Cloud platforms for remote monitoring system : a comparative case study

Currently, industrial companies are increasingly introducing services to extend their tangible products. Remote monitoring solutions are one of the most implemented services by machine builders to manage their relationship with customers and also improve their business performance in the digital manufacturing era. However, the conventional method of remote monitoring cannot fulfil distributed business environments. Therefore, new solutions are needed to enable remote connection in manufacturing. By reviewing recent literature and proposing new features for software which can be used for remote service and operations, this research paper introduces a remote monitoring system connecting into a central cloud-based system with edge computing network architecture, namely Cloud-based Remote Monitoring (CloudRM). This proposed CloudRM also has been implemented in two different case companies for analysis and evaluation from a value proposition and technical implementation point of view. It shows significant improvement of production management and measurement by using CloudRM.fi=vertaisarvioitu|en=peerReviewed

Differential Privacy for Industrial Internet of Things: Opportunities, Applications and Challenges

The development of Internet of Things (IoT) brings new changes to various fields. Particularly, industrial Internet of Things (IIoT) is promoting a new round of industrial revolution. With more applications of IIoT, privacy protection issues are emerging. Specially, some common algorithms in IIoT technology such as deep models strongly rely on data collection, which leads to the risk of privacy disclosure. Recently, differential privacy has been used to protect user-terminal privacy in IIoT, so it is necessary to make in-depth research on this topic. In this paper, we conduct a comprehensive survey on the opportunities, applications and challenges of differential privacy in IIoT. We firstly review related papers on IIoT and privacy protection, respectively. Then we focus on the metrics of industrial data privacy, and analyze the contradiction between data utilization for deep models and individual privacy protection. Several valuable problems are summarized and new research ideas are put forward. In conclusion, this survey is dedicated to complete comprehensive summary and lay foundation for the follow-up researches on industrial differential privacy

Smart logistics nodes:concept and classification

This paper presents the Smart Logistics Node concept, which combines the physical infrastructure of logistics nodes with digital systems to enhance collaboration. The Smart Logistics Node benefits from data sharing, supporting infrastructure, and Connected and Automated Transport (CAT) technologies. Based on a literature review on logistics nodes and CAT, we propose a general classification of Smart Logistics Nodes distinguishing upon the node function, degree of organisational (de-)centralisation, digital integration, and infrastructure support for automated driving. Then, we classify sixteen logistics nodes and find that high digital integration is common while automation is lacking. Further automation entails mixed traffic on public roads and requires organisational changes that do not always align with current business models. Our work supports the adoption of emerging technology at logistics nodes and the comparability of business cases. Ultimately, node authorities can use our concept and classification to draw a roadmap to develop CAT capabilities.</p

Successful Collaboration in Global Production Networks - fair, secured, connected

In today\u27s world, manufacturing companies face many challenges due to the uncertainty and complexity of environmental influences as well as increasing competitive pressures. The pandemic has clearly illustrated how volatile and fragile our supply chains have become. One way to overcome these chal-lenges together is to collaborate with other companies in the value network. Collaborations, i.e. successful cooperation with strategic partners and customers to achieve common goals, will continue to gain in importance. Instead of individual companies, entire value chains and networks will therefore compete with each other in the future. This will require a shift toward fast and seamless data exchange between the players in the value network. Advancing digitization and thus a generally increasingly networked world are increasingly supporting such collaborations, as the sharing and collaborative use of data is becom-ing much simpler. At the same time, the right handling of data will be decisive for competition. Digitization is moving from being a driver of change to an enabler of change. Innovative business models and the exploita-tion of the potential hidden in data will make it possible to realize reliable, flexible and, at the same time, resource-conserving value creation. The number of existing cloud-based collaboration platforms is growing steadily. Small and medium-sized enterprises in particular have to serve many different customer platforms at the same time, while they them-selves are still struggling with internal digitization challenges. Standardization initiatives for secure data rooms in the industry, such as GAIA-X, therefore hold great potential. In addition to these fundamental infrastructural issues, there are further challenges with regard to collaboration projects. Particular importance is attached to the competent handling of data protection and data security. There are often reservations that the disclosure of data and information will result in the loss of hard-earned expertise and com-petitive advantages that have been built up over time. At the same time, however, users from an engineering environment are only able to assess the risks of digital collaboration to a limited extent. In order to secure one\u27s own competitive position in the long term, digital competencies must therefore be built up and barriers to collaboration overcome. Success stories and clear recommendations for action can provide an important impetus for the implementation of successful collaboration projects, showing how collaborations can be approached in practice and what added value they generate. That is why we would like to provide manufacturing compa-nies with such guidance in the form of this action guide. The collaboration projects explained below and the best practices derived from them are intended to help companies find their own strategies on the path to more collaboration. We hope you enjoy reading this guide and are always available for questions and discussions

Towards self-organizing logistics in transportation:a literature review and typology

Deploying self-organizing systems is a way to cope with the logistics sector's complex, dynamic, and stochastic nature. In such systems, automated decision-making and decentralized or distributed control structures are combined. Such control structures reduce the complexity of decision-making, require less computational effort, and are therefore faster, reducing the risk that changes during decision-making render the solution invalid. These benefits of self-organizing systems are of interest to many practitioners involved in solving real-world problems in the logistics sector. This study, therefore, identifies and classifies research related to self-organizing logistics (SOL) with a focus on transportation. SOL is an interdisciplinary study across many domains and relates to other concepts, such as agent-based systems, autonomous control, and decentral systems. Yet, few papers directly identify this as self-organization. Hence, we add to the existing literature by conducting a systematic literature review that provides insight into the field of SOL. The main contribution of this paper is two-fold: (i) based on the findings from the literature review, we identify and synthesize 15 characteristics of SOL in a typology, and (ii) we present a two-dimensional SOL framework alongside the axes of autonomy and cooperativity to position and contrast the broad range of literature, thereby creating order in the field of SOL and revealing promising research directions.</p

Collaborative approaches in sustainable and resilient manufacturing

Publisher Copyright: © 2022, The Author(s).In recent years, the manufacturing sector is going through a major transformation, as reflected in the concept of Industry 4.0 and digital transformation. The urge for such transformation is intensified when we consider the growing societal demands for sustainability. The notion of sustainable manufacturing has emerged as a result of this trend. Additionally, industries and the whole society face the challenges of an increasing number of disruptive events, either natural or human-caused, that can severely affect the normal operation of systems. Furthermore, the growing interconnectivity between organizations, people, and physical systems, supported by recent developments in information and communication technologies, highlights the important role that collaborative networks can play in the digital transformation processes. As such, this article analyses potential synergies between the areas of sustainable and resilient manufacturing and collaborative networks. The work also discusses how the responsibility for the various facets of sustainability can be distributed among the multiple entities involved in manufacturing. The study is based on a literature survey, complemented with the experience gained from various research projects and related initiatives in the area, and is organized according to various dimensions of Industry 4.0. A brief review of proposed approaches and indicators for measuring sustainability from the networked manufacturing perspective is also included. Finally, a set of key research challenges are identified to complement strategic research agendas in manufacturing.publishersversionpublishe