Time series database in Industrial IoT and its testing tool

Abstract. In the essence of the Industrial Internet of Things is data gathering. Data is time and event-based and hence time series data is key concept in the Industrial Internet of Things, and specific time series database is required to process and store the data. Solution development and choosing the right time series database for Industrial Internet of Things solution can be difficult. Inefficient comparison of time series databases can lead to wrong choices and consequently to delays and financial losses. This thesis is improving the tools to compare different time series databases in context of the Industrial Internet of Things. In addition, the thesis identifies the functional and non-functional requirements of time series database in Industrial Internet of Things and designs and implements a performance test bench. A practical example of how time series databases can be compared with identified requirements and developed test bench is also provided. The example is used to examine how selected time series databases fulfill these requirements. Eight functional requirements and eight non-functional requirements were identified. Functional requirements included, e.g., aggregation support, information models, and hierarchical configurations. Non-functional requirements included, e.g., scalability, performance, and lifecycle. Developed test bench took Industrial Internet of Things point of view by testing the database in three scenarios: write heavy, read heavy, and concurrent write and read operations. In the practical example, ABB’s cpmPlus History, InfluxDB, and TimescaleDB were evaluated. Both requirement evaluation and performance testing resulted that cpmPlus History performed best, InfluxDB second best, and TimescaleDB the worst. cpmPlus History showed extensive support for the requirements and best performance in all performance test cases. InfluxDB showed high performance for data writing while TimescaleDB showed better performance for data reading.Aikasarjatietokanta teollisuuden esineiden internetissä ja sen testipenkki. Tiivistelmä. Teollisuuden esineiden internetin ytimessä on tiedon keruu. Tieto on aika ja tapahtuma pohjaista ja sen vuoksi aikasarjatieto on teollisuuden esineiden internetin avainkäsitteitä. Prosessoidakseen tällaista tietoa tarvitaan erityinen aikasarjatietokanta. Sovelluskehitys ja oikean aikasarjatietokannan valitseminen teollisuuden esineiden internetin ratkaisuun voi olla vaikeaa. Tehoton aikasarjatietokantojen vertailu voi johtaa vääriin valintoihin ja siten viiveisiin sekä taloudellisiin tappioihin. Tässä diplomityössä kehitetään työkaluja, joilla eri aikasarjatietokantoja teollisuuden esineiden internetin ympäristössä voidaan vertailla. Diplomityössä tunnistetaan toiminnalliset ja ei-toiminnalliset vaatimukset aikasarjatietokannalle teollisuuden esineiden internetissä ja suunnitellaan ja toteutetaan suorituskykytestipenkki aikasarjatietokannoille. Työ tarjoaa myös käytännön esimerkin kuinka aikasarjatietokantoja voidaan vertailla tunnistetuilla vaatimuksilla ja kehitetyllä testipenkillä. Esimerkkiä hyödynnetään tutkimuksessa, jossa selvitetään kuinka nykyiset aikasarjatietokannat täyttävät tunnistetut vaatimukset. Diplomityössä tunnistettiin kahdeksan toiminnallista ja kahdeksan ei-toiminnallista vaatimusta. Toiminnallisiin vaatimuksiin sisältyi mm. aggregoinnin tukeminen, informaatiomallit ja hierarkkiset konfiguraatiot. Ei-toiminnallisiin vaatimuksiin sisältyi mm. skaalautuvuus, suorituskyky ja elinkaari. Kehitetty testipenkki otti teollisuuden esineiden internetin näkökulman kolmella eri testiskenaariolla: kirjoituspainoitteinen, lukemispainoitteinen ja yhtäaikaiset kirjoitus- ja lukemisoperaatiot. Käytännön esimerkissä ABB:n cpmPlus History, InfluxDB ja TimescaleDB tietokannat olivat arvioitavina. Sekä vaatimusten arviointi että suorituskykytestit osoittivat cpmPlus History:n suoriutuvan parhaiten, InfluxDB:n toiseksi parhaiten ja TimescaleDB:n huonoiten. cpmPlus History tuki tunnistettuja vaatimuksia laajimmin ja tarjosi parhaan suorituskyvyn kaikissa testiskenaarioissa. InfluxDB antoi hyvän suorituskyvyn tiedon kirjoittamiselle, kun vastaavasti TimescaleDB osoitti parempaa suorituskykyä tiedon lukemisessa

Smart factory benefits and specification for piloting

Abstract. This thesis aims to build a base for the road towards a smart factory and gather information about the field by examining related technologies, requirements and challenges, and available solutions from Finnish providers. Through these examinations, occurring challenges in the reference location are highlighted and ideas to tackle these are proposed, most suitable technologies and use cases are described, and the pilot is designed around the most suitable solution. In addition, an overview of the factory is examined, and ongoing projects and suitable data gathering methods are described so that the current situation, development activities, and necessary methods for data gathering are known. To gather all this information, a literature review, survey, and straight contacts were made. A literature review was used for the examination of the key areas of the topic, a survey to examine the occurring challenges, and straight contacts to gather the information about the available solutions and production. Based on the findings, the pilot is designed, a roadmap of the future steps is proposed, and to conclude the topic achievable benefits and specification for the piloting are described. This research led to the conclusion that the current situation is at the Industry 3.0 stage and there are some challenges on the road toward the era of Industry 4.0. In addition, many solutions and technologies are already available, and some ongoing projects are related to these. Now is the time to make the vision clear and compile all the individual projects together and change the target towards building a smart factory.Älykkään tehtaan hyödyt ja vaatimusmäärittely pilotoinnille. Tiivistelmä. Tämän diplomityön tavoitteena on rakentaa pohja älykkäälle tehtaalle ja sen pilotoinnille sekä kerryttää tietoa aihepiiristä. Pohjan rakentamisen keskiössä on aihepiiriin liittyvien teknologioiden, vaatimusten ja haasteiden sekä suomalaisten toimittajien tarjoamien ratkaisuiden tutkiminen. Tutkimusten pohjalta referenssikohteessa esiintyviä haasteita nostetaan esille ja niihin ehdotetaan ratkaisuja, sopivimpia teknologioita ja käyttökohteita esitellään ja pilotointi suunnitellaan sopivinta ratkaisua hyödyntäen. Näiden lisäksi tehtaan yleiskuvaa käydään läpi, aihepiiriin liittyviä meneillään olevia projekteja tarkastellaan ja sopivimpia datan keräysmentelmiä esitellään, jotta tehtaan tehtaan nykytila, meneillään olevat aihepiirin kehityshankkeet ja vaadittavat datan keräysmentelmät tiedetään. Näiden tietojen koostamiseksi hyödynnettiin kirjallisuuskatsausta, kyselyä sekä suoraa kontaktointia ratkaisujen tarjoajiin sekä tuotannon työnjohtajiin ja tuotannonsuunnittelijaan. Kirjallisuuskatsauksella hankittiin tietoa aihepiiristä ja siihen liittyvistä teknologioista, kyselyllä selvitettiin referenssikohteessa esiintyviä haasteita ja suoralla kontaktoinnilla hankittiin tietoa tarjolla olevista ratkaisuista ja tuotantoon liittyvistä asioista. Tulosten pohjalta suunnitellaan ratkaisun pilotointi, kehitetään tiekartta tulevista askelista ja tiivistetään saavutettavat hyödyt ja vaatimusmäärittely, jotta saavutetaan otsikon mukainen kokonaisuus. Tämä tutkimus on osoittanut, että tehtaan nykytila on teollisuus 3.0 tasolla ja matkalla kohti teollisuus 4.0 aikakautta haasteita tulee esiintymään. Lisäksi useita aihepiirin ratkaisuita ja teknologioita on jo tarjolla sekä osa meneillään olevista projekteista liittyy näihin. Nyt olisi hyvä aika kirkastaa visiota, yhdistää näitä yksittäisiä projekteja yhteen ja muuttaa kokonaisuuden suunta kohti älykkään tehtaan rakentamista

Network Coding-Based Next-Generation IoT for Industry 4.0

Industry 4.0 has become the main source of applications of the Internet of Things (IoT), which is generating new business opportunities. The use of cloud computing and artificial intelligence is also showing remarkable improvements in industrial operation, saving millions of dollars to manufacturers. The need for time-critical decision-making is evidencing a trade-off between latency and computation, urging Industrial IoT (IIoT) deployments to integrate fog nodes to perform early analytics. In this chapter, we review next-generation IIoT architectures, which aim to meet the requirements of industrial applications, such as low-latency and highly reliable communications. These architectures can be divided into IoT node, fog, and multicloud layers. We describe these three layers and compare their characteristics, providing also different use-cases of IIoT architectures. We introduce network coding (NC) as a solution to meet some of the requirements of next-generation communications. We review a variety of its approaches as well as different scenarios that improve their performance and reliability thanks to this technique. Then, we describe the communication process across the different levels of the architecture based on NC-based state-of-the-art works. Finally, we summarize the benefits and open challenges of combining IIoT architectures together with NC techniques

Creation of an Experimental Engineering Toolbox for the Digital Transformation of Manual Jet Engine Assembly

The fast and safe motion of goods and people is one of the foundations of the modern world. Jet aircraft is the fastest transport at the moment along with high-speed trains. Accordingly, both production and maintenance of aircrafts are an important task of our modern industrial environment as well. Modern aircraft engines require appropriate care and understanding of design and manufacturing. This is even more important, as the production of aerospace engines remains a manual process in many cases with limited data sources. Thus, quality control will need to take into account verification of manufacturing and assembly steps through specific checks and controls whilst implementing additional data sources. Automation of tasks still is at a low level. In this article a review of the challenges with regard to controls, automation and process and technical understanding for aerospace engine production and repair is provided. As this requires the collaboration of many teams and partners, an improvement and step change towards deeper understanding and process efficiency is required. As many operations remain manual, innovations for how humans interact with the technology and collaborate with an industrial environment are needed. The project in this article demonstrates the creation and usage of the proposed solutions for collaboration, troubleshooting and error correction

Remote Management of Embedded Systems

Možnosti dnešních vestavěných zařízení rapidně rostou. Jejich výkon dovoluje běh složitějších aplikací v prostředích Internetu věcí (IoT). Složité aplikace bývají náchylné na chyby a vyžadují průběžnou aktualizaci. Systém, který umožňuje aktualizace většího množství vzdálených vestavěných zařízení, byl navrhnut a implementován. Systém byl implementován na základě studie existujících řešení a podmínek projektu BeeeOn, který se zabývá chytrou domácností.Possibilities of today's embedded devices are growing rapidly. Their performance allows them to run more complex applications in Internet of Things (IoT) environments. Complex applications tend to be error-prone and require continual updates. A system that is capable of updating a multitude of remote embedded devices was designed and implemented. This system was created based on the study of existing solutions and requirements of the project BeeeOn which concerns itself with smart homes.

SMArc: a proposal for a smart, semantic middleware architecture focused on Smart City energy management

Among the main features that are intended to become part of what can be expected from the Smart City, one of them should be an improved energy management system, in order to benefit from a healthier relation with the environment, minimize energy expenses, and offer dynamic market opportunities. A Smart Grid seems like a very suitable infrastructure for this objective, as it guarantees a two-way information flow that will provide the means for energy management enhancement. However, to obtain all the required information, another entity must care about all the devices required to gather the data. What is more, this entity must consider the lifespan of the devices within the Smart Grid—when they are turned on and off or when new appliances are added—along with the services that devices are able to provide. This paper puts forward SMArc—an acronym for semantic middleware architecture—as a middleware proposal for the Smart Grid, so as to process the collected data and use it to insulate applications from the complexity of the metering facilities and guarantee that any change that may happen at these lower levels will be updated for future actions in the system

An integrative framework for cooperative production resources in smart manufacturing

Under the push of Industry 4.0 paradigm modern manufacturing companies are dealing with a significant digital transition, with the aim to better address the challenges posed by the growing complexity of globalized businesses (Hermann, Pentek, & Otto, Design principles for industrie 4.0 scenarios, 2016). One basic principle of this paradigm is that products, machines, systems and business are always connected to create an intelligent network along the entire factory\u2019s value chain. According to this vision, manufacturing resources are being transformed from monolithic entities into distributed components, which are loosely coupled and autonomous but nevertheless provided of the networking and connectivity capabilities enabled by the increasingly widespread Industrial Internet of Things technology. Under these conditions, they become capable of working together in a reliable and predictable manner, collaborating among themselves in a highly efficient way. Such a mechanism of synergistic collaboration is crucial for the correct evolution of any organization ranging from a multi-cellular organism to a complex modern manufacturing system (Moghaddam & Nof, 2017). Specifically of the last scenario, which is the field of our study, collaboration enables involved resources to exchange relevant information about the evolution of their context. These information can be in turn elaborated to make some decisions, and trigger some actions. In this way connected resources can modify their structure and configuration in response to specific business or operational variations (Alexopoulos, Makris, Xanthakis, Sipsas, & Chryssolouris, 2016). Such a model of \u201csocial\u201d and context-aware resources can contribute to the realization of a highly flexible, robust and responsive manufacturing system, which is an objective particularly relevant in the modern factories, as its inclusion in the scope of the priority research lines for the H2020 three-year period 2018-2020 can demonstrate (EFFRA, 2016). Interesting examples of these resources are self-organized logistics which can react to unexpected changes occurred in production or machines capable to predict failures on the basis of the contextual information and then trigger adjustments processes autonomously. This vision of collaborative and cooperative resources can be realized with the support of several studies in various fields ranging from information and communication technologies to artificial intelligence. An update state of the art highlights significant recent achievements that have been making these resources more intelligent and closer to the user needs. However, we are still far from an overall implementation of the vision, which is hindered by three major issues. The first one is the limited capability of a large part of the resources distributed within the shop floor to automatically interpret the exchanged information in a meaningful manner (semantic interoperability) (Atzori, Iera, & Morabito, 2010). This issue is mainly due to the high heterogeneity of data model formats adopted by the different resources used within the shop floor (Modoni, Doukas, Terkaj, Sacco, & Mourtzis, 2016). Another open issue is the lack of efficient methods to fully virtualize the physical resources (Rosen, von Wichert, Lo, & Bettenhausen, 2015), since only pairing physical resource with its digital counterpart that abstracts the complexity of the real world, it is possible to augment communication and collaboration capabilities of the physical component. The third issue is a side effect of the ongoing technological ICT evolutions affecting all the manufacturing companies and consists in the continuous growth of the number of threats and vulnerabilities, which can both jeopardize the cybersecurity of the overall manufacturing system (Wells, Camelio, Williams, & White, 2014). For this reason, aspects related with cyber-security should be considered at the early stage of the design of any ICT solution, in order to prevent potential threats and vulnerabilities. All three of the above mentioned open issues have been addressed in this research work with the aim to explore and identify a precise, secure and efficient model of collaboration among the production resources distributed within the shop floor. This document illustrates main outcomes of the research, focusing mainly on the Virtual Integrative Manufacturing Framework for resources Interaction (VICKI), a potential reference architecture for a middleware application enabling semantic-based cooperation among manufacturing resources. Specifically, this framework provides a technological and service-oriented infrastructure offering an event-driven mechanism that dynamically propagates the changing factors to the interested devices. The proposed system supports the coexistence and combination of physical components and their virtual counterparts in a network of interacting collaborative elements in constant connection, thus allowing to bring back the manufacturing system to a cooperative Cyber-physical Production System (CPPS) (Monostori, 2014). Within this network, the information coming from the productive chain can be promptly and seamlessly shared, distributed and understood by any actor operating in such a context. In order to overcome the problem of the limited interoperability among the connected resources, the framework leverages a common data model based on the Semantic Web technologies (SWT) (Berners-Lee, Hendler, & Lassila, 2001). The model provides a shared understanding on the vocabulary adopted by the distributed resources during their knowledge exchange. In this way, this model allows to integrate heterogeneous data streams into a coherent semantically enriched scheme that represents the evolution of the factory objects, their context and their smart reactions to all kind of situations. The semantic model is also machine-interpretable and re-usable. In addition to modeling, the virtualization of the overall manufacturing system is empowered by the adoption of an agent-based modeling, which contributes to hide and abstract the control functions complexity of the cooperating entities, thus providing the foundations to achieve a flexible and reconfigurable system. Finally, in order to mitigate the risk of internal and external attacks against the proposed infrastructure, it is explored the potential of a strategy based on the analysis and assessment of the manufacturing systems cyber-security aspects integrated into the context of the organization\u2019s business model. To test and validate the proposed framework, a demonstration scenarios has been identified, which are thought to represent different significant case studies of the factory\u2019s life cycle. To prove the correctness of the approach, the validation of an instance of the framework is carried out within a real case study. Moreover, as for data intensive systems such as the manufacturing system, the quality of service (QoS) requirements in terms of latency, efficiency, and scalability are stringent, an evaluation of these requirements is needed in a real case study by means of a defined benchmark, thus showing the impact of the data storage, of the connected resources and of their requests

Truth, Beauty, Freedom, and Money: Technology-Based Art and the Dynamics of Sustainability

Proposes innovative new approaches and models for art and technology institutions, and provides details for an "Arts Lab," a unique hybrid art center and research lab

Network coding for reliable wireless sensor networks

Wireless sensor networks are used in many applications and are now a key element in the increasingly growing Internet of Things. These networks are composed of small nodes including wireless communication modules, and in most of the cases are able to autonomously con gure themselves into networks, to ensure sensed data delivery. As more and more sensor nodes and networks join the Internet of Things, collaboration between geographically distributed systems are expected. Peer to peer overlay networks can assist in the federation of these systems, for them to collaborate. Since participating peers/proxies contribute to storage and processing, there is no burden on speci c servers and bandwidth bottlenecks are avoided. Network coding can be used to improve the performance of wireless sensor networks. The idea is for data from multiple links to be combined at intermediate encoding nodes, before further transmission. This technique proved to have a lot of potential in a wide range of applications. In the particular case of sensor networks, network coding based protocols and algorithms try to achieve a balance between low packet error rate and energy consumption. For network coding based constrained networks to be federated using peer to peer overlays, it is necessary to enable the storage of encoding vectors and coded data by such distributed storage systems. Packets can arrive to the overlay through any gateway/proxy (peers in the overlay), and lost packets can be recovered by the overlay (or client) using original and coded data that has been stored. The decoding process requires a decoding service at the overlay network. Such architecture, which is the focus of this thesis, will allow constrained networks to reduce packet error rate in an energy e cient way, while bene ting from an e ective distributed storage solution for their federation. This will serve as a basis for the proposal of mathematical models and algorithms that determine the most e ective routing trees, for packet forwarding toward sink/gateway nodes, and best amount and placement of encoding nodes.As redes de sensores sem fios são usadas em muitas aplicações e são hoje consideradas um elemento-chave para o desenvolvimento da Internet das Coisas. Compostas por nós de pequena dimensão que incorporam módulos de comunicação sem fios, grande parte destas redes possuem a capacidade de se configurarem de forma autónoma, formando sistemas em rede para garantir a entrega dos dados recolhidos. (…

An integrative framework for cooperative production resources in smart manufacturing

Under the push of Industry 4.0 paradigm modern manufacturing companies are dealing with a significant digital transition, with the aim to better address the challenges posed by the growing complexity of globalized businesses (Hermann, Pentek, & Otto, Design principles for industrie 4.0 scenarios, 2016). One basic principle of this paradigm is that products, machines, systems and business are always connected to create an intelligent network along the entire factory’s value chain. According to this vision, manufacturing resources are being transformed from monolithic entities into distributed components, which are loosely coupled and autonomous but nevertheless provided of the networking and connectivity capabilities enabled by the increasingly widespread Industrial Internet of Things technology. Under these conditions, they become capable of working together in a reliable and predictable manner, collaborating among themselves in a highly efficient way. Such a mechanism of synergistic collaboration is crucial for the correct evolution of any organization ranging from a multi-cellular organism to a complex modern manufacturing system (Moghaddam & Nof, 2017). Specifically of the last scenario, which is the field of our study, collaboration enables involved resources to exchange relevant information about the evolution of their context. These information can be in turn elaborated to make some decisions, and trigger some actions. In this way connected resources can modify their structure and configuration in response to specific business or operational variations (Alexopoulos, Makris, Xanthakis, Sipsas, & Chryssolouris, 2016). Such a model of “social” and context-aware resources can contribute to the realization of a highly flexible, robust and responsive manufacturing system, which is an objective particularly relevant in the modern factories, as its inclusion in the scope of the priority research lines for the H2020 three-year period 2018-2020 can demonstrate (EFFRA, 2016). Interesting examples of these resources are self-organized logistics which can react to unexpected changes occurred in production or machines capable to predict failures on the basis of the contextual information and then trigger adjustments processes autonomously. This vision of collaborative and cooperative resources can be realized with the support of several studies in various fields ranging from information and communication technologies to artificial intelligence. An update state of the art highlights significant recent achievements that have been making these resources more intelligent and closer to the user needs. However, we are still far from an overall implementation of the vision, which is hindered by three major issues. The first one is the limited capability of a large part of the resources distributed within the shop floor to automatically interpret the exchanged information in a meaningful manner (semantic interoperability) (Atzori, Iera, & Morabito, 2010). This issue is mainly due to the high heterogeneity of data model formats adopted by the different resources used within the shop floor (Modoni, Doukas, Terkaj, Sacco, & Mourtzis, 2016). Another open issue is the lack of efficient methods to fully virtualize the physical resources (Rosen, von Wichert, Lo, & Bettenhausen, 2015), since only pairing physical resource with its digital counterpart that abstracts the complexity of the real world, it is possible to augment communication and collaboration capabilities of the physical component. The third issue is a side effect of the ongoing technological ICT evolutions affecting all the manufacturing companies and consists in the continuous growth of the number of threats and vulnerabilities, which can both jeopardize the cybersecurity of the overall manufacturing system (Wells, Camelio, Williams, & White, 2014). For this reason, aspects related with cyber-security should be considered at the early stage of the design of any ICT solution, in order to prevent potential threats and vulnerabilities. All three of the above mentioned open issues have been addressed in this research work with the aim to explore and identify a precise, secure and efficient model of collaboration among the production resources distributed within the shop floor. This document illustrates main outcomes of the research, focusing mainly on the Virtual Integrative Manufacturing Framework for resources Interaction (VICKI), a potential reference architecture for a middleware application enabling semantic-based cooperation among manufacturing resources. Specifically, this framework provides a technological and service-oriented infrastructure offering an event-driven mechanism that dynamically propagates the changing factors to the interested devices. The proposed system supports the coexistence and combination of physical components and their virtual counterparts in a network of interacting collaborative elements in constant connection, thus allowing to bring back the manufacturing system to a cooperative Cyber-physical Production System (CPPS) (Monostori, 2014). Within this network, the information coming from the productive chain can be promptly and seamlessly shared, distributed and understood by any actor operating in such a context. In order to overcome the problem of the limited interoperability among the connected resources, the framework leverages a common data model based on the Semantic Web technologies (SWT) (Berners-Lee, Hendler, & Lassila, 2001). The model provides a shared understanding on the vocabulary adopted by the distributed resources during their knowledge exchange. In this way, this model allows to integrate heterogeneous data streams into a coherent semantically enriched scheme that represents the evolution of the factory objects, their context and their smart reactions to all kind of situations. The semantic model is also machine-interpretable and re-usable. In addition to modeling, the virtualization of the overall manufacturing system is empowered by the adoption of an agent-based modeling, which contributes to hide and abstract the control functions complexity of the cooperating entities, thus providing the foundations to achieve a flexible and reconfigurable system. Finally, in order to mitigate the risk of internal and external attacks against the proposed infrastructure, it is explored the potential of a strategy based on the analysis and assessment of the manufacturing systems cyber-security aspects integrated into the context of the organization’s business model. To test and validate the proposed framework, a demonstration scenarios has been identified, which are thought to represent different significant case studies of the factory’s life cycle. To prove the correctness of the approach, the validation of an instance of the framework is carried out within a real case study. Moreover, as for data intensive systems such as the manufacturing system, the quality of service (QoS) requirements in terms of latency, efficiency, and scalability are stringent, an evaluation of these requirements is needed in a real case study by means of a defined benchmark, thus showing the impact of the data storage, of the connected resources and of their requests