each is sheared uniquely with the kinematic transformation. All are then intersected to form the T-Map of the given shape in a single frame of reference. For an axis, the generic T-Map primitive represents each circular limit to its tolerance-zone. Both are transformed to a central frame of reference and are intersected to form the T-Map. The paper also contains the construction for the first five-dimensional (5D) T-Map for controlling the minimum wall thickness between two concentric cylinders with a least-material-condition (LMC) tolerance specification on position. It is formed by adding the dimension of size to the T-Map for an axis. The T-Maps described are consistent with geometric dimensioning and tolerancing standards and industry practice. Finally, transformations are presented to translate between small displacement torsor (SDT) coordinates and the classical coordinates for lines and planes used in T-Maps.

Commentary by Dr. Valentin Fuster
J. Comput. Inf. Sci. Eng. 2018;18(4):041010-041010-8. doi:10.1115/1.4040952.

The mass production paradigm strives for uniformity, and for assembly operations to be identical for each individual product. To accommodate geometric variation between individual parts, tolerances are introduced into the design. However, this method can yield suboptimal quality. In welded assemblies, geometric variation in ingoing parts can significantly impair quality. When parts misalign in interfaces, excessive clamping force must be applied, resulting in additional residual stresses in the welded assemblies. This problem may not always be cost-effective to address simply by tightening tolerances. Therefore, under new paradigm of mass customization, the manufacturing approach can be adapted on an individual level. This paper focuses on two specific mass customization techniques: permutation genetic algorithms (GA) and virtual locator trimming. Based on these techniques, a six-step method is proposed, aimed at minimizing the effects of geometric variation. The six steps are nominal reference point optimization, permutation GA configuration optimization, virtual locator trimming, clamping, welding simulation, and fatigue life evaluation. A case study is presented, which focuses on the selective assembly process of a turbine rear structure of a commercial turbofan engine, where 11 nominally identical parts are welded into a ring. Using this simulation approach, the effects of using permutation GAs and virtual locator trimming to reduce variation are evaluated. The results show that both methods significantly reduce seam variation. However, virtual locator trimming is far more effective in the test case presented, since it virtually eliminates seam variation. These results underscore the potential of virtual trimming and GAs in manufacturing, as a means both to reduce cost and increase functional quality.

Commentary by Dr. Valentin Fuster
J. Comput. Inf. Sci. Eng. 2018;18(4):041011-041011-13. doi:10.1115/1.4040608.

As the core component of an automobile, the internal combustion engine (ICE) nowadays is still a typical complex engineering system. Tolerance design for ICEs is of great importance since small changes in the dimensions and clearances of ICE components may result in large variations on the performance and cost of manufactured products. In addition, uncertainty in tolerance design has great impact on the engine performance. Although tolerance optimization for the key components of ICEs has been discussed, few of them take uncertainty into consideration. In this regard, robust optimization (RO) for the tolerances of ICEs remains a critical issue. In this work, a novel RO approach is proposed to deal with the tolerance optimization problem for ICEs under parameter and model uncertainties, even considering metamodeling uncertainty from Gaussian processes (GP). A typical parameter uncertainty in ICEs exists in the rotation speed which can vary randomly due to the inherent randomness. AVL EXCITE software is used to build the simulation models of ICE components, which brings in model uncertainty. GP models are used as the analysis model in order to combine the corresponding simulation and experimental data together, which introduces metamodeling uncertainty. The proposed RO approach provides a general and systematic procedure for determining robust optimal tolerances and has competitive advantages over traditional experience-based tolerance design. In addition to the ICE example, a numerical example is utilized to demonstrate the applicability and effectiveness of the proposed approach.

Commentary by Dr. Valentin Fuster
J. Comput. Inf. Sci. Eng. 2018;18(4):041012-041012-14. doi:10.1115/1.4040710.

There are a large number of real-world engineering design problems that are multi-objective and multiconstrained, having uncertainty in their inputs. Robust optimization is developed to obtain solutions that are optimal and less sensitive to uncertainty. Since most of complex engineering design problems rely on time-consuming simulations, the robust optimization approaches may become computationally intractable. To address this issue, an advanced multi-objective robust optimization approach based on Kriging model and support vector machine (MORO-KS) is proposed in this work. First, the main problem in MORO-KS is iteratively restricted by constraint cuts formed in the subproblem. Second, each objective function is approximated by a Kriging model to predict the response value. Third, a support vector machine (SVM) classifier is constructed to replace all constraint functions classifying design alternatives into two categories: feasible and infeasible. The proposed MORO-KS approach is tested on two numerical examples and the design optimization of a micro-aerial vehicle (MAV) fuselage. Compared with the results obtained from other MORO approaches, the effectiveness and efficiency of the proposed MORO-KS approach are illustrated.

Commentary by Dr. Valentin Fuster
J. Comput. Inf. Sci. Eng. 2018;18(4):041013-041013-9. doi:10.1115/1.4040981.

This paper presents an adaptive and computationally efficient curvature-guided algorithm for localizing optimum knot locations in fitted splines based on the local minimization of an objective error function. Curvature information is used to narrow the searching area down to a data subset where the local error function becomes one-dimensional, convex, and bounded, thus guaranteeing a fast numerical solution. Unlike standard curvature-guided methods, typically relying on heuristic rules, the novel method here presented is based on a phenomenological approach as the error function to be minimized represents geometrical properties of the curve to be fitted, consequently reducing case-sensitivity issues and the possibility of defining spurious knots. A knot-readjustment procedure performed in the vicinity of a newly created knot has the ability of dispersing knots from otherwise highly knot-populated regions, a feature known to generate undesired local oscillations. The performance of the introduced method is tested against three other methods described in the literature, each handling the knot-placement problem via a different paradigm. The quality of the fitted splines for several datasets is compared in terms of the overall accuracy, the number of knots, and the computing efficiency. It is demonstrated that the novel algorithm leads to a significantly smaller knot vector and a much lower computing time, while preserving or improving the overall accuracy.

Topics: Splines , Algorithms , Errors
Commentary by Dr. Valentin Fuster
J. Comput. Inf. Sci. Eng. 2018;18(4):041014-041014-13. doi:10.1115/1.4040982.

We introduce an intuitive gesture-based interaction technique for creating and manipulating simple three-dimensional (3D) shapes. Specifically, the developed interface utilizes low-cost depth camera to capture user's hand gesture as the input, maps different gestures to system commands and generates 3D models from midair 3D sketches (as opposed to traditional two-dimensional (2D) sketches). Our primary contribution is in the development of an intuitive gesture-based interface that enables novice users to rapidly construct conceptual 3D models. Our development extends current works by proposing both design and technical solutions to the challenges of the gestural modeling interface for conceptual 3D shapes. The preliminary user study results suggest that the developed framework is intuitive to use and able to create a variety of 3D conceptual models.

Commentary by Dr. Valentin Fuster
J. Comput. Inf. Sci. Eng. 2018;18(4):041015-041015-11. doi:10.1115/1.4041166.

To obtain real-time interactions in the virtual cockpit system (VCS), a real-time trajectory generation method based on dynamical nonlinear optimization and regression prediction for the haptic feedback manipulator (HFM) is presented in this paper. First, a haptic feedback system based on servoserial manipulator is constructed. Then, the trajectory planning problem for the HFM is formulated as a nonlinear optimization problem to balance the motion time and power consumption and ensure the safety of physical human–robot interactions (pHRI). Multiple optimization problems are solved to generate the optimal database off-line. Finally, the classified multivariate (CM) regression method is presented to learn the database and generate optimal trajectories with arbitrary initial and objective positions on-line. Results show that trajectories with rapidity, safety, and lower power consumption can be generated in real-time by this method, which lay a basis of haptic interactions in the VCS.

Commentary by Dr. Valentin Fuster

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