Ontology based semantic-predictive model for reconfigurable automation systems

Due to increasing product variety and complexity, capability to support reconfiguration is a key competitiveness indicator for current automation system within large enterprises. Reconfigurable manufacturing systems could efficiently reuse existing knowledge in order to decrease the required skills and design time to launch new products. However, most of the software tools developed to support design of reconfigurable manufacturing system lack integration of product, process and resource knowledge, and the design data is not transferred from domain-specific engineering tools to a collaborative and intelligent platform to capture and reuse design knowledge. The focus of this research study is to enable integrated automation systems design to support a knowledge reuse approach to predict process and resource changes when product requirements change. The proposed methodology is based on a robust semantic-predictive model supported by ontology representations and predictive algorithms for the integration of Product, Process, Resource and Requirement (PPRR) data, so that future automation system changes can be identified at early design stages

Essentials In Ontology Engineering: Methodologies, Languages, And Tools

In the beginning of the 90s, ontology development was similar to an art: ontology developers did not have clear guidelines on how to build ontologies but only some design criteria to be followed. Work on principles, methods and methodologies, together with supporting technologies and languages, made ontology development become an engineering discipline, the so-called Ontology Engineering. Ontology Engineering refers to the set of activities that concern the ontology development process and the ontology life cycle, the methods and methodologies for building ontologies, and the tool suites and languages that support them. Thanks to the work done in the Ontology Engineering field, the development of ontologies within and between teams has increased and improved, as well as the possibility of reusing ontologies in other developments and in final applications. Currently, ontologies are widely used in (a) Knowledge Engineering, Artificial Intelligence and Computer Science, (b) applications related to knowledge management, natural language processing, e-commerce, intelligent information integration, information retrieval, database design and integration, bio-informatics, education, and (c) the Semantic Web, the Semantic Grid, and the Linked Data initiative. In this paper, we provide an overview of Ontology Engineering, mentioning the most outstanding and used methodologies, languages, and tools for building ontologies. In addition, we include some words on how all these elements can be used in the Linked Data initiative

Towards a Semantic Knowledge Management Framework for Laminated Composites

The engineering of laminated composite structures is a complex task for design engineers and manufacturers, requiring significant management of manufacturing process and materials information. Ontologies are becoming increasingly commonplace for semantically representing knowledge in a formal manner that facilitates sharing of rich information between people and applications. Moreover, ontologies can support first-order logic and reasoning by rule engines that enhance automation. To support the engineering of laminated composite structures, this work developed a novel Semantic LAminated Composites Knowledge management System (SLACKS) that is based on a suite of ontologies for laminated composites materials and design for manufacturing (DFM) and their integration into a previously developed engineering design framework. By leveraging information from CAD/FEA tools and materials data from online public databases, SLACKS uniquely enables software tools and people to interoperate, to improve communication and automate reasoning during the design process. With SLACKS, this research shows the power of integrating relevant domains of the product lifecycle, such as design, analysis, manufacturing and materials selection through the engineering case study of a wind turbine blade. The integration reveals a usable product lifecycle knowledge tool that can facilitate efficient knowledge creation, retrieval and reuse, from design inception to manufacturing of the product

Towards the Semantic Grid: A State of the Art Survey of Semantic Web Services and their Applicability to Collaborative Design, Engineering, and Procurement

Today, organizations within the engineering and manufacturing domains place as much emphasis on the management and flow of knowledge through a value chain as they do commodities that are more tangible in nature. For example, parts suppliers in the Canadian automotive sector are often asked to collaborate with auto manufacturers in designing and engineering their product, instead of simply producing and supplying it. Such fundamental changes in the overarching economics of this industry have led to a greater focus on collaboration, both in terms of communicating across geographic divides to design components, as well as new requirements to merge heterogeneous data stores in order to manage this distributed procurement process. Our work on this project centred on finding solutions to the above by surveying the state of the industry, as well as assessing the potential employability of related tools in the workplace. It was concluded that the Access Grid (a low-cost, open-source videoconferencing platform) held significant potential to facilitate the high-quality sharing of audiovisual material, while semantic technologies (the “semantic web” and “semantic web services”) represented a feasible solution to the issues of data integration. When combined, these technologies form the “semantic grid”, the focus of this paper. Overall, it is concluded that the past and present business success of this ICT in the information management sector may, with future work, link databases with the visualization interface to provide concurrent cost-benefit analyses

A Semantic Data Model to Represent Building Material Data in AEC Collaborative Workflows

The specification of building material is required in multiple phases of engineering and construction projects towards holistic BIM implementations. Building material information plays a vital role in design decisions by enabling different simulation processes, such as energy, acoustic, lighting, etc. Utilization and sharing of building material information between stakeholders are some of the major influencing factors on the practical implementation of the BIM process. Different meta-data schemas (e.g. IFC) are usually available to represent and share material information amongst partners involved in a construction project. However, these schemas have their own constraints to enable efficient data sharing amongst stakeholders. This paper explains these constraints and proposes a methodological approach for the representation of material data using semantic web concepts aiming to support the sharing of BIM data and interoperability enhancements in collaboration workflows. As a result, the DICBM (https://w3id.org/digitalconstruction/BuildingMaterials) ontology was developed which improves the management of building material information in the BIM-based collaboration process.:Abstract 1. Introduction and Background 1.1 Building Information Modeling for collaboration 1.2 Information management in AEC using semantic web technologies 2 DICBM: Digital Construction Building Material Ontology 2.1 Building Material Data in IFC 2.2 Overview of the building material ontology 2.3 Integration of external ontology concepts and roles 2.4 Material Definition 2.5 Material, Material Type, and Material Property 2.6 Data Properties in DICBM 3 Conclusions Acknowledgments Reference

Analyzing and Implementing a Feature Mapping Approach to CAD System Interoperability

Interoperable information exchange between computer-aided design (CAD) systems is one of the major problems to enable information integration in a collaborative engineering environment. Although a significant amount of work has been done on the extension and standardization of CAD data formats as well as the cooperation of CAD systems in both academy and industry, these approaches are generally low-level and narrowly targeted. Lack of fundamental study of interoperability and generic solution to this problem is the major issue. Our intention of this research is to design a solution of CAD feature interoperability as generic as possible based on a theoretical foundation of language types. In this paper, we present a fundamental model of semantic features and feature mapping process based on the type theory. We implement and demonstrate our approach for automated feature exchange between commercial CAD systems

Ontology based semantic engineering framework and tool for reconfigurable automation systems integration

Digital factory modelling based on virtual design and simulation is now emerging as a part of mainstream engineering activities, and it is typically geared towards reducing the product design cycle time. Reconfigurable manufacturing systems can benefit from reusing the existing knowledge in order to decrease the required skills and design time to launch new product generations. The various industrial simulation systems are currently integrating product design, matching processes and resource requirements to decrease the required skills and design time to launch new products. However, the main focus of current reconfigurable manufacturing systems has been modular production lines to support different manufacturing tasks. Additionally, the design data is not transferrable from various domain-specific software to a collaborative and intelligent platform, which is required to capture and reuse design knowledge. Product design is still dependent on the knowledge of designers and does not link to the existing knowledge on processes and resources, which are in separate domains. To address these issues, this research developed an integration method based on semantic technologies and product, process, resource and requirements (PPRR) ontologies called semantic-ontology engineering framework (SOEF). SOEF transferred original databases to an ontology-based automation data structure with a semantic analysis engine. A pre-defined semantic model is developed to recognise custom requirement and map existing knowledge with processing data in the automation assembly aspect. The main research contribution is using semantic technology to process automation documentation and map semantic data to the PPRR ontology structure. Furthermore, this research also contributes to the automatic modification of system simulation based on custom requirements. The SOEF uses a JAVA-based command-line user interface to present semantic analysis results and import ontology outputs to the vueOne system simulation tool for system evaluation

Past, present and future of information and knowledge sharing in the construction industry: Towards semantic service-based e-construction

The paper reviews product data technology initiatives in the construction sector and provides a synthesis of related ICT industry needs. A comparison between (a) the data centric characteristics of Product Data Technology (PDT) and (b) ontology with a focus on semantics, is given, highlighting the pros and cons of each approach. The paper advocates the migration from data-centric application integration to ontology-based business process support, and proposes inter-enterprise collaboration architectures and frameworks based on semantic services, underpinned by ontology-based knowledge structures. The paper discusses the main reasons behind the low industry take up of product data technology, and proposes a preliminary roadmap for the wide industry diffusion of the proposed approach. In this respect, the paper stresses the value of adopting alliance-based modes of operation

Practitioner requirements for integrated Knowledge-Based Engineering in Product Lifecycle Management.

The effective management of knowledge as capital is considered essential to the success of engineering product/service systems. As Knowledge Management (KM) and Product Lifecycle Management (PLM) practice gain industrial adoption, the question of functional overlaps between both the approaches becomes evident. This article explores the interoperability between PLM and Knowledge-Based Engineering (KBE) as a strategy for engineering KM. The opinion of key KBE/PLM practitioners are systematically captured and analysed. A set of ranked business functionalities to be fulfiled by the KBE/PLM systems integration is elicited. The article provides insights for the researchers and the practitioners playing both the user and development roles on the future needs for knowledge systems based on PLM

An Ontology-Based Method for Semantic Integration of Business Components

Building new business information systems from reusable components is today an approach widely adopted and used. Using this approach in analysis and design phases presents a great interest and requires the use of a particular class of components called Business Components (BC). Business Components are today developed by several manufacturers and are available in many repositories. However, reusing and integrating them in a new Information System requires detection and resolution of semantic conflicts. Moreover, most of integration and semantic conflict resolution systems rely on ontology alignment methods based on domain ontology. This work is positioned at the intersection of two research areas: Integration of reusable Business Components and alignment of ontologies for semantic conflict resolution. Our contribution concerns both the proposal of a BC integration solution based on ontologies alignment and a method for enriching the domain ontology used as a support for alignment.Comment: IEEE New Technologies of Distributed Systems (NOTERE), 2011 11th Annual International Conference; ISSN: 2162-1896 Print ISBN: 978-1-4577-0729-2 INSPEC Accession Number: 12122775 201