An artificial intelligence-based collaboration approach in industrial IoT manufacturing : key concepts, architectural extensions and potential applications

The digitization of manufacturing industry has led to leaner and more efficient production, under the Industry 4.0 concept. Nowadays, datasets collected from shop floor assets and information technology (IT) systems are used in data-driven analytics efforts to support more informed business intelligence decisions. However, these results are currently only used in isolated and dispersed parts of the production process. At the same time, full integration of artificial intelligence (AI) in all parts of manufacturing systems is currently lacking. In this context, the goal of this manuscript is to present a more holistic integration of AI by promoting collaboration. To this end, collaboration is understood as a multi-dimensional conceptual term that covers all important enablers for AI adoption in manufacturing contexts and is promoted in terms of business intelligence optimization, human-in-the-loop and secure federation across manufacturing sites. To address these challenges, the proposed architectural approach builds on three technical pillars: (1) components that extend the functionality of the existing layers in the Reference Architectural Model for Industry 4.0; (2) definition of new layers for collaboration by means of human-in-the-loop and federation; (3) security concerns with AI-powered mechanisms. In addition, system implementation aspects are discussed and potential applications in industrial environments, as well as business impacts, are presented

Measuring the Firm Competitiveness by the Capacity of Operational Flexibility Using Industry 4.0

openL'integrazione delle tecnologie dell'Industria 4.0 nei moderni processi produttivi ha innescato una profonda trasformazione nelle pratiche industriali globali. Questa tesi si concentra su queste trasformazioni nell'illustre panorama tedesco, pioniere nell'innovazione manifatturiera e nell'adozione di Industria 4.0. La tesi esplora il modo in cui la gestione dei dati e la personalizzazione influiscono sulla competitività dell'impresa grazie alla flessibilità operativa che comportano. L'obiettivo fondamentale di questa ricerca è duplice: esplorare l'importanza delle capacità di gestione dei dati nella produzione intelligente e il loro legame con le strategie di personalizzazione e la flessibilità operativa, e mostrare la loro influenza combinata sulla competitività delle aziende manifatturiere tedesche. Analizzando il ruolo della gestione strategica dei dati insieme a un'efficace personalizzazione, questo studio cerca di scoprire i meccanismi che alimentano una migliore competitività nel paradigma dell'industria 4.0. Con la rivoluzione dello stile manifatturiero dalla produzione di massa a quella personalizzata, la determinazione delle richieste e delle preferenze dei clienti è diventata progressivamente importante per i produttori. Verrà discusso l'effetto delle prestazioni della rete di dati di produzione per la personalizzazione di massa e le strategie di adattamento per diventare più flessibili e competitivi.The integration of Industry 4.0 technologies into modern manufacturing processes has ignited a profound transformation in global industrial practices. This thesis focuses on these transformations in Germany's distinguished landscape—an eminent pioneer in manufacturing innovation and Industry 4.0 adoption. It explores how data management and customization affect firm competitiveness by operational flexibility they bring with. The fundamental objective of this research is twofold: to explore the significance of data management capabilities in smart manufacturing and its link to customization strategies and operational flexibility, and to show their combined influence on firm competitiveness among German manufacturing firms. By dissecting the role of strategic data management in tandem with effective customization, this study endeavors to uncover the mechanisms that fuel improved competitiveness in the industry 4.0 paradigm. With the revolution in manufacturing style from mass to customized production, determining customer demands and preferences have grown gradually significant for the manufacturers. The effect of manufacturing data network performance for mass customization and adaptive strategies to become more flexible and competitive will be discussed

Digital technologies catalyzing business model innovation in supply chain management - the case of parcel lockers as a solution for improving sustainable city mobility

The rise of information technologies pushes companies into digital restructuring. Organizations integrating emerging technologies into their supply chains can boost efficiency by streamlining processes and making more informed decisions using predictive analytics. This research dis-cusses major enablers for digital transformation and presents the application of those along different parts of a digital supply chain, while focusing on technical characteristics, implementations, and impact on organizational capabilities and strategies. The parcel lockers are a technology that sustains and improves last-mile delivery. By combining it with night-time delivery improves the City's Sustainable Mobility and, therefore, reduces the local emissions and city congestion

The Boost 4.0 Experience

In the last few years, the potential impact of big data on the manufacturing industry has received enormous attention. This chapter details two large-scale trials that have been implemented in the context of the lighthouse project Boost 4.0. The chapter introduces the Boost 4.0 Reference Model, which adapts the more generic BDVA big data reference architectures to the needs of Industry 4.0. The Boost 4.0 reference model includes a reference architecture for the design and implementation of advanced big data pipelines and the digital factory service development reference architecture. The engineering and management of business network track and trace processes in high-end textile supply are explored with a focus on the assurance of Preferential Certification of Origin (PCO). Finally, the main findings from these two large-scale piloting activities in the area of service engineering are discussed.publishersversionpublishe

Reviewing literature on digitalization, business model innovation, and sustainable industry : past achievements and future promises

Digitalization is revolutionizing the way business is conducted within industrial value chains through the use of Internet of Things (IoT) technologies, intensive data exchange and predictive analytics. However, technological application on its own is not enough; profiting from digitalization requires business model innovation such as making the transition to advanced service business models. Yet, many research gaps remain in analyzing how industrial companies can leverage digitalization to transform their business models to achieve sustainability benefits. Specifically, challenges related to value creation, value delivery, and value capture components of business model innovation need further understanding as well as how alignment of these components drive sustainable industry initiatives. Thus, this special issue editorial attempts to take stock of the emerging research field through a literature review and providing a synthesis of special issue contributions. In doing so, we contribute by developing a framework that communicates and sets the direction for future research by linking digitalization, business model innovation, and sustainability in industrial settings.fi=vertaisarvioimaton|en=nonPeerReviewed

Investigating the Factors, Challenges, and Role of Stakeholders in Implementing Industry 5.0 and Its Impact on Supply Chain Operations: A Study of the Global Agri-Food Supply Chain

Industry 5.0 may assist businesses to become more constructive and competitive in the global economy in the Fifith Industrial Revolution era. Therefore, a critical review of prior literature is presented in this paper to examine how Industry 5.0 will impact supply chain operations within the agricultural sector. Additionally, it examines influencing factors, challenges, stakeholder roles, and recommendations identified from the literature. Industry 5.0 has multiple benefits for the agri-food sector such as improved agility, responsiveness, efficiency, productivity, precise decision-making, as well as cost-effectiveness

DevOps for Digital Leaders

DevOps; continuous delivery; software lifecycle; concurrent parallel testing; service management; ITIL; GRC; PaaS; containerization; API management; lean principles; technical debt; end-to-end automation; automatio

Digitalisation of Development and Supply Networks: Sequential and Platform-Driven Innovations

We draw from an eight-year dataset of 98 organisational entities involved in pre-competitive innovation networks across the UK pharmaceutical sector. These data map into three networks that are representative of: (i) a product development-led sequential pathway that begins with digitalised product development, followed by digitalisation of supply networks, (ii) a supply network-led sequential pathway that starts with digitalised supply networks, followed by digitalisation of product development, and (iii) a parallel — platform-driven — pathway that enables simultaneous digitalisation of development, production, and supply networks. We draw upon extant literature to assess these network structures along three dimensions — strategic intent, the integrative roles of nodes with high centrality, and innovation performance. We conduct within-case and cross-case analyses to postulate 10 research propositions that compare and contrast modalities for sequential and platform-based digitalisation involving collaborative innovation networks. With sequential development, our propositions are congruent with conventional pathways for mitigating innovation risks through modular moves. On the other hand, we posit that platform-based design rules, rather than modular moves, mitigate the risks for parallel development pathways, and lead to novel development and delivery mechanisms