Self-managed Workflows for Cyber-physical Systems

Workflows are a well-established concept for describing business logics and processes in web-based applications and enterprise application integration scenarios on an abstract implementation-agnostic level. Applying Business Process Management (BPM) technologies to increase autonomy and automate sequences of activities in Cyber-physical Systems (CPS) promises various advantages including a higher flexibility and simplified programming, a more efficient resource usage, and an easier integration and orchestration of CPS devices. However, traditional BPM notations and engines have not been designed to be used in the context of CPS, which raises new research questions occurring with the close coupling of the virtual and physical worlds. Among these challenges are the interaction with complex compounds of heterogeneous sensors, actuators, things and humans; the detection and handling of errors in the physical world; and the synchronization of the cyber-physical process execution models. Novel factors related to the interaction with the physical world including real world obstacles, inconsistencies and inaccuracies may jeopardize the successful execution of workflows in CPS and may lead to unanticipated situations. This thesis investigates properties and requirements of CPS relevant for the introduction of BPM technologies into cyber-physical domains. We discuss existing BPM systems and related work regarding the integration of sensors and actuators into workflows, the development of a Workflow Management System (WfMS) for CPS, and the synchronization of the virtual and physical process execution as part of self-* capabilities for WfMSes. Based on the identified research gap, we present concepts and prototypes regarding the development of a CPS WFMS w.r.t. all phases of the BPM lifecycle. First, we introduce a CPS workflow notation that supports the modelling of the interaction of complex sensors, actuators, humans, dynamic services and WfMSes on the business process level. In addition, the effects of the workflow execution can be specified in the form of goals defining success and error criteria for the execution of individual process steps. Along with that, we introduce the notion of Cyber-physical Consistency. Following, we present a system architecture for a corresponding WfMS (PROtEUS) to execute the modelled processes-also in distributed execution settings and with a focus on interactive process management. Subsequently, the integration of a cyber-physical feedback loop to increase resilience of the process execution at runtime is discussed. Within this MAPE-K loop, sensor and context data are related to the effects of the process execution, deviations from expected behaviour are detected, and compensations are planned and executed. The execution of this feedback loop can be scaled depending on the required level of precision and consistency. Our implementation of the MAPE-K loop proves to be a general framework for adding self-* capabilities to WfMSes. The evaluation of our concepts within a smart home case study shows expected behaviour, reasonable execution times, reduced error rates and high coverage of the identified requirements, which makes our CPS~WfMS a suitable system for introducing workflows on top of systems, devices, things and applications of CPS.:1. Introduction 15 1.1. Motivation 15 1.2. Research Issues 17 1.3. Scope & Contributions 19 1.4. Structure of the Thesis 20 2. Workflows and Cyber-physical Systems 21 2.1. Introduction 21 2.2. Two Motivating Examples 21 2.3. Business Process Management and Workflow Technologies 23 2.4. Cyber-physical Systems 31 2.5. Workflows in CPS 38 2.6. Requirements 42 3. Related Work 45 3.1. Introduction 45 3.2. Existing BPM Systems in Industry and Academia 45 3.3. Modelling of CPS Workflows 49 3.4. CPS Workflow Systems 53 3.5. Cyber-physical Synchronization 58 3.6. Self-* for BPM Systems 63 3.7. Retrofitting Frameworks for WfMSes 69 3.8. Conclusion & Deficits 71 4. Modelling of Cyber-physical Workflows with Consistency Style Sheets 75 4.1. Introduction 75 4.2. Workflow Metamodel 76 4.3. Knowledge Base 87 4.4. Dynamic Services 92 4.5. CPS-related Workflow Effects 94 4.6. Cyber-physical Consistency 100 4.7. Consistency Style Sheets 105 4.8. Tools for Modelling of CPS Workflows 106 4.9. Compatibility with Existing Business Process Notations 111 5. Architecture of a WfMS for Distributed CPS Workflows 115 5.1. Introduction 115 5.2. PROtEUS Process Execution System 116 5.3. Internet of Things Middleware 124 5.4. Dynamic Service Selection via Semantic Access Layer 125 5.5. Process Distribution 126 5.6. Ubiquitous Human Interaction 130 5.7. Towards a CPS WfMS Reference Architecture for Other Domains 137 6. Scalable Execution of Self-managed CPS Workflows 141 6.1. Introduction 141 6.2. MAPE-K Control Loops for Autonomous Workflows 141 6.3. Feedback Loop for Cyber-physical Consistency 148 6.4. Feedback Loop for Distributed Workflows 152 6.5. Consistency Levels, Scalability and Scalable Consistency 157 6.6. Self-managed Workflows 158 6.7. Adaptations and Meta-adaptations 159 6.8. Multiple Feedback Loops and Process Instances 160 6.9. Transactions and ACID for CPS Workflows 161 6.10. Runtime View on Cyber-physical Synchronization for Workflows 162 6.11. Applicability of Workflow Feedback Loops to other CPS Domains 164 6.12. A Retrofitting Framework for Self-managed CPS WfMSes 165 7. Evaluation 171 7.1. Introduction 171 7.2. Hardware and Software 171 7.3. PROtEUS Base System 174 7.4. PROtEUS with Feedback Service 182 7.5. Feedback Service with Legacy WfMSes 213 7.6. Qualitative Discussion of Requirements and Additional CPS Aspects 217 7.7. Comparison with Related Work 232 7.8. Conclusion 234 8. Summary and Future Work 237 8.1. Summary and Conclusion 237 8.2. Advances of this Thesis 240 8.3. Contributions to the Research Area 242 8.4. Relevance 243 8.5. Open Questions 245 8.6. Future Work 247 Bibliography 249 Acronyms 277 List of Figures 281 List of Tables 285 List of Listings 287 Appendices 28

The Hierarchic treatment of marine ecological information from spatial networks of benthic platforms

Measuring biodiversity simultaneously in different locations, at different temporal scales, and over wide spatial scales is of strategic importance for the improvement of our understanding of the functioning of marine ecosystems and for the conservation of their biodiversity. Monitoring networks of cabled observatories, along with other docked autonomous systems (e.g., Remotely Operated Vehicles [ROVs], Autonomous Underwater Vehicles [AUVs], and crawlers), are being conceived and established at a spatial scale capable of tracking energy fluxes across benthic and pelagic compartments, as well as across geographic ecotones. At the same time, optoacoustic imaging is sustaining an unprecedented expansion in marine ecological monitoring, enabling the acquisition of new biological and environmental data at an appropriate spatiotemporal scale. At this stage, one of the main problems for an effective application of these technologies is the processing, storage, and treatment of the acquired complex ecological information. Here, we provide a conceptual overview on the technological developments in the multiparametric generation, storage, and automated hierarchic treatment of biological and environmental information required to capture the spatiotemporal complexity of a marine ecosystem. In doing so, we present a pipeline of ecological data acquisition and processing in different steps and prone to automation. We also give an example of population biomass, community richness and biodiversity data computation (as indicators for ecosystem functionality) with an Internet Operated Vehicle (a mobile crawler). Finally, we discuss the software requirements for that automated data processing at the level of cyber-infrastructures with sensor calibration and control, data banking, and ingestion into large data portals.Peer ReviewedPostprint (published version

Towards Prescriptive Analytics in Cyber-Physical Systems

More and more of our physical world today is being monitored and controlled by so-called cyber-physical systems (CPSs). These are compositions of networked autonomous cyber and physical agents such as sensors, actuators, computational elements, and humans in the loop. Today, CPSs are still relatively small-scale and very limited compared to CPSs to be witnessed in the future. Future CPSs are expected to be far more complex, large-scale, wide-spread, and mission-critical, and found in a variety of domains such as transportation, medicine, manufacturing, and energy, where they will bring many advantages such as the increased efficiency, sustainability, reliability, and security. To unleash their full potential, CPSs need to be equipped with, among other features, the support for automated planning and control, where computing agents collaboratively and continuously plan and control their actions in an intelligent and well-coordinated manner to secure and optimize a physical process, e.g., electricity flow in the power grid. In today’s CPSs, the control is typically automated, but the planning is solely performed by humans. Unfortunately, it is intractable and infeasible for humans to plan every action in a future CPS due to the complexity, scale, and volatility of a physical process. Due to these properties, the control and planning has to be continuous and automated in future CPSs. Humans may only analyse and tweak the system’s operation using the set of tools supporting prescriptive analytics that allows them (1) to make predictions, (2) to get the suggestions of the most prominent set of actions (decisions) to be taken, and (3) to analyse the implications as if such actions were taken. This thesis considers the planning and control in the context of a large-scale multi-agent CPS. Based on the smart-grid use-case, it presents a so-called PrescriptiveCPS – which is (the conceptual model of) a multi-agent, multi-role, and multi-level CPS automatically and continuously taking and realizing decisions in near real-time and providing (human) users prescriptive analytics tools to analyse and manage the performance of the underlying physical system (or process). Acknowledging the complexity of CPSs, this thesis provides contributions at the following three levels of scale: (1) the level of a (full) PrescriptiveCPS, (2) the level of a single PrescriptiveCPS agent, and (3) the level of a component of a CPS agent software system. At the CPS level, the contributions include the definition of PrescriptiveCPS, according to which it is the system of interacting physical and cyber (sub-)systems. Here, the cyber system consists of hierarchically organized inter-connected agents, collectively managing instances of so-called flexibility, decision, and prescription models, which are short-lived, focus on the future, and represent a capability, an (user’s) intention, and actions to change the behaviour (state) of a physical system, respectively. At the agent level, the contributions include the three-layer architecture of an agent software system, integrating the number of components specially designed or enhanced to support the functionality of PrescriptiveCPS. At the component level, the most of the thesis contribution is provided. The contributions include the description, design, and experimental evaluation of (1) a unified multi-dimensional schema for storing flexibility and prescription models (and related data), (2) techniques to incrementally aggregate flexibility model instances and disaggregate prescription model instances, (3) a database management system (DBMS) with built-in optimization problem solving capability allowing to formulate optimization problems using SQL-like queries and to solve them “inside a database”, (4) a real-time data management architecture for processing instances of flexibility and prescription models under (soft or hard) timing constraints, and (5) a graphical user interface (GUI) to visually analyse the flexibility and prescription model instances. Additionally, the thesis discusses and exemplifies (but provides no evaluations of) (1) domain-specific and in-DBMS generic forecasting techniques allowing to forecast instances of flexibility models based on historical data, and (2) powerful ways to analyse past, current, and future based on so-called hypothetical what-if scenarios and flexibility and prescription model instances stored in a database. Most of the contributions at this level are based on the smart-grid use-case. In summary, the thesis provides (1) the model of a CPS with planning capabilities, (2) the design and experimental evaluation of prescriptive analytics techniques allowing to effectively forecast, aggregate, disaggregate, visualize, and analyse complex models of the physical world, and (3) the use-case from the energy domain, showing how the introduced concepts are applicable in the real world. We believe that all this contribution makes a significant step towards developing planning-capable CPSs in the future.Mehr und mehr wird heute unsere physische Welt überwacht und durch sogenannte Cyber-Physical-Systems (CPS) geregelt. Dies sind Kombinationen von vernetzten autonomen cyber und physischen Agenten wie Sensoren, Aktoren, Rechenelementen und Menschen. Heute sind CPS noch relativ klein und im Vergleich zu CPS der Zukunft sehr begrenzt. Zukünftige CPS werden voraussichtlich weit komplexer, größer, weit verbreiteter und unternehmenskritischer sein sowie in einer Vielzahl von Bereichen wie Transport, Medizin, Fertigung und Energie – in denen sie viele Vorteile wie erhöhte Effizienz, Nachhaltigkeit, Zuverlässigkeit und Sicherheit bringen – anzutreffen sein. Um ihr volles Potenzial entfalten zu können, müssen CPS unter anderem mit der Unterstützung automatisierter Planungs- und Steuerungsfunktionalität ausgestattet sein, so dass Agents ihre Aktionen gemeinsam und kontinuierlich auf intelligente und gut koordinierte Weise planen und kontrollieren können, um einen physischen Prozess wie den Stromfluss im Stromnetz sicherzustellen und zu optimieren. Zwar sind in den heutigen CPS Steuerung und Kontrolle typischerweise automatisiert, aber die Planung wird weiterhin allein von Menschen durchgeführt. Leider ist diese Aufgabe nur schwer zu bewältigen, und es ist für den Menschen schlicht unmöglich, jede Aktion in einem zukünftigen CPS auf Basis der Komplexität, des Umfangs und der Volatilität eines physikalischen Prozesses zu planen. Aufgrund dieser Eigenschaften müssen Steuerung und Planung in CPS der Zukunft kontinuierlich und automatisiert ablaufen. Der Mensch soll sich dabei ganz auf die Analyse und Einflussnahme auf das System mit Hilfe einer Reihe von Werkzeugen konzentrieren können. Derartige Werkzeuge erlauben (1) Vorhersagen, (2) Vorschläge der wichtigsten auszuführenden Aktionen (Entscheidungen) und (3) die Analyse und potentiellen Auswirkungen der zu fällenden Entscheidungen. Diese Arbeit beschäftigt sich mit der Planung und Kontrolle im Rahmen großer Multi-Agent-CPS. Basierend auf dem Smart-Grid als Anwendungsfall wird ein sogenanntes PrescriptiveCPS vorgestellt, welches einem Multi-Agent-, Multi-Role- und Multi-Level-CPS bzw. dessen konzeptionellem Modell entspricht. Diese PrescriptiveCPS treffen und realisieren automatisch und kontinuierlich Entscheidungen in naher Echtzeit und stellen Benutzern (Menschen) Prescriptive-Analytics-Werkzeuge und Verwaltung der Leistung der zugrundeliegenden physischen Systeme bzw. Prozesse zur Verfügung. In Anbetracht der Komplexität von CPS leistet diese Arbeit Beiträge auf folgenden Ebenen: (1) Gesamtsystem eines PrescriptiveCPS, (2) PrescriptiveCPS-Agenten und (3) Komponenten eines CPS-Agent-Software-Systems. Auf CPS-Ebene umfassen die Beiträge die Definition von PrescriptiveCPS als ein System von wechselwirkenden physischen und cyber (Sub-)Systemen. Das Cyber-System besteht hierbei aus hierarchisch organisierten verbundenen Agenten, die zusammen Instanzen sogenannter Flexibility-, Decision- und Prescription-Models verwalten, welche von kurzer Dauer sind, sich auf die Zukunft konzentrieren und Fähigkeiten, Absichten (des Benutzers) und Aktionen darstellen, die das Verhalten des physischen Systems verändern. Auf Agenten-Ebene umfassen die Beiträge die Drei-Ebenen-Architektur eines Agentensoftwaresystems sowie die Integration von Komponenten, die insbesondere zur besseren Unterstützung der Funktionalität von PrescriptiveCPS entwickelt wurden. Der Schwerpunkt dieser Arbeit bilden die Beiträge auf der Komponenten-Ebene, diese umfassen Beschreibung, Design und experimentelle Evaluation (1) eines einheitlichen multidimensionalen Schemas für die Speicherung von Flexibility- and Prescription-Models (und verwandten Daten), (2) der Techniken zur inkrementellen Aggregation von Instanzen eines Flexibilitätsmodells und Disaggregation von Prescription-Models, (3) eines Datenbankmanagementsystem (DBMS) mit integrierter Optimierungskomponente, die es erlaubt, Optimierungsprobleme mit Hilfe von SQL-ähnlichen Anfragen zu formulieren und sie „in einer Datenbank zu lösen“, (4) einer Echtzeit-Datenmanagementarchitektur zur Verarbeitung von Instanzen der Flexibility- and Prescription-Models unter (weichen oder harten) Zeitvorgaben und (5) einer grafische Benutzeroberfläche (GUI) zur Visualisierung und Analyse von Instanzen der Flexibility- and Prescription-Models. Darüber hinaus diskutiert und veranschaulicht diese Arbeit beispielhaft ohne detaillierte Evaluation (1) anwendungsspezifische und im DBMS integrierte Vorhersageverfahren, die die Vorhersage von Instanzen der Flexibility- and Prescription-Models auf Basis historischer Daten ermöglichen, und (2) leistungsfähige Möglichkeiten zur Analyse von Vergangenheit, Gegenwart und Zukunft auf Basis sogenannter hypothetischer „What-if“-Szenarien und der in der Datenbank hinterlegten Instanzen der Flexibility- and Prescription-Models. Die meisten der Beiträge auf dieser Ebene basieren auf dem Smart-Grid-Anwendungsfall. Zusammenfassend befasst sich diese Arbeit mit (1) dem Modell eines CPS mit Planungsfunktionen, (2) dem Design und der experimentellen Evaluierung von Prescriptive-Analytics-Techniken, die eine effektive Vorhersage, Aggregation, Disaggregation, Visualisierung und Analyse komplexer Modelle der physischen Welt ermöglichen und (3) dem Anwendungsfall der Energiedomäne, der zeigt, wie die vorgestellten Konzepte in der Praxis Anwendung finden. Wir glauben, dass diese Beiträge einen wesentlichen Schritt in der zukünftigen Entwicklung planender CPS darstellen.Mere og mere af vores fysiske verden bliver overvåget og kontrolleret af såkaldte cyber-fysiske systemer (CPSer). Disse er sammensætninger af netværksbaserede autonome IT (cyber) og fysiske (physical) agenter, såsom sensorer, aktuatorer, beregningsenheder, og mennesker. I dag er CPSer stadig forholdsvis små og meget begrænsede i forhold til de CPSer vi kan forvente i fremtiden. Fremtidige CPSer forventes at være langt mere komplekse, storstilede, udbredte, og missionskritiske, og vil kunne findes i en række områder såsom transport, medicin, produktion og energi, hvor de vil give mange fordele, såsom øget effektivitet, bæredygtighed, pålidelighed og sikkerhed. For at frigøre CPSernes fulde potentiale, skal de bl.a. udstyres med støtte til automatiseret planlægning og kontrol, hvor beregningsagenter i samspil og løbende planlægger og styrer deres handlinger på en intelligent og velkoordineret måde for at sikre og optimere en fysisk proces, såsom elforsyningen i elnettet. I nuværende CPSer er styringen typisk automatiseret, mens planlægningen udelukkende er foretaget af mennesker. Det er umuligt for mennesker at planlægge hver handling i et fremtidigt CPS på grund af kompleksiteten, skalaen, og omskifteligheden af en fysisk proces. På grund af disse egenskaber, skal kontrol og planlægning være kontinuerlig og automatiseret i fremtidens CPSer. Mennesker kan kun analysere og justere systemets drift ved hjælp af det sæt af værktøjer, der understøtter præskriptive analyser (prescriptive analytics), der giver dem mulighed for (1) at lave forudsigelser, (2) at få forslagene fra de mest fremtrædende sæt handlinger (beslutninger), der skal tages, og (3) at analysere konsekvenserne, hvis sådanne handlinger blev udført. Denne afhandling omhandler planlægning og kontrol i forbindelse med store multi-agent CPSer. Baseret på en smart-grid use case, præsenterer afhandlingen det såkaldte PrescriptiveCPS hvilket er (den konceptuelle model af) et multi-agent, multi-rolle, og multi-level CPS, der automatisk og kontinuerligt tager beslutninger i nær-realtid og leverer (menneskelige) brugere præskriptiveanalyseværktøjer til at analysere og håndtere det underliggende fysiske system (eller proces). I erkendelse af kompleksiteten af CPSer, giver denne afhandling bidrag til følgende tre niveauer: (1) niveauet for et (fuldt) PrescriptiveCPS, (2) niveauet for en enkelt PrescriptiveCPS agent, og (3) niveauet for en komponent af et CPS agent software system. På CPS-niveau, omfatter bidragene definitionen af PrescriptiveCPS, i henhold til hvilken det er det system med interagerende fysiske- og IT- (under-) systemer. Her består IT-systemet af hierarkisk organiserede forbundne agenter der sammen styrer instanser af såkaldte fleksibilitet (flexibility), beslutning (decision) og præskriptive (prescription) modeller, som henholdsvis er kortvarige, fokuserer på fremtiden, og repræsenterer en kapacitet, en (brugers) intention, og måder til at ændre adfærd (tilstand) af et fysisk system. På agentniveau omfatter bidragene en tre-lags arkitektur af et agent software system, der integrerer antallet af komponenter, der er specielt konstrueret eller udbygges til at understøtte funktionaliteten af PrescriptiveCPS. Komponentniveauet er hvor afhandlingen har sit hovedbidrag. Bidragene omfatter beskrivelse, design og eksperimentel evaluering af (1) et samlet multi- dimensionelt skema til at opbevare fleksibilitet og præskriptive modeller (og data), (2) teknikker til trinvis aggregering af fleksibilitet modelinstanser og disaggregering af præskriptive modelinstanser (3) et database management system (DBMS) med indbygget optimeringsproblemløsning (optimization problem solving) der gør det muligt at formulere optimeringsproblemer ved hjælp af SQL-lignende forespørgsler og at løse dem "inde i en database", (4) en realtids data management arkitektur til at behandle instanser af fleksibilitet og præskriptive modeller under (bløde eller hårde) tidsbegrænsninger, og (5) en grafisk brugergrænseflade (GUI) til visuelt at analysere fleksibilitet og præskriptive modelinstanser. Derudover diskuterer og eksemplificerer afhandlingen (men giver ingen evalueringer af) (1) domæne-specifikke og in-DBMS generiske prognosemetoder der gør det muligt at forudsige instanser af fleksibilitet modeller baseret på historiske data, og (2) kraftfulde måder at analysere tidligere-, nutids- og fremtidsbaserede såkaldte hypotetiske hvad-hvis scenarier og fleksibilitet og præskriptive modelinstanser gemt i en database. De fleste af bidragene på dette niveau er baseret på et smart-grid brugsscenarie. Sammenfattende giver afhandlingen (1) modellen for et CPS med planlægningsmulighed, (2) design og eksperimentel evaluering af præskriptive analyse teknikker der gør det muligt effektivt at forudsige, aggregere, disaggregere, visualisere og analysere komplekse modeller af den fysiske verden, og (3) brugsscenariet fra energiområdet, der viser, hvordan de indførte begreber kan anvendes i den virkelige verden. Vi mener, at dette bidrag udgør et betydeligt skridt i retning af at udvikle CPSer til planlægningsbrug i fremtiden

Augmented Active-Bending Formwork for Concrete, A Manufacturing Technique for Accessible Local Construction of Structural Systems

This research introduces Augmented Reality (AR) for manufacturing concrete structures through an open platform for autonomous construction. The study was developed under the following scopes: computational algorithms for bending simulations, materiality tests, system implementation, and a set of Augmented Reality (AR) tools. AR devices offer a technological tool that allows for a self-built environment through holographic guidance, allowing the untrained workforce to participate in the process. This technology can help users select the system to construct through an Open-Source platform, reducing the gap between complex computational geometries and construction processes. The research aims to investigate a building system that could benefit the UN Objectives SDG 10 by increasing the access to technology in undeveloped communities, SDG 11 and SDG 12 by promoting a self-sustainable method of construction based on local resources and material efficiency. In conjunction with the development of the AR Platform and augmented manufacturing, a 1:1 prototype was built in Quito, Ecuador, with the help of seven people with no previous knowledge of digital tools or construction. Presenting a novel, fast, and affordable concrete formwork connected with AR assisted assembly methods that facilitate access to more efficient and advanced building technology

A Conceptual Framework to Support Digital Transformation in Manufacturing Using an Integrated Business Process Management Approach

Digital transformation is no longer a future trend, as it has become a necessity for businesses to grow and remain competitive in the market. The fourth industrial revolution, called Industry 4.0, is at the heart of this transformation, and is supporting organizations in achieving benefits that were unthinkable a few years ago. The impact of Industry 4.0 enabling technologies in the manufacturing sector is undeniable, and their correct use offers benefits such as improved productivity and asset performance, reduced inefficiencies, lower production and maintenance costs, while enhancing system agility and flexibility. However, organizations have found the move towards digital transformation extremely challenging for several reasons, including a lack of standardized implementation protocols, emphasis on the introduction of new technologies without assessing their role within the business, the compartmentalization of digital initiatives from the rest of the business, and the large-scale implementation of digitalization without a realistic view of return on investment. To instill confidence and reduce the anxiety surrounding Industry 4.0 implementation in the manufacturing sector, this paper presents a conceptual framework based on business process management (BPM). The framework is informed by a content-centric literature review of Industry 4.0 technologies, its design principles, and BPM method. This integrated framework incorporates the factors that are often overlooked during digital transformation and presents a structured methodology that can be employed by manufacturing organizations to facilitate their transition towards Industry 4.0

Massive-Scale Automation in Cyber-Physical Systems: Vision & Challenges

The next era of computing is the evolution of the Internet of Things (IoT) and Smart Cities with development of the Internet of Simulation (IoS). The existing technologies of Cloud, Edge, and Fog computing as well as HPC being applied to the domains of Big Data and deep learning are not adequate to handle the scale and complexity of the systems required to facilitate a fully integrated and automated smart city. This integration of existing systems will create an explosion of data streams at a scale not yet experienced. The additional data can be combined with simulations as services (SIMaaS) to provide a shared model of reality across all integrated systems, things, devices, and individuals within the city. There are also numerous challenges in managing the security and safety of the integrated systems. This paper presents an overview of the existing state-of-the-art in automating, augmenting, and integrating systems across the domains of smart cities, autonomous vehicles, energy efficiency, smart manufacturing in Industry 4.0, and healthcare. Additionally the key challenges relating to Big Data, a model of reality, augmentation of systems, computation, and security are examined

Advances in Production Management Systems: Issues, Trends, and Vision Towards 2030

Since its inception in 1978, the IFIP Working Group (WG) 5.7 on Advances in Production Management Systems (APMS) has played an active role in the fields of production and production management. The Working Group has focused on the conception, development, strategies, frameworks, architectures, processes, methods, and tools needed for the advancement of both fields. The associated standards created by the IFIP WG5.7 have always been impacted by the latest developments of scientific rigour, academic research, and industrial practices. The most recent of those developments involves the Fourth Industrial Revolution, which is having remarkable (r)evolutionary and disruptive changes in both the fields and the standards. These changes are triggered by the fusion of advanced operational and informational technologies, innovative operating and business models, as well as social and environmental pressures for more sustainable production systems. This chapter reviews past, current, and future issues and trends to establish a coherent vision and research agenda for the IFIP WG5.7 and its international community. The chapter covers a wide range of production aspects and resources required to design, engineer, and manage the next generation of sustainable and smart production systems.acceptedVersio

Manufacturing Value Modelling, Flexibility, and Sustainability: from theoretical definition to empirical validation

The aim of this PhD thesis is to investigate the relevance of flexibility and sustainability within the smart manufacturing environment and understand if they could be adopted as emerging competitive dimensions and help firms to take decisions and delivering value