Integration Framework of MES Toward Data Security Interoperation

© 2020, Springer Nature Switzerland AG. The core problem of the application of MES (Manufacturing Execution System) in intelligent manufacturing systems is integration, which solves the problem of the data interoperation between the distributed manufacturing systems. The previous researches on MES integration rarely considered the problem of system data security access. A three-level data security access mechanism based on the independence of the system administrators, security administrators, and security auditors is proposed which integrated into the MES integration framework to guarantee the business and engineering data security access for the related distributed clients. The principle is using the domain to make the logical isolation for different clients and data sources and applying the pre-defined data sharing rules for safe access. In the proposed MES integration framework model, the data interoperation between MES and the engineering software systems is discussed which includes ERP (Enterprise Resource Management), CAPP (Computer Aided Process Planning), DNC (Distribution Numerical Control), WMS (Warehouse Management System), and SCADA (Supervisory Control and Data Acquisition), etc., the implementation method of personalized data display GUI is discussed as well. The study is based on the KMMES developed by Wuhan KM-Software of China, and it has been deployed in over forty companies from the sections of aerospace, automotive, shipbuilding and other industries

The NIF LinkOut Broker: A Web Resource to Facilitate Federated Data Integration using NCBI Identifiers

This paper describes the NIF LinkOut Broker (NLB) that has been built as part of the Neuroscience Information Framework (NIF) project. The NLB is designed to coordinate the assembly of links to neuroscience information items (e.g., experimental data, knowledge bases, and software tools) that are (1) accessible via the Web, and (2) related to entries in the National Center for Biotechnology Information’s (NCBI’s) Entrez system. The NLB collects these links from each resource and passes them to the NCBI which incorporates them into its Entrez LinkOut service. In this way, an Entrez user looking at a specific Entrez entry can LinkOut directly to related neuroscience information. The information stored in the NLB can also be utilized in other ways. A second approach, which is operational on a pilot basis, is for the NLB Web server to create dynamically its own Web page of LinkOut links for each NCBI identifier in the NLB database. This approach can allow other resources (in addition to the NCBI Entrez) to LinkOut to related neuroscience information. The paper describes the current NLB system and discusses certain design issues that arose during its implementation

SAMI: Service-Based Arbitrated Multi-Tier Infrastructure for Mobile Cloud Computing

Mobile Cloud Computing (MCC) is the state-ofthe- art mobile computing technology aims to alleviate resource poverty of mobile devices. Recently, several approaches and techniques have been proposed to augment mobile devices by leveraging cloud computing. However, long-WAN latency and trust are still two major issues in MCC that hinder its vision. In this paper, we analyze MCC and discuss its issues. We leverage Service Oriented Architecture (SOA) to propose an arbitrated multi-tier infrastructure model named SAMI for MCC. Our architecture consists of three major layers, namely SOA, arbitrator, and infrastructure. The main strength of this architecture is in its multi-tier infrastructure layer which leverages infrastructures from three main sources of Clouds, Mobile Network Operators (MNOs), and MNOs' authorized dealers. On top of the infrastructure layer, an arbitrator layer is designed to classify Services and allocate them the suitable resources based on several metrics such as resource requirement, latency and security. Utilizing SAMI facilitate development and deployment of service-based platform-neutral mobile applications.Comment: 6 full pages, accepted for publication in IEEE MobiCC'12 conference, MobiCC 2012:IEEE Workshop on Mobile Cloud Computing, Beijing, Chin

Towards quality analysis of MES through CMM data interoperation

© Published under licence by IOP Publishing Ltd. The implementation of MBD/MBE (Model-based Design and Engineering) in the product design and manufacturing can effectively support multi-step data interoperation among "Design-Manufacture-Measurement."Due to the limited data interoperation functions provided by the current CMM software (Coordinate Measurement Machine), most studies of MBD/MBE focused on designing the upstream. In contrast, the downstream (the underlying measurement data utilization) research is less. MES has an essential function in managing the manufacturing quality that analyses the condition and its development trend by collecting the manufacturing process quality data. Insufficient use of the underlying measurement data will lead to limited MES functions, especially for the capability of decision-making in intelligent manufacturing systems. The paper presents a measurement data interoperation method based on the interoperation layer method to support the quality analysis in MES (Manufacturing Execution System), discusses the relevant critical logic and data processing flow of the layer. It is verified that it can provide more comprehensive measurement data for quality management in the workshop

Study on interoperation and its' implementation of MES to support virtual factory

© 2020 Published under licence by IOP Publishing Ltd. The data interoperation between VF (virtual factory) platform and MES (Manufacturing Execution System) plays an important role in intelligent factory construction. The study focuses on the integration strategy between the VF and the MES by incorporating VF manufacturing assets in two ways, i.e., vertical integration (used for production line performance evaluation) and the horizontal integration (cloud manufacturing based on manufacturing assets services discovery and their composition). The VF platform which integrates the manufacturing assets in two manners is designed as the bottom layer in the entire integration framework. It has been applied to build a four tiers integration model in an intelligent production system construction of a domestic ship manufacturer and verified its feasibility and availability

Consuming multiple linked data sources: Challenges and Experiences

Linked Data has provided the means for a large number of considerable knowledge resources to be published and interlinked utilising Semantic Web technologies. However it remains difficult to make use of this ‘Web of Data’ fully, due to its inherently distributed and often inconsistent nature. In this paper we introduce core challenges faced when consuming multiple sources of Linked Data, focussing in particular on the problem of querying. We compare both URI resolution and federated query approaches, and outline the experiences gained in the development of an application which utilises a hybrid approach to consume Linked Data from the unbounded web

FAIR Convergence Matrix: Optimizing the Reuse of Existing FAIR-Related Resources

The FAIR principles articulate the behaviors expected from digital artifacts that are Findable, Accessible, Interoperable and Reusable by machines and by people. Although by now widely accepted, the FAIR Principles by design do not explicitly consider actual implementation choices enabling FAIR behaviors. As different communities have their own, often well-established implementation preferences and priorities for data reuse, coordinating a broadly accepted, widely used FAIR implementation approach remains a global challenge. In an effort to accelerate broad community convergence on FAIR implementation options, the GO FAIR community has launched the development of the FAIR Convergence Matrix. The Matrix is a platform that compiles for any community of practice, an inventory of their self-declared FAIR implementation choices and challenges. The Convergence Matrix is itself a FAIR resource, openly available, and encourages voluntary participation by any self-identified community of practice (not only the GO FAIR Implementation Networks). Based on patterns of use and reuse of existing resources, the Convergence Matrix supports the transparent derivation of strategies that optimally coordinate convergence on standards and technologies in the emerging Internet of FAIR Data and Services

Identifying, naming and interoperating data in a Phenotyping platform network : the good, the bad and the ugly

The EPPN2020 is a research project funded by Horizon 2020 Programme of the EU that will provide European public and private scientific sectors with access to a wide range of state-of-the-art plant phenotyping installations, techniques and methods. Specifically, EPPN2020 includes access to 31 plant phenotyping installations, and joint research activities to develop: novel technologies and methods for environmental and plant measurements.Here we present the results of the discussions of the 2019 annual project meeting to adopt community-approved architectural choices. It focuses on persistent identification of data and real objects, the naming of variables and the priorities for increasing interoperability among phenotyping installations. We describe the main elements to prioritize (the good) in order to enhance Findable, Accessible, Interoperable and Reusable (FAIR) quality for each data management system with a pragmatic concern for all partners. The plant phenotyping community gathers different actors with various means and practices. Among all the recommendations (including the bad: avoiding bad practices), the community requests identification methods (including the use of ontologies) compatible with the ‘local’ pre-existing ones. The identification scheme being adopted is based on Uniform Resource Identifiers (URIs) with independant left and right parts for each identifier. It focuses on the associated objects and variables common to all EPPN2020 members, namely the experimental units (which can be a plant in a pot or a plot), sensors and variables. A common architecture for identifiers and variable names is presented in order to enable a first level of interoperation between information systems.In conclusion, we present some of the next challenges (the ugly) that need to be addressed by the EPPN2020 community related with i) the partial reuse of pre-existing ontologies, ii) the persistence of long-term access to data iii) interoperation between all potential users of the phenotyping data

Integration of protein data sources through PO

Resolving heterogeneity among various protein data sources is a crucial problem if we want to gain more information about proteomics process. Information from multiple protein databases like PDB, SCOP, and UniProt need to integrated to answer user queries. Issues of Semantic Heterogeneity haven?t been addressed so far in Protein Informatics. This paper outlines protein data source composition approach based on our existing work of Protein Ontology (PO). The proposed approach enables semi-automatic interoperation among heterogeneous protein data sources. The establishment of semantic interoperation over conceptual framework of PO enables us to get a better insight on how information can be integrated systematically and how queries can be composed. The semantic interoperation between protein data sources is based on semantic relationships between concepts of PO. No other such generalized semantic protein data interoperation framework has been considered so far