The flexibility claimed by the next generation production systems induces a deep modification of the behaviour and the core itself of the control systems. Over-connectivity and data management ...abilities targeted by Industry 4.0 paradigm enable the emergence of more flexible and reactive control systems, based on the cooperation of autonomous and connected entities in the decision-making process. From most relevant articles extracted from existing literature, a list of 10 key enablers for Industry 4.0 is first presented. During the last 20 years, the holonic paradigm has become a major paradigm of Intelligent Manufacturing Systems. After the presentation of the holonic paradigm and holon properties, this article highlights how historical and current holonic control architectures can partly fulfil Industry 4.0 key enablers. The remaining unfulfilled key enablers are then the subject of an extensive discussion on the remaining research perspectives on holonic architectures needed to achieve a complete support of Industry 4.0.
This paper addresses the engineering of the ethical behaviors of autonomous industrial cyber-physical human systems in the context of Industry 4.0. An ethical controller is proposed to be embedded ...into these autonomous systems, to enable their successful integration in the society and its norms. This proposed controller that integrates machine ethics is realized through three main strategies that utilize two ethical paradigms, namely deontology, and consequentialism. These strategies are triggered according to the type of event sensed and the state of the autonomous industrial cyber-physical human systems, their combination being potentially unknown or posing ethical dilemmas. Two case studies are investigated, that deal with a fire emergency, and two different contexts i.e. one with an autonomous train, and one with an autonomous industrial plant, are discussed to illustrate the controller utilization. The case studies demonstrate the potential benefits and exemplify the need to integrate ethical behaviors in autonomous industrial cyber-physical human systems already at the design phase. The proposed approach, use cases, and discussions make evident the need to address ethical aspects in new efforts to engineer industrial systems in the context of Industry 4.0.
In this paper, a layered architecture incorporating Blockchain technology (BCT) and Machine Learning (ML) is proposed in the context of the Industrial Internet-of-Things (IIoT) for smart ...manufacturing applications. The proposed architecture is composed of five layers covering sensing, network/protocol, transport enforced with BCT components, application and advanced services (i.e., BCT data, ML and cloud) layers. BCT enables gathering sensor access control information, while ML brings its effectivity in attack detection such as DoS (Denial of Service), DDoS (Distributed Denial of Service), injection, man in the middle (MitM), brute force, cross-site scripting (XSS) and scanning attacks by employing classifiers differentiating between normal and malicious activity. The design of our architecture is compared to similar ones in the literature to point out potential benefits. Experiments, based on the IIoT dataset, have been conducted to evaluate our contribution, using four metrics: Accuracy, Precision, Sensitivity and Matthews Correlation Coefficient (MCC). Artificial Neural Network (ANN), Decision Tree (DT), Random Forest, Naive Bayes, AdaBoost and Support Vector Machine (SVM) classifiers are evaluated regarding these four metrics. Even if more experiments are required, it is illustrated that the proposed architecture can reduce significantly the number of DDoS, injection, brute force and XSS attacks and threats within an advanced framework for sensor access control in IIoT networks based on a smart contract along with ML classifiers.
This paper presents an efficient approach for solving the optimal reactive power dispatch problem. It is a non-linear constrained optimization problem where two distinct objective functions are ...considered. The proposed approach is based on the hybridization of the particle swarm optimization method and the tabu-search technique. This hybrid approach is used to find control variable settings (i.e., generation bus voltages, transformer taps and shunt capacitor sizes) which minimize transmission active power losses and load bus voltage deviations. To validate the proposed hybrid method, the IEEE 30-bus system is considered for 12 and 19 control variables. The obtained results are compared with those obtained by particle swarm optimization and a tabu-search without hybridization and with other evolutionary algorithms reported in the literature.
The industry 4.0 concepts are moving towards flexible and energy efficient factories. Major flexible production lines use battery-based automated guided vehicles (AGVs) to optimize their handling ...processes. However, optimal AGV battery management can significantly shorten lead times. In this paper, we address the scheduling problem in an AGV-based job-shop manufacturing facility. The considered schedule concerns three strands: jobs affecting machines, product transport tasks’ allocations and AGV fleet battery management. The proposed model supports outcomes expected from Industry 4.0 by increasing productivity through completion time minimization and optimizing energy by managing battery replenishment. Experimental tests were conducted on extended benchmark literature instances to evaluate the efficiency of the proposed approach.
Currently, enhancing sustainability, and in particular reducing energy consumption, is a huge challenge for manufacturing enterprises. The vision of the fourth industrial revolution (so-called ...“industry 4.0”) is not only to optimize production and minimize costs, but also to reduce energy consumption and enhance product life-cycle management. To address this challenge, a multi-agent architecture aimed at elaborating predictive and reactive energy-efficient scheduling through collaboration between cyber physical production and energy systems is proposed in this paper. Smart, sustainable decision tools for cyber physical production systems (CPPS) and cyber physical energy systems (CPES) are proposed. The decision tools are data-driven, agent-based models with dynamic interaction. The main aim of agent behaviours in the cyber part of CPPS is to find a predictive and reactive energy-efficient schedule. The role of agents in CPES is to control the energy consumption of connected factories and switch between the different renewable energy sources. Dynamic mechanisms in CPPS and CPES are proposed to adjust the energy consumption of production systems based on the availability of the renewable energy. The proposed approach was validated on a physically distributed architecture using networked embedded systems and real-time data sharing from connected sensors in each cyber physical systems. A series of instances inspired from the literature were tested to assess the performance of the proposed method. The results prove the efficiency of the proposed approach in adapting the energy consumption of connected factories based on a real-time energy threshold.
One objective of Industry 4.0 is to reach a better system performance as well as to have a better consideration of humans. This would be done by benefiting from knowledge and experience of humans, ...and balancing in a reactive way some complex or complicated tasks with intelligent systems. Several studies already dealt with such an objective, but few are done at a methodological level, which forbids, for example, the correct evaluation of design choices in terms of human awareness of the situation or mental workload when designing intelligent manufacturing systems integrating the human. Indeed, increasing the intelligence and autonomy of industrial systems and their composing entities (resources, products, robots…), as fostered by Industry 4.0, increases their overall complexity. This modification reduces the ability to understand the behaviors of these systems, and leads to the difficulty for humans not only to elaborate alternative decisions when required, but also to make effective decisions and understand their consequences. This paper evaluates such a design methodology, the Cognitive Work Analysis (CWA), and its applicability when designing an assistance system to support Human in the control of Intelligent Manufacturing System in Industry 4.0. Among several functions identified through the application of CWA, the assistant system might have to integrate a digital twin of the intelligent manufacturing system. The evaluation of the methodology through the one of the designed assistant systems is done using a micro-world, which is an intelligent manufacturing cell composed of intelligent mobile ground robots, products, and static production robots interacting together and with a human supervisor in charge of the reaching of several time-based and energy-based performances indicators. The assistant system embeds a digital twin of the intelligent manufacturing system. Twenty-three participants took part in experiments to evaluate the designed assistance system. First results show that the assistance system enables participants to have a correct awareness of the situation and a correct evaluation of their alternative decisions, while their mental workload is managed and expected production performances are reached. This paper contains an analysis of these experiments and points out some limits of the CWA method in the context of Industry 4.0, especially the lack of tool enabling to specify clearly the cooperation processes between the supervisor and the intelligent manufacturing system. This paper concludes with potential research avenues, the main one being the potential benefits of coupling CWA with human–machine cooperation principles to fine tune and adapt the cooperation between the human and the intelligent manufacturing system.
This editorial introduces the special issue of the Elsevier journal, Engineering Application of Artificial Intelligence, on Distributed control of production systems. The current technology in ...communication and embedded systems allows products and production resources to play a more active role in the production process. This new active capacity will generate major changes in organizations and information systems (e.g., Enterprise Resource Planning (ERP) and Manufacturing Execution Systems (MES)). New approaches are now required for modelling, testing and assessing the features made possible by the decisional and informational capabilities of these new active entities. One among the many possibilities is to use agents and holons, since agent and holon-based approaches assume interaction between intelligent entities to facilitate the emergence of a global behavior. This special issue thus focuses on the possible applications of distributed approaches for the design, evaluation and implementation of new control architectures for production systems. Both fundamental and applied research papers are presented.
The competitiveness of modern companies depends today on the ability to implement digitised technologies into production processes in human-friendly ways. The aim of this paper is to analyse ethical ...aspects of human-cobot cooperation in industrial production and to design a process standard aimed at ensuring an ethically stable cooperative workplace. The scientific contribution of this study lies in the identification and definition of standardized parameters of the ethics of the production process in the workplace. Based on the analysis of cooperative workplaces in 250 industrial companies, a code of ethics has been defined, i.e. a process standard that determines the navigation of the design by selected optimization criteria necessary for setting up a hybrid workplace defined as human and cobot (collaborative robot) with the support of digitised technologies. In the presented results and the final discussion attention is devoted to the need to radically change the philosophy of workplace standardization in the sense of equal access to workload settings by humans and robots. In the process of standardization, it is necessary to consider the difference in the standardization of human jobs and cobot jobs: the thinking process. In modern industrial companies the need has arisen to create working standards that take into account the adaptive ability of cobots and adapt the cobots’ workflow to human needs concerning performance and productivity. The presented results include recommendations for industrial companies to develop an ethical and stable production workplace based on an adequately defined form of cooperation.
In recent years, more and more manufacturers and operators of fleets of mobile systems have been focusing their efforts on studying and developing conditional maintenance, monitoring, and diagnostic ...strategies to cope with an increasingly competitive, unstable, costly, and unpredictable environment. This paper proposes a case study concerning the application of a novel event management architecture, called EMH
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, to a fleet of trains. This EMH
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architecture, which applies the holonic paradigm, aims to facilitate the monitoring and diagnosis of a fleet of mobile systems. It is based on a recursive decomposition of cooperative monitoring holons. The definition of a generic event modeling, called SurfEvent, is the second key element of the contribution. EMH
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has been designed to be applicable to any kind of system or equipment up to fleet level. The edge computing paradigm has been adopted for implementation purpose. The EMH
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architecture is designed to facilitate asynchronous and progressive onboard and off-board deployments. A real-world application of EMH
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to a fleet of ten trains currently in use, in collaboration with our industrial partner, Bombardier Transport, is presented. Three key performances indicators have been estimated by comparing EMH
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with the current industrial situation. These indicators are (1) the number of fleet maintenance visits, (2) the time needed by a maintenance operator to investigate and diagnose, and (3) the time needed by the system to update data regarding the health status and monitoring of trains. Results obtained outperformed industrial expectations. The paper finally discusses feedbacks from experience and limitations of the work.
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