A STUDY OF THE USE OF MIXED REALITY FOR CAPTURING HUMAN OBSERVATION AND INFERENCES IN PRODUCTION ENVIRONMENTS

Augmented and mixed reality is already considered as needful technology of the modern production systems. It is primarily employed to virtualize proper digital content, mainly related to 3D objects, into the human visual field allowing people to visualize and understand complex spatial shapes, their mutual relations, and positioning. Yet, the huge potential of the technology is waiting to be revealed in its usage for collecting and recording human observations and inferences about the context of the production environment. Its bi-directional interface makes it the most direct and the most efficient knowledge capturing means to date. The paper presents the challenges and benefits that come from the usage of a conceptual interface of an mixed reality application that is designed to collect data, semantics and knowledge about the production context directly from the man-in-process. As a production environment for the development, implementation, and testing of mixed reality applications for this purpose, various processes for the assembly and maintenance of medium-voltage equipment were used

A Novel Enhanced Quantum PSO for Optimal Network Configuration in Heterogeneous Industrial IoT

A novel enhanced quantum particle swarm optimization algorithm for IIoT deployments is proposed. It provides enhanced connectivity, reduced energy consumption, and optimized delay. We consider heterogeneous scenarios of network topologies for optimal path configuration by exploring and exploiting the hunts. It uses multiple inputs from heterogeneous IIoT into quantum and bio-inspired optimization techniques. The differential evolution operator and crossover operations are used for information interchange among the nodes to avoid trapping into local minima. The different topology scenarios are simulated to study the impact of $p$ -degrees of connectivity concerning objective functions’ evaluation and compared with existing techniques. The results demonstrate that our algorithm consumes a minimum of 30.3% lesser energy. Furthermore, it offers improved searching precision and convergence swiftness in the possible search space for $p$ -disjoint paths and reduces the delay by a minimum of 26.7%. Our algorithm also improves the throughput by a minimum of 29.87% since the quantum swarm inclines to generate additional diverse paths from multiple source nodes to the gateway

A Collaboration-Oriented M2M Messaging Mechanism for the Collaborative Automation between Machines in Future Industrial Networks

Machine-to-machine (M2M) communication is a key enabling technology for industrial internet of things (IIoT)-empowered industrial networks, where machines communicate with one another for collaborative automation and intelligent optimisation. This new industrial computing paradigm features high-quality connectivity, ubiquitous messaging, and interoperable interactions between machines. However, manufacturing IIoT applications have specificities that distinguish them from many other internet of things (IoT) scenarios in machine communications. By highlighting the key requirements and the major technical gaps of M2M in industrial applications, this article describes a collaboration-oriented M2M (CoM2M) messaging mechanism focusing on flexible connectivity and discovery, ubiquitous messaging, and semantic interoperability that are well suited for the production line-scale interoperability of manufacturing applications. The designs toward machine collaboration and data interoperability at both the communication and semantic level are presented. Then, the application scenarios of the presented methods are illustrated with a proof-of-concept implementation in the PicknPack food packaging line. Eventually, the advantages and some potential issues are discussed based on the PicknPack practice

A Collaboration-Oriented M2M Messaging Mechanism for the Collaborative Automation between Machines in Future Industrial Networks

Machine-to-machine (M2M) communication is a key enabling technology for industrial internet of things (IIoT)-empowered industrial networks, where machines communicate with one another for collaborative automation and intelligent optimisation. This new industrial computing paradigm features high-quality connectivity, ubiquitous messaging, and interoperable interactions between machines. However, manufacturing IIoT applications have specificities that distinguish them from many other internet of things (IoT) scenarios in machine communications. By highlighting the key requirements and the major technical gaps of M2M in industrial applications, this article describes a collaboration-oriented M2M (CoM2M) messaging mechanism focusing on flexible connectivity and discovery, ubiquitous messaging, and semantic interoperability that are well suited for the production line-scale interoperability of manufacturing applications. The designs toward machine collaboration and data interoperability at both the communication and semantic level are presented. Then, the application scenarios of the presented methods are illustrated with a proof-of-concept implementation in the PicknPack food packaging line. Eventually, the advantages and some potential issues are discussed based on the PicknPack practice

The Impact of Industry 4.0 on Supply Chain Capability and Supply Chain Resilience: A Dynamic Resource-Based View

Industry 4.0, a collection of emerging intelligent and digital technologies, has been the main interest of both researchers and practitioners in operations management (OM) in recent years. Despite its proclaimed effectiveness in supply chain (SC) management, empirical studies examining the effects of Industry 4.0 adoption on SC resilience have been underrepresented in the current OM literature. In our study, we explore the effects of 16 Industry 4.0 technologies and IT advancement concerning SC resilience through the mediating roles of SC capabilities with respect to SC collaboration and SC visibility. Following the dynamic resource-based view (RBV), we regard Industry 4.0 adoption and IT advancement as two important IT resources with heterogeneity, SC collaboration and SC visibility as essential SC dynamic capabilities, and SC resilience as competitive advantages. We suggest the combination and evolution of IT resources and dynamic SC capabilities helps firms obtain the competitive advantage regarding SC resilience. Using data from a survey of 408 Chinese manufacturing firms, we reveal Industry 4.0 adoption is positively related to IT advancement and that Industry 4.0 has a nonsignificant impact on SC capabilities, whereas IT advancement has a positive impact on SC capabilities. Additionally, both SC collaboration and visibility positively influence SC resilience and significantly mediate the impacts of Industry 4.0 and IT advancement on SC resilience. Our study offers an enhanced understanding of the specific flows between Industry 4.0 and SC resilience and provides nuanced insights for both literature and practice

The impact of industry 4.0 on supply chain capability and supply chain resilience: A resource-based view

Industry 4.0, a collection of emerging intelligent and digital technologies, has been the main interest of both researchers and practitioners in operations management (OM) in recent years. Despite its proclaimed effectiveness in supply chain (SC) management, empirical studies examining the effects of Industry 4.0 adoption on SC resilience have been underrepresented in the current OM literature. In our study, we explore the effects of 16 Industry 4.0 technologies and IT advancement concerning SC resilience through the mediating roles of SC capabilities with respect to SC collaboration and SC visibility. Following the dynamic resource-based view (RBV), we regard Industry 4.0 adoption and IT advancement as two important IT resources with heterogeneity, SC collaboration and SC visibility as essential SC dynamic capabilities, and SC resilience as competitive advantages. We suggest the combination and evolution of IT resources and dynamic SC capabilities helps firms obtain the competitive advantage regarding SC resilience. Using data from a survey of 408 Chinese manufacturing firms, we reveal Industry 4.0 adoption is positively related to IT advancement and that Industry 4.0 has a nonsignificant impact on SC capabilities, whereas IT advancement has a positive impact on SC capabilities. Additionally, both SC collaboration and visibility positively influence SC resilience and significantly mediate the impacts of Industry 4.0 and IT advancement on SC resilience. Our study offers an enhanced understanding of the specific flows between Industry 4.0 and SC resilience and provides nuanced insights for both literature and practice

Internet of Things and Sensors Networks in 5G Wireless Communications

The Internet of Things (IoT) has attracted much attention from society, industry and academia as a promising technology that can enhance day to day activities, and the creation of new business models, products and services, and serve as a broad source of research topics and ideas. A future digital society is envisioned, composed of numerous wireless connected sensors and devices. Driven by huge demand, the massive IoT (mIoT) or massive machine type communication (mMTC) has been identified as one of the three main communication scenarios for 5G. In addition to connectivity, computing and storage and data management are also long-standing issues for low-cost devices and sensors. The book is a collection of outstanding technical research and industrial papers covering new research results, with a wide range of features within the 5G-and-beyond framework. It provides a range of discussions of the major research challenges and achievements within this topic

Internet of Things and Sensors Networks in 5G Wireless Communications

This book is a printed edition of the Special Issue Internet of Things and Sensors Networks in 5G Wireless Communications that was published in Sensors

Internet of Things and Sensors Networks in 5G Wireless Communications

This book is a printed edition of the Special Issue Internet of Things and Sensors Networks in 5G Wireless Communications that was published in Sensors