Exchange Of Model Data Research Articles

A security framework for QaaS model in intelligent transportation systems

Recent advances in the development of intelligent transportation systems (ITSs) impose complex services that utilize Query-as-a-Service Model in ITS microsystems. Such model is vulnerable to a vast range of security threats such as Man-in-the-Middle attacks. Intelligent sensors and microsystems provide important systems-level functionalities to smart cities applications, which enhance data acquisition and system control services. This paper proposes a communication framework that handles intrusion threats to intelligent sensors during the data acquisition and service provision phases. The contributions of this research are: (1) Proposing a reliable Query-as-a-Service communication model based on Fog computing architecture, (2) Proposing communication protocols that preserve the integrity of exchanged data through intelligent sensors, and (3) Providing a security analysis based on the mobile nature of vehicles in ITS microsystems. Our proposed methodology is a data-driven one, in which entities exchange data models instead of the data itself, thus, minimizing the communication overhead and providing a smart way to tolerate misinformation. We have conducted experiments to analyze the impact of failure rate and the size of exchanged data on our proposed framework. In addition, the computational cost has been tested against the amount of communicated data reports. The results indicated that the proposed framework showed high performance in terms of the impact of data granularity on the failure rate and computational cost. Our proposed methodology achieved 89.6% detection rate, 3.5% false-detection rate, and <0.02 probability of query failure. Accordingly, our proposed framework overcomes the major limitations of traditional cloud-based model.

A BIM Based Framework for Damage Segmentation, Modeling, and Visualization Using IFC

Paper-based data acquisition and manual transfer between incompatible software or data formats during inspections of bridges, as done currently, are time-consuming, error-prone, cumbersome, and lead to information loss. A fully digitized workflow using open data formats would reduce data loss, efforts, and the costs of future inspections. On the one hand, existing studies proposed methods to automatize data acquisition and visualization for inspections. These studies lack an open standard to make the gathered data available for other processes. On the other hand, several studies discuss data structures for exchanging damage information among different stakeholders. However, those studies do not cover the process of automatic data acquisition and transfer. This study focuses on a framework that incorporates automatic damage data acquisition, transfer, and a damage information model for data exchange. This enables inspectors to use damage data for subsequent analyses and simulations. The proposed framework shows the potentials for a comprehensive damage information model and related (semi-)automatic data acquisition and processing.

Adaptive CAM planning to support co-design in the building industry

Co-design describes a collaborative design process between different stakeholders. These stakeholders usually come from various domains. To enable co-design, data has to be exchanged between the stakeholders. Current approaches to data management in the building industry are usually oriented along the process chain and therefore only allow a unidirectional flow of information. This is an obstacle in the implementation of co-design within the building industry.As more and more buildings are built by utilizing prefabricated modules to accelerate the on-site building process and to reduce the cost, a major effort in terms of implementing co-design is to link the design information of the building industry with the production information of the manufacturing industry. The problem occurs as the building industry mainly uses the fndustry Foundation Classes and the manufacturing industry uses the Standard for the Exchange of Product Model Data as a data format to exchange information. This leads to a break in the flow of information. Furthermore, information about the manufacturability of products, that is generated during the computer-aided manufacturing process, cannot be easily returned to the architect who can utilize the information to adapt the design in the computer-aided design process.This paper addresses these problems by defining a data processing pipeline that enables the conversion of the geometric design information stored in IFC into the STEP data format. From there, the CAM strategy can be defined and results in an executable G-Code. The information of the CAM planning is returned to the architect, who can adapt the design by interpreting the results of the CAM processing. To close the co-design loop, the G-Code for the design adaptions can be generated automatically by reusing the predefined CAM strategy.

A New Implementation of ontostep: Flexible Generation of Ontology and Knowledge Graphs of express-Driven Data

Abstract ontostep is a method to translate the STandard for the Exchange of Product Model Data (STEP) schema and its instances to an ontology and knowledge graphs represented in the web ontology language (owl). ontostep models can be integrated with any owl models to enrich their semantics. However, the current implementation has several limitations, mainly in (1) supporting the latest International Organization for Standardization (ISO) 10303 schemas and (2) generating various representation types depending on the purpose of use. We present an improved implementation of ontostep to overcome these limitations. In this article, we demonstrate that the new implementation can successfully translate STEP schemas and instances in a faster and more flexible way, thus furthering the adoption of the full capabilities of ISO 10303. By encoding STEP entities in owl, we facilitate integration with other standards through knowledge graphs.

STEP-NC-Compliant Implementation to Support Mixed-Control Technologies Applied to Stone-Processing Machines Based on Industrial Automation Standards

STEP-NC (Standard for the Exchange of Product Model Data–Numerical Control) for metal milling and turning is not implemented by industrial computer numerical controllers. Solutions reported are prototypes based on post-processing in G-code. Moreover, minority machining processes, such as stone cutting, have not yet been contemplated in the STEP-NC standard. This article takes that sector as a use case. An extended STEP-NC model for circular saw stone-cutting operations is proposed, and a prototype automation implementation is developed to work with this extended model. This article shows how modern technological resources for coordinated axes control provided by many industrial controllers for the automation of general-purpose machines can speed up the processes of implementing STEP-NC numerical controllers. This article proposes a mixed and flexible approach for STEP-NC-based machine automation, where different strategies can coexist when it comes to executing STEP-NC machining files, so controllers do not need to implement the standard in an exhaustive way for all the possible features, but only at selected ones when convenient. This is demonstrated in a prototype implementation which is able to process STEP-NC product files with mixed-feature types: standard milling and non-standard sawblade features for stone processing.

Establishment of a finite element model based on craniofacial soft tissue thickness measurements and stress analysis of medical goggles

In this study, an accurate finite element (FE) stress analysis of head-mounted products for Chinese users was performed. Using craniofacial computed tomography scans of 280 Chinese individuals, the total soft tissue thickness and thickness of the fat and muscle layers for 41 landmarks were measured. The data were used to construct FE head models (FEH). An FE stress test was conducted to analyse the wearing of medical goggles using two FE models based on one-layer (FEH 1) and three-layer (FEH 3) soft tissue material parameters. When compared with the experimental results, the modelling results for FEH 3 were more realistic than those for FEH 1. Wearing medical goggles led to stress concentration over five landmark areas, A: upper medial forehead, B: temporal, C: zygion, D: infraorbital fossa and E: rhinion, of which B, C and D caused the most discomfort during long-term goggle wear. Practitioner summary: A precise FE head model can reflect the complex contact pressure of a head-related product. Two FE models based on one- and three-layer soft tissue material parameters were established and tested separately with medical goggles. The model can be used to improve the comfort of head-related products. Abbreviations: FE: finite element; FEH: FE head models; FEH 1: FE models based on one-layer; FEH 3: FE models based on three-layer; VR: virtual reality; AR: augmented reality; 3D: three-dimensional; WSU: Wayne State University; WSUBIM: Wayne State University Brain Injury Model; CT: computed tomography; MRI: magnetic resonance imaging; CFSTT: craniofacial soft tissue thickness; FSR: force sensing resistor; NURBS: non-uniform rational basis spline; SPSS: statistical product and service solutions; STL: stereolithography; STP: standard for the exchange of product model data; BDF: glyph bitmap distribution format; EEG: electroencephalogram

Building Information Modeling for Bridges and Structures: Outcomes and Lessons Learned from the Steel Bridge Industry

The recent push to adopt building information modeling (BIM) for bridges and structures in the transportation industry has encountered major barriers owing to the lack of standardization. Unlike the building industry that has the National BIM Standard®–United States (NBIMS-US™) as a formal open platform standard and guide for the development of interoperable BIM software, the transportation industry does not currently have a similar open platform standard to enable the creation of interoperable BIM software to serve the needs of transportation stakeholders. The purpose of this paper is to present the findings of the research for one of the first use cases and development of data exchange requirements and model view definitions in adopting the open platform NBIMS-US applied to bridges and structures for the U.S. transportation industry. A subcommittee of the American Association of State Highway and Transportation Officials and the National Steel Bridge Alliance Steel Bridge Collaboration was formed to conduct a pilot study into the creation of information delivery manuals (IDMs) for steel bridges. This study served as pilot for the development of future IDMs in the transportation industry. As a result, the current IDM for Steel Bridge Detailing and Fabrication serves as the starting point of TPF-5(372) BIM for Bridges and Structures development of the Design to Fabrication model view definition. Finally, this study provided the outcomes and recommendations needed to expedite the development of IDMs for other use cases in the bridge and transportation industry.

Standard health data exchange model enables the use and reuse of data to improve maternal health programs and services: a case study from India

Background The evidence on development of a health data exchange (HDX) in India is lacking, both in terms of the use of data for patient care (use) and aggregate data use (reuse) to improve maternal health services and programs. This study describes the requirements and proposes an HDX model development, focused on the adoption and use of design standardization. Methods A landscape analysis was conducted through a literature review to understand the existing HDX models. A qualitative case study focusing on a tertiary care state government hospital in India was performed. Twenty key informants were selected through purposive sampling and virtual interviews were undertaken. A mix of deductive and primarily inductive data analysis was conducted using the NVIVO 12.0 software. Findings Following an iterative design process and based on the essential requirements suggested by the key informants, an inter-organizational HDX scheme was developed. The HDX model leverages the electronic health records to enable the use of data for patient care, and use of aggregate patient data to support management and administrative decisions at the institutional, state-wide and national levels. The model describes how to balance the inter-organizational and intra-organizational data exchange needs. Integrating systems at the local level with those at the state and the national level was identified as one of the key components of this process. Conclusions The patient-level data is critical for the delivery of best attainable health care. At the same time, the aggregate data is critical, especially in the domain of decision-making and global health. The development of a versatile HDX model is a pre-requisite for a successful use and reuse of data, by ensuring that no functionality is lost and that the data is used in the best way possible.

CNC-C2: an ISO14649 and IEC61499 compliant controller

ABSTRACT Manufacturing systems in the present industry must be flexible and allow fast reconfiguration to supply increasing demands for diversified products. Thus, a standard model for data exchange should be employed in a manner that the same data can be interpreted and used in different machines. In this work the ISO14649 (STEP-NC) standard is used to fulfil this requirement. Also, CNCs must be easily reprogrammable and able to reuse code for different tasks to reduce programming time. The contribution of this work is presenting a manufacturing system which is compliant to IEC 61499 and to STEP-NC, integrating them to fulfil requirements of interoperability and flexibility. A system, named CNC-C2, was developed (Computerised Numeric Control Compliant to STEP-NC and Compliant to IEC61499) with several software tools and integrated them to a machining hardware, also developed and presented in this paper. Experiments were performed in a test workpiece including STEP-NC compliant drilling, planar facing, linear and circular cutting features while using IEC61499 Function Blocks networks to perform the computational task. CNC-C2 achieved unprecedented interoperability and flexibility thanks to its compliance to Function Blocks and STEP-NC standards.

Research on Key Processes of Plastic Stamping and Forming Machinery Manufacturing Based on CAD Technology

The paper adopts the parametric modeling technology of SolidWorks software, introduces CAE-driven design ideas in the stamping process, and realizes the parametric association and process of the blank grid and the tool grid based on the parametric tool grid model of the triangular face The parametric correlation between the parameters and the parametric correlation between the design model and the analysis model ensure that the product design, process design and forming simulation model are updated simultaneously, and the parametric CAE analysis and the true seamless integration of CAD/CAE are realized. By establishing a unified design and simulation model, the system avoids surface loss and accuracy loss caused by model data exchange between traditional CAE software and CAD platform. Through the parametric application of the forming simulation of the automobile bumper produced by an enterprise, and the comparison between the simulation results and the experimental results, the practicability and accuracy of the system are verified.

STEP AP 242 Managed Model-based 3D Engineering: An Application Towards the Automation of Fixture Planning

Fixture design and planning is one of the most important manufacturing activities, playing a pivotal role in deciding the lead time for product development. Fixture design, which affects the part-quality in terms of geometric accuracy and surface finish, can be enhanced by using the product manufacturing information (PMI) stored in the neutral standard for the exchange of product model data (STEP) file, thereby integrating design and manufacturing. The present paper proposes a unique fixture design approach, to extract the geometry information from STEP application protocol (AP) 242 files of computer aided design (CAD) models, for providing automatic suggestions of locator positions and clamping surfaces. Automatic feature extraction software “FiXplan”, developed using the programming language C#, is used to extract the part feature, dimension and geometry information. The information from the STEP AP242 file is deduced using geometric reasoning techniques, which in turn is utilized for fixture planning. The developed software is observed to be adept in identifying the primary, secondary, and tertiary locating faces and locator position configurations of prismatic components. Structural analysis of the prismatic part under different locator positions was performed using commercial finite element method software, ABAQUS, and the optimized locator position was identified on the basis of minimum deformation of the workpiece. The area-ratio (base locator enclosed area (%)/work piece base area (%)) for the ideal locator configuration was observed as 33%. Experiments were conducted on a prismatic workpiece using a specially designed fixture, for different locator configurations. The surface roughness and waviness of the machined surfaces were analysed using an Alicona non-contact optical profilometer. The best surface characteristics were obtained for the surface machined under the ideal locator positions having an area-ratio of 33%, thus validating the predicted numerical results. The efficiency, capability and applicability of the developed software is demonstrated for the finishing operation of a sensor cover – a typical prismatic component having applications in the naval industry, under different locator configurations. The best results were obtained under the proposed ideal locator configuration of area-ratio 33%.

KibioR & Kibio: a new architecture for next-generation data querying and sharing in big biology.

The growing production of massive heterogeneous biological data offers opportunities for new discoveries. However, performing multi-omics data analysis is challenging, and researchers are forced to handle the ever-increasing complexity of both data management and evolution of our biological understanding. Substantial efforts have been made to unify biological datasets into integrated systems. Unfortunately, they are not easily scalable, deployable and searchable, locally or globally. This publication presents two tools with a simple structure that can help any data provider, organization or researcher, requiring a reliable data search and analysis base. The first tool isKibio, a scalable and adaptable data storage based on Elasticsearch search engine. The second tool isKibioR, a R package to pull, push and searchKibiodatasets or any accessible Elasticsearch-based databases. These tools apply a uniform data exchange model and minimize the burden of data management by organizing data into a decentralized, versatile, searchable and shareable structure. Several case studies are presented using multiple databases, from drug characterization to miRNAs and pathways identification, emphasizing the ease of use and versatility of the Kibio/KibioR framework. Both KibioR and Elasticsearch are open source. KibioR package source is available at https://github.com/regisoc/kibior and the library on CRAN at https://cran.r-project.org/package=kibior. Supplementary data are available at Bioinformatics online.

Integrative data processing for cyber-physical off-site and on-site construction promoting co-design

The term co-design describes a collaborative design process, usually across the boundaries of individual areas. A major aspect, and often an obstacle in the implementation of the co-design approach, is the establishment of a centralized data management system. In the past, the data management concept has been approached from different perspectives. Current approaches usually are oriented along the process chain and thus reflect a unidirectional flow of information. Neither the information feedback nor the reaction to adjustments in upstream model steps is supported, which makes continuous collaboration more difficult and at best reduces the co-design approach for continuous data usage. This paper addresses these weaknesses while outlining an integrative data processing concept enabling co-design between the domains of construction and industrial prefabrication.Geometrical information generated during architectural design and construction planning is reused for the production of components, manufacturing-related design adjustments are transferred back into the domain of construction. Changes throughout the entire process are centrally recorded. To ensure independence from the software tools used and to consider their great diversity, data exchange is largely based on standards, namely industry foundation classes and the standard for the exchange of product model data. In order to counteract the sequential processing according to a waterfall model and to support the co-design approach, the industrial prefabrication toolchain, consisting of computer-aided manufacturing software and downstream postprocessors, is largely automated, so that reprocessing of a workpiece for minor geometric adjustments no longer requires any interaction of the production planner.

Application of artificial neural network techniques in computer aided process planning - a review

Computer aided process planning (CAPP) bridges the gap between computer aided design and computer aided manufacturing. CAPP research includes neural network approaches, knowledge-based techniques, Petri nets, agent- based, fuzzy set theory, genetic algorithm, standard for the exchange of product model data (STEP)-Compliant CAPP and internet-based techniques. This study mainly focuses on the application of the artificial neural network (ANN) techniques in CAPP because of their learning ability and huge potential toward dynamic planning. The role of an artificial neural network in feature recognition, machine selection, operation and machine tool selection are emphasised in detail in this survey paper.

Multi-domain simulation utilizing SysML: state of the art and future perspectives

Increasing system complexity requires adapted methodologies to tackle the challenges that come along with multi-domain systems development. Model-Based Systems Engineering (MBSE) provides significant support by using models to describe different aspects of an examined system already in the early stages of the development process. The Systems Modeling Language (SysML) can be utilized to establish a common system information basis on a comparatively abstract level for all participating stakeholders. Although SysML models are able to encompass system information like requirements, structure, behaviour and parametrics, in many cases additional specialized simulation or computation models are needed, especially for early design decision-making and verification activities. Ideally, the input data and the calculated results are automatically exchanged between the SysML modelling editor and the involved simulation tools. Hence, tool chain integration is a crucial factor to provide the necessary interconnectivity to achieve multi-domain simulation. In general, the integration of simulation environments with SysML tools is mainly limited by two factors. First, as the tools available for modelling with SysML are legion, interface solutions are usually developed for a specific tool and therefore, their usage is restricted to that particular software. Second, evolving standards like the Functional Mock-up Interface (FMI) provide capabilities to ease model data exchange and co-simulation, but the implementation of different versions of various standards in the tools causes incompatibilities. In this work a state of the art of the integration between simulation environments and available SysML modelling tools with respect to utilized standards and their implementation maturity is presented. Additionally, the capabilities of the reviewed tools to support co-simulation are evaluated. Furthermore, existing challenges are highlighted, and potential improvements are discussed.

Development of the PC-based Integrated Interface System of STEP file for CNC Machining Application: Circular Features

STEP is a general data format that observes the international standard ISO 10303-21. STEP means Standard for the Exchange of Product model data. It consists of the 3D geometry of a computer-aided design (CAD) model in the configuration of boundary representation (B-rep). By extracting, refining and decoding the geometric data correctly, the data can be utilized for writing G-code for Computer Numerical Control (CNC) machining application. Usually G-codes can either be manually generated by skilled machinists or automatically generated by computer-aided manufacturing (CAM) software. However, manually generated G-code is inefficient and susceptible to error. Meanwhile automated generation G-code requires significant setup cost. This paper describes the design and development of an integrated interface system, an instrument aimed to be used to analyze STEP files and generate machining tool path based on ISO 6983 format. This developed interface reduces the need for high setup cost as well as eliminates human limitations. The interface at present is able of detecting circular machining features on the workpiece. Circular machining features are created by 3D modelling software and retained as STEP file. The STEP file which contains geometrical data is then uploaded to the interface system as an input file which is structurally analyzed and processed. Finally, the ideal machining tool path in the G Code format is proposed and generated. By bypassing the CAM software and its proprietary post processor, the outcome of this research is important to enhance compatibility between different CNC machine systems

Enriching standards-based digital thread by fusing as-designed and as-inspected data using knowledge graphs

Realizing the digital thread is essential for linking and orchestrating data across the product lifecycle in smart manufacturing. Linking heterogeneous lifecycle data is critical to maintain associativity and traceability in a digital thread. Recently, researchers have successfully leveraged ontology models with knowledge graphs in engineering domains for threading different lifecycle data. One of the most successful of such efforts is OntoSTEP which enables the formal capture of information embedded in the STandard for Exchange of Product model data (STEP) data representation, or ISO 10303. Meanwhile, an emerging inspection standard, called the Quality Information Framework (QIF), has garnered significant attention as it can bring quality information into the digital thread. Implementing more automated methods for product quality assurance is challenging due to the lack of unified information models from design to inspection. To this end, we propose an approach to fuse as-designed data represented in STEP and as-inspected data represented in QIF in a standards-based digital thread based on ontology with knowledge graphs. Specifically, we present an automated pipeline for generating knowledge graphs representing STEP and QIF data, a mapping implementation to integrate STEP and QIF knowledge graphs, and rules and queries to demonstrate the integration’s potential for better decision making with respect to product quality assurance.

Research and Implementation of Digital Twin Heterogeneous Data Exchange System

Digital twin is one of the most important technologies to realize system intelligence and automation, and it seamlessly integrates the digital and physical space. So far, the concept of digital twin has been proposed for nearly 15 years, and the importance of digital twin is increasingly recognized by academia and industry, with a large number of digital twin models applied in different industries. The interoperability of different models has become a major challenge for digital twins. In this paper, we propose a system for heterogeneous data exchange of different models, and demonstrates the data interaction prototype of the mechanical and thermal models of the electric box load parts, finally we evaluated the effectiveness of our system.

Malicious User Detection for Cooperative Mobility Tracking in Autonomous Driving

The mobility status of self and surrounding vehicles provides important information to various tasks in autonomous driving (AD) and intelligent transportation system (ITS). Accordingly, a precise, stable, and robust mobility tracking framework is essential. Compared with self-tracking that relies only on mobility observations from onboard sensors [e.g., global positioning system (GPS), inertial measurement unit (IMU), and camera], cooperative tracking markedly increases the precision and reliability of the mobility information by integrating observations from roadside units (RSUs) and nearby vehicles through vehicle-to-everything (V2X) communications in the Internet of Vehicles (IoV). Nevertheless, cooperative tracking can be quite vulnerable if there are malicious users sending bogus observations in the cooperative network. In this article, we present a malicious user detection framework, which includes two sequential detection algorithms and a secure mobility data exchange and fusion model to detect and remove bogus mobility information and integrate proposed detection algorithms with previous data fusion algorithms, which secures the cooperative mobility tracking in AD, ITS. Simulations validate the effectiveness and robustness of the proposed framework under different types of attacks.

A Model of Data and Data Exchange in Competitive Markets

Companies are increasingly using data to predict behavior, automate and improve the relation with their customers. In this context, data exchange rises important concerns regarding competition, concentration and welfare. This paper presents a novel linear demand model that capture data and information effects in competitive markets, which are summarized in a precision parameter. Subsequently, this modelling approach is applied to study the firms incentives to exchange data and the implications in terms of market variables, welfare and concentration measures. We found that incentives to data exchange between competitor firms emerge providing that the information gains are relatively stronger than the competitor information gains, and the associated strategic correlation effect is not too strong. The results also suggest that market concentration tends to increase after data exchange, but both consumers and producers benefit from it. The reason is that better data allows firms to delivering varieties closer to consumers' needs.