Special Session on Industry 4.0

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A framework for smart production-logistics systems based on CPS and industrial IoT

Industrial Internet of Things (IIoT) has received increasing attention from both academia and industry. However, several challenges including excessively long waiting time and a serious waste of energy still exist in the IIoT-based integration between production and logistics in job shops. To address these challenges, a framework depicting the mechanism and methodology of smart production-logistics systems is proposed to implement intelligent modeling of key manufacturing resources and investigate self-organizing configuration mechanisms. A data-driven model based on analytical target cascading is developed to implement the self-organizing configuration. A case study based on a Chinese engine manufacturer is presented to validate the feasibility and evaluate the performance of the proposed framework and the developed method. The results show that the manufacturing time and the energy consumption are reduced and the computing time is reasonable. This paper potentially enables manufacturers to deploy IIoT-based applications and improve the efficiency of production-logistics systems

Empowering citizens' cognition and decision making in smart sustainable cities

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Advances in Internet technologies have made it possible to gather, store, and process large quantities of data, often in real time. When considering smart and sustainable cities, this big data generates useful information and insights to citizens, service providers, and policy makers. Transforming this data into knowledge allows for empowering citizens' cognition as well as supporting decision-making routines. However, several operational and computing issues need to be taken into account: 1) efficient data description and visualization, 2) forecasting citizens behavior, and 3) supporting decision making with intelligent algorithms. This paper identifies several challenges associated with the use of data analytics in smart sustainable cities and proposes the use of hybrid simulation-optimization and machine learning algorithms as an effective approach to empower citizens' cognition and decision making in such ecosystemsPeer ReviewedPostprint (author's final draft

Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications

A novel framework for the use of workflow system in the integration of supply chain tiers

The global competition has imposed challenges to supply chain integration, mainly, during the process of obtain information to make demand management decisions. This paper proposes an integrated framework for data collection, analysis and results dissemination in the supply chain management (SCM), contributing to research and alternatives for \u201cThe Bullwhip Effect\u201d issue. In this sense, it is necessary to discuss the integration of supply chain management, Enterprise Resources Planning (ERP) functionality and others systems, to enlarge this scope to the total supply chain players. The ERP web-based tool and Workflow Systems (WS) can contribute to solve issues related to supply chain management. Starting from a detailed analysis of the research background regarding current SCM definitions and integration problems, Information Technology and Communication (ITC) development and WS in order to map and ensure flow fluency; the paper proposes a model to increase the overall integrations and an application in a case study for supporting the decisions that are aligned with the company\u2019s strategic objectives. This paper is divided in: research background; proposed model of the SC integration; case study, conclusions and future research

Survey on Additive Manufacturing, Cloud 3D Printing and Services

Cloud Manufacturing (CM) is the concept of using manufacturing resources in a service oriented way over the Internet. Recent developments in Additive Manufacturing (AM) are making it possible to utilise resources ad-hoc as replacement for traditional manufacturing resources in case of spontaneous problems in the established manufacturing processes. In order to be of use in these scenarios the AM resources must adhere to a strict principle of transparency and service composition in adherence to the Cloud Computing (CC) paradigm. With this review we provide an overview over CM, AM and relevant domains as well as present the historical development of scientific research in these fields, starting from 2002. Part of this work is also a meta-review on the domain to further detail its development and structure

An overview on the obsolescence of physical assets for the defence facing the challenges of industry 4.0 and the new operating environments

Libro en Open AccessThis contribution is intended to observe special features presented in physical assets for defence. Particularly, the management of defence assets has to consider not only the reliability, availability, maintainability and other factors frequently used in asset management. On the contrary, such systems should also take into account their adaptation to changing operating environments as well as their capability to changes on the technological context. This study approaches to the current real situation where, due to the diversity of conflicts in our international context, the same type of defence systems must be able to provide services under different boundary conditions in different areas of the globe. At the same time, new concepts from the Industry 4.0 provide quick changes that should be considered along the life cycle of a defence asset. As a finding or consequence, these variations in operating conditions and in technology may accelerate asset degradation by modifying its reliability, its up-to-date status and, in general terms, its end-of-life estimation, depending of course on a diversity of factors. This accelerated deterioration of the asset is often known as “obsolescence” and its implications are often evaluated (when possible), in terms of costs from different natures. The originality of this contribution is the introduction of a discussion on how a proper analysis may help to reduce errors and mistakes in the decision-making process regarding the suitability or not of repairing, replacing, or modernizing the asset or system under study. In other words, the obsolescence analysis, from a reliability and technological point of view, could be used to determine the conservation or not of a specific asset fleet, in order to understand the effects of operational and technology factors variation over the functionality and life cycle cost of physical assets for defence

Agent and cyber-physical system based self-organizing and self-adaptive intelligent shopfloor

The increasing demand of customized production results in huge challenges to the traditional manufacturing systems. In order to allocate resources timely according to the production requirements and to reduce disturbances, a framework for the future intelligent shopfloor is proposed in this paper. The framework consists of three primary models, namely the model of smart machine agent, the self-organizing model, and the self-adaptive model. A cyber-physical system for manufacturing shopfloor based on the multiagent technology is developed to realize the above-mentioned function models. Gray relational analysis and the hierarchy conflict resolution methods were applied to achieve the self-organizing and self-adaptive capabilities, thereby improving the reconfigurability and responsiveness of the shopfloor. A prototype system is developed, which has the adequate flexibility and robustness to configure resources and to deal with disturbances effectively. This research provides a feasible method for designing an autonomous factory with exception-handling capabilities