Research Papers

J. Comput. Inf. Sci. Eng. 2017;17(2):021001-021001-7. doi:10.1115/1.4034385.

This work presents an approach to simulate laser cutting of ceramic substrates utilizing a phase field model for brittle fracture. To start with, the necessary thermoelastic extension of the original phase field model is introduced. Here, the Beer–Lambert law is used in order to model the effect of the laser on the substrate. The arising system of partial differential equations—which comprises the balance of linear momentum, the energy balance, and the evolution equation that governs crack propagation—is solved by a monolithic finite-element scheme. Finally, the influences of the laser power and the initial groove size on the manufactured work piece are analyzed numerically in simulations of a laser-cutting process.

Commentary by Dr. Valentin Fuster
J. Comput. Inf. Sci. Eng. 2017;17(2):021002-021002-7. doi:10.1115/1.4034473.

The process of selective laser sintering (SLS) involves selective heating and fusion of powdered material using a moving laser beam. Because of its complicated manufacturing process, physical modeling of the transformation from powder to final product in the SLS process is currently a challenge. Existing simulations of transient temperatures during this process are performed either using finite-element (FE) or discrete-element (DE) methods which are either inaccurate in representing the heat-affected zone (HAZ) or computationally expensive to be practical in large-scale industrial applications. In this work, a new computational model for physical modeling of the transient temperature of the powder bed during the SLS process is developed that combines the FE and the DE methods and accounts for the dynamic changes of particle contact areas in the HAZ. The results show significant improvements in computational efficiency over traditional DE simulations while maintaining the same level of accuracy.

Commentary by Dr. Valentin Fuster
J. Comput. Inf. Sci. Eng. 2017;17(2):021003-021003-15. doi:10.1115/1.4034386.

Scattered light sensors are optical sensors commonly used in industrial applications. They are particularly well suited to characterizing surface roughness. In contrast to most geometric measuring devices, a scattered light sensor measures reflection angles of surfaces according to the principle of the so-called mirror facet model. Surfaces can be evaluated based on the statistical distribution of the surface angles, meaning the gradients. To better understand how the sensor behaves, it is helpful to create a virtual model. Ray-tracing methods are just as conceivable as purely mathematical methods based on convolution. The mathematical description is especially interesting because it promotes fundamental comprehension of angle-resolved scattered light measurement technology and requires significantly less computation time than ray-tracing algorithms. Simplified and idealized assumptions are accepted. To reduce the effort required to simulate the sensor, an attempt was made to implement an idealized mathematical model using Matlab® to be able to quickly generate information on scattered light distribution without excessive effort. Studies were conducted to determine the extent to which the results of modeling correspond to the transfer characteristics of a virtual Zemax sensor, on the one hand, and with the measurement results of the actual scattered light sensor, on the other hand.

Commentary by Dr. Valentin Fuster
J. Comput. Inf. Sci. Eng. 2017;17(2):021004-021004-10. doi:10.1115/1.4035269.

Information exchange and sharing become a necessity for digital factory but they have been more challenging as the industry is computerized more. This is mainly because the capabilities of computerized systems have grown significantly in a very rapid pace in their own information structure, and they require to retrieve various data from different computer systems. ISO 10303–STEP has been developed to provide a neutral format for exchanging product data. However, implementation of STEP has several issues, including the following two: (1) the complete STEP file should be processed even for querying a small set of data, and (2) information required for realizing any functional activity (e.g., any analysis on any part of a product) is not explicitly identified. Hence, in this study, functionality-based conformance classes (FCCs) are developed to organize the current conformance classes (CCs) (which are the classes required to be implemented fully in order to be conformant to any particular STEP standard) for supporting different functional activities. Following the concept of data exchange specification (DEX)/template, several templates that are repeatedly used small information groups are introduced in order to create manageable sets of data constructs. In this study, the FCCs for 1D tolerance analysis are developed by enriching the available STEP information models with GD&T. The use of extended STEP models is illustrated with a case study.

Commentary by Dr. Valentin Fuster
J. Comput. Inf. Sci. Eng. 2017;17(2):021005-021005-8. doi:10.1115/1.4034872.

Modern cyber-physical production systems (CPPS) connect different elements like machine tools and workpieces. The constituent elements are often equipped with high-performance sensors as well as information and communication technology, enabling them to interact with each other. This leads to an increasing amount and complexity of data that requires better analysis tools to support system refinement and revision performed by an expert. This paper presents a user-guided visual analysis approach that can answer relevant questions concerning the behavior of cyber-physical systems. The approach generates visualizations of aggregated views that capture an entire production system as well as specific characteristics of individual data features. To show the applicability of the presented methodologies, an exemplary production system is simulated and analyzed.

Commentary by Dr. Valentin Fuster
J. Comput. Inf. Sci. Eng. 2017;17(2):021006-021006-7. doi:10.1115/1.4034585.

The deployment of modern information and communication technologies (ICT) within manufacturing systems leads to the creation of so-called cyber-physical production systems that consist of intelligent interconnected production facilities. One of the expected features of cyber-physical production systems is found to be the capability of self-organization and decentralized process planning in manufacturing. The functionality as well as the benefit of such self-organization concepts is yet to be proved. In this paper, the implementation of a virtual test field for the simulation of manufacturing systems based on a multi-agent system modeling concept is presented and used to evaluate a concept of decentralized process planning. Thereby, special focus is laid on the impact on energy consumption. The simulation results show the potential for energy reduction in manufacturing by a decentralized process-planning concept and yields hints for further development of such concepts.

Commentary by Dr. Valentin Fuster
J. Comput. Inf. Sci. Eng. 2017;17(2):021007-021007-9. doi:10.1115/1.4034999.

In multiscale materials modeling, it is desirable that different levels of details can be specified in different regions of interest without the separation of scales so that the geometric and physical properties of materials can be designed and characterized. Existing materials modeling approaches focus more on the representation of the distributions of material compositions captured from images. In this paper, a multiscale materials modeling method is proposed to support interactive specification and visualization of material microstructures at multiple levels of details, where designer's intent at multiple scales is captured. This method provides a feature-based modeling approach based on a recently developed surfacelet basis. It has the capability to support seamless zoom-in and zoom-out. The modeling, operation, and elucidation of materials are realized in both the surfacelet space and the image space.

Commentary by Dr. Valentin Fuster
J. Comput. Inf. Sci. Eng. 2017;17(2):021008-021008-10. doi:10.1115/1.4034741.

Controlling and accomplishing the desired functional material composition in a heterogeneous object (HO) is a close loop process and requires frequent remodeling-and-analysis. Thus, flexibility and capability to efficiently modify the existing CAD model of a heterogeneous object are essential aspects of heterogeneous object modeling. The current work unfolds such capabilities of the developed material convolution surface approach. The geometric and material control features associated with the approach demonstrate the potential to modify existing material-distributions to remodel complex material variations and assure rapid heterogeneous composition adaptations. Convolution material primitives (CMPs), material potential functions, and heterogeneous and grading enclosure are manipulated to achieve desired material compositions across the heterogeneous region. The manipulation process for each control feature has been established. A few examples of modeling and modifying complex material-distributions have been reported for the validation of work.

Topics: Modeling , Geometry
Commentary by Dr. Valentin Fuster
J. Comput. Inf. Sci. Eng. 2017;17(2):021009-021009-8. doi:10.1115/1.4034010.

Additive manufacturing, also known as three-dimensional (3D) printing, enables production of complex customized shapes without requiring specialized tooling and fixture, and mass customization can then be realized with larger adoption. The slicing procedure is one of the fundamental tasks for 3D printing, and the slicing resolution has to be very high for fine fabrication, especially in the recent developed continuous liquid interface production (CLIP) process. The slicing procedure is then becoming the bottleneck in the prefabrication process, which could take hours for one model. This becomes even more significant in mass customization, where hundreds or thousands of models have to be fabricated. We observe that the customized products are generally in a same homogeneous class of shape with small variation. Our study finds that the slicing information of one model can be reused for other models in the same homogeneous group under a properly defined parameterization. Experimental results show that the reuse of slicing information has a maximum of 50 times speedup, and its utilization is dropped from more than 90% to less than 50% in the prefabrication process.

Commentary by Dr. Valentin Fuster
J. Comput. Inf. Sci. Eng. 2017;17(2):021010-021010-13. doi:10.1115/1.4034132.

Industry has been chasing the dream of integrating and linking data across the product lifecycle and enterprises for decades. However, industry has been challenged by the fact that the context in which data are used varies based on the function/role in the product lifecycle that is interacting with the data. Holistically, the data across the product lifecycle must be considered an unstructured data set because multiple data repositories and domain-specific schema exist in each phase of the lifecycle. This paper explores a concept called the lifecycle information framework and technology (LIFT). LIFT is a conceptual framework for lifecycle information management and the integration of emerging and existing technologies, which together form the basis of a research agenda for dynamic information modeling in support of digital-data curation and reuse in manufacturing. This paper provides a discussion of the existing technologies and activities that the LIFT concept leverages. Also, the paper describes the motivation for applying such work to the domain of manufacturing. Then, the LIFT concept is discussed in detail, while underlying technologies are further examined and a use case is detailed. Lastly, potential impacts are explored.

Topics: Manufacturing , Design
Commentary by Dr. Valentin Fuster
J. Comput. Inf. Sci. Eng. 2017;17(2):021011-021011-11. doi:10.1115/1.4034268.

The goal of this paper is to illustrate the use of category theory (CT) as a basis for the integration of manufacturing service databases. In this paper, we use as our reference prior work by Kulvatunyou et al. (2013, “An Analysis of OWL-Based Semantic Mediation Approaches to Enhance Manufacturing Service Capability Models,” Int. J. Comput. Integr. Manuf., 27(9), pp. 803–823) on the use of web ontology language (OWL)-based semantic web tools to study the integration of different manufacturing service capability (MSC) databases using a generic-model approach that they propose in their paper. We approach the same task using a different set of tools, specifically CT and FQL, a functorial query language based on categorical mathematics. This work demonstrates the potential utility of category-theoretic information management tools and illustrates some advantages of categorical techniques for the integration and evolution of databases. We conclude by making the case that a category-theoretic approach can provide a more flexible and robust approach to integration of existing and evolving information.

Commentary by Dr. Valentin Fuster
J. Comput. Inf. Sci. Eng. 2017;17(2):021012-021012-9. doi:10.1115/1.4034874.

Shape deformation is a well-known problem in additive manufacturing (AM). For example, in the stereolithography (SL) process, some of the factors that lead to part deformation including volumetric shrinkage, thermal cooling, added supporting structures, and the layer-by-layer building process. Variant sources of deformation and their interactions make it difficult to predict and control the shape deformation to achieve high accuracy that is comparable to numerically controlled machining. In this paper, a computational framework based on a general reverse compensation approach is presented to reduce the shape deformation in AM processes. In the reverse compensation process, the shape deformation is first calculated by physical measurements. A novel method to capture the physical deformation by finding the optimal correspondence between the deformed shape and the given nominal model is presented. The amount of compensation is determined by a compensation profile that is established based on nominal and offset models. The compensated digital model can be rebuilt using the same building process for a part with significantly less part deformation than the built part related to the nominal model. Two test cases have been performed to demonstrate the effectiveness of the presented computational framework. There is a 40–60% improvement in terms of L2- and L-norm measurements on geometric errors.

Topics: Deformation , Shapes
Commentary by Dr. Valentin Fuster
J. Comput. Inf. Sci. Eng. 2017;17(2):021013-021013-9. doi:10.1115/1.4035787.

Design for additive manufacturing (DFAM) gives designers new freedoms to create complex geometries and combine parts into one. However, it has its own limitations, and more importantly, requires a shift in thinking from traditional design for subtractive manufacturing. There is a lack of formal and structured guidelines, especially for novice designers. To formalize knowledge of DFAM, we have developed an ontology using formal web ontology language (OWL)/resource description framework (RDF) representations in the Protégé tool. The description logic formalism facilitates expressing domain knowledge as well as capturing information from benchmark studies. This is demonstrated in a case study with three design features: revolute joint, threaded assembly (screw connection), and slider–crank. How multiple instances (build events) are stored and retrieved in the knowledge base is discussed in light of modeling requirements for the DFAM knowledge base: knowledge capture and reuse, supporting a tutoring system, integration into cad tools. A set of competency questions are described to evaluate knowledge retrieval. Examples are given with SPARQL queries. Reasoning with semantic web rule language (SWRL) is exemplified for manufacturability analysis. Knowledge documentation is the main objective of the current ontology. However, description logic creates multiple opportunities for future work, including representing and reasoning about DFAM rules in a structured modular hierarchy, discovering new rules with induction, and recognizing patterns with classification, e.g., what leads to “successful” versus “unsuccessful” fabrications.

Commentary by Dr. Valentin Fuster

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In