DIN Spec 91345 RAMI 4.0 compliant data pipelining: An approach to support data understanding and data acquisition in smart manufacturing environments

Today, data scientists in the manufacturing domain are confronted with a set of challenges associated to data acquisition as well as data processing including the extraction of valuable in-formation to support both, the work of the manufacturing equipment as well as the manufacturing processes behind it. One essential aspect related to data acquisition is the pipelining, including various commu-nication standards, protocols and technologies to save and transfer heterogenous data. These circumstances make it hard to understand, find, access and extract data from the sources depend-ing on use cases and applications. In order to support this data pipelining process, this thesis proposes the use of the semantic model. The selected semantic model should be able to describe smart manufacturing assets them-selves as well as to access their data along their life-cycle. As a matter of fact, there are many research contributions in smart manufacturing, which already came out with reference architectures or standards for semantic-based meta data descrip-tion or asset classification. This research builds upon these outcomes and introduces a novel se-mantic model-based data pipelining approach using as a basis the Reference Architecture Model for Industry 4.0 (RAMI 4.0).Hoje em dia, os cientistas de dados no domínio da manufatura são confrontados com várias normas, protocolos e tecnologias de comunicação para gravar, processar e transferir vários tipos de dados. Estas circunstâncias tornam difícil compreender, encontrar, aceder e extrair dados necessários para aplicações dependentes de casos de utilização, desde os equipamentos aos respectivos processos de manufatura. Um aspecto essencial poderia ser um processo de canalisação de dados incluindo vários normas de comunicação, protocolos e tecnologias para gravar e transferir dados. Uma solução para suporte deste processo, proposto por esta tese, é a aplicação de um modelo semântico que descreva os próprios recursos de manufactura inteligente e o acesso aos seus dados ao longo do seu ciclo de vida. Muitas das contribuições de investigação em manufatura inteligente já produziram arquitecturas de referência como a RAMI 4.0 ou normas para a descrição semântica de meta dados ou classificação de recursos. Esta investigação baseia-se nestas fontes externas e introduz um novo modelo semântico baseado no Modelo de Arquitectura de Referência para Indústria 4.0 (RAMI 4.0), em conformidade com a abordagem de canalisação de dados no domínio da produção inteligente como caso exemplar de utilização para permitir uma fácil exploração, compreensão, descoberta, selecção e extracção de dados

Plethora : a framework for the intelligent control of robotic assembly systems

Plethora : a framework for the intelligent control of robotic assembly system

Automation of machine learning models benchmarking

Dissertação de mestrado em Engenharia InformáticaNa área de ciência de dados, o machine learning está-se a revelar uma ferramenta essencial para resolver problemas complexos. As empresas estão a investir em equipas de ciência de dados e Machine Learning para desenvolver modelos que apresentem valor para os clientes. No entanto, estes modelos são uma pequena percentagem de uma pipeline de projetos de Machine Learning (ML) e, para entregar um produto de ML completo, é necessário um número maior de componentes. DevOps é uma mentalidade de engenharia e um conjunto de práticas que visa unificar o processo de desenvolvimento e o processo de operações em um software, MLOps é um conceito similar a DevOps mas aplicado ao desenvolvimento e entrega de soluções de ML. O nível de automatização das etapas em uma pipeline de ML define a maturidade do processo de ML, que reflete a velocidade de treino de novos modelos com novos dados ou de treino de novos modelos com diferentes implementações. Um sistema de ML é um sistema de software, desenvolvimento e atualizações contínuas são necessárias para garantir um sistema que escale conforme as necessidades. O principal objetivo desta tese é apoiar a criação de um sistema integrado de ML com uma arquitetura que proporcione a capacidade de ser continuamente operada em um ambiente de produção. Um conceito para avaliação de desempenho de algoritmos deve ser elaborado e implementado. O principal obetivo e melhorar e ace'erar o cicio de desenvolvimento de modelos de ML na empresa. Para atingir este objetivo surge a necessidade de definir uma arquitetura com especificações e a implementação de processos automatizadas num pipeline de ML existente, este processo têm como objetivo alcançar uma ferramenta de benchmark de modelos, com capacidade de analisar o desempenho do modelo, um motor de inferência e um banco de dados para armazenar todas as métricas computadas. Um sistema baseado em IA em desenvolvimento fornece o caso de estudo para desenvolver e validar a arquitetura. Os avanços atuais na área da condução semiautomática introduz a necessidade de sistemas de monitoramento que podem localizar e detectar eventos especificas no veículo. Os conjuntos de sensores são instalados dentro da cabine para alimentar sistemas inteligentes que visam analisar e sinalizar certos comportamentos que podem impactar a segurança e o conforto dos passageiros..In the field of data science, ML is proving to be a core feature to solve complex real-world problems. Businesses are investing in data science and ML teams to develop AI based models that can deliver business value to their users. However, these models are only a small fraction of an ML project pipeline, and to deliver an end to end ML product, a greater number of components are needed. DevOps is an engineering mindset and a set of practices that aims to unify the development process and the operation process on software. MlOps is a similar concept to DevOps but applicable to the development and delivery of ML based solutions. The automation of the steps in a ML pipeline defines the maturity of the ML process, reflecting the velocity of training new models given new data or training new models given new implementations. An ML system is a software system that can support development, provide continuous integration and continuous delivery apply to help guarantee that one can reliably build and operate ML systems at scale. The main objective of this thesis are to support the creation of an integrated ML system with an archi tecture that provides the ability to be continuously operated in a production-like environment. Furthermore, a concept to evaluate the performance of algorithms shall be devised and implemented. The end goal is to improve and accelerate the ML development lifecycle. To achieve this goal surges the need to define an architecture alongside specifications and the implementation of several automated steps into an existing ML pipeline. To improve and accelerate model development an model engine benchmark tool is devised capable of several features, including the ability to have dashboards for model performance evaluation, an automatic inference engine, performance metrics for the model and a database to store all the computed metrics and metadata. An AI-based system under development provides the case study to develop and validate this architec ture. The current advances of semi-automated driving introduce the need for monitoring systems to scan and detect specific events in the vehicle. Sensor clusters are installed inside the vehicle cabin to feed data to intelligent systems that aim to analyze and red flag certain behaviours that can potentially impact passengers safety and comfort while using the vehicle

Architecture of Smart Grid Testing Platform and Integration of MultiPower Laboratory

Traditional electrical grids are shifting towards Smart Grids that could deliver electricity in sustainable, economic and secure way. Simultaneously, characteristics of electrical grids are becoming much more complex that require development of several Smart Grid functionalities. This thesis studies architecture modeling of Smart Grid Testing Platform (SGTP) and integration of MultiPower laboratory. The architecture was defined in collaboration with research project team in a project called “Integrated business platform of distributed energy resources” (HEILA). Furthermore, the main goals are to produce an architecture model, which promotes specific Smart Grid related use cases, and interconnect the MultiPower laboratory with the platform. This thesis is divided into two parts. Firstly, background, challenges with Smart Grids, the HEILA project and MultiPower laboratory are introduced. Then, Smart Grid Architecture Model (SGAM) Framework, tools and related architecture definitions in different projects are studied. In addition, information models defined by IEC 61850 standard and Common Information Model (CIM), Smart API, HyperText Transfer Protocol (HTTP) and MQ Telemetry Transport (MQTT) protocols are studied because of their central role in the architecture model and integration. Secondly, results are presented with descriptions of the architecture model and integration process. The architecture model presents how different actors cooperate in order to offer and use flexibility related services on distribution level. The architecture model increases level of details, adds functionalities and changes some of the protocols used when compared to the related architectures. Additionally, self-descriptive and more flexible messaging are introduced as messages contain semantic information and they are not bound to any specific format. The function positioning with two-way communications promotes decentralized data acquisition and control. Generally, that may ease market integration, privacy, autonomy and scalability issues. As a result, the architecture may promote development and utilization of different kind of flexibility related services and products. However, information objects should be added to the standard mapping on information layer of the model since it would increase level of details. The integration was successful since monitoring and controlling of the MultiPower equipment is possible with current version of the SGTP as tests demonstrate. Technical requirements in the use cases were fulfilled. In future research work in the HEILA project message encryption, validation and CIM utilization should be considered. Moreover, Energy Management System (EMS) and equipment that is more suitable for routine testing should be considered for the MultiPower

Federated Data Modeling for Built Environment Digital Twins

The digital twin (DT) approach is an enabler for data-driven decision making in architecture, engineering, construction, and operations. Various open data models that can potentially support the DT developments, at different scales and application domains, can be found in the literature. However, many implementations are based on organization-specific information management processes and proprietary data models, hindering interoperability. This article presents the process and information management approaches developed to generate a federated open data model supporting DT applications. The business process modeling notation and transaction and interaction modeling techniques are applied to formalize the federated DT data modeling framework, organized in three main phases: requirements definition, federation, validation and improvement. The proposed framework is developed adopting the cross-disciplinary and multiscale principles. A validation on the development of the federated building-level DT data model for the West Cambridge Campus DT research facility is conducted. The federated data model is used to enable DT-based asset management applications at the building and built environment levels

Insights on innovation management practices at T-Systems. Analysis of a new business model for identity services on public computer network systems

Projecte final de carrera fet en col.laboració amb T-Systems International GmbHCatalà: Aquesta monografia identifica elements de gestió de la innovació en una coneguda companyia alemanya del sector TIC (T-Systems International GmbH) i exerceix un anàlisi crític sobre ells a partir de l'estudi d'una iniciativa de negoci denominada Projecte CifraH (Citizen Interoperability Folder for Relationships based on Avatar Hosting per les seves sigles en anglès) originada en T-Systems ITC Iberia SAU, una unitat internacional de la companyia.Castellà: Esta monografía identifica elementos de gestión de la innovación en una conocida compañía alemana del sector TIC (T-Systems International GmbH) y los somete a un análisis crítico a partir del estudio de una iniciativa de negocio denominada Proyecto CifraH (Citizen Interoperability Folder for Relationships based on Avatar Hosting por sus siglas en inglés) llevada a cabo en T-Systems ITC Iberia SAU, una unidad internacional de la compañía.English: This monographic identifies innovation management elements at a major German IT services firm (T-Systems International GmbH) and subjects them to critical analysis through the study of a corporate business initiative known as Project CifraH (Citizen Interoperability Folder for Relationships based on Avatar Hosting) undertaken at an international subsidiary of the company