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Accepted Manuscripts

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Review Article  
Siva Chaitanya Chaduvula, Adam Dachowicz, Mikhail Atallah and Jitesh H. Panchal
J. Comput. Inf. Sci. Eng   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/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 anti-counterfeiting 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.
TOPICS: Manufacturing, Design, Security, Collaboration, Product development, Watermarking, Leakage, Innovation, Intellectual property, Cycles, Encryption
research-article  
Dimitris Mourtzis, Anna-Maria Papatheodorou and Sophia Fotia
J. Comput. Inf. Sci. Eng   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 towards 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.
TOPICS: Computer software, Decision making, Storage, Data collection, Sustainability, Visualization
Editorial  
Jitesh H. Panchal
J. Comput. Inf. Sci. Eng   doi: 10.1115/1.4040307
This is the first special issue based on selected papers presented at the 37th ASME Computers and Information in Engineering (CIE) conference held in Cleveland, Ohio, August 6-9, 2017. The CIE conference is held annually in conjunction with the International Design Engineering Technical Conferences (IDETC). The ASME CIE conference is the flagship conference of the ASME's CIE division. This special issue contains 11 papers selected from 95 papers presented at the conference on diverse topics related to the Journal of Computing and Information Science in Engineering (JCISE). The topics range from computational methods to human-computer interactions.
TOPICS: Computers and information in engineering , Design engineering, Computers, Computational methods
research-article  
Baris Yalçin, Cihan Demir, Murat Gokce and Ahmet Koyun
J. Comput. Inf. Sci. Eng   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 & academia due to the financial cost related with public health risks, environmental responsibility and energy efficiency. In this paper, to find a reliable & 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.
TOPICS: Water leakage, Algorithms, Pipes, Water distribution, Leakage, Health risk assessment, Disasters, Energy efficiency, Nuclear power stations, Water, Pressure, Flow (Dynamics), Cooling, Fluids, Sensors, Waste disposal
Review Article  
Francesco Tamburrino, Serena Graziosi and Monica Bordegoni
J. Comput. Inf. Sci. Eng   doi: 10.1115/1.4040131
This review focuses on the design process of additive manufactured Meso-Scale Lattice Structures (MSLSs). They are arrays of 3D printed trussed unit cells, whose dimension spans 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.
TOPICS: Design, Computer software, Additive manufacturing, Dimensions, Manufacturing, Arches
research-article  
Robert Kirkwood and James A. Sherwood
J. Comput. Inf. Sci. Eng   doi: 10.1115/1.4040024
CAD/CAM/CAE integration offers designers, analysts, and manufacturers the opportunity to share data efficiently throughout the product development process. CAM for NC programming 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 article 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 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.
TOPICS: Computer-aided design, Design, Computer-aided engineering, Solid models, Finishes, Engineering design processes, Product development, Computer programming
research-article  
Binbin Zhang, Prakhar Jaiswal, Rahul Rai and Saigopal Nelaturi
J. Comput. Inf. Sci. Eng   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 simultaneously possess properties of multiple different materials. Emerging AM technologies enables 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 multi-material AM techniques.
TOPICS: Additive manufacturing, Functionally graded materials, Multifunctional materials, Path planning, Shapes, Manufacturing, Wakes, Modeling, Classification
research-article  
Craig Shakarji and Vijay Srinivasan
J. Comput. Inf. Sci. Eng   doi: 10.1115/1.4039583
This paper addresses the combinatorial characterizations of the optimality conditions for constrained least-squares fitting of circles, cylinders, and spheres to a set of input points. It is shown that the necessary condition for optimization requires contacting at least two input points. It is also shown that there exist cases where the optimal condition is achieved while contacting only two input points. These problems arise in digital manufacturing, where one is confronted with the task of processing a (potentially large) number of points with three-dimensional coordinates to establish datums on manufactured parts. The optimality conditions reported in this paper provide the necessary conditions to verify if a candidate solution is feasible, and to design new algorithms to compute globally optimal solutions.
TOPICS: Cylinders, Fittings, Manufacturing, Algorithms, Design, Optimization
research-article  
Ramin Sabbagh, Farhad Ameri and Reid Yoder
J. Comput. Inf. Sci. Eng   doi: 10.1115/1.4039553
Manufacturing capability analysis is a necessary step in the early stages of supply chain formation. In the contract manufacturing industry, companies often advertise their capabilities and services in an unstructured format on the company website. The unstructured capability data usually portrays a realistic view of the services a supplier can offer. If parsed and analyzed properly, unstructured capability data can be used effectively for initial screening and characterization of manufacturing suppliers specially when dealing with a large pool of suppliers. This work proposes a novel framework for capability-based supplier classification that relies on the unstructured capability narratives available on the suppliers websites. Four document classification algorithms, namely, Support Vector Machine (SVM), Nave Bayes (NB), Random Forest (RF), and K-Nearest Neighbour (KNN) are used as the text classification techniques. One of the innovative aspects of this work is incorporating a thesaurus-guided method for feature selection and tokenization of capability data. The thesaurus contains the formal and informal vocabulary used in the contract machining industry for advertising manufacturing capabilities. A web-based tool is developed for the generation of the concept vector model associated with each capability narrative and extraction of features from the input documents. The proposed supplier classification framework is validated experimentally through forming two capability classes, namely, heavy component machining and difficult and complex machining, based on real capability data. It was concluded that thesaurus-guided method improves the precision of the classification process.
TOPICS: Manufacturing, Text analytics, Machining, Support vector machines, Algorithms, Feature extraction, Feature selection, Manufacturing industry, Supply chains
research-article  
Gaurav Ameta, Gagandeep Singh, Joseph K. Davidson and Jami Shah
J. Comput. Inf. Sci. Eng   doi: 10.1115/1.4039473
For the first time, Tolerance-Maps© (T-Maps©) are constructed to model composite positional tolerancing applied to patterns (arrays) of features. The T-Map for a feature is a range (codomain) of points obtained by mapping all the variational possibilities (domain) of a feature within its tolerance-zone to a hypothetical Euclidean point space. T-Maps have been developed for tolerances applied to single features, but not for specifications available for tolerancing patterns of features. In this paper, the different pattern tolerancing from the Standards produce distinctions in geometric shape, proportions, and/or dimensions of a T-Map. The T-Map geometry is different when tolerances are specified with composite position tolerancing rather than with two-single-segment control frames. Additional changes to geometry occur when material modifiers are also specified. Two levels of T-Maps are proposed for a pattern of features; assembly-level and part-level. Assembly-level ensures the assembly of an engaging pattern of pins and holes, such as the array of pins on an integrated circuit which are to be inserted into a base. Part-level models the variations between the two parts that contain the engaging patterns. The assembly-level T-maps apply to any number of engaging pin/hole features arranged in any pattern: linear, circular, rectangular, or irregular. In this paper, the part-level T-Map is restricted to linear patterns. The different specifications are compared with a statistical analysis of misalignment for an assembly with linear pattern of pins and holes.
TOPICS: Composite materials, Manufacturing, Pins (Engineering), Geometry, Integrated circuits, Shapes, Statistical analysis, Dimensions
research-article  
William Bailey, Judy Che, Poyu Tsou and Mark Jennings
J. Comput. Inf. Sci. Eng   doi: 10.1115/1.4039474
Integrated vehicle simulation models are being increasingly used to improve engineering efficiency and reduce the number of real-world prototypes needed to understand vehicle attributes and subsystem interactions. Each domain within the vehicle must be represented by its own model developed with the appropriate physics, behavior, fidelity, and interfaces needed to interact with other domains in the vehicle. Planning and managing the development of these models across a large, multidisciplinary group of engineers can be a significant effort. In particular, carefully managing each model's interfaces is crucial to enabling the entire process; missing or inappropriately used signals can cause significant issues when many separate domain models are integrated together. To help system engineers better manage these interfaces across a broad variety of applications, a SysML-based modeling approach is proposed to describe these models and their interfaces formally and completely. However, even with a consistent modeling approach, creating and managing interfaces across a large number of domains and applications can be a significant, error-prone task. To reduce the amount of manual modeling work required and help scale the process for complex models, an interface management framework is proposed to help automate the process of importing existing interfaces, routing and visualizing them, and exporting model templates for developers to use when creating new models. By automating this process, it becomes significantly easier to reuse models across simulation architectures (rather than creating new models from scratch) and frees up resources to improve simulation accuracy throughout a system's design.
TOPICS: Physics, Engineers, Simulation, Engineering prototypes, Design, Modeling, Vehicles, Architecture, Errors, Signals, Simulation models
research-article  
Kevin Lesniak and Conrad Tucker
J. Comput. Inf. Sci. Eng   doi: 10.1115/1.4039472
Modern RGB-D sensing systems are capable of reconstructing convincing virtual representations of real world environments. These virtual reconstructions can be used as the foundation for Virtual Reality (VR) and Augmented Reality (AR) environments due to their high quality visualizations. However, a main limitation of modern virtual reconstruction methods is the time it takes to incorporate new data and update the virtual reconstruction. This delay prevents the reconstruction from accurately rendering dynamic objects or portions of the environment (like an engineer performing an inspection of a machinery or lab space). The authors propose a multi-sensor method to dynamically capture objects in an indoor environment. The method automatically aligns the sensors using modern image homography techniques, and leverages Graphics Processing Units (GPUs) to process the large number of independent RGB-D data points and render them in real-time. Incorporating and aligning multiple sensors allows a larger area to be captured from multiple angles, providing a more complete virtual representation of the physical space. Performing processing on GPU's leverages the large number of processing cores available to minimize the delay between data capture and rendering. A case study using commodity RGB-D sensors, computing hardware, and standard TCP internet connections is presented to demonstrate the viability of the proposed method.
TOPICS: Rendering, Sensors, Delays, Graphics processing units, Machinery, Internet, Virtual reality, Inspection, Engineers, Hardware, Space, Visualization
research-article  
Dedy Ariansyah, Giandomenico Caruso, Daniele Ruscio and Monica Bordegoni
J. Comput. Inf. Sci. Eng   doi: 10.1115/1.4039313
Advanced driver assistance systems (ADASs) allow information provision through visual, auditory, and haptic signals to achieve multi-dimensional goals of mobility. However, processing information from ADAS requires operating expenses of mental workload that drivers incur from their limited attentional resources. The change in driving condition can modulate driver's workload and potentially impair drive's interaction with ADAS. This paper shows how the measure of cardiac activity (heart rate and the indexes of autonomic nervous system) could discriminate the influence of different driving conditions on driver's workload associated with attentional resources engaged while driving with ADAS. Fourteen drivers performed a car following task with visual ADAS in driving simulator. Driver's workload was manipulated in two conditions: one in monotonous condition (constant speed); and another in more active condition (variable speed). Results showed that driver's workload was similarly affected, but the amount of attentional resources allocation was slightly distinct between both conditions. The analysis of main effect of time demonstrated that drivers' workload increased over time without alterations in autonomic indexes regardless of driving condition. However, the main effect of driving condition produced a higher level of sympathetic activation on variable speed driving compared to driving with constant speed. Variable speed driving requires more adjustment of steering wheel movement to maintain lane-keeping performance, which led to higher level of task involvement and increased task engagement. The proposed measures could help to design new adaptive working modalities for ADAS on the account of variation in driving condition.
TOPICS: Design, Haptics, Signals, Nervous system, Steering wheels, Mechanical admittance
research-article  
John Michopoulos, Athanasios P. Iliopoulos, John Steuben and Virginia DeGiorgi
J. Comput. Inf. Sci. Eng   doi: 10.1115/1.4039311
In order to account and compensate for the dissipative processes contributing to the aging of cathodic surfaces protected by impressed current cathodic protection (ICCP) systems, it is necessary to develop the proper modeling and numerical infrastructure that can predict aging associated with quantities affecting the controller of these systems. In the present work we describe various approaches for developing Cathodic Surface Aging Models (CSAMs) based on both data-driven and first principles based methodologies. A computational ICCP framework is implemented in a manner that enables the simulation of the effects of cathodic aging in a manner that allows the utilization of various CSAMs that effect the relevant potentiodynamic polarization curves of the cathodic materials. An application of this framework demonstrates the capabilities of this system. We introduce a data-driven CSAM based on a loft-surface approximation, and in response to the limitations of this approach we also formulate a first principles based multiphysics and thermodynamic theory for aging. Furthermore, we discuss the design of a systematic experimental task for validating and calibrating this theory in the near future.
TOPICS: Cathodic protection, Modeling, Approximation, Polarization (Waves), Control equipment, Simulation, Polarization (Electricity), Polarization (Light), Design
research-article  
John Steuben, Athanasios P. Iliopoulos and John Michopoulos
J. Comput. Inf. Sci. Eng   doi: 10.1115/1.4039312
The precise control of mass and energy deposition associated with Additive Manufacturing (AM) processes enables the topological specification and realization of how space can be filled by material in multiple scales. Consequently, AM can be pursued in a manner that is optimized such that fabricated objects can best realize performance specifications. In the present work, we propose a computational multiscale method that utilizes the unique meso-scale structuring capabilities of implicit slicers for AM, in conjunction with existing topology optimization tools for the macro-scale, in order to generate structurally optimized components. The use of this method is demonstrated on two example objects including a load bearing bracket and a hand tool. This paper also includes discussion concerning the applications of this methodology, its current limitations, a reimagining of the additive manufacturing digital thread and the future work required to enable its widespread use.
TOPICS: Optimization, Topology, Additive manufacturing, Hand tools, Stress, Thread, Bearings
Technical Brief  
Chih-Hsing Chu and I-Jan Wang
J. Comput. Inf. Sci. Eng   doi: 10.1115/1.4039335
The cosmetic mask is a popular skin care product widely used by young, and particularly female, consumers. Most cosmetic masks currently on the market offer very few sizes from which to choose; this results in ill-fitting masks with reduced comfortability and skin care functionality. This paper describes how to realize customized design of cosmetic masks using 3D parametric face models derived from scanned facial data. The parametric models approximate individual faces by using a nonlinear regression model with boundary conditions determined as a set of easy-to-measure facial parameters. The models provide the reference geometry for 3D mask designs. A prototyping mask design system implementing the proposed parametric modeling method is created to demonstrate the customized design process. The system allows the user to define the mask shape on the 3D meshes of a face model by specifying inner and outer boundary curves. An automatic flattening function is implemented to unfold the trimmed meshes into a 2D pattern with reduced shape distortion. This study uses cosmetic facial masks as an example product to demonstrate the practical value of applying large-scale anthropometric data for the realization of human-centered design customization.
TOPICS: Design, Shapes, Skin, Respirators, Modeling, Boundary-value problems, Fittings, Geometry, Regression models
research-article  
Dimitrios Anagnostakis, J.M. Ritchie, T Lim, Raymond Sung and Richard Dewar
J. Comput. Inf. Sci. Eng   doi: 10.1115/1.4039194
Capturing the strategy followed during a Coordinate Measuring Machine (CMM) inspection planning session has been an extremely challenging issue due to the time-consuming nature of traditional methods, such as interviewing experts and technical documents data mining. This paper presents a methodology demonstrating how a motion capture-based system can facilitate direct and non-intrusive CMM operator logging for capturing planning strategies and representing in knowledge formats. With the use of recorded motion data, embedded knowledge and expertise can be captured automatically and formalized in various formats such as motion trajectory graphs, inspection plans, Integrated DEFinition (IDEF) model diagrams and other representations. Additionally, a part program can be generated for driving a CMM to execute component measurement. The system's outputs can be used to help understand how a CMM inspection strategy is planned, as well as training aids for inexperienced operators and the rapid generation of part programs.
TOPICS: Inspection, Coordinate measuring machines, Trajectories (Physics), Data mining
research-article  
Krishnanand Kaipa, Carlos Morato and Satyandra K. Gupta
J. Comput. Inf. Sci. Eng   doi: 10.1115/1.4039061
This paper presents a framework to build hybrid cells that support safe and efficient human-robot collaboration during assembly operations. Our approach allows asynchronous collaborations between human and robot. The human retrieves parts from a bin and places them in the robot's workspace, while the robot picks up the placed parts and assembles them into the product. We present the design details of the overall framework comprising three modules - plan generation, system state monitoring, and contingency handling. We describe system state monitoring and present a characterization of the part tracking algorithm. We report results from human-robot collaboration experiments using a KUKA robot and a 3D-printed mockup of a simplified jet-engine assembly to illustrate our approach.
TOPICS: Robots, Manufacturing, Design, Collaboration, Jet engines, Additive manufacturing, Algorithms
research-article  
Nathan Kalish, Joseph K. Davidson, Satchit Ramnath, Payam Haghighi and Jami S. Shah
J. Comput. Inf. Sci. Eng   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 5D T-Map for controlling the minimum wall thickness between two concentric cylinders with a least-material-condition 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.
TOPICS: Kinematics, Dimensions, Finishing, Construction, Pins (Engineering), Space, Cylinders, Displacement, Shapes, Wall thickness, Hull, Geometric dimensioning and tolerancing, Mathematics
research-article  
Bruno S. Machado, Nilanjan Chakraborty, Mohamed Mamlouk and Prodip K. Das
J. Comput. Inf. Sci. Eng   doi: 10.1115/1.4037942
In this study, a three-dimensional agglomerate model of an anion exchange membrane fuel cell is proposed in order to account the detailed composition of the catalyst layers (CLs). Here, a detailed comparison between the agglomerate and a macro-homogeneous model is provided, elucidating the effects of the first implementation on the overall performance and the individual losses, the effects operating temperature and inlet relative humidity on the cell performance, and the catalyst layer utilisation by the effectiveness factor. The results show that the macro-homogeneous model overestimates the cell performance compared to the agglomerate model due to the resistances associated with the species and ionic transport in the catalyst layers. Consequently the hydration is negatively affected, resulting in a higher ohmic resistance. The activation overpotential is over-predicted by the macro-homogeneous model, as the agglomerate model relates the transportation resistances within the domain with the CL composition. Despite the higher utilisation in the anode CL, the cathode CL utilisation presents significant drop near the membrane-CL interface, due to the higher current density and low oxygen concentration. Additionally, the effects of operating temperature and relative humidity at the flow channel inlet were analysed. Similar to the macro-homogeneous model, the overall cell performance of the agglomerate model is enhanced with increasing operating temperature due to the better electrochemical kinetics. However, as the relative humidity at the inlet is reduced, the overall performance of the cell deteriorates due to the poor hydration of the membrane.
TOPICS: Fuel cells, Membranes, Catalysts, Operating temperature, Current density, Oxygen, Transportation systems, Flow (Dynamics), Anodes, Overvoltage

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