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Several strategies have been detected in the extant literature to understand how Circular Economy (CE) can be pursued. Considering all the End-of-Life (EoL) management practices detected, disassembly processes have been identified as strategic. However, only scattered attempts have explored how digital technologies (specifically, simulation) can support the CE adoption, by focusing on disassembly processes. This research detects, through a systematic literature review, how so far simulation approaches have been proposed and applied in the extant literature to foster the disassembly process with a focus on Printed Circuit Boards (PCBs). At this purpose, the main roles played by simulation to ease the disassembly process, also through the support of Industry 4.0 (I4.0) technologies, have been detected. Based on the results obtained, two roles of simulation to support the disassembly process (Sequence planning and process optimization and Training) seem the most interesting from the twofold CE/I4.0 perspective, combining up to date technologies with traditional simulation approaches. Discussed in a deeper and sector-independent way, results provide directions about the lifecycle phases to be explored through simulations, the technologies to be involved, and both the final purpose and the type of simulation approach to be adopted. Finally, the gaps needing for further contributions, raised from the adoption of a Digitized Disassembly, are listed, and the main technologies so far employed to cope with them, through a Virtual/Augmented Disassembly-oriented Simulation perspective, have also been detected and provided as a guide for those who want to approach the hybrid simulation/disassembly research context.  相似文献   

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The increasing competition among industries has leveraged the emergence of various tools and methods for maintenance decision-making support. This paper identifies in literature the application areas of industrial maintenance decision-making, the relationships between these areas and the ways in which authors integrate tools and methods. This information makes it possible to identify trends and deficiencies in this context, helping to centralize the efforts required for future work. This work follows a series of structured steps for a systematic literature review of papers related to the main topic available in online databases. The selected papers are subject to a content assessment and grouped according to the application areas. The direct comparison between these areas and the construction of a relational matrix provide a quantitative interpretation of the results and well-structured information. Additionally, this paper proposes a framework based on information from the literature, which summarizes the origin and flow of information used in the development of models, showing the relationship among application areas of decision making. The research undertaken identifies trends focused on joint production systems optimization and increasing the deployment of methods for autonomous equipment predictions.  相似文献   

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In recent years, Industry 4.0 has been introduced as a popular term to describe the trend towards digitisation and automation of the manufacturing environment. Despite its potential benefits in terms of improvements in productivity and quality, this concept has not gained much attention in the construction industry. This development is founded in the fact that the far-reaching implications of the increasingly digitised and automated manufacturing environment are still widely unknown. Against this backdrop, the primary objective of this paper is to explore the state of the art as well as the state of practice of Industry 4.0 relating technologies in the construction industry by pointing out the political, economic, social, technological, environmental and legal implications of its adoption. In this context, we present the results of our triangulation approach, which consists of a comprehensive systematic literature review and case study research, by illustrating a PESTEL framework and a value chain model. Additionally, we provide recommendations for further research within a research agenda.  相似文献   

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Industry 4.0 (I4.0) was introduced in 2011, and its advanced enablers strongly affect industrial practices. In the current literature, while several papers offer general reviews on the topic, contributions exploring the evidences coming from the implementation of I4.0 in multi-sector Small and Medium Enterprises (SMEs) and large enterprises are few and expected. To address this gap, a comprehensive review of the main I4.0 enabling technologies is conducted, focusing on implementation experiences in companies belonging to different sectors. Forty (40) real case studies are analyzed and compared. The results show that 63% of the identified applications involve large enterprises in the transport sector, that is, automotive, aeronautics, and railway, adopting a structured set of enabling technologies. SMEs engaged in I4.0 projects primarily belong to the mechanical engineering sector, and 37% of such projects deals with the preliminary feasibility analysis of introducing a single enabling technology. Conclusions and trends guide researchers and practitioners in understanding the implementation level of I4.0 technologies.  相似文献   

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ContextMany researchers adopting systematic reviews (SRs) have also published papers discussing problems with the SR methodology and suggestions for improving it. Since guidelines for SRs in software engineering (SE) were last updated in 2007, we believe it is time to investigate whether the guidelines need to be amended in the light of recent research.ObjectiveTo identify, evaluate and synthesize research published by software engineering researchers concerning their experiences of performing SRs and their proposals for improving the SR process.MethodWe undertook a systematic review of papers reporting experiences of undertaking SRs and/or discussing techniques that could be used to improve the SR process. Studies were classified with respect to the stage in the SR process they addressed, whether they related to education or problems faced by novices and whether they proposed the use of textual analysis tools.ResultsWe identified 68 papers reporting 63 unique studies published in SE conferences and journals between 2005 and mid-2012. The most common criticisms of SRs were that they take a long time, that SE digital libraries are not appropriate for broad literature searches and that assessing the quality of empirical studies of different types is difficult.ConclusionWe recommend removing advice to use structured questions to construct search strings and including advice to use a quasi-gold standard based on a limited manual search to assist the construction of search stings and evaluation of the search process. Textual analysis tools are likely to be useful for inclusion/exclusion decisions and search string construction but require more stringent evaluation. SE researchers would benefit from tools to manage the SR process but existing tools need independent validation. Quality assessment of studies using a variety of empirical methods remains a major problem.  相似文献   

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Industry 4.0, an initiative from Germany, has become a globally adopted term in the past decade. Many countries have introduced similar strategic initiatives, and a considerable research effort has been spent on developing and implementing some of the Industry 4.0 technologies. At the ten-year mark of the introduction of Industry 4.0, the European Commission announced Industry 5.0. Industry 4.0 is considered to be technology-driven, whereas Industry 5.0 is value-driven. The co-existence of two Industrial Revolutions invites questions and hence demands discussions and clarifications. We have elected to use five of these questions to structure our arguments and tried to be unbiased for the selection of the sources of information and for the discussions around the key issues. It is our intention that this article will spark and encourage continued debate and discussion around these topics.  相似文献   

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Changing production systems and product requirements can trace their origin in volatile customer behaviour and evolving product requirements. This dynamic nature of customer requirements has been described as a constantly moving target, thus presenting a significant challenge for several aspects of product development. To deal with this constant and sometimes unpredictable product evolution, cyber physical production systems (CPPS) that employ condition monitoring, self-awareness and reconfigurability principles, have to be designed and implemented. This research contributes a CPPS design approach that proactively provides the required CPPS design knowledge. This approach aims to minimise or avoids future consequences and disruptions on the CPPS. This knowledge needs to be provided at the right time whilst not being intrusive to the production system designer’s cognitive activity. To effectively deal with the complexity of the cyber physical production system design activity with a manual method would lead to a time consuming, and complex support tool which is hard to implement, and difficult to use. The CPPS design approach has therefore been implemented in a prototype digital factory tool. This paper describes in detail the system requirements and system architecture for this tool. In order to establish the effectiveness of the proposed approach for designing cyber physical production systems, the prototype digital factory tool has been evaluated with a case study and a number of semi-structured interviews with both industrial and scientific stakeholders. The encouraging results obtained from this research evaluation have shown that such an approach for supporting the CPPS design activity makes stakeholders aware of their decision consequences and is useful in practice. This result can lead the way for the development and integration of such knowledge-based decision-making approaches within state-of-the-art digital factory and Computer Aided Engineering Design (CAED) tools.  相似文献   

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Due date control (DDC) can be regarded as one of the competitive abilities of an enterprise. Based on advanced connected technologies implemented in Industry 4.0, DDC can collect processing information accurately and in real time to be integrated with production systems. It is an intelligent event-driven feedback control that can be designed to control process plans. In this study, a work-in-process alert system framework is developed based on a machine-to-machine communication approach. Subsequently, a manufacturer can monitor and perform DDC for each process based on the buffer control of the theory of constraints. The latter is a methodology for identifying the most important limiting factor, such as constraints, that prevents the attainment of a goal and then systematically improves that constraint until it is no longer the limiting factor. Furthermore, using hybrid strategies of Industry 3.5, a material planner can collaborate with suppliers to improve delivery performance. This approach is effective in semiconductor manufacturing.  相似文献   

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The increasing importance of automation and smart capabilities for factories and other industrial systems has led to the concept of Industry 4.0 (I4.0). This concept aims at creating systems that improve the vertical and horizontal integration of production through (i) comprehensive and intelligent automation of industrial processes, (ii) informed and decentralized real-time decision making, and (iii) stringent quality requirements that can be monitored at any time. The I4.0 infrastructure, supported in many cases by robots, sensors, and algorithms, demands highly skilled workers able to continuously monitor the quality of both the items to be produced and the underlying production processes.While the first attempts to develop smart factories and enhance the digital transformation of companies are under way, we need adequate methods to support the identification and specification of quality attributes that are relevant to I4.0 systems. Our main contribution is to provide a refined version of the ISO 25010 quality model specifically tailored to those qualities demanded by I4.0 needs. This model aims to provide actionable support for I4.0 software engineers that are concerned with quality issues. We developed our model based on an exhaustive analysis of similar proposals using the design science method as well as expertise from seasoned engineers in the domain. We further evaluate our model by applying it to two important I4.0 reference architectures further clarifying its application.  相似文献   

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Connectivity and data exchange are key features of Industry 4.0. In this paradigm, (Industrial) Internet of Things ((I)IoT) devices are a vital component facilitating the collection and transmission of environmental data from the physical system to the central station for processing and analysis (digital twin [DT]). However, although (I)IoT devices play a critical role in this process, they are not inherently equipped to run strong encryption mechanisms to secure the data they transmit over wired or wireless channels. This research aims to explore the potential of DTs in securing Industry 4.0 applications and the security mechanism employed to ensure confidentiality, integrity, and authentication of data communicated between (I)IoT and DT through a systematic literature review (SLR). This SLR, based on the analysis of 67 papers published between 2018 and 2023, underscores the evolving significance of DT technology, particularly within the ambit of Industry 4.0. The findings illuminate the pervasive influence of DT technology across multiple industrial sectors. The result SLR revealed that DT is growing and being widely adopted as a security tool particularly in Industry 4.0 using enabling technology like machine learning, data analytics, blockchain, and 5G networks to provide security solutions such as intrusion detection, vulnerability assessment, cyber range, and threat intelligence.  相似文献   

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Manufacturers expect the extra value of Industry 4.0 as the world is experiencing digital transformation. Studies have proved the potential of the Internet of Things (IoT) for reducing cost, improving efficiency, quality, and achieving data-oriented predictive maintenance services. Collecting a wide range of real-time data from products and the environment requires smart sensors, reliable communications, and seamless integration. IoT, as a critical Industry 4.0 enabler emerges smart home appliances for higher customer satisfaction, energy efficiency, personalisation, and advanced Big data analytics. However, established factories with limited resources are facing challenges to change the longstanding production lines and meet customer’s requirements. This study aims to fulfil the gaps by transforming conventional home appliances to IoT-enabled smart systems with the ability to integrate into a smart home system. An industry-led case study demonstrates how to turn conventional appliances to smart products and systems (SPS) by utilising the state-of-the-art Industry 4.0 technologies.  相似文献   

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In recent years, the Industry 4.0 concept brings new demands and trends in different areas; one of them is distributing computational power to the cloud. This concept also introduced the Reference Architectural Model for Industry 4.0 (RAMI 4.0). The efficiency of data communications within the RAMI 4.0 model is a critical issue. Aiming to evaluate the efficiency of data communication in the Cloud Based Cyber-Physical Systems (CB-CPS), this study analyzes the periods and data amount required to communicate with individual hierarchy levels of the RAMI 4.0 model. The evaluation of the network properties of the communication protocols eligible for CB-CPS is presented. The network properties to different cloud providers and data centers’ locations have been measured and interpreted. To test the findings, an architecture for cloud control of laboratory model was proposed. It was found that the time of the day; the day of the week; and data center utilization have a negligible impact on latency. The most significant impact lies in the data center distance and the speed of the communication channel. Moreover, the communication protocol also has impact on the latency. The feasibility of controlling each level of RAMI 4.0 through cloud services was investigated. Experimental results showed that control is possible in many solutions, but these solutions mostly cannot depend just on cloud services. The intelligence on the edge of the network will play a significant role. The main contribution is a thorough evaluation of different cloud providers, locations, and communication protocols to provide recommendations sufficient for different levels of the RAMI 4.0 architecture.  相似文献   

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The realm of digital twins is experiencing rapid growth and presents a wealth of opportunities for Industry 4.0. In conjunction with traditional simulation methods, digital twins offer a diverse range of possibilities. However, many existing tools in the domain of open-source digital twins concentrate on specific use cases and do not provide a versatile framework. In contrast, the open-source digital twin framework, OpenTwins, aims to provide a versatile framework that can be applied to a wide range of digital twin applications. In this article, we introduce a re-definition of the original OpenTwins platform that enables the management of custom simulation services and the management of FMI simulation services, which is one of the most widely used simulation standards in the industry and its coexistence with machine learning models, which enables the definition of the next-gen digital twins. Thanks to this integration, digital twins that reflect reality better can be developed, through hybrid models, where simulation data can feed the scarcity of machine learning data and so forth. As part of this project, a simulation model developed through the hydraulic software Epanet was validated in OpenTwins, in addition to an FMI simulation service. The hydraulic model was implemented and tested in an agricultural use case in collaboration with the University of Córdoba, Spain. A machine learning model has been developed to assess the behavior of an FMI simulation through machine learning.  相似文献   

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The development of system‐of‐systems (SoS) requires a continuous interplay between design decisions on the SoS level and those on the level of its constituent systems (CS), which often preexist and need to be adapted as the SoS evolves. This involves not only preparing the CS to participate in a particular SoS, but also designing the CS architecture to make it easily adaptable to a future SoS context. The problem is in part addressed in an emerging SoS framework in the manufacturing domain called Industry 4.0. It focuses on connected and digitalized production with the ambition of increasing flexibility and efficiency. This paper investigates how Industry 4.0 standards can be used in an SoS context to make CS more flexible and adaptive, and evaluates their usefulness outside manufacturing. The study is based on a case from the construction domain, for which a generic SoS architecture is developed. Several extensions and adaptations of Industry 4.0 are suggested, including specifications of ontologies for missions and workflows.  相似文献   

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Smart manufacturing offers a high level of adaptability and autonomy to meet the ever-increasing demands of product mass customization. Although digitalization has been used on the shop floor of modern factory for decades, some manufacturing operations remain manual and humans can perform these better than machines. Under such circumstances, a feasible solution is to have human operators collaborate with computational intelligence (CI) in real time through augmented reality (AR). This study conducts a systematic review of the recent literature on AR applications developed for smart manufacturing. A classification framework consisting of four facets, namely interaction device, manufacturing operation, functional approach, and intelligence source, is proposed to analyze the related studies. The analysis shows how AR has been used to facilitate various manufacturing operations with intelligence. Important findings are derived from a viewpoint different from that of the previous reviews on this subject. The perspective here is on how AR can work as a collaboration interface between human and CI. The outcome of this work is expected to provide guidelines for implementing AR assisted functions with practical applications in smart manufacturing in the near future.  相似文献   

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The rapidly changing market demands entail a modern production system to cope with ever more diversified production orders. Not only the parameters and flow of the production process, sometimes the production resources and the corresponding application systems which make production decision and control even need to be reconfigurable. Due to the inability to provide dynamically reconfigurable manufacturing resources, systems and application systems, enterprises have to sacrifice profits to narrow their business scope or take risks to purchase a large number of production resources. In any case, it has brought operational burden to enterprises. This paper systematically analyses the production management requirements of a large-scale production system in terms of both hardware (production equipment) and software (application system) which is oriented to dynamic production demands, and then proposes a production service system enabled by cloud-based smart resource hierarchy (PnSS-CSRH). The platform is based on an open resource management system and inherits the general cloud structure and the AUTOM framework. PnSS-CSRH provides industrial users with integrated and synchronization services for the software and hardware resources involved in the production process in the PnSS mode. Using the integrated service mode, PnSS-CSRH not only helps resource providers to increase the frequency of resource leases, provides customers with targeted and systemic hardware and software overall solutions, and increases the platform usage rate, which brings more benefits to the stakeholders of PnSS-CSRH. At last, the PnSS-CSRH is used to provide services to the case company to validate the effectiveness.  相似文献   

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Web调查平台的可信度研究   总被引:1,自引:0,他引:1  
王刚  刘路放  冯博琴 《计算机工程》2002,28(5):133-134,138
分析了当前Web调查平台的特点,针对其在可信度方面的不足,结合受限调查的特征,提出了分级可信度加权统计模型。该模型能够针对不同要求的调查内容,为辅助决策提供最高价值的参考信息,有效地解决了当前调查平台存在的可信度问题。  相似文献   

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工业控制系统除了应用于生产制造行业外,还广泛应用于交通、水利和电力等关键基础设施.随着工业数字化、网络化、智能化的推进,许多新技术应用于工业控制系统,提高了工业控制系统的智能化水平,但其也给工业控制系统的安全带来严峻的挑战.因此,工业控制系统的安全倍受研究人员的关注.为了让研究人员系统化地了解目前的研究进展,调研了近3年Web of Science核心数据库、EI数据库和CCF推荐网络与信息安全国际学术会议中发表的与工业控制系统安全相关论文以及其他相关的高水平研究工作.首先,介绍工业控制系统的体系结构及面临的威胁.然后,依据工业控制系统的体系结构,自上而下将其安全研究工作分为ICS-云平台通信安全、HMI-设备通信安全、设备固件安全以及其他安全研究,并从攻击和防御角度进行分析和整理.最后,提出当前工业控制系统安全研究依然面临的主要挑战,并指出未来研究发展的方向.  相似文献   

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