Continuous maintenance and the future – Foundations and technological challenges

High value and long life products require continuous maintenance throughout their life cycle to achieve required performance with optimum through-life cost. This paper presents foundations and technologies required to offer the maintenance service. Component and system level degradation science, assessment and modelling along with life cycle ‘big data’ analytics are the two most important knowledge and skill base required for the continuous maintenance. Advanced computing and visualisation technologies will improve efficiency of the maintenance and reduce through-life cost of the product. Future of continuous maintenance within the Industry 4.0 context also identifies the role of IoT, standards and cyber security

Operations Management of Satellite Launch Centers

Driven by the business potentialities of the satellite industry, the last years witnessed a massive increase of attention in the space industry. This sector has been always considered critical by national entities and international organizations worldwide due to economic, cultural, scientific, military and civil implications. The need of cutting down satellite launch costs has become even more impellent due to the competition generated by the entrance in the sector of new players, including commercial organizations. Indeed, the high demand of satellite services requires affordable and flexible launch. In this context, a fundamental aspect is represented by the optimization of launch centers' logistics. The aim of this paper is to investigate and review the benefits and potential impact that consolidated operations research and management strategies, coupled with emerging paradigms in machine learning and control can have in the satellite industry, surveying techniques which could be adopted in advanced operations management of satellite launch centers

Anomaly detection in a fleet of industrial assets with hierarchical statistical modeling

Abstract Anomaly detection in asset condition data is critical for reliable industrial asset operations. But statistical anomaly classifiers require certain amount of normal operations training data before acceptable accuracy can be achieved. The necessary training data are often not available in the early periods of assets operations. This problem is addressed in this paper using a hierarchical model for the asset fleet that systematically identifies similar assets, and enables collaborative learning within the clusters of similar assets. The general behavior of the similar assets are represented using higher level models, from which the parameters are sampled describing the individual asset operations. Hierarchical models enable the individuals from a population, comprising of statistically coherent subpopulations, to collaboratively learn from one another. Results obtained with the hierarchical model show a marked improvement in anomaly detection for assets having low amount of data, compared to independent modeling or having a model common to the entire fleet.This research was funded by the EPSRC and BT Prosperity Partnership project: Next Generation Converged Digital Infrastructure, grant number EP/R004935/

Teknoekonominen toteutettavuusanalyysi etäylläpidon liitettävyydestä tehtaissa

Maintenance activities play a major role in factory operations, as they prevent breakdowns and extend machine life. With the advances in sensor, computing and communications technology, sensor data can be increasingly exploited for real-time supervision of machine condition. However, the acquisition of the data is challenging due to proprietary technologies and interfaces applied in Industrial Networks. Therefore, sensor data is rarely utilized in other processes than automation. As the industry is heading towards a new industrial era, also referred to as Industrial Internet or Industrie 4.0, there is growing need to improve data availability for applications that can realize its potential value. In this research, the focus is on the feasibility of remote maintenance deployment in factories. The topic is approached from the connectivity viewpoint. The research is conducted by reviewing the literature, and by interviewing numerous industry experts regarding the connectivity and data exploitation in factories. These form the basis for the value network analysis, in which Value Network Configuration (VNC) method is applied, to analyze the value distribution among different actors in alternative remote connection cases. As a result of the VNC analysis, three alternative value network configurations are formed. They provide a high-level technical architecture of the remote connection implementation and discuss the accumulated value of each actor concerning remote maintenance service. The insights gained from the VNCs and literature are then employed to propose a future technical architecture for remote maintenance connectivity in factories.Huoltotoimet ovat suuressa roolissa tehtaan toiminnassa, sillä ne ehkäisevät konerikkoja ja pidentävät koneen käyttöikää. Sensori-, laskenta- ja tietoliikenneteknologian kehittymisen johdosta sensoridataa voidaan hyödyntää yhä enemmän koneen kunnon reaaliaikaiseen valvontaan. Datan saanti on kuitenkin haastavaa teollisissa verkoissa käytettyjen sovelluskohtaisten teknologioiden ja liitäntöjen takia. Sen vuoksi sensoridataa hyödynnetään harvoin muissa prosesseissa kuin automaatiossa. Teollisuuden suunnatessa kohti uutta teollista aikakautta, joka tunnetaan myös nimillä Teollinen Internet ja Teollisuus 4.0, on datan saatavuutta parannettava sovelluskohteille, jotka voivat realisoida sen potentiaalisen arvon. Tämä tutkimus tarkastelee etäylläpidon käyttöönoton toteutettavuutta tehtaissa. Aihetta lähestytään liitettävyyden näkökulmasta. Tutkimus suoritetaan tarkastelemalla kirjallisuutta sekä haastattelemalla lukuisia teollisuuden asiantuntijoita koskien liitettävyyttä ja datan hyödyntämistä tehtaissa. Nämä muodostavat perustan arvoverkkoanalyysille, jossa sovelletaan arvoverkkokonfiguraatio-menetelmää, jolla analysoidaan arvon jakautumista eri toimijoiden kesken vaihtoehtoisissa etäyhteystapauksissa. Arvoverkkokonfiguraatioanalyysin tuloksena muodostetaan kolme vaihtoehtoista arvoverkkokonfiguraatiota. Ne tarjoavat korkean tason teknisen arkkitehtuurin etäyhteyden implementaatiosta ja tarkastelevat toimijoiden kerryttämää arvoa etäylläpitopalvelun osalta. Arvoverkkokonfiguraatioista ja kirjallisuudesta saatujen näkemysten pohjalta esitellään lisäksi tulevaisuuden tekninen arkkitehtuuri etäylläpidon liitettävyydelle tehtaissa

Smart Manufacturing

This book is a collection of 11 articles that are published in the corresponding Machines Special Issue “Smart Manufacturing”. It represents the quality, breadth and depth of the most updated study in smart manufacturing (SM); in particular, digital technologies are deployed to enhance system smartness by (1) empowering physical resources in production, (2) utilizing virtual and dynamic assets over the Internet to expand system capabilities, (3) supporting data-driven decision-making activities at various domains and levels of businesses, or (4) reconfiguring systems to adapt to changes and uncertainties. System smartness can be evaluated by one or a combination of performance metrics such as degree of automation, cost-effectiveness, leanness, robustness, flexibility, adaptability, sustainability, and resilience. This book features, firstly, the concepts digital triad (DT-II) and Internet of digital triad things (IoDTT), proposed to deal with the complexity, dynamics, and scalability of complex systems simultaneously. This book also features a comprehensive survey of the applications of digital technologies in space instruments; a systematic literature search method is used to investigate the impact of product design and innovation on the development of space instruments. In addition, the survey provides important information and critical considerations for using cutting edge digital technologies in designing and manufacturing space instruments

An industrial analytics methodology and fog computing cyber-physical system for Industry 4.0 embedded machine learning applications

Industrial cyber-physical systems are the primary enabling technology for Industry 4.0, which combine legacy industrial and control engineering, with emerging technology paradigms (e.g. big data, internet-of-things, artificial intelligence, and machine learning), to derive self-aware and self-configuring factories capable of delivering major production innovations. However, the technologies and architectures needed to connect and extend physical factory operations to the cyber world have not been fully resolved. Although cloud computing and service-oriented architectures demonstrate strong adoption, such implementations are commonly produced using information technology perspectives, which can overlook engineering, control and Industry 4.0 design concerns relating to real-time performance, reliability or resilience. Hence, this research compares the latency and reliability performance of cyber-physical interfaces implemented using traditional cloud computing (i.e. centralised), and emerging fog computing (i.e. decentralised) paradigms, to deliver real-time embedded machine learning engineering applications for Industry 4.0. The findings highlight that despite the cloud’s highly scalable processing capacity, the fog’s decentralised, localised and autonomous topology may provide greater consistency, reliability, privacy and security for Industry 4.0 engineering applications, with the difference in observed maximum latency ranging from 67.7% to 99.4%. In addition, communication failures rates highlighted differences in both consistency and reliability, with the fog interface successfully responding to 900,000 communication requests (i.e. 0% failure rate), and the cloud interface recording failure rates of 0.11%, 1.42%, and 6.6% under varying levels of stress

2020 NASA Technology Taxonomy

This document is an update (new photos used) of the PDF version of the 2020 NASA Technology Taxonomy that will be available to download on the OCT Public Website. The updated 2020 NASA Technology Taxonomy, or "technology dictionary", uses a technology discipline based approach that realigns like-technologies independent of their application within the NASA mission portfolio. This tool is meant to serve as a common technology discipline-based communication tool across the agency and with its partners in other government agencies, academia, industry, and across the world

Teollisen Internetin käyttöönotto automaatiolaitteissa

Industrial Internet is a term that is used to describe digitalization of industry. It is a research direction in Finland, where there are already various groups studying it. Despite this, the term Industrial Internet is still relatively vague and there is a lack of concreteness around the topic. The objective of this thesis is to explore the current status of Industrial Internet and study the capabilities of automation devices from an Industrial Internet point of view. I explore Industrial Internet through a literary review where I study various use cases. The use cases of Industrial Internet are divided into two main types: platform centric and machine to machine (M2M) communication centric. The use cases provide a list of characteristics and requirements for Industrial Internet from these two perspectives. General requirements are, for example scalability and flexibility, which are achieved through various IT technologies, such as Service-Oriented-Architecture. This thesis also consists of a practical part where I configured the control logic and data collection for a test bed that simulates drop tests of active magnetic bearings. The control logic consists of a programmable logic controller and corresponding software. The data collection consists of software for collecting and analyzing measurement data and the measuring equipment. After the literary review and practical part, I propose the creation of a cloud based Industrial Internet platform around the active magnetic test bed. The purpose of the platform is to provide a direction for further research. The creation of the platform consists of two phases: first phase includes the creation of the platform so that the test bed achieves current functionality but cloud based. The second phase consists of changing the platform to meet the requirements of the literature review. The end results will be an application independent system solution for Industrial Internet.Teollinen Internet on termi, jolla kuvataan teollisuuden digitalisaatiota. Aihe on kasvavan kiinnostuksen kohde ja esim. Suomessa on useita tahoja, jotka panostavat aiheen tutkimukseen. Siltikin Teollinen Internet on käsitteenä epäselvä ja sitä vaivaa konkretian puute. Tämän työn tarkoituksena on tutustua Teollisen Internetin nykytilaan ja automaatiolaitteiden ominaisuuksiin Teollisen Internetin näkökulmasta. Teollisen Internetin esimerkit jakautuvat pääasiassa kahteen luokkaan: alustalähtöisiin ja koneiden väliseen kommunikaatioon (M2M-kommunikaatio). Esimerkit tarjoavat listan ominaisuuksia ja vaatimuksia Teolliselle Internetille kummastakin näkökulmasta. Yleisiä ominaisuuksia ovat esimerkiksi skaalattavuus ja joustavuus, jotka saavutetaan erilaisilla tietoteknisillä vaatimuksilla, esim. palvelukeskeisellä arkkitehtuurilla. Lisäksi työhön kuuluu käytännön osuus, jossa kirjoitin ohjainlogiikan ja datankeräyksen testilaitteeseen, joka simuloi aktiivimagneettilaakerien pudotuskokeita. Ohjainlogiikka koostui PLC-laitteesta ja siihen liittyvistä ohjelmistoista. Datan keräys koostui mittausdatan keräykseen ja purkamiseen vaadittavista ohjelmistoista sekä laitteistosta. Kirjallisuudesta kerättyjen vaatimusten ja käytännön kokemuksien perusteella esitän pilvipohjaisen, Teolliseen Internetiin suunnatun ohjelmistoalustan kehittämistä testilaitteen ympärille. Ohjelmistoalusta voi toimia yliopistollisen jatkotutkimuksen pohjana. Ohjelmistoalustan toteuttaminen tapahtuu kahdessa vaiheessa: ensimmäisessä vaiheessa kehitetään pilvipohjainen alusta, joka saavuttaa testilaitteiston nykyisen toiminnallisuuden. Toisessa vaiheessa ohjelmistoalusta muutetaan vastaamaan Teollisen Internetin vaatimuksia, jolla saavutetaan sovellusriippumaton järjestelmäratkaisu