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Industry 4.0 (I4.0) brings a set of challenges that need to be settled to enable the expected industrial revolution. Cyber-Physical Systems (CPS) and Autonomous Robots are two of mainstream I4.0 technologies and can be combined with other Enabling Technologies to overcome main I4.0 challenges. This Systematic Literature Review (SLR) aimed to understand how these Enabling Technologies were combined with CPS and Autonomous Robots to achieve fully featured I4.0 solutions. The 5C is a CPS architecture which was used as a measurement to CPS compliance. After filtering and processing 15,144 papers from six different academic search engines, it was found that full 5C compliant solutions are rare to find; that not all enabling technologies were integrated; and most of existing research focused in implementing practical solutions, but comparison to conventional approaches is scarce. We conclude that there is a need for further research to accomplish full 5C I4.0. [ABSTRACT FROM AUTHOR]

Under a mass individualisation paradigm, the individualised design of manufacturing systems is difficult as it involves adaptive integrating both new and legacy machines for the formation of part families with uncertainty. A systematic virtual model mirroring the real world of manufacturing system is essential to bridge the gap between its design and operation. This paper presents a digital twin-driven methodology for rapid individualised designing of the automated flow-shop manufacturing system. The digital twin merges physics-based system modelling and distributed semi-physical simulation to provide engineering solution analysis capabilities and generates an authoritative digital design of the system at pre-production phase. An effective feedbacking of collected decision-support information from the intelligent multi-objective optimisation of the dynamic execution is presented to boost the applicability of the digital twin vision in the designing of AFMS. Finally, a bi-level iterative coordination mechanism is proposed to achieve optimal design performance for required functions of AFMS. A case study is conducted to prove the feasibility and effectiveness of the proposed methodology. [ABSTRACT FROM AUTHOR]

While Industry 4.0 research has predominantly focussed on the connection of machines and digital systems and solutions, it is important to consider the role of human workers within the envisaged Industry 4.0 environments. This paper presents the concept of a digital administration shell to support the integration of humans in Industry 4.0 environments and an architecture for the development of such an administration shell. The Biography-Attributes-Schedule-Execution (BASE) architecture builds on holonic systems principles and is guided by the requirements and responsibilities of the Resource Holon, as developed in the Holonic Manufacturing Systems paradigm. The functionality and value of the BASE architecture administration shell is demonstrated by means of a case study implementation. [ABSTRACT FROM AUTHOR]

This paper investigates the secure optimal tracking control problem for cyber-physical systems, in which the controller-actuator channel is jammed by denial-of-service attacks. Without leveraging model knowledge, learning-based tracking control algorithms are proposed by utilizing the measured input-output data. The impact of malicious attacks on tracking performance is discussed. More specifically, an augmented system consisted of the system model and the reference model is derived. Then the states of the augmented system are rewritten by utilizing the input, output, and reference trajectory, following which both the Bellman equation and algebraic Riccati equation are given. The conditions of existence and uniqueness of the solution to the algebraic Riccati equation are derived. Furthermore, both policy iteration and value iteration learning-based tracking control algorithms are provided for cyber-physical systems against denial-of-service attacks, and the convergence of the algorithms is also proved. Finally, a DC motor system and a numerical example are given to illustrate the effectiveness of the proposed control algorithms. [ABSTRACT FROM AUTHOR]

Cyber-Physical Systems (CPSs) require the interfacing of two different time domains: (1) the physical time-continuous domain and (2) the computational time-discrete domain. The Nyquist-Shannon sampling theorem allows transitions from one domain to the other. To preserve the informational signal between both domains, strictly periodic sampling, also known as uniform spaced sampling, is required. CPSs utilise real-time systems to meet temporal constraints. However, real-time systems introduce jitter when several tasks are executed; consequently, the uniform spaced sampling is jeopardized. The Paley-Wiener-Levinson theorem should be used for non-uniform spaced sampling, but its complexity makes it unsuitable for runtime execution in CPSs. Jitter in real-time systems may cause perturbations in CPS applications. In this paper, frequency domain methodologies are proposed to analyse the perturbations introduced by real-time systems in physical applications. It is shown that jitter may introduce frequency components with the potential to jeopardize the dynamics of the physical application. In this paper, it is proposed that jitter should be related to the period of the fundamental frequency to sample, instead of to the period of the real-time task. The frequency domain methodology proposed should be used to analyse the real-time system behaviour from a CPS application point of view. [ABSTRACT FROM AUTHOR]

The Fourth Industrial Revolution, also known as Industry 4.0, stems from the rapid advancement of digital technologies such as the Internet of Things and Cyber-Physical Production Systems. It has the potential to weave positive changes to firms and impact organizational structure layers. Therefore, it provides an impetus for the collaboration of factories, suppliers, and customers. Nevertheless, due to the difference of Industry 4.0 vision among companies, there is a lack of unified perception and approach of its implementation roadmap. Therefore, many firms in both developed and developing countries that step in the way of digital transformation encounter not only organizational, technological, and operational challenges but are also compelled to cope with a large deal of confusion. Hence, this paper aims to identify the main concepts, characteristics, and technology enablers related to Industry 4.0 to provide stakeholders with a clear understanding of this paradigm. It then clusters and matches the derived concepts and characteristics associated with Industry 4.0. Further, the paper provides an analysis of how these clusters are supported by technology enablers of Industry 4.0, as well as managerial implications. [ABSTRACT FROM AUTHOR]

In this paper, we address the problem of developing a unified method for quantifying and improving the cyber resilience of large-scale cyber-physical systems (CPSs) against cyber-attacks targeting structural controllability. To this end, we provide necessary and sufficient conditions to extend the concept of structural controllability of single-layer systems to two-layer CPSs comprising of power network as the physical layer and communication network as the cyber layer. Next, in order to assess cyber resilience, we introduce the notion of $ R $ R -resilient CPS as the maximum number of cyber nodes that can be attacked by an adversary while preserving the structural controllability of the entire CPS. Furthermore, we provide an algorithm to find the optimal network reconfiguration matrix to increase the resilience level of CPS from $ R $ R -resilient to $ ({R + 1}) $ (R + 1) -resilient by adding a minimum number of transmission lines to the physical layer or communication links to the cyber layer, or both. Additionally, the proposed methodology is extended to achieve $ ({R + \alpha }) $ (R + α) -resilient CPS, where α>1. The effectiveness of the proposed method is verified through simulations of IEEE 14, IEEE 39, and IEEE 118 power networks with different cyber topologies, considering four scenarios of denial-of-service (DoS) attacks, including targeted and random node attacks. [ABSTRACT FROM AUTHOR]

This paper investigates the secure state estimation problem of the cyber-physical systems (CPSs) in the presence of malicious attacks. Considering the destructiveness and stealthiness of the attacker, a novel stochastic transmission scheme, in which the repeater generates transmission data by randomly combining some measurement values, is proposed to ensure the effectiveness of the attack detector. A filter equipped with the $ \chi ^2 $ χ 2 detector and the stochastic transmission scheme is proposed to conduct the secure state estimation. The attack probability condition of the estimation error being mean-square bounded is given, which indicates that stochastic transmission scheme has a limited effect on the filter. Some numerical simulations are given to illustrate the effectiveness of the proposed transmission scheme. [ABSTRACT FROM AUTHOR]

Regeneration processes of complex capital goods such as components of aircraft engines are highly complex and require a multi-disciplinary perspective, bringing together expertise from different fields such as production engineering, image-based measuring technology, turbomachinery, and operations management. Sustainability requirements and digitalisation opportunities both demand and suggest systematic, flexible, and economically efficient design and operation of the regeneration process chains. This multi-disciplinary case study documents the design and operation of a cyber-physical system demonstrator for individual, flexible and economically optimised maintenance, repair, and overhaul (MRO) actions on extremely valuable components of aircraft engines: high-pressure turbine blades. This system demonstrator hence brings together research results from different disciplines considered jointly in the German Collaborative Research Centre 871 'Product-Regeneration'. To cope with the substantial variability in used-good damage patterns and the resulting MRO actions, the system demonstrator operates with a virtual layer and uses a virtual twin of the object to be regenerated. In addition to a functional simulation, a central component of that virtual layer is a project-scheduling-based decision support system used to both select the MRO actions and control the shop floor. This paper hence describes how recent research results can be combined to achieve innovative, efficient, and sustainable regeneration processes. [ABSTRACT FROM AUTHOR]

Digital twinning presents an exciting opportunity enabling real-time optimization of the control and operations of cyber-physical systems (CPS) with data-driven simulations, while facing prohibitive computational burdens. This paper introduces a method, Sequential Allocation using Machine-learning Predictions as Light-weight Estimates (SAMPLE) to address this computational challenge by leveraging machine learning models trained off-line in a predictive simulation learning setting prior to a real-time decision. SAMPLE integrates machine learning predictions with data generated by real-time execution of a digital twin in a rigorous yet flexible way, and optimally guides the digital twin simulation to achieve the computational efficiency required for real-time decision-making in a CPS. Numerical experiments demonstrate the viability of SAMPLE to select optimal decisions in real-time for CPS control and operations, compared to those of using only machine learning or simulations. [ABSTRACT FROM AUTHOR]

The principles of self-organization and emerging systems are based on the philosophy of distributed systems, where a large number of elementary units execute a set of usually simple local rules and interact only with some of their neighboring units, so that a desired behavior globally appears. It has demonstrated its potential as a feasible alternative for the control of complex systems, which are characterized by their dynamism, unpredictability, imprecision, uncertainty, without fixed limits, incomplete information, and also, with high levels of complexity and heterogeneity, among other things. In this sense, this paper explores the studies carried out around the emergent control systems, to deepen their conceptual bases, principles, architecture and methodologies. Also, the paper studies their role in the context of Cyber-Physical Systems, analyzing its applications and contributions to the Industry 4.0. In this way, this paper carries out a systematic review of the literature, in order to determine the trends in this domain, and the challenges and future directions. [ABSTRACT FROM AUTHOR]

Manufacturing has evolved and become more automated, computerised and complex. In this paper, the origin, current status and the future developments in manufacturing are disused. Smart manufacturing is an emerging form of production integrating manufacturing assets of today and tomorrow with sensors, computing platforms, communication technology, control, simulation, data intensive modelling and predictive engineering. It utilises the concepts of cyber-physical systems spearheaded by the internet of things, cloud computing, service-oriented computing, artificial intelligence and data science. Once implemented, these concepts and technologies would make smart manufacturing the hallmark of the next industrial revolution. The essence of smart manufacturing is captured in six pillars, manufacturing technology and processes, materials, data, predictive engineering, sustainability and resource sharing and networking. Material handling and supply chains have been an integral part of manufacturing. The anticipated developments in material handling and transportation and their integration with manufacturing driven by sustainability, shared services and service quality and are outlined. The future trends in smart manufacturing are captured in ten conjectures ranging from manufacturing digitisation and material-product-process phenomenon to enterprise dichotomy and standardisation. [ABSTRACT FROM AUTHOR]

Cyber-Physical Systems (CPS) is a new generation of digital technology that is concerned with the integration and inter-dependencies of the cyber and physical world alongside computational elements. As a new and leading technology, its applications are seen in different projects involving energy and this has however generated lots of interest from the industry, researchers in academia and the government. This paper presents an extensive overview and modernistic research on the applications relating to energy CPS and the security issues and challenges revolving around this research path. In order to achieve this, a systematic literature review was carried out which enabled the analysing and classifying of different applications and security issues described in selected publications. Furthermore, the systematic review permitted the discourse stringing these research areas as well as providing future lines of research. Also, results from the review show the paths where there are increasing research focus and expected research trend in the future years to come. These results will not only be useful in serving as a guide to researchers but will also create new research paths to more experienced researchers to actively follow. [ABSTRACT FROM AUTHOR]

In this paper, a Lyapunov-based design method for event-triggered control with self-triggered sampling is proposed. In the proposed method, update of the control input and sampling of the state are individually determined based on two kinds of upper bounds of the Lyapunov function. By the proposed method, a non-monotonic Lyapunov function can be constructed. By non-monotonic decrease of a Lyapunov function, the number of communications can be reduced. In the neighborhood of the origin, we consider a control method such that the state stays in a certain set. As a result, it is guaranteed that the closed-loop system is uniformly ultimately bounded. Through a numerical example, we demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, the distributed mixed H 2 / H ∞ fusion filter design problem is investigated for a class of cyber-physical systems subject to non-ideal measurements under Round-Robin protocol. To save the limited communication resources, the Round-Robin protocol is employed to schedule the data transmissions from the sensors to the remote filters. The measurement is imperfect by taking into account the noises, the random saturations, nonlinearity perturbations and packet dropouts. The objective of this study is to propose a desired fusion filtering method that ensures the prescribed performance constraints on both the local and fusion filtering error dynamics. With the aid of Lyapunov function and stochastic analysis technique, a sufficient condition is established to guarantee the mixed H 2 / H ∞ performance index for the local filtering error systems, and then the filter parameter matrices are derived by resorting to the solutions to some matrix inequalities. Subsequently, on the basis of the obtained local state estimates, the proper fusion parameters are acquired by solving a convex optimisation problem. Finally, a numerical example is provided to demonstrate the effectiveness of the designed fusion filter. [ABSTRACT FROM AUTHOR]

Nowadays, the emphasis on manufacturing has shifted from a manufacturer-dominating to a customer-centric manner by actively involving users into the co-creation process to realise individual satisfaction. In such era, the rapid development of information and communication technology (e.g. wireless sensor network, and cyber-physical systems) enables a promising market of IT-driven product, i.e. smart, connected product, and also changes the way of user–manufacturer interaction in the product development process. However, to the best of authors' knowledge, co-creation manner in such context is scarcely reported. Meanwhile, there is a lack of any paradigms given to enable such product open innovation along the lifecycle for personalisation concerns. Aiming to fill this gap, this paper, as an explorative research, proposes a new product development paradigm, i.e. smart, connected open architecture product (SCOAP). It follows the adaptable design principles for product extendibility and lifecycle consideration. Moreover, it enlarges the scope of existing open architecture product by involving IT-driven innovation consideration as well. Hence, the definitions, characteristics, evaluation criteria, development method, and lifecycle co-creation context of SCOAP are presented in details. To make it more concrete, a demo project of a smart, connected open architecture bicycle is given at last. [ABSTRACT FROM AUTHOR]

Agility is a key characteristic in disaster relief operations. Intelligent process-aware information systems (IPAISs) can support agility in disaster relief operations through providing information and process reach and richness to manage dynamic inter-operations. In this research, based on relevant reference architectures, a conceptual overview of an IPAIS to support agility in disaster relief operations is described. This conceptual overview includes the dynamic partnering, the collaborative process composition, the collaborative ontology management, the global workflow engine, the run-time coordination, the dynamic rule management, the run-time process proposer, and the dynamic interoperability adaptor components. Based on this conceptual overview, a systematic literature review is conducted to explore emerging approaches that can be applied to realise intelligent process-centred collaborative inter-operations to respond disasters. The findings of the conducted review show the applicability of the emerging multi-agent service-oriented modelling and analysis approaches, optimal control theory based methodologies, social network analysis techniques, data-driven inductive methods, resilient-centred approaches for robustness and agility, self-organisation mechanisms based on cyber physical systems and systems of systems perspectives, simulation methods, and trust management procedures to support the realisation of the components of an IPAIS in the context of disaster relief operations. [ABSTRACT FROM AUTHOR]

Wireless sensor networks, which play a significant role in monitoring complex environments that change rapidly over time, were used in the Artificial Intelligence method. External factors or the device designers themselves are both responsible for this complex behavior. Sensor networks often use machine learning techniques to adapt to such conditions, eliminating the need for excessive redesign. Cyber-physical systems (CPS) appeared as the promising option for improving physical-virtual interactions. The quality of the system containing processing information is primarily determined by the system function. There are many benefits obtained while combining Artificial Intelligence (AI) and Cyber-Physical Systems (CPSs) in buildings. In CPS-based indoor environment has various design schemes containing measurement and intelligent buildings in the control system consisting of detection, tracking, execution, and communication modules. The Multi-Agent System (MAS) is the smallest control unit that simulates among neurons and it flexibly provides the information. To mimic the interactions between human neurons, multi-agents are used. In this paper, the CPS's information world is built on the fundamental principle of granular formal concepts and the theory of granular computing is investigated. The calculation module is used by Back-Propagation Neural Network (BPNN) for pattern recognition and classification by environmental information. Various parameters namely the normalized root mean square error, peak signal-to-noise ratio, mean square error, and the mean absolute error are chosen as the objective assessment criteria to assess the benefits of the proposed method and the effectiveness of the proposed system is proven. [ABSTRACT FROM AUTHOR]

Safety-critical cyber-physical systems (SC-CPS) have the characteristics of distributed, heterogeneous, strong coupling of computing resources and physical resources. With the increased acceptance of Model-Driven Development (MDD) in the safety-critical domain, the SysML language has been broadly used. Increasing complexity results in the formal verification of the SysML models of SC-CPS often faces the so-called state-explosion problem. Moreover, safety analysis is also an important step to ensure the quality of SC-CPS. Thus, this article proposes an integrated SysML modelling and verification approach to cover specification of nominal behaviour and safety. First, an extension of SysML is presented, in which the contract information (i.e. Assume and Guarantee) is extended for SysML block diagrams and a Safety Profile is proposed to describe safety-related concepts. Second, the transformation from SysML to the compositional verification tool OCRA is given. Third, the safety analysis is achieved by translating the Safety Profile model into FTA (Fault Tree Analysis). Finally, the prototype tools including SysML2OCRA and SafetyProfile2FTA are represented, and the effectiveness of the method proposed in this paper is verified through actual industrial cases. [ABSTRACT FROM AUTHOR]

This paper is concerned with the secure H ∞ control problem for cyber-physical systems (CPSs) under time-delay attacks, which cause the systems' information to be received with delays. Through transforming the H ∞ control problem to a two-player zero-sum game problem, the H ∞ controller can be obtained by solving the saddle point for the game. Due to the unknown system parameters, a model-free reinforcement learning (RL) method is applied, and the measurement feedback controller is designed based on the historical inputs and the tracking errors. To obviate the requirement of the initial admissible policy, the value iteration (VI) of the adaptive dynamic program (ADP) algorithm is proposed to solve the approximate saddle point. Moreover, the convergence of the proposed algorithm is proved. Finally, a networked circuit system is employed to show the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

In this paper, the important issue is proposed, that is, the robust control of a class of cyber-physical systems (CPSs) in the complex environment where unknown disturbances, unknown bounded delays and stochastic malicious attacks coexist. A Lyapunov–Krasovskii functional (LKF) containing certain double and triple integral terms is constructed to exploit merits of the presented generalised single and double integral inequalities which are tighter than some existing single and double inequalities, leading to the stability analysis result with less conservatism. Furthermore, by using stochastic analysis technique, the stability analysis and H ∞ output feedback controller design are transformed into the convex optimisation problems solved by the linear matrix inequality (LMI) strategy. Finally, the actual load frequency control (LFC) power system and the classical numerical examples are provided to show the rationality for modelling and the advancement of the developed method. [ABSTRACT FROM AUTHOR]

The worldwide manufacturing industry is facing a wide range of changes. Examples include the diversification of customer demands, increases in labor costs and energy resource costs, environmental pollution, and growth uncertainty. Based on the experience of advanced countries and global manufacturers, smart manufacturing systems (SMS) have the potential to address these. SMS can connect raw materials, production systems, logistic companies, and maintenance schedules using the capabilities of industrial, internet of things (IoT). These connections are creating cyber-physical production systems (CPPS) and linking functions across the entire product lifecycle. These connections are possible today because of the advances in digital manufacturing (DM) technologies that can facilitate factory design, redesign, and analysis in CPPS and help to continuously and efficiently manage factory performance optimization. However, implementing DM today, especially in SMEs, is difficult because the required interface standards and data schema do not exist – unlike other technologies and system such as CAD, PLM, MES, and SCM. This paper describes an approach to design and develop such a data schema based on a reference activity model developed by NIST. The paper then develops a cloud-based DM system based on the data schema. Lastly, its application cases are described, and application effects are discussed. [ABSTRACT FROM AUTHOR]

Industry 4.0 is one of the trending topics among the academicians and practitioners around the world. The pros and cons of Industry 4.0 are significantly important because it will help the organizations to make a sensible decision regarding its implementation. Though there are many studies on Industry 4.0, there is a dearth of academic literature which collates and analyses the Pros and Cons of Industry 4.0. The purpose of this paper is to investigate what are the pros and cons of implementation of Industry 4.0 in organizations from academic perspective. A comprehensive and systematic literature review is conducted on the earlier studies on Industry 4.0. Descriptive, categorical, keyword and thematic analysis are conducted on the final sample of sixty-four articles. This study finds nine pros and seven cons while implementing Industry 4.0 in organizations and also the future research directions is explicated. [ABSTRACT FROM AUTHOR]

Rapid advances in industrialisation and informatisation methods have spurred tremendous progress in developing the next generation of manufacturing technology. Today, we are on the cusp of the Fourth Industrial Revolution. In 2013, amongst one of 10 ‘Future Projects’ identified by the German government as part of its High-Tech Strategy 2020 Action Plan, the Industry 4.0 project is considered to be a major endeavour for Germany to establish itself as a leader of integrated industry. In 2014, China’s State Council unveiled their ten-year national plan, Made-in-China 2025, which was designed to transform China from the world’s workshop into a world manufacturing power. Made-in-China 2025 is an initiative to comprehensively upgrade China’s industry including the manufacturing sector. In Industry 4.0 and Made-in-China 2025, many applications require a combination of recently emerging new technologies, which is giving rise to the emergence of Industry 4.0. Such technologies originate from different disciplines including cyber-physical Systems, IoT, cloud computing, Industrial Integration, Enterprise Architecture, SOA, Business Process Management, Industrial Information Integration and others. At this present moment, the lack of powerful tools still poses a major obstacle for exploiting the full potential of Industry 4.0. In particular, formal methods and systems methods are crucial for realising Industry 4.0, which poses unique challenges. In this paper, we briefly survey the state of the art in the area of Industry 4.0 as it relates to industries. [ABSTRACT FROM AUTHOR]

Traditionally, the resources of embedded devices which are employed for process control at shop floors were resource constrained. However, advances in embedded system technologies permit the enhancement of the processing and storage capabilities of embedded devices. Therefore, semantic descriptions of manufacturing systems can now be hosted and computed at the device level. This fact permits the creation of a decentralised solution for controlling processes at the lowest level of the manufacturing enterprises and the reduction in the time and effort requirements for the configuration and information exchange. The eScop project presented the Open Knowledge-Driven Manufacturing Execution System (OKD-MES) solution, which enables monitoring and controlling production systems openly and allows runtime re-configurability of interconnected industrial equipment and services. This research work presents how part of the OKD-MES functionality can be handled at lower level. More precisely, the OKD-MES representation and management of knowledge can be decentralised and handled at the shop floor level, where the industrial machines are connected to devices that are capable of controlling the execution of processes. The main objective of this paper is to describe a decentralised vision for the OKD-MES framework, which is a centric solution in terms of knowledge management. Moreover, the article also discusses some of the advantages to be gained from decentralising the management of knowledge model semantic descriptions. [ABSTRACT FROM AUTHOR]

Cyber-Physical Systems (CPSs) use sensors and actuators to interface between an embedded system and the physical world. The time-continuous domain of the physical world should be periodically sampled by real-time tasks in an embedded system to preserve its dynamic properties in the time-discrete domain. Because the task execution pattern may vary during runtime, a jitter in the execution of a real-time task hinders the periodicity of its execution. The effects of jitters in CPSs are difficult to determine when the premises of the Nyquist-Shannon sampling theorem are not satisfied. This paper proposes using frequency domain analysis to determine the perturbations that a real-time system produces on real-world applications; accordingly, the paper defines both a design and an evaluation criterion for real-time systems in CPS applications. The Fixed Priority discipline is analysed through simulations to conclude that no special design techniques are required when the utilization factors are less than 20%. [ABSTRACT FROM AUTHOR]

This paper aims to review the state-of-the-art in Cyber-Physical Systems (CPS) as a key element to Industry 4.0 and to provide engineering managers with adequate and sufficient knowledge about CPS, highlighting their characteristics, technologies, capabilities, and applications. A three-stage research method was applied to provide an extensive search and systematic literature review (SLR). We identified, selected, and reviewed 218 publications. The convergences in specific areas in which studies are still needed were detailed. We identified 5 characteristics, 7 capabilities, 17 related technologies, and 11 areas of application. Four application areas remain as an opportunity to be explored in future research, such as environmental sustainability; smart and precision agriculture; smart construction, and social sciences. This article is the first to present a wide-ranging review of CPS and bringing together a significant number of publications. Its originality is focused on detailing and analyzing CPS characteristics, technologies, and multidisciplinary applications allowing engineering professionals and managers to identify which technologies a manufacturing equipment should integrate, as well as the level of development of each of them to achieve its full operation in Industry 4.0 environment. The main limitation of this work is the fact that new features, applications, and technologies will certainly appear soon. [ABSTRACT FROM AUTHOR]

Cyber-Physical Systems (CPSs), with the intrinsical vulnerability of the cyber layer, are always suffering from malicious data injection (DI) attacks. In this paper, switched counteraction principle based defense strategies are designed for secure state estimation (SSE) of CPSs under sparse DI attacks. Firstly, the physical layer is modelled by a hybrid mechanism, based on which malicious injections are excluded by implementing adaptively switched counteraction searching. Sufficient conditions are established to ensure the feasibility of SSE design. Next, by set cover approach, a defence strategy is presented to further relax the computation burden caused by combinational brute force search. Two numerical examples are given to illustrate the effectiveness and potential of the proposed design methods. [ABSTRACT FROM AUTHOR]

This paper considers Enterprise Information Systems functional architecture and carries out review of AI applications integrated in Customer Relationship Management, Supply Chain Management, Inventory and logistics, Production Planning and Scheduling, Finance and accounting, Product Lifecycle Management and Human Resources, with special attention to the manufacturing enterprises. Enhanced capabilities are identified and proposed as AI services. AI-enablement implements improved decision-making or automation by using Machine Learning models or logic-based systems. It is a process of the enterprise transformation leading to the convergence of the four major disruptive technologies, namely Industrial Internet of Things, Agent-based Distributed Systems, Cloud Computing and Artificial Intelligence. [ABSTRACT FROM AUTHOR]

This paper reviews some of the most recently reported research into challenges and leading innovations in intelligent manufacturing for the Factories of the Future (FoF). Such research can be categorised as addressing five broad topic areas: manufacturing systems frameworks, theories and models; the pervasiveness of Cyber-Physical Systems (CPSs); the critical role of semantic technologies and interoperability; the Virtual Organisation (VO) of manufacturing systems and the servitisation of manufacturing systems. The paper analyses conceptual, theoretical, empirical and technological contributions from several leading authors in domain area. This paper identifies a wide range of research topics from the elaboration of manufacturing systems frameworks to models, from sensors to CPSs, to the application of semantic technologies and interoperability architectures of the data and information generated by manufacturing agents, how VOs are shaping manufacturing environments and the increasing challenge of deploying manufacturing systems to support servitisation. The paper concludes elaborating final considerations on the challenges and leading innovations in intelligent manufacturing for the FoF research area. [ABSTRACT FROM PUBLISHER]

Methods and principles of Lean Production have become the major concepts to create highly efficient processes since the early 1990s. Due to its high effectiveness by reducing complexity and focusing on value-adding tasks, the Lean concept is still successful. Nevertheless, its changeability to produce highly customised products is limited. Industry 4.0 describes the vision of a smart production which can meet these future market requirements. Enablers are innovative information and communication technologies and the integration of all production entities into a common digital network. Lean Automation is the application of Industry 4.0 technologies to Lean Production methods in order to combine benefits from both domains. First proprietary Lean Automation solutions exist, but to enhance changeability in production, a common, unified communication interface is required. This paper presents the ongoing work towards an interface for digitising Lean Production methods using Cyber Physical Systems. [ABSTRACT FROM AUTHOR]

Lean Management (LM) is one of the most widely used business strategies for the last three decades. Industry 4.0 shows all the promise of the fourth industrial revolution using automation technologies like cyber-physical systems, internet of things and cloud computing. The purpose of this paper is to propose an integration model of Industry 4.0 and LM. A summary literature review of Industry 4.0 and LM is carried out to construct a theoretical model of integration. The previous literature is used to develop and propose an integration model of Industry 4.0 and LM. The horizontal, vertical and end-to-end engineering integration model are integrated with LM methodology. Testable research propositions are proposed between Industry 4.0 and LM. The model proposed is novel and it raises the important issue of integration of LM with Industry 4.0. This is the first paper which proposes the integration framework of LM with Industry 4.0. [ABSTRACT FROM AUTHOR]

Current mass individualisation and service-oriented paradigm calls for high flexibility and agility in the warehouse system to adapt changes in products. This paper proposes a novel digital twin-driven joint optimisation approach for warehousing in large-scale automated high-rise warehouse product-service system. A Digital Twin System is developed to aggregate real-time data from physical warehouse product-service system and then to map it to the cyber model. A joint optimisation model on how to timely optimise stacked packing and storage assignment of warehouse product-service system is integrated to the Digital Twin System. Through perceiving online data from the physical warehouse product-service system, periodical optimal decisions can be obtained via the joint optimisation model and then fed back to the semi-physical simulation engine in the Digital Twin System for verifying the implementation result. A demonstrative prototype is developed and verified with a case study of a tobacco warehouse product-service system. The proposed approach can maximise the utilisation and efficiency of the large-scale automated high-rise warehouse product-service system. [ABSTRACT FROM AUTHOR]

This paper is concerned with the distributed secure estimation problem for a cyber-physical system (CPS) with fading measurements and false data injection (FDI) attacks, where the fading probability of measurements is assumed to be individual for each sensor, and the FDI attacks occur at the physical system layer to intensively modify the system's state. For improving security of the system, an attack detection mechanism is proposed based on an FDI attack observer constructed by minimising the upper bound of observation error covariance. Then a complete distributed state estimation algorithm is given to provide locally reliable estimation. A sufficient condition is provided to guarantee boundedness of the estimation error covariance. Finally, the effectiveness of the proposed method is illustrated by numerical simulation and practical example simulation. [ABSTRACT FROM AUTHOR]

Smart technologies with higher degrees of autonomy will be essential to achieve the next breakthrough in both agility and productivity in future manufacturing systems, often referred to as Industry 4.0. However, the technologies will also bring substantial design and integration challenges and novelty risks to manufacturing businesses. The aim of this paper is to analyse the current landscape and to identify the challenges for introducing smart technologies into manufacturing systems in Europe. Expert knowledge from both industrial and academic practitioners in the field was extracted using an online survey. A workshop was used to triangulate and extend the survey results. The findings indicate three main challenges for the ubiquitous implementation of smart technologies in manufacturing are: i) the perceived risk of novel technologies, ii) the complexity of integration, and iii) the consideration of human factors. Recommendations are made based on these findings to transform the landscape for smart manufacturing. [ABSTRACT FROM AUTHOR]

Emerging industrial platforms such as the Internet of Things (IoT), Industrial Internet (II) in the US and Industrie 4.0 in Europe have tremendously accelerated the development of new generations of Cyber-Physical Systems (CPS) that integrate humans and human organizations (H-CPS) with physical and computation processes and extend to societal-scale systems such as traffic networks, electric grids, or networks of autonomous systems where control is dynamically shifted between humans and machines. Although such societal-scale CPS can potentially affect many aspect of our lives, significant societal strains have emerged about the new technology trends and their impact on how we live. Emerging tensions extend to regulations, certification, insurance, and other societal constructs that are necessary for the widespread adoption of new technologies. If these systems evolve independently in different parts of the world, they will 'hard-wire' the social context in which they are created, making interoperation hard or impossible, decreasing reusability, and narrowing markets for products and services. While impacts of new technology trends on social policies have received attention, the other side of the coin – to make systems adaptable to social policies – is nearly absent from engineering and computer science design practice. This paper focuses on technologies that can be adapted to varying public policies and presents (1) hard problems and technical challenges and (2) some recent research approaches and opportunities. The central goal of this paper is to discuss the challenges and opportunities for constructing H-CPS that can be parameterized by social context. The focus in on three major application domains: connected vehicles, transactive energy systems, and unmanned aerial vehicles. Abbreviations: CPS: Cyber-physical systems; H-CPS: Human-cyber-physical systems; CV: Connected vehicle; II: Industrial Internet; IoT: Internet of Things [ABSTRACT FROM AUTHOR]

The emergence and continuing rise of cyber-physical systems (CPS) poses significant challenges and opportunities for production and logistics firms. In order to exploit the potential of CPS in the corporate context, it is essential to understand CPS applications from a holistic systems perspective. This service systems perspective creates an understanding of the processes, activities and the corresponding resources (participants, information, technologies). In order to expand the knowledge on the design of such service systems, this paper identifies CPS applications from industrial production and logistics and analyses their influence on processes, activities and resources. By combining related literature and interviews with specialists from both industries, the following four key challenges for the design of service systems were identified: (i) the challenge of 'information management', meaning the design and management of information flows and the related infrastructure; (ii) the collaboration management' between the internal and external actors involved in the service system; (iii) the capability exploitation' of CPS; and (iv) the 'management of the increasing complexity' of CPS-based service systems, which results from an extended resource base. [ABSTRACT FROM AUTHOR]

Nowadays, manufacturing firms need the reconfigurability capability to be responsive in the current context characterised by unpredictable and frequent market changes and the reduction of product life cycle. Despite the relevance of the subject, a challenge for practitioners is the development of a strategy aimed to increase the level of reconfigurability with long-term goals of customisation and responsiveness. Moreover, traditional manufacturing paradigms are disrupted by the transformation of manufacturing systems in cyber-physical systems (CPS), thus introducing innovative means also to increase the level of reconfigurability in manufacturing systems. This study investigates how the technologies underlying CPS support the reconfigurability capability along system life cycle. Thus the technologies underlying CPS are classified into seven categories and it is shown how they enable the sequence of utilisation of the reconfigurability characteristics (modularity, integrability, diagnosability, scalability, convertibility and customisation) along the system life cycle. The results of the study can guide practitioners in developing reconfigurability as a strategic capability. Moreover, different directions for future research can be considered, as discussed in the conclusion. [ABSTRACT FROM AUTHOR]

Increasing global competition on product quality and production costs, and the need for flexibility in production petition for transformed production processes which enable high level of connectivity and integration between business processes and systems. Much of the conventional computer- integrated efforts and advanced manufacturing technologies are limited in scope and restricted to only some organisational areas. Such limited scope, which stems from limited connectivity and integration between manufacturing and enterprise systems, confines the achievement of full potential of these systems within manufacturing. Industry 4.0, characterised by computing developments, can create a platform for addressing integration challenge through enabling comprehensive connectivity. Hence, this paper, through following deductive research paradigm and using systems theory as the theoretical base, aims to investigate recent academic research and industrial reports in the area of Industry 4.0 and smart manufacturing to provide detailed insights on execution of Industry 4.0, and to propose a theoretical framework for operationalisation of Industry 4.0 in manufacturing. [ABSTRACT FROM AUTHOR]

Security issues of cyber-physical systems have received increasing attentions in recent years. In this paper, deception attacks on the remote state estimator equipped with the chi-squared failure detector are considered, and it is assumed that the attacker can monitor and modify all the sensor data. A novel adaptive optimisation-offline cyber attack strategy is proposed, where using the current and previous sensor data, the attack can yield the largest estimation error covariance while ensuring to be undetected by the chisquared monitor. From the attacker's perspective, the attack is better than the existing linear deception attacks to degrade the systemperformance. Finally, some numerical examples are provided to demonstrate theoretical results. [ABSTRACT FROM AUTHOR]

Cradle to grave product support has been a key issue in the engineering sector over many years, particularly because product engineering legacy knowledge is often lost during the product development process unless rigorously captured in some way. This is particularly the case during formal design reviews at any point during a product's lifecycle where engineering changes are not fully documented or where salient but important aspects of decision making are difficult to document explicitly. Though many software systems are available to support design reviews, they have not necessarily met the expectations of industry. Consequently, traditional knowledge capture methods tend to be time-consuming, costly and disruptive leading to many companies simply giving up on this crucial aspect of product development. This paper presents research carried out with regard to prototyping and testing a potential knowledge engineering capture and reuse solution, demonstrating real-time user-logging using virtual design environments focused on team-based design ‘reviews’. Called the Virtual Aided Design Engineering Review (VADER) system, it provides millisecond precision time-phased knowledge capture in an automatic and unobtrusive manner. Both structured and unstructured data are synthesised via a ubiquitous integration and temporal synchronisation (UbiITS) framework that enables interactive information mapping, retrieval and mining. VADER's frontend includes a virtual reality based 3D model view display as a multiuser collaborative interface and an auxiliary web interface for concurrent access by multiple distributed users during product design discussions. Feedback from engineers using the system demonstrated that this concept is one which believe would substantially enhance their engineering task knowledge capture, rapid retrieval and reuse capability. It was also surmised that, if required, such a system can be extended throughout the whole product development process capturing individual and team-based engineers’ inputs across the whole cradle-to-grave product life cycle. Also, due to its generic nature, this approach is not limited only to engineering applications or virtual environments but can potentially be used in other sectors using computer-based technologies of any kind. [ABSTRACT FROM PUBLISHER]

To address the security of cyber-physical systems, stealthy attacks, a class of false data injection attacks that can impact a system without being detected, have been studied in the recent decade. The existing discussions on stealthy attack design have rarely considered systems with switching structures, but recent literature shows the importance of this problem. Therefore, we are motivated to investigate a stealthy man-in-the-middle attack strategy that can be applied to switched systems. Specifically, we first investigate how to design a stealthy attack without using mode information. Then, we consider whether the attacker can infer the mode information that can be used to design a stealthy attack. By combining mode identification and stealthy attack design, a stealthy man-in-the-middle attack strategy for switched systems is proposed. In addition, the feasibility and effectiveness of the strategy are discussed, and an illustrative numerical example is given to demonstrate the proposed strategy. [ABSTRACT FROM AUTHOR]

Recently, large scale cyber physical systems (LS-CPS) leverage network-cores provided by application providers (APs) to carry out analytics. These CPS-APs uses the automated cloud to gather traffic data streams, thereby reducing infrastructure and maintenance costs. However, network reliability and maintainability considering the arrival rate of user application requests presents a major challenge such as Edge-to-Fog and Fog-to-Cloud resource auto-scaling constraints. QoS dynamic reliability, as well as its flexible management, could offer an efficient network for CPS. In this paper, CloudMesh CPS architecture is presented as a promising solution to support services like Input-Output (IO) data stream, traffic engineering, service function optimization and software defined network monitoring in CPS IPv6 data-center core. Dynamic reliability modeling for QoS parameter scaling based on observable history is presented. Hence, QoS proactive auto-scaling algorithm (PASCQA) embedded with a heuristic predictor is introduced in CloudMesh CPS. IO streams are captured by the predictor which analyzes the QoS history for reliable global performance. Finally, the work realized the critical performance aspects of CPS architecture and analyzed the effects of QoS parameter configuration for real-time deployment. The implementation results show that CloudMesh offers satisfactory QoS metrics compared with Fat-tree-1 and Fat-tree-2 for CPS applications. [ABSTRACT FROM AUTHOR]

Plant stresses and diseases cause major losses to agricultural productivity and quality. Left unchecked, stresses and diseases can spread and propagate to nearby plants, causing even more damage, necessitating early detection. To address this challenge, the Agricultural Robotic System for Plant Stress Propagation Detection (ARS/PSPD) is developed. In this cyber-physical system, the robot agents are assigned scanning tasks to detect stresses in greenhouse plants. The problem of plant stress propagation detection is formulated with disruption propagation network modelling, which captures the plant stress occurrence and propagation mechanisms. The network modelling enables better situation awareness and augments the development of advanced collaborative scanning protocols. Five collaborative scanning protocols are designed and implemented in this research, with one protocol serving as a baseline, three protocols utilising disruption propagation network analysis, and one protocol utilising Bayesian network inference. The scanning protocols minimise errors and conflicts in scanning task allocation and enable better plant stress detection. The five ARS/PSPD collaborative scanning protocols are validated with numerical experiments, using agricultural greenhouses as experiment settings. The experiments show that the scanning protocol using Bayesian network inference outperforms all other protocols in all scenarios, with 16.92% fewer undetected plant stresses and 12.28% fewer redundant scans. [ABSTRACT FROM AUTHOR]

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Additive Manufacturing (AM) requires integrated networking, embedded controls and cloud computing technologies to increase their efficiency and resource utilisation. However, currently there is no readily applicable system that can be used for cloud-based AM. The objective of this research is to develop a framework for designing a cyber additive manufacturing system that integrates an expert system with Internet of Things (IoT). An Artificial Neural Network (ANN) based expert system was implemented to classify input part designs based on CAD data and user inputs. Three ANN algorithms were trained on a knowledge base to identify optimal AM processes for different part designs. A two-stage model was used to enhance the prediction accuracy above 90% by increasing the number of input factors and datasets. A cyber interface was developed to query AM machine availability and resource capability using a Node-RED IoT device simulator. The dynamic AM machine identification system developed using an application programme interface (API) that integrates inputs from the smart algorithm and IoT interface for real-time predictions. This research establishes a foundation for the development of a cyber additive design for manufacturing system which can dynamically allocate digital designs to different AM techniques over the cyber network. [ABSTRACT FROM AUTHOR]

Recent developments in domains of ambient intelligence (AmI), Internet of Things, cyber-physical systems (CPS), ubiquitous/pervasive computing, etc., have led to numerous attempts to apply ICT solutions in the occupational safety and health (OSH) area. A literature review reveals a wide range of examples of smart materials, smart personal protective equipment and other AmI applications that have been developed to improve workers’ safety and health. Because the use of these solutions modifies work methods, increases complexity of production processes and introduces high dynamism into thus created smart working environments (SWE), a new conceptual framework for dynamic OSH management in SWE is called for. A proposed framework is based on a new paradigm of OSH risk management consisting of real-time risk assessment and the capacity to monitor the risk level of each worker individually. A rationale for context-based reasoning in SWE and a respective model of the SWE-dedicated CPS are also proposed. [ABSTRACT FROM PUBLISHER]

The information and communication technology (ICT) field is rapidly advancing and has developed several disrupting technologies, including artificial intelligence, virtual reality, big data, cloud computing solutions, and the Internet of Things (IoT). This new automation is pervasive throughout production or manufacturing. It allows the integration of the next generation commuting system popularly called Cyber-Physical Systems (CPS) to join the physical and simulated worlds, marking the arrival of industry 4.0, commonly referred to as a fourth industrial revolution. The term "Industry 4.0" refers to a wide range of technologies applied in the manufacturing industry, encompassing everything from product design to Supply Chain Management (SCM). To contribute to the execution of research in industry 4.0, the current study investigates the specific application of fourth industrial revolution technologies in smart manufacturing systems. First, a theoretical outline of various applications of Industry 4.0 is presented for smart manufacturing systems. Second, CPS-enabled smart (design, control, monitoring, and machining) is introduced through distinct illustrative scenarios. Third, based on these illustrative scenarios, new advancements and their potential applicability through Industry 4.0 in manufacturing industries are discussed. Finally, various challenges and prospects are recognized for Industry 4.0 and explored to assist manufacturing sectors in achieving further growth. [ABSTRACT FROM AUTHOR]

Smart Manufacturing and Industry 4.0 production environments integrate the physical and decisional aspects of manufacturing processes into autonomous and decentralised systems. One of the main aspects in these systems is production planning, in particular scheduling operations on machines. We introduce here a new decision-making schema, Smart Scheduling, intended to yield flexible and efficient production schedules on the fly, taking advantage of the features of these new environments. The ability to face unforeseen and disruptive events is one of the main improvements in our proposed schema, which uses an efficient screening procedure (Tolerance Scheduling) to lessen the need of rescheduling in the face of those events. [ABSTRACT FROM AUTHOR]

The combination of lean production and Industry 4.0 exhibits excellent potential in advancing operations management and, especially, production control. This improvement potential is applicable to the semi-process industry (S-PI), as higher product variety and higher demand variability require greater flexibility from production systems. This flexibility is difficult to achieve in S-PI environments, in which it is imperative to cope with the long setup times and stability needed for the high utilization requirements. Heijunka addresses this stability-flexibility paradox but was designed for short setup times and is thus considered not directly applicable. In this article, we use design science research to adapt Heijunka to the S-PI and combine it with cyber-physical systems technologies. The developed production control concept, every product every cycle (EPEC) 4.0, aims to schedule the production system as efficiently as possible, providing the necessary flexibility and minimum schedule perturbation. Furthermore, we present the findings from a validation case study within the automotive supply industry. [ABSTRACT FROM AUTHOR]