Industry 4.0 leads to the digitalization era. Everything is digital; business models, environments, production systems, machines, operators, products and services. It’s all interconnected inside the ...digital scene with the corresponding virtual representation. The physical flows will be mapped on digital platforms in a continuous manner. On a higher level of automation, many systems and software are enabling factory communications with the latest trends of information and communication technologies leading to the state-of-the-art factory, not only inside but also outside factory, achieving all elements of the value chain on a real-time engagement. Everything is smart. This disruptive impact on manufacturing companies will allow the smart manufacturing ecosystem paradigm. Industry 4.0 is the turning point to the end of the conventional centralized applications. The Industry 4.0 environment is scanned on this paper, describing the so-called enabling technologies and systems over the manufacturing environment.
Smart Factory has already become an irresistible entity in manufacturing, which has led to a much wider scope of existing manufacturing innovations and the achievement of qualitative improvements. ...Unsurpassed progress has been made in the manufacturing sector through the combination of professional know-how and advanced IT, and HACCP has already thoroughly managed all steps from raw materials for agricultural and livestock products to processing, packaging and distribution before digitalization. Sanitary issues in each country have now been raised to the level of national security under the influence of COVID-19. Although HACCP is already well-managed by country, we have looked at this discussion and detailed technological transformation from a digital data perspective, as it is now possible to collect, store, record and report data to government offices more smartly in line with technological advances in smart factories. The intersection of smart factories and HACCPs is consistent in terms of data collection, storage and utilization. Furthermore, the addition of Blockchain technology to strictly prevent data forgery is more interesting. Although the use of Blockchain in general factories has been relatively insignificant, it is expected that the use of Blockchain technology will be expanded through smart HACCP, which forms the interface between smart factory technology and HACCP, and that agricultural, livestock and household factories will introduce more smart factories.
Overview: The development of novel digital technologies connected to the Internet of Things, along with advancements in artificial intelligence and automation, is enabling a new wave of manufacturing ...innovation. "Smart factories" will leverage industrial equipment that communicates with users and with other machines, automated processes, and mechanisms to facilitate real-time communication between the factory and the market to support dynamic adaptation and maximize efficiency. Smart factories can yield a range of benefits, such as increased process efficiency, product quality, sustainability, and safety and decreased costs. However, companies face immense challenges in implementing smart factories, given the large-scale, systemic transformation the move requires. We use data gathered from in-depth studies of five factories in two leading automotive manufacturers to analyze these challenges and identify the key steps needed to implement the smart factory concept. Based on our analysis, we offer a preliminary maturity model for smart factory implementation built around three overarching principles: cultivating digital people, introducing agile processes, and configuring modular technologies.
•Augmented Reality (AR) is a major part of industry 4.0 advancements.•While AR is not ready yet for industrial deployment in some areas, it is already used in others.•Hardware and software still ...require improvements in certain areas of AR.•The context of research concerning AR is getting increasingly broader as its implementation rises.•The future research needs to focus on intelligent manufacturing applications of AR.
Industry increasingly moves towards digitally enabled ‘smart factories’ that utilise the internet of things (IoT) to realise intelligent manufacturing concepts like predictive maintenance or extensive machine to machine communication. A core technology to facilitate human integration in such a system is augmented reality (AR), which provides people with an interface to interact with the digital world of a smart factory. While AR is not ready yet for industrial deployment in some areas, it is already used in others. To provide an overview of research activities concerning AR in certain shop floor operations, a total of 96 relevant papers from 2011 to 2018 are reviewed. This paper presents the state of the art, the current challenges, and future directions of manufacturing related AR research through a systematic literature review and a citation network analysis. The results of this review indicate that the context of research concerning AR gets increasingly broader, especially by addressing challenges when implementing AR solutions.
•Identified 16 specific requirements for manufacturing Small and Medium-sized Enterprises (SME).•Literature review of 15 Smart Manufacturing / Industry maturity/assessment models.•Identified specific ...research gaps by matching SM maturity models to SME requirements.
The objective of this paper is to critically review currently available Smart Manufacturing (SM) and Industry 4.0 maturity models, and analyze their fit recognizing the specific requirements of Small and Medium-sized Enterprises (SMEs). To this end, this paper presents features that are characteristic for SMEs and identify research gaps needed to be addressed to successfully support manufacturing SMEs in their progress towards Industry 4.0. The results of this study show that only a limited number of the SM and Industry 4.0 roadmaps, maturity models, frameworks and readiness assessments that are available today reflect the specific requirements and challenges of SMEs. The main findings include: (1) the current standard starting “level 1″ (base level) of most maturity models appears to be disconnected from the real digitization and smart manufacturing maturity level of many SMEs. Therefore, we propose a “level 0″ specifically designed to reflect the ‘real - base level’ for SMEs; (2) the transition from this new base level, “level 0″, to the current standard “level 1”, requires significant effort including a mind-set change; (3) maturity models and readiness assessments can be associated with an SM toolkit, and (4) SMEs need to develop their own, unique SM or Industry 4.0 vision and roadmap. This study provides insights that help towards developing a realistic SM (Industry 4.0) maturity model for SMEs that reflects their industrial realities more accurately. With the help of SM maturity models that are more customized to the SME specific requirements, the SMEs’ stakeholders will be able to better define their SM (Industry 4.0) vision, roadmap, and strategic projects. It will ultimately lower the entry barrier and reduce the risk of the transition process towards SM and Industry 4.0 and support the critical change in culture. Summarizing, we identified manufacturing SMEs’ specific requirements, conducted a literature review of current SM maturity models, and discussed how these maturity models reflect the SME specific requirements.
A cyber-physical system (CPS) is a new trend in smart manufacturing-related research, where the physical system acts as a data access role with sensors and communication systems to collect real-world ...information and communicate to computation modules (i.e. cyber layer), which further analyse and notify the findings to the corresponding physical systems through multiple feedback loops. This paper develops a conceptual framework for a new paradigm called smart factory based on CPS by applying virtual-real mapping and fusion, digital twin, big data-driven, virtualisation, and edge-to-cloud service technology to the manufacturing system. The definitions, characteristics, architectures and previous case studies on smart factory based on CPS are explained in detail. In the paradigm, the digital twin merges the physical system modelling and cyberspace simulation to provide an intelligence solution simulation analysis ability. This generates a variety of digital designs of production processes, quality, cost, efficiency and environmental impact analysis about smart factory business mode in the preproduction phase based on big data which can be analysed, and provide authoritative solutions for actual physical space. The proposed system is applied and validated in a real case study from the circuit breaker production industry.
•Identification of characteristics of CPSs in Manufacturing.•Distinction in “technological” characteristics of CPSs, intended as technological systems implemented within a factory – and “operations ...management” characteristics to build CPS-based smart factories.•Synthesis of the findings in a comprehensive schema which visually distinguishes between technological characteristics of CPSs and operations management characteristics, to build future CPS-based smart factories.•Identification of priorities for future research on CPS-based smart factories.
The emergence of new technologies is providing new ways to compete in the current context of changeable and unpredictable market requirements. The focus of this paper is on Cyber-Physical Systems (CPSs), as one of the most promising transformative technological concept of such a context, thus considered by literature as the building blocks of future smart factories. However, CPSs are still in their conceptualization phase. To this end, much literature effort has been put on their technological characterization, while there is a lack of knowledge on the operations management characterization to manage such new systems. To contribute in this latter direction, this paper reviews literature in order to distinguish between technological characteristics of CPSs and operations management characteristics to build future CPS-based smart factories. This paper remarks the need for research on operations management characteristics as these may be the ones actually leading operations managers to the concrete implementation of CPS-based factories in manufacturing.
The globalization of products and markets increases the distance between the origin of products and consumers. This leads to a condition where customers don't have information about the origins of ...their products. Thus, traceability has become an essential sub-system of manufacturing supply chain management. However, due to globalization and complexity of supply chain interactions among the suppliers and manufacturing enterprises, it is hard to pinpoint the exact contributions of different actors in a supply chain. Integrated supply network structure with suitable visibility and usage of real time data transfer is another area of great importance. This paper focuses on how NFT (Non-Fungible Token) coupled with smart contracts could utilize blockchain to make it easier to track the products in a supply chain. Explaining how NFT's could help in tracking the contributions of different stakeholders in a supply chain by tracking the product throughout the entire process of sourcing, production, and sale by using a digital twin. In a manufacturing supply chain enabled by NFT Technology, whenever raw materials are transferred and processed through the supply chain, an NFT would be attached to its digital twin which will capture the created values. Each NFT can easily and uniquely be known by its data stored. Data would be updated based on real time information and will enable the stakeholders to trace the product information about how much each company has contributed to the produced products. The data stored in the form of a smart contract in the blockchain prevents the data being entered from being destroyed, eliminated, or changed without permission. Thus, there is a secure data flow among different stakeholders.
The work describes some peculiar aspects of industrial research project mainly based on the implementation of technologies enabling Industry 4.0 paradigm in the region Calabria, Italy. In particular, ...the focus is on the I4.0 Framework, machine interconnection and the role of Enterprise Resource Planning (ERP) systems. Since Calabria is a less developed Region, the adoption of Industry 4.0 technologies can be a greater opportunity for local small and medium enterprises (SMEs) to boost their manufacturing processes and, consequently, economic development. The Framework 4.0 offers a structured approach to integrate various industrial components, optimising production lines and supply chains. Machine interconnection is a crucial aspect of Industry 4.0, creating intelligent networks that enable real-time data analysis and autonomous decision-making. By incorporating Internet of Things (IoT) sensors and data analytics, Calabrian industries can achieve enhanced productivity and predictive maintenance. Integration with the Framework 4.0 provides end-to-end visibility, supporting better planning, informed decision-making and improved collaboration. However, the adoption of Industry 4.0 in Calabria presents challenges, including the need for substantial investments in technology and infrastructure, upskilling the workforce and addressing cybersecurity vulnerabilities. In conclusion, Industry 4.0 holds transformative potential for Calabria's industries and the ones belonging to other less developer European regions; leveraging the Framework 4.0, machine interconnection, and ERP systems, the regions can achieve increased competitiveness and sustainable economic growth in the Fourth Industrial Revolution.
To make production more competitive, the new factories need to be built according to the guidelines of smart factories. The existing literature describes different approaches how to plan and design ...the smart factories. Therefore, the paper presents a step-by-step methodology for efficient planning of smart factory from the initial idea to the final realization in the real environment. The methodology includes eight crucial steps, which covers organizing the workshops in the company, explaining terms and definitions commonly used for smart factories, analysing and defining the employee's competences and the technological level of the company, analysing the possibilities of integration of smart I4.0 technologies, developing of digital twins at different levels, designing the visualization and finally building the smart factory in a real environment. The methodology is designed according to the needs of several partners and manufacturers, which are collaborating within the various European projects related to the smart factories.
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