Interoperability and information discovery

In the context of information systems, there is interoperability when the distinctions between separate information systems are not a barrier to accomplishing a task that spans those systems. Interoperability so defined implies that there are commonalities among the systems involved and that one can exploit such commonalities to achieve interoperability. The challenge of a particular interoperability task is to identify relevant commonalities among the systems involved and to devise mechanisms that exploit those commonalities.

The present paper focuses on the particular interoperability task of information discovery. The Global Information Locator Service (GILS) is described as a policy, standards, and technology framework for addressing interoperable information discovery on a global and long‐term basis. While there are many mechanisms for people to discover and use all manner of data and information resources, GILS initiatives exploit certain key commonalities that seem to be sufficient to realize useful information discovery interoperability at a global, long‐term scale.

This paper describes ten of the specific commonalities that are key to GILS initiatives. It presents some of the practical implications for organizations in various roles: content provider, system engineer, intermediary, and searcher. The paper also provides examples of interoperable information discovery as deployed using GILS in four types of information communities: bibliographic, geographic, environmental, and government.     

Strategic advantages of interoperability for global manufacturing using CNC technology

In the domain of manufacturing, computer numerically controllers (CNC) technology is a major contributor to the production capacity of the enterprises. The advances in CNC technology coupled with enhancements in computing systems have provided the basis to re-examine the way in which computer-aided systems (CAx) can be used to enable global manufacturing. Interoperability of the various components of the CAx chain is therefore a major prerequisite for manufacturing enterprises for becoming strategically agile and consequently globally competitive. Being interoperable, resources can be utilized interchangeably in a plug-and-produce manner. Over the last 8 years the eminence of a STEP standard for machining entitled STEP-NC (numerical control) has become a well-known vehicle for research to improve the level of information availability at the CNC machine tool. In this paper, the authors introduce the background to the evolution of CNC manufacturing over the last 50 years and the current standards available for programming. A review of the literature in interoperable CNC manufacturing is then provided relating to milling, turn–mill and other NC processes. The major part of the paper provides a strategic view of how interoperability can be implemented across the CAx chain with a range of standards used to regulate the flow of information. Finally, the paper outlines the advantages and major issues for future developments in interoperability, identifying future key requirements and limiting factors.     

A semantic interoperability framework for software as a service systems in cloud computing environments

In cloud computing environments in software as a service (SaaS) level, interoperability refers to the ability of SaaS systems on one cloud provider to communicate with SaaS systems on another cloud provider. One of the most important barriers to the adoption of SaaS systems in cloud computing environments is interoperability. A common tactic for enabling interoperability is the use of an interoperability framework or model. During the past few years, in cloud SaaS level, various interoperability frameworks and models have been developed to provide interoperability between systems. The syntactic interoperability of SaaS systems have already been intensively researched. However, not enough consideration has been given to semantic interoperability issues. Achieving semantic interoperability is a challenge within the world of SaaS in cloud computing environments. Therefore, a semantic interoperability framework for SaaS systems in cloud computing environments is needed. We develop a semantic interoperability framework for cloud SaaS systems. The capabilities and value of service oriented architecture for semantic interoperability within cloud SaaS systems have been studied and demonstrated. This paper is accomplished through a number of steps (research methodology). It begins with a study on related works in the literature. Then, problem statement and research objectives are explained. In the next step, semantic interoperability requirements for SaaS systems in cloud computing environments that are needed to support are analyzed. The details of the proposed semantic interoperability framework for SaaS systems in cloud computing environments are presented. It includes the design of the proposed semantic interoperability framework. Finally, the evaluation methods of the semantic interoperability framework are elaborated. In order to evaluate the effectiveness of the proposed semantic interoperability framework for SaaS systems in cloud computing environments, extensive experimentation and statistical analysis have been performed. The experiments and statistical analysis specify that the proposed semantic interoperability framework for cloud SaaS systems is able to establish semantic interoperability between cloud SaaS systems in a more efficient way. It is concluded that using the proposed framework, there is a significant improvement in the effectiveness of semantic interoperability of SaaS systems in cloud computing environments.     

Supervisory synthesis for product-driven automation and its application to a flexible assembly cell

A make-to-order business model requires manufacturing control to face customised product variability and traceability. Considering the product as central to the automation rationale provides each product occurrence with informational and decisional capabilities. This paper considers a formal framework for such product-driven automation within the context of the Supervisory Control Theory. Two interoperable classes of supervisors are synthesised. Product supervisors control routings through the manufacturing system according to customised product specifications and resource capabilities, and resource supervisors manage the execution of operations required by product supervisors. A case study, based on a flexible assembly cell, illustrates the approach and opens issues for industrial practice.     

An interoperable solution for Cloud manufacturing

Cloud manufacturing is a new concept extending and adopting the concept of Cloud computing for manufacturing. The aim is to transform manufacturing businesses to a new paradigm in that manufacturing capabilities and resources are componentized, integrated and optimized globally. This study presents an interoperable manufacturing perspective based on Cloud manufacturing. A literature search has been undertaken regarding Cloud architecture and technologies that can assist Cloud manufacturing. Manufacturing resources and capabilities are discussed in terms of Cloud service. A service-oriented, interoperable Cloud manufacturing system is proposed. Service methodologies are developed to support two types of Cloud users, i.e., customer user and enterprise user, along with standardized data models describing Cloud service and relevant features. Two case studies are undertaken to evaluate the proposed system. Cloud technology brings into manufacturing industry with a number of benefits such as openness, cost-efficiency, resource sharing and production scalability.     

Interoperability of Learning Objects Copyright in the LUISA Semantic Learning Management System

Abstract

Semantic Web technology is able to provide the required computational semantics for interoperability of learning resources across different Learning Management Systems (LMS) and Learning Object Repositories (LOR). The EU research project LUISA (Learning Content Management System Using Innovative Semantic Web Services Architecture) addresses the development of a reference semantic architecture for the major challenges in the search, interchange, and delivery of learning objects in a service-oriented context. One of the key issues, highlighted in this paper, is Digital Rights Management (DRM) interoperability. A Semantic Web approach to copyright management has been followed, which places a Copyright Ontology as the key component for interoperability among existing DRM systems and other licensing schemes like Creative Commons. Moreover, Semantic Web tools like reasoners, rule engines and semantic queries facilitate the implementation of an interoperable copyright management component in the LUISA architecture.     

An object-oriented framework for developing distributed manufacturing architectures

Management of complexity, changes and disturbances is one of the key issues of production today. Distributed, agent-based structures represent viable alternatives to hierarchical systems provided with reactive/proactive capabilities. In the paper, approaches to distributed manufacturing architectures are surveyed, and their fundamental features are highlighted, together with the main questions to be answered while designing new structures. Moreover, an object-oriented simulation framework for development and evaluation of multi-agent manufacturing architectures is introduced.     

Knowledge framework for intelligent manufacturing systems

Nowadays, competition is experienced not only among companies but among global supply chains and business networks. There is a demand for intelligent world-class solutions capable of reinforcing partnerships and collaborations with an improved cross-cultural understanding. However due to the proliferation of terminology, organizations from similar business environments have trouble cooperating, and are experiencing difficulties exchanging electronically vital information, such as product and manufacturing data, even when using international standards. To address similar interoperability problems, the Intelligent manufacturing systems program () is providing an opportunity to develop industry-led R&D initiatives, building common semantics and integrated solutions. The SMART-fm project was one of those initiatives. It led to the development of the international standard for product data representation and exchange in the furniture sector (ISO 10303-236) and identified the challenge of semantic interoperability which is today a major challenge in modern enterprise integration. This paper presents a knowledge framework to address that challenge and make interoperable intelligent manufacturing systems a reality. It proposes to use semantically enriched international product data standards, and knowledge representation elements as a basis for achieving seamless enterprise interoperability.     

Interoperable access framework for internet of things backhauled heterogeneous applications

Internet of Things (IoT) provides large-scale interoperable service delegations for heterogeneous users through pervasive access. The interconnection of different devices and services in an on-demand and pervasive manner provides seamless responses for different applications. However, a few interconnected devices are stuck into a resource-constraint problem due to limited access and unavailability. This article proposes an interoperable access framework (IAF) for pervasive application services (PAS) for providing robust end-user solutions. The proposed framework balances the accessibility and semantics and its responses for providing seamless interoperability support. In this framework, transfer learning for different limited and free-flow service accessibility is used. The teaching is recurrent for identifying the unavailability of the resources. The process of serving the requests is achieved through interoperable replacement services. It reduces the impact of resource-constraint in the IoT platform, wherein the semantics between unavailability and accessibility is analyzed flawlessly. The proposed framework's performance is verified using the metrics service delay, responses, unavailability, resource utilization, and successful access.     

Achieving Mobile Agent Systems interoperability through software layering

Interoperability is a key issue for a wider adoption of mobile agent systems (MASs) in heterogeneous and open distributed environments where agents, in order to fulfill their tasks, must interact with non-homogeneous agents and traverse different agent platforms to access remote resources. To date, while several approaches have been proposed to deal with different aspects of MAS interoperability, they all lack the necessary flexibility to provide an adequate degree of interoperability among the currently available MASs. In this paper, we propose an application-level approach grounded in the software layering concept, which enables execution, migration and communication interoperability between Java-based mobile agent systems, thus overcoming major setbacks affecting the other approaches currently proposed for supporting MAS interoperability. In particular, we define a Java-based framework, named JIMAF, which relies on an event-driven, proxy-based mobile agent model and supports interoperable mobile agents which can be easily coded and adapted to existing MASs without any modifications of the MAS infrastructures. Results from the performance evaluation of MAS interoperability was carried by using JIMAF atop Aglets, Ajanta, Grasshopper, and Voyager, demonstrating that the high-level JIMAF approach offers high efficacy while maintaining overhead at acceptable levels for target computing environments.     

A survey on the service interoperability in cloud computing: Client-centric and provider-centric perspectives

The vendor lock-in is a prominent issue in cloud computing. It is caused by cloud providers who offer proprietary services, which hinders the cloud interoperability. Client-centric interoperability enables the migration of the data and applications across clouds; it gives the clients control over their workloads and a wider range of service choices. Whereas, provider-centric interoperability allows the providers to collaborate. Thus, providers, who have spare resources, can lend them to other providers who lack computational or storage capabilities to overcome the limitations of their local resources. In this article, we conduct a survey to differentiate between client- and provider-centric interoperability solutions. We aim to provide an up-to-date analysis of the current tendencies and the neglected areas of the cloud interoperability field. Thus, we study the cloud service interoperability evolution through the years. Furthermore, we propose definitions for the intra-cloud and inter-cloud interoperability. Moreover, we propose a taxonomy to classify the cloud interoperability approaches into client-centric and provider-centric categories. Then, for each category, we classify the approaches based on their interoperability environment into single cloud or interconnected clouds. Finally, we analyze and compare the approaches based on multiple criteria. The study reveals the focus on the client-centric solutions and the interoperability in interconnected clouds. We notice more interest in the data and application levels interoperability, mainly, in infrastructure as a service model. We also find that client-centric solutions are, mostly, semantic technologies and brokers. However, provider-centric solutions are middleware, protocols, and standards. We conclude that a generic cloud service interoperability model is needed.     

Semantic Interoperability Aggregation in Service Requirements Refinement

Semantic refinement of stakeholders’ requirements is a fundamental issue in requirements engineering. Facing with the on-demand collaboration problem among the heterogeneous, autonomous, and dynamic service resources in the Web, service requirements refinement becomes extremely important, and the key issue in service requirements refinement is semantic interoperability aggregation. A method for creating connecting ontologies driven by requirement sign ontology is proposed. Based on connecting ontologies, a ...     

A generic interoperability testing framework and a systematic development process for automated interoperability testing

Interoperability is a prerequisite to allow users to access systems implemented by different vendors seamlessly. A good baseline to achieve interoperability is the implementation of a common set of standards. However, this is often not sufficient as different implementations of a standard are not necessarily interoperable. Therefore, different implementations of systems need to be assessed for interoperability by applying interoperability testing. In this article, we present a generic framework that enables automated interoperability testing with message checks, which assess the compliance of messages exchanged between systems. The goal of this framework is the provision of a basic functionality of interoperability test entities, the definition of a generic interoperability test environment, and guidelines for the specification of automated interoperability tests. The framework also considers aspects related to interoperability testing including verdicts, automation, and limitations of the system under test. Through the application of the framework, interoperability of systems can be assessed, systems can be validated, and standards can be improved. In addition, we present a systematic development process for automated interoperability tests to formalize the development and specification of an interoperability test system. We also consider aspects and critical issues, which are important for the development of a complete interoperability test system. The framework and the process are language and system technology independent. We present their application in a case study that includes interoperability tests for the Internet Protocol Multimedia Subsystem (IMS) using the Testing and Test Control Notation Version 3 (TTCN-3).     

Semantic interoperability in building design: Methods and tools

Semantic interoperability is a crucial element to make building information models understandable and model data sharable across multiple design disciplines and heterogeneous computer systems. This paper presents a new approach and its software implementation for the development of building design objects with semantics of interoperable information to support semantic interoperability in building designs. The novelty of the approach includes its incorporation of building design domain ontology, object-based CAD information modeling, and interoperability standard to make building information models and model data semantically interoperable. A set of methods are proposed to address the issues of object-based building information representation compliant with the Industrial Foundation Classes (IFC); extension of IFC models with the supplementary information; and semantic annotation of the interoperable and extensible information sets. The prototype implementation of these methods provides a set of Web-enabled software tools for effectively generating, managing, and reusing the semantically interoperable building objects in design applications of architectural CAD, structural analysis, and building code conformance checking.     

Digital twin-based industrial cloud robotics: Framework,control approach and implementation

Industrial cloud robotics (ICR) integrates cloud computing with industrial robots (IRs). The capabilities of industrial robots can be encapsulated as cloud services and used for ubiquitous manufacturing. Currently, the digital models for process simulation, path simulation, etc. are encapsulated as cloud services. The digital models in the cloud may not reflect the real state of the physical robotic manufacturing systems due to inaccurate or delayed condition update and therefore result in inaccurate simulation and robotic control. Digital twin can be used to realize fine sensing control of the physical manufacturing systems by a combination of high-fidelity digital model and sensory data. In this paper, we propose a framework of digital twin-based industrial cloud robotics (DTICR) for industrial robotic control and its key methodologies. The DTICR is divided into physical IR, digital IR, robotic control services, and digital twin data. First, the robotic control capabilities are encapsulated as Robot Control as-a-Service (RCaaS) based on manufacturing features and feature-level robotic capability model. Then the available RCaaSs are ranked and parsed. After manufacturing process simulation with digital IR models, RCaaSs are mapped to physical robots for robotic control. The digital IR models are connected to the physical robots and updated by sensory data. A case is implemented to demonstrate the workflow of DTICR. The results show that DTICR is capable to synchronize and merge digital IRs and physical IRs effectively. The bidirectional interaction between digital IRs and physical IRs enables fine sensing control of IRs. The proposed DTICR is also flexible and extensible by using ontology models.     

A dynamic and static data based matching method for cloud 3D printing

3D printing is widely used in such sectors as industry, medical, sports and education with the rapid development 3D printing technology and continual breakthrough of new material technology. Faced with the continual expansion of 3D printing market and the diversity and rapid growth of the scale of 3D printing devices, efficiently manage 3D print resources in the environment of distributed network manufacturing is a critical problem urgently to resolve. As a novel business paradigm, Cloud manufacturing can effectively integrate and manage manufacturing resources. Therefore, based on the cloud manufacturing paradigm, this study focuses on dynamic and static data based matching method for cloud 3D printing. In this paper, we propose a modeling framework to describe two models of the print task and print resource by model-based systems engineering. This modeling framework can support the efficient matching of the two types of models. Finally, the dynamic and static data based matching method can realistically simulate the supply-demand matching process of cloud 3D printing platform and provide a technical solution for quick supply-demand matching of large-scale resources in the environment of cloud manufacturing. During in the modeling process, we not only consider the static characteristics of 3D printers and analyze quantitatively all the parameter indicators of static characteristics, but also consider the dynamic characteristics of 3D printers to establish a universal dynamic data acquisition system, which can be used for real-time monitoring and automatic diagnosis of the health status of 3D printers. Therefore, this matching method has important theoretical significance and engineering value.     

Big Data and virtualization for manufacturing cyber-physical systems: A survey of the current status and future outlook

The recent advances in sensor and communication technologies can provide the foundations for linking the physical manufacturing facility and machine world to the cyber world of Internet applications. The coupled manufacturing cyber-physical system is envisioned to handle the actual operations in the physical world while simultaneously monitor them in the cyber world with the help of advanced data processing and simulation models at both the manufacturing process and system operational levels. Moreover, a sensor-packed manufacturing system in which each process or piece of equipment makes available event and status information, coupled with market research for true advanced Big Data analytics, seem to be the right ingredients for event response selection and operation virtualization. As a drawback, the resulting manufacturing cyber-physical system will be vulnerable to the inevitable cyber-attacks, unfortunately, so common for the software and Internet-based systems. This reality makes cybersecurity penetration within the manufacturing domain a need that goes uncontested across researchers and practitioners. This work provides a review of the current status of virtualization and cloud-based services for manufacturing systems and of the use of Big Data analytics for planning and control of manufacturing operations. Building on already developed cloud business solutions, cloud manufacturing is expected to offer improved enterprise manufacturing and business decision support. Based on the current state-of-the-art cloud manufacturing solutions and Big Data applications, this work also proposes a framework for the development of predictive manufacturing cyber-physical systems that include capabilities for attaching to the Internet of Things, and capabilities for complex event processing and Big Data algorithmic analytics.     

Design,programming and orchestration of heterogeneous manufacturing systems through VR-powered remote collaboration

Modern manufacturing systems are often composed of a variety of highly customized units and specifically designed manufacturing cells. Optimization of assembly and training of staff requires a series of demo installations and excessive use of costly operational resources. In some cases, components are located at different sites, making the orchestration of the whole system even more difficult.Virtual Reality (VR) collaboration environments offer a solution by enabling high fidelity testing and training of complex manufacturing systems. On the other hand, such platforms are difficult to implement in an engineering perspective, as they are required to provide reliable, standard interfaces towards both robotic components and human operators.The VirCA (Virtual Collaboration Arena) platform is a software framework that supports various means of collaboration through the use of 3D augmented/virtual reality as a communication medium. VirCA offers functions for the high-level interoperability of heterogeneous components in a wide range of domains, spanning from research & development, through remote education to orchestration and management of industrial processes in manufacturing applications. This paper provides an overview of the industrial requirements behind high-fidelity virtual collaboration and demonstrates how the VirCA platform meets these requirements. Use cases are provided to illustrate the usability of the platform.     

A multi-agent and cloud-edge orchestration framework of digital twin for distributed production control

The demands for mass individualization and networked collaborative manufacturing are increasing, bringing significant challenges to effectively organizing idle distributed manufacturing resources. To improve production efficiency and applicability in the distributed manufacturing environment, this paper proposes a multi-agent and cloud-edge orchestration framework for production control. A multi-agent system is established both at the cloud and the edge to achieve the operation mechanism of cloud-edge orchestration. By leveraging Digital Twin (DT) technology and Industrial Internet of Things (IIoT), real-time status data of the distributed manufacturing resources are collected and processed to perform the decision-making and manufacturing execution by the corresponding agent with permission. Based on the generated data of distributed shop floors and factories, the cloud production line model is established to support the optimal configuration of the distributed idle manufacturing resources by applying a systematic evaluation method and digital twin technology, which reflects the actual manufacturing scenario of the whole production process. In addition, a rescheduling decision prediction model for distributed control adjustment on the cloud is developed, which is driven by Convolutional Neural Network (CNN) combined with Bi-directional Long Short-Term Memory (BiLSTM) and attention mechanism. A self-adaptive strategy that makes the real-time exceptions results available on the cloud production line for holistic rescheduling decisions is brought to make the distributed manufacturing resources intelligent enough to address the influences of different degrees of exceptions at the edge. The applicability and efficiency of the proposed framework are verified through a design case.