Improving automation standards via semantic modelling: Application to ISA88

Standardization is essential for automation. Extensibility, scalability, and reusability are important features for automation software that rely in the efficient modelling of the addressed systems. The work presented here is from the ongoing development of a methodology for semi-automatic ontology construction methodology from technical documents. The main aim of this work is to systematically check the consistency of technical documents and support the improvement of technical document consistency. The formalization of conceptual models and the subsequent writing of technical standards are simultaneously analyzed, and guidelines proposed for application to future technical standards. Three paradigms are discussed for the development of domain ontologies from technical documents, starting from the current state of the art, continuing with the intermediate method presented and used in this paper, and ending with the suggested paradigm for the future. The ISA88 Standard is taken as a representative case study. Linguistic techniques from the semi-automatic ontology construction methodology is applied to the ISA88 Standard and different modelling and standardization aspects that are worth sharing with the automation community is addressed. This study discusses different paradigms for developing and sharing conceptual models for the subsequent development of automation software, along with presenting the systematic consistency checking methodPeer ReviewedPostprint (author's final draft

Cost Estimation in Initial Stages of Product Development – An Ontological Approach

Cost estimation in the early stages of the product development process is fraught with uncertainties. The conceptual design is characterized by the absence of data, the most critical being costs. Decisions based on incorrect assumptions impact a project significantly and can increase unexpected costs in the future. As there are no structured means of obtaining costs in the conceptual phase, the reuse of data from past projects is an alternative discussed in the literature. Knowledge management approaches suggest a search for data in successful earlier projects. The use of ontologies has been regarded as an approach to capturing either knowledge stored in database or tacit knowledge. The proposed solution, in the form of an expert system built upon an ontological model, seeks to estimate costs based on costs in previous projects as well as expert tacit knowledge. The model is demonstrated by queries with needed functions and requirements. The ontological model searches the necessary information and generates a cost estimation. The present research project follows the methodological framework Design Science Research, presenting an overhead crane as a case study. The proposed approach has great potential in other industrial contexts as well

Cost estimation in initial development stages of products: an ontological approach

Cost estimation in the early stages of a product are fraught with uncertainties. The conceptual design of product development is characterized by the absence of data, the most critical being costs. The costs impact in the initial phases of the project is low, when discovered in later stages represent great risks. As there are no structured alternatives to obtaining costs in the conceptual phase, the reuse of data from past projects is an alternative discussed in the literature. Knowledge management approaches can search for data, nonexistent in the current phases, in successful earlier projects. The use of ontology is discussed as an approach in generating knowledge stored in a database. The proposed solution seeks to estimate costs based on previous projects. A query is formulated to describe the product function and settings. The ontological model searches the classes, instances, and properties in the database and generates a cost estimation. The costs of the previous project are reused to generate a new agile cost estimate without the need to consult other industry sectors. This dissertation project follows the methodological framework Design Science Research to make partial deliveries up to the final artifact, an ontological model. This proposal has great potential in the industry, considering there are no tools attending the initial phases with the same efficiency.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Estimativas de custos nas fases iniciais de um produto são repletas de incertezas. O projeto conceitual do desenvolvimento de produto e caracterizado pela ausência de dados, sendo os mais críticos os custos. O impacto dos custos nas fases iniciais do projeto e baixo, quando descobertos em fases posteriores representam grandes riscos. Como não existem meios estruturados de obtenção dos custos no projeto na fase conceitual, o reuso de dados de projetos passados e uma alternativa discutida na literatura. Abordagens de gerenciamento de conhecimento podem buscar dados, inexistentes nas fases atuais, em projetos anteriores bem sucedidos. O uso de ontologia e discutido como uma abordagem na geração de conhecimento armazenado em um banco de dados. A solução proposta busca estimar custos baseada em projetos anteriores. E formulada uma pergunta que descreva a função do produto e configurações. O modelo ontológico busca na base de dados classes, instâncias e propriedades e gera uma estimativa de custos. Os custos do projeto anterior são reutilizados para gerar uma nova estimativa de custos ágil sem necessidade de consultar outros setores da indústria. Este projeto de dissertação segue o framework metodológico Design Science Research para fazer entregas parciais ate a entrega do artefato final, um modelo ontológico. Esta proposta possui grande potencial na indústria, considerando que não existem ferramentas que atendam as fases iniciais com a mesma eficiência

A framework to represent, capture, and trace ontology development processes

This article presents OntoTracED, a comprehensive framework to represent, capture and trace ontology development processes. It has three components: (i) a conceptual model that defines the framework foundations, (ii) an ontological engineering domain model (OEDM), which specifies and describes design objects, as well as those operations that are particular to a specific ontology development methodology, and (iii) a computational support environment, named TracED(aaS). This contribution first offers an overview of the ontology development process characteristics and then describes the main features of each OntoTracED component. The framework capabilities are illustrated by means of a case study addressing the use of TracED(aaS) throughout the development of an ontology of industrial interest. It is shown that this proposal makes a strong contribution in the ontological engineering field since the whole ontology development process, its history, rationale, and all the intermediate products can be captured in an integrated fashion.Fil: Vegetti, Maria Marcela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; ArgentinaFil: Roldán, María Luciana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; ArgentinaFil: Gonnet, Silvio Miguel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; ArgentinaFil: Leone, Horacio Pascual. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; ArgentinaFil: Henning, Gabriela Patricia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentin

A multi-level framework approach to improve organisational business process understanding within automotive manufacturing

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonBusiness processes are an integral part of today’s multinational corporations, allowing them to create best practice working models. Not only do business processes play an important role in defining working practices, they can also provide a basis for understanding and improvement. One key difficulty is to capture multiple aspects of a process. Capturing these allows an organisation to use these models for multiple purposes, such as learning while obtaining a high process maturity. There is not a single modelling technique that spans over multiple purposes. This research provides a critical overview of the literature of business process modelling to propose a multi-level framework (MLF). This framework aims to model a single crossfunctional process using multiple modelling techniques to address different organisational purposes and achieve a higher process maturity. Three modelling techniques were identified as appropriate to form part of such a framework: Rich Picture Diagrams (RPD), Business Process Modelling Notation (BPMN) and 4D ontologies. Design Science Research was used in three iterations to build the levels of the multi-level framework in an iterative and incremental design approach. The first two iterations used semistructured interviews to gather data, involve stakeholders and evaluate the models, whilst the third iteration proposes a method to develop and evaluate 4D ontologies. The created artefacts form the process overview (using RPD), application view (using BPMN) and semantic view (4D) levels for the final MLF of a cross-functional process. It addresses organisational purposes such as learning, process development and IT requirements, and covers maturity levels from process creation to optimisation. Involvement of stakeholders in the development and evaluation revealed high satisfaction with the provided views and increased their understanding of the process. Future work would further evaluate the overall framework and study the effects of full implementation within industry

Development and Evaluation of a Holistic, Cloud-driven and Microservices-based Architecture for Automated Semantic Annotation of Web Documents

The Semantic Web is based on the concept of representing information on the web such that computers can both understand and process them. This implies defining context for web information to give them a well-defined meaning. Semantic Annotation defines the process of adding annotation data to web information for the much-needed context. However, despite several solutions and techniques for semantic annotation, it is still faced with challenges which have hindered the growth of the semantic web. With recent significant technological innovations such as Cloud Computing, Internet of Things as well as Mobile Computing and their various integrations with semantic technologies to proffer solutions in IT, little has been done towards leveraging these technologies to address semantic annotation challenges. Hence, this research investigates leveraging cloud computing paradigm to address some semantic annotation challenges, with focus on an automated system for providing semantic annotation as a service. Firstly, considering the current disparate nature observable with most semantic annotation solutions, a holistic perspective to semantic annotation is proposed based on a set of requirements. Then, a capability assessment towards the feasibility of leveraging cloud computing is conducted which produces a Cloud Computing Capability Model for Holistic Semantic Annotation. Furthermore, an investigation into application deployment patterns in the cloud and how they relate to holistic semantic annotation was conducted. A set of determinant factors that define different patterns for application deployment in the cloud were identified and these resulted into the development of a Cloud Computing Maturity Model and the conceptualisation of a “Cloud-Driven” development methodology for holistic semantic annotation in the cloud. Some key components of the “Cloud-Driven” concept include Microservices, Operating System-Level Virtualisation and Orchestration. With the role Microservices Software Architectural Patterns play towards developing solutions that can fully maximise cloud computing benefits; CloudSea: a holistic, cloud-driven and microservices-based architecture for automated semantic annotation of web documents is proposed as a novel approach to semantic annotation. The architecture draws from the theory of “Design Patterns” in Software Engineering towards its design and development which subsequently resulted into the development of twelve Design Patterns and a Pattern Language for Holistic Semantic Annotation, based on the CloudSea architectural design. As proof-of-concept, a prototype implementation for CloudSea was developed and deployed in the cloud based on the “Cloud-Driven” methodology and a functionality evaluation was carried out on it. A comparative evaluation of the CloudSea architecture was also conducted in relation to current semantic annotation solutions; both proposed in academic literature and existing as industry solutions. In addition, to evaluate the proposed Cloud Computing Maturity Model for Holistic Semantic Annotation, an experimental evaluation of the model was conducted by developing and deploying six instances of the prototype and deploying them differently, based on the patterns described in the model. This empirical investigation was implemented by testing the instances for performance through series of API load tests and results obtained confirmed the validity of both the “Cloud-Driven” methodology and the entire model

Development and Evaluation of a Holistic, Cloud-driven and Microservices-based Architecture for Automated Semantic Annotation of Web Documents

The Semantic Web is based on the concept of representing information on the web such that computers can both understand and process them. This implies defining context for web information to give them a well-defined meaning. Semantic Annotation defines the process of adding annotation data to web information for the much-needed context. However, despite several solutions and techniques for semantic annotation, it is still faced with challenges which have hindered the growth of the semantic web. With recent significant technological innovations such as Cloud Computing, Internet of Things as well as Mobile Computing and their various integrations with semantic technologies to proffer solutions in IT, little has been done towards leveraging these technologies to address semantic annotation challenges. Hence, this research investigates leveraging cloud computing paradigm to address some semantic annotation challenges, with focus on an automated system for providing semantic annotation as a service. Firstly, considering the current disparate nature observable with most semantic annotation solutions, a holistic perspective to semantic annotation is proposed based on a set of requirements. Then, a capability assessment towards the feasibility of leveraging cloud computing is conducted which produces a Cloud Computing Capability Model for Holistic Semantic Annotation. Furthermore, an investigation into application deployment patterns in the cloud and how they relate to holistic semantic annotation was conducted. A set of determinant factors that define different patterns for application deployment in the cloud were identified and these resulted into the development of a Cloud Computing Maturity Model and the conceptualisation of a “Cloud-Driven” development methodology for holistic semantic annotation in the cloud. Some key components of the “Cloud-Driven” concept include Microservices, Operating System-Level Virtualisation and Orchestration. With the role Microservices Software Architectural Patterns play towards developing solutions that can fully maximise cloud computing benefits; CloudSea: a holistic, cloud-driven and microservices-based architecture for automated semantic annotation of web documents is proposed as a novel approach to semantic annotation. The architecture draws from the theory of “Design Patterns” in Software Engineering towards its design and development which subsequently resulted into the development of twelve Design Patterns and a Pattern Language for Holistic Semantic Annotation, based on the CloudSea architectural design. As proof-of-concept, a prototype implementation for CloudSea was developed and deployed in the cloud based on the “Cloud-Driven” methodology and a functionality evaluation was carried out on it. A comparative evaluation of the CloudSea architecture was also conducted in relation to current semantic annotation solutions; both proposed in academic literature and existing as industry solutions. In addition, to evaluate the proposed Cloud Computing Maturity Model for Holistic Semantic Annotation, an experimental evaluation of the model was conducted by developing and deploying six instances of the prototype and deploying them differently, based on the patterns described in the model. This empirical investigation was implemented by testing the instances for performance through series of API load tests and results obtained confirmed the validity of both the “Cloud-Driven” methodology and the entire model