Digital Manufacturing

Knitwear is a consolidated industry in Italy and, at the same time, a typical expression of the Made in Italy paradigm linked to the ideas of craftsmanship. While, on the one hand, knitwear is associated with the idea of craft and manufacturing traditions, on the other hand, it is nowadays produced by numerical control machines (CNC) where the technological contribution and the level of automation are very relevant. The convergence of physical and digital environments, at the heart of the Fashion Industry 4.0 debate, is an established feature of knitwear design practice. In the contemporary industrial scenario, knitted items are produced on digitally programmed machines through sophisticated software, and the manual contribution of the individual operator during the knitting phase is reduced to a minimum. In the light of these premises, this contribution questions the opportunity and value of the integration of digital technologies in the storytelling of traditional manufacturing without losing the power to evoke Made in Italy's values such as quality, aesthetic refinement, and exclusivity. To analyze these issues, the authors report the case study of SMT -Società Manifattura Tessile, a leading knitting company where the technological presence equals that of traditional manufacturing craftmanship, keeping both elements at balance. The case study suggests the importance of the contemporary knitting craftsman to increasingly develop communication skills to make the relationship between technology and manufacturing explicit and possibly smoothly blend it with the Made in Italy archetypes.

Stucco jobs make a considerable share in the total scope of finishing construction operations. Stucco jobs represent an intricate technology involving a great number of manual operations. Mechanization of stucco operations allows reducing labor costs on their performance and increasing labor productivity. This paper is aimed at the selection of optimal workplace practices during façade stucco jobs using powered tools to treat concrete and brick surfaces of outer walls of buildings and facilities. The paper discusses organizational and technological solutions in performing façade stucco jobs including workplace management, workflow process, and equipment and tools utilized. An overview of existent powered tools for the treatment of concrete and brick surfaces is given; the results of undertaken testing of milling tools for the treatment of concrete and reinforced concrete structures are analyzed. Based on the study findings, the authors have concluded that in the improvement of productivity and quality of façade finishing jobs, a great role belongs to correct (rational) organization of labor using the straightforward segmented workflow, performance of works by specialized crews of workers, and utilization of high-performance tools and appliances. Different locations and composition of surfaces being stuccoed require different types of powered tools. The development of new prototypes and the improvement of existent powered tools for surface treatment allows increasing efficiency and reducing the cost of work. New options of star inertia mills made of different materials for powered tools equipped with a flexible roll are suggested.

This paper investigates the evolving synergy between humans, extended reality (XR), and robotics in the Architecture, Engineering, Construction, and Operation (AECO) sector, proposing a shift from augmentation toward cointelligent autonomy. While emerging technologies such as AI, XR, and robotics offer transformative potential for construction, they are often implemented without fully engaging human creativity, craftsmanship, and decision-making. We introduce a co-intelligent framework in which human and machine intelligences collaborate-each contributing distinct capabilities across the design-to-production continuum. Drawing from experimental prototypes and prior research, we demonstrate how XR can enhance human intuition and spatial reasoning through immersive guidance. AI and robotics support autonomy in repetitive or complex fabrication tasks. Case studies include XR-assisted steam-bending, real-time robotic training via imitation learning, and AI-driven assembly generation using generative design models. These examples highlight how humans and machines can share perception, intent, and action through mixed-reality environments. We argue that technological augmentation can democratize access to advanced fabrication by lowering the skill barrier and fostering new creative roles rather than displacing human labor. The paper offers a theoretical model for shared agency, where cognitive and physical augmentation blend with machine perception and autonomy to form a seamless co-intelligent workflow. By reimagining the architect as an orchestrator of human-machine collaboration, we propose a hybrid design ecology in which intuition, ethics, and social values remain central. This research lays the groundwork for scalable, inclusive, and adaptive architectural practices responsive to the evolving nature of work, technology, and the built environment.

Throughout history, technology has had a crucial influence on the development of our society. Different eras have been defined by sets of technological advancements, which at the same time had a profound impact on the built environment and construction. It has been proposed that, after the internet age, we are entering a new era-the 'Augmented Age' (King, 2016), while physicist Michio Kaku argues for the future in which architects rely heavily on Augmented Reality technologies (Kaku, 2015). Machines have become an inseparable part of our daily life. We are immersing ourselves into rapidly developing mixed realities, with portable devices (smartphones, tablets etc.) augmenting our perception of the environment. Barriers between humans and machines are increasingly blurred, and the modes of interaction between them becoming progressively sophisticated at a rapid pace. The future of manufacturing jobs will be embedded with technological add-ons that will augment the capabilities of the workers. This augmentation will come from the XR devices, including (Augmented and Mixed reality) and human-machine collaboration and automation. This relation between technology and human labour will have a high impact on architecture. It will change the traditional roles in the production chain, affecting everything from the way we design to the ways we manufacture. Concepts like designer and artisan are again brought together through Immersive technology. In the same way, the barriers between user and designer are continuously diluted through these technological advances. This paper reflects on the current state of XR technologies in architecture and how they will influence design and production.

Quality management decisions require precise and reliable measuring results. In manufacturing and assembling processes, production metrology plays a significant role in generating such results. For this reason, coordinate measuring machines (CMMs) are used more and more often due to their universality and flexibility. The quality of results generated by CMMs is highly dependent on the skills of the CMM operators. In order to minimize technicians' influence, they need to be provided with the necessary knowledge to carry out such tasks. Efforts to introduce training at a national level led to the European project EUKOM, which developed a usercentred training course using new learning methods to meet the demands of CMM operators [1]. This project led to the foundation of the registered association CMTrain. Today, this association offers manufacturer-independent courses in coordinate metrology and it is continually improving learning methods and learning contents.

The availability of relatively capable and inexpensive hardware components has made it feasible to consider large-scale systems of autonomous aquatic drones for maritime tasks. In this paper, we present the CORATAM and HANCAD projects, which focus on the fundamental challenges related to communication and control in swarms of aquatic drones. We argue for: (i) the adoption of a heterogeneous approach to communication in which a small subset of the drones have long-range communication capabilities while the majority carry only short-range communication hardware, and (ii) the use of decentralized control to facilitate inherent robustness and scalability. A heterogeneous communication system and decentralized control allow for the average drone to be kept relatively simple and therefore inexpensive. To assess the proposed methodology, we are currently building 25 prototype drones from off-the-shelf components. We present the current hardware designs and discuss the results of simulation-based experiments involving swarms of up to 1,000 aquatic drones that successfully patrolled a 20 km-long strip for 24 hours.

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

The digital transformation of manufacturing (a phenomenon also known as “Industry 4.0” or “Smart Manufacturing”) is finding a growing interest both at practitioner and academic levels, but is still in its infancy and needs deeper investigation. Even though current and potential advantages of digital manufacturing are remarkable, in terms of improved efficiency, sustainability, customization, and flexibility, only a limited number of companies has already developed ad hoc strategies necessary to achieve a superior performance. Through a systematic review, this study aims at assessing the current state of the art of the academic literature regarding the paradigm shift occurring in the manufacturing settings, in order to provide definitions as well as point out recurring patterns and gaps to be addressed by future research. For the literature search, the most representative keywords, strict criteria, and classification schemes based on authoritative reference studies were used. The fin...

Knitwear is a consolidated industry in Italy and, at the same time, a typical expression of the Made in Italy paradigm linked to the ideas of craftsmanship. While, on the one hand, knitwear is associated with the idea of craft and manufacturing traditions, on the other hand, it is nowadays produced by numerical control machines (CNC) where the technological contribution and the level of automation are very relevant. The convergence of physical and digital environments, at the heart of the Fashion Industry 4.0 debate, is an established feature of knitwear design practice. In the contemporary industrial scenario, knitted items are produced on digitally programmed machines through sophisticated software, and the manual contribution of the individual operator during the knitting phase is reduced to a minimum. In the light of these premises, this contribution questions the opportunity and value of the integration of digital technologies in the storytelling of traditional manufacturing without losing the power to evoke Made in Italy's values such as quality, aesthetic refinement, and exclusivity. To analyze these issues, the authors report the case study of SMT -Società Manifattura Tessile, a leading knitting company where the technological presence equals that of traditional manufacturing craftmanship, keeping both elements at balance. The case study suggests the importance of the contemporary knitting craftsman to increasingly develop communication skills to make the relationship between technology and manufacturing explicit and possibly smoothly blend it with the Made in Italy archetypes.

This paper explores questions of materiality in contemporary architecture in
light of emerging developments in the discipline, building on the author’s
previous work on the subject. After presenting a conceptual distinction between
matter, material, and materiality—here defined as a socially constructed,
relational phenomenon—the paper examines ongoing and potential
shifts in the materiality of buildings driven by the rise of digital design and
the adaptation to the challenges of the Anthropocene. Key topics include the
movement from form to process in contemporary design, the renewed centrality
of materials, the “material turn” in the humanities and social sciences,
and the return of ornament. In conclusion, architecture is described as both a
medium and a regulator of the human relationship to the material world.

OECD Working Papers should not be reported as representing the official views of the OECD or of its member countries. The opinions expressed and arguments employed are those of the authors. Working Papers describe preliminary results or research in progress by the author(s) and are published to stimulate discussion on a broad range of issues on which the OECD works. Comments on Working Papers are welcomed, and may be sent to Directorate for Science, Technology and Innovation, OECD,

The paper analyses the contribution of Technological and Environmental Design and Architecture to overcoming poverty, one of the most urgent contemporary challenges, in line with Goal 1 of the UN Agenda 2030. Contextualising this issue in the global scenario, this paper critically illustrates some international events, research and good practices that are replicable and adaptable in similar contexts and are contributing to the cultural debate and action to eradicate poverty. It will be highlighted how the two disciplines can act in synergy as a pedagogical and economic tool, capable of promoting a culture of dignity and possibility for the design of architectures, objects, and societies, influencing, in a multidimensional way, the impact of poverty on people’s lives.

Este escrito comenta el concepto de organicismo digital en la arquitectura y el diseño, como un consecuente del organicismo iniciado en los tiempos del Art Nouveau, y desarrollado también, aunque mínimamente, a lo largo de todo el siglo XX. Implementado este, a finales del siglo XX y principios del XXI, con los nuevos medios digitales, que empiezan a aparecer entonces, pudiendo añadírsele el adjetivo de digital. Queda así como una fusión entre los principios de la naturaleza, bioaprendidos, y las capacidades tecnológicas actuales: inspirado por las formas y sistemas orgánicos de los seres vivos, se corrobora que el uso de herramientas digitales avanzadas, como la inteligencia artificial, algoritmos generativos y la impresión 3D, permite aplicar, replicar e incluso mejorar esos principios naturales en la creación de entornos construidos. El organicismo digital no sólo bioaprende de las formas naturales, sino que también adopta la lógica funcional y la eficiencia que subyacen en los sistemas biológicos. Se argumenta que la arquitectura y el diseño pueden evolucionar hacia soluciones más sostenibles, adaptativas y eficientes, integrando procesos y características propias de la biología, y que a su vez se integren de manera más armónica en su entorno, más responsable con el medio ambiente, más eficiente en el uso de recursos.

The increasing consumer demand for sustainable textiles has led companies to invest in organic and recycled materials while adopting green manufacturing processes to reduce their environmental footprint. The textile industry is exploring innovative approaches such as upcycling and green chemistry to regenerate textile waste fibers sustainably. And these efforts are aimed at transforming the fashion and textile industry towards a more sustainable and eco-friendly future. To achieve this the textile industries, have to leverage on the technological advancements available which one of it is, various applications of ML models for a more accurate and efficient results. This study focused on the application of a hybrid machine learning model which is the combination of Seasonal Auto-Regressive Integrated Moving Average (SARIMA) model and Long Short-Term Memory (LSTM) networks for Accurate Production Forecasting in Textile Industry. Research studies reviewed gave important insights into the study. This study adopted a quantitative research approach, using a five-year historical production data from a textile company to train and evaluate the hybrid ML model. The research design includes data collection, preprocessing, model training, evaluation, and comparative analysis. The research analysis presents a well-performing predictive model, as evidenced by the high R-squared value of 0.87, relatively low root mean squared error (RMSE) of 1.23, low mean squared error (MSE) of 1.51, and low mean absolute error (MAE) of 0.98. However, the residual time series and the predicted and actual values plots suggest possible degradation in the model's performance over time.

Digital manufacturing has been considered, over the last decade, as a highly promising set of technologies for reducing product development times and cost as well as for addressing the need for customization, increased product quality, and faster response to the market. This paper describes the evolution of information technology systems in manufacturing, outlining their characteristics and the challenges to be addressed in the future. Together with the digital manufacturing and factory concepts, the technologies considered in this paper include computer-aided design, engineering, process planning and manufacturing, product data and life-cycle management, simulation and virtual reality, automation, process control, shopfloor scheduling, decision support, decision making, manufacturing resource planning, enterprise resource planning, logistics, supply chain management, and e-commerce systems. These technologies are discussed in the context of the digital factory and manufacturing con...

Among the challenges posed by the new industrial revolution-Industry 4.0 is the integration of systems associated with manufacturing. In this sense, the inspection process assumes an important role since it provides the information base to make the decisions that allow reaching the design and quality specifications. From the manufacturing point of view, Additive Manufacturing (AM) contains the potential to meet production demands by making efficient use of resources, reducing manufacturing time, and enabling the manufacture of complex parts. The idea of integrating the inspection process with a robotic system for additive manufacturing seeks both to improve the quality of the parts produced and to find methods to optimize the process and create a sustainable system. However, to make this combination a reality, it is necessary to face the barriers posed by the lack of integration of the information produced by the different computerized systems throughout the life cycle of the product. Thus, there is no integration of feedback information from shop-floor necessary for inspection and validation of the part manufactured with AM, which does not allow a closed-loop digital thread. Concerning this, the present article proposes the development of an integration strategy with a digital data model based on STEP-NC (Standard for the Exchange of Product model data -Numerical Control) for closed-loop AM. The data models in STEP-NC for the AM and inspection tasks it develops, highlighting the scenario of integrated feedback for the closed-loop AM digital thread. Are presented the architecture of integration validated by using an open AM platform and the results of error control over the parts.

Generative artificial intelligence is transforming digital manufacturing by introducing novel capabilities that go beyond traditional AI approaches focused on classification and prediction. As these technologies mature from experimental concepts to practical solutions, they revolutionize product design, factory floor operations, and supply chain management. Manufacturing organizations implementing generative AI are experiencing significant benefits across the value chain, from reduced design cycles and improved material efficiency to optimized production scheduling and enhanced supply chain resilience. Despite implementation challenges related to data quality, computational requirements, and human-AI collaboration, structured solutions are emerging that enable broader adoption. Integrating multimodal systems, transfer learning techniques, and potentially quantum computing capabilities promises to accelerate these transformations further, making generative AI a cornerstone of manufacturing excellence and competitive advantage in the Industry 4.0 era.

This research investigates the organization and movement of root systems, emphasizing their ability to connect, adhere, and interact with organisms while maintaining self-awareness. Root movements depend on capillary adhesion, enabling the fixation and elevation of natural elements such as moss, spider webs, and raindrops. The research of biotectonics introduces an innovative approach to surface adaptation, where upper layers emerge from lower layers, facilitating root colonization through site-specific knowledge. This layered integration is not an imitation but a self-generating system, requiring collaboration with biological intelligence. Scale is not only a unit of measurement but a medium for interaction between natural and artificial systems. The project examines the adaptation of natural organisms to physical surfaces, analyzing their behavioral patterns and constructing multi-scaled prototypes to explore cross-scale interactions. The research integrates digital modeling and artificial intelligence to map invisible traces in physical models, encoding root dynamics within structured surfaces. Interactive architectural facades are designed by leveraging biological and structural properties of root systems, forming adaptive environments responsive to external conditions. By synthesizing biotectonic principles, the study explores the role of frequency and density in shaping surface formations that accommodate living organisms. Surfaces are reimagined as dynamic, bio-integrated structures that interact with environmental factors such as soil moisture, sunlight, and atmospheric changes. The ultimate goal is to redefine architecture through biologically driven design methodologies, creating living surfaces that evolve, respond, and grow, bridging the gap between built environments and natural ecosystems.

Food and drink is the largest manufacturing sector worldwide and has significant environmental impact in terms of resource use, emissions, and waste. However, food and drink manufacturers are restricted in addressing these issues due to the tight profit margins they operate within. The advances of two industrial digital technologies, sensors and machine learning, present manufacturers with affordable methods to collect and analyse manufacturing data and enable enhanced, evidence-based decision making. These technologies will enable manufacturers to reduce their environmental impact by making processes more flexible and efficient in terms of how they manage their resources. In this article, a methodology is proposed that combines online sensors and machine learning to provide a unified framework for the development of intelligent sensors that work to improve food and drink manufacturers' resource efficiency problems. The methodology is then applied to four food and drink manufact...

This pilot study develops a process to evaluate in-situ defect detection and self-healing in Ti-6Al-4V fabricated using laser-based powder bed fusion. A tailor-made test specimen was designed and manufactured for the nanofocus tube X-ray computed tomography (XCT) system. In situ optical tomography was used to capture infrared images containing heat signatures of the hot laser interaction zone. Depicting natural process variation, defective regions were seeded using process manipulation (up to ±30%) in proximity of the experimental standard volumetric energy density (VED). The concomitant defects and heat signatures were both spatially and temporally captured. The results indicate that porosity significantly grows from an average value of 27 parts per million (PPM) to a value of 337 PPM comprising defect sizes of <112 µm when the VED increases by 30%. The outcome confirmed that Ti-6Al-4V can self-heal these defective regions by up to 7 ± 1 layers using the standard VED. A convolutional neural network was trained (n = 211) and was verified with XCT. The model demonstrated prediction accuracy of 94% for the six classes of unfamiliar defective regions. This work enables in-situ detection and healing of defective regions caused by process uncertainty that can shift the quality frontier of novel product design and development.

Improving the productivity of the welding process as well as its product quality requires an evolutionary shift toward intelligent behaviour from the conventional welding process. The 4th industrial revolution, also called Industry 4.0, can take this welding process to the whole new level which introduced customized and flexible production technologies along with smart elements. This whole revolution would create a welding station operating in an intelligent way and reliable to do monitoring and controlling the welding process in real-time. These functions generate strategic decision-making based on the algorithm of welding process parameters which can be controlled and measured through welding process variables. Moreover, the Industrial Internet of Things (IIoT) is leading to architectural changes to a welding station, including greater connectivity to industrial systems to improve quality production. Development of a reference architecture is the imperative guideline for production experts to make easier and more exact planning of smart welding station by using all the key technologies of Industry 4.0. In this paper, we proposed this reference architecture with the aim to implement this smart welding station and determine what is needed to realize it in a structured way. It will provide greater efficiency to welding implementation and eventually improve cost-saving, and iterative improvements of a physical prototype.

The emergence of Industry 4.0 (I4.0), which uses smart manufacturing as a strategy to solve industry challenges, is associated with significant research efforts that focus on cyber-physical systems, the internet of things, big data, and artificial intelligence. Utilizing I4.0 system performance and decision-making technologies, real-time monitoring, and system control, we developed a smart welding station system. The platform provides guidance for implementing a reliable welding system with a minimal amount of effort using certain characteristics of I4.0 technologies. In this study, a practical guide for the application of Reference Architectural Model Industry 4.0 (RAMI 4.0) and the use of technologies for smartization of welding systems are presented. First, we discuss the conceptual approach of a smart welding station system to create a platform for the station. Enabling technologies and their working functions are then defined. In addition, characteristics of RAMI 4.0 that apply to implement the system into the major architecture of selected RAMI 4.0 areas are analyzed. Finally, a designed platform for a smart welding station system based on five layers and three hierarchies of the production of RAMI 4.0 is presented.

The advent of technological development and integration of many fields including digital, physical and biological systems are key to the success of the Fourth Industrial Revolution, (FIR). Embracing of industry 4.0 by organizations is the key to global competitiveness and on the contrary, failure to adopt FIR may cause countries to lag behind in terms of economic development. The current studies have not fully covered on the use as well as levels of industry 4.0 implementation within developing countries. Most developed countries have put in place public policies that focus on implementing industry 4.0 in their respective countries. This means that it becomes critical, if not imperative, that developing countries like Zimbabwe also take steps to adapt industry 4.0 so as to remain relevant and competitive in the global economy as well as not be adversely affected by these technologies if not adopted. Zimbabwe, like most developing countries encounters a lot of problems in its endeavor to fully implement FIR technologies such as lack of commitment, infrastructure and lack of skilled workers. The objective of this study is to assess the implementation levels of industry 4.0 in Zimbabwean Manufacturing Industries, identify and discuss the challenges as well as issues faced by the organizations as well as coming up with recommendations in the implementation of industry 4.0 framework.

Substantial progress and development in additive manufacturing (AM) technologies have been realised during the last decade but have hardly been implemented on AM systems due to old numerical solutions still used by the AM digital thread, for instance STL (1987) and G-code (ISO 6963, 1982). In this field, more traditional processes like machining have challenged this issue by adopting the Standard for the Exchange of Product model data compliant Numerical Control (STEP-NC) standard that enables advanced and intelligent manufacturing by taking advantage of the full computing performance of numerical controllers in manufacturing machines. This standard integrates the whole digital chain (CAD-CAM-CAPP-CNC-CMM) in a unique file with information on design and manufacturing and enables manufacturing of high-value products directly without numerical data conversion or post-processing. This study presents a new STEP-NC data model for AM technologies developed with the ISO TC184/SC1/WG7 committee. A STEP-NC platform initially developed for machining processes has been adapted to implement and validate the AM data model. It enables AM directly from a STEP-NC file, as well as hybrid manufacturing (AM and machining), and allows integration of several optimisation and simulation modules that extend the possibility of advanced and intelligent AM, for instance inprocess manufacturing optimisation.

espanolSe ha tornado constante el recien desarrollo de impresoras 3–D de codigo abierto en las industrias con base en aditivos distribuidos de alto valor tecnicamente viable, como en la fabricacion de objetos a partir de acrilonitrilo–butadieno–estireno (ABS) en especial, que posee temperaturas bajas de fusion suficientes para utilizar en la extrusion fuera de una instalacion industrial, como en impresiones 3D para mantener su forma en temperaturas medias de uso. Se deben reconocer algunas partes impresas de piezas ABS para utilizacion en aplicaciones de ingenieria, que exigen una buena resistencia a la corrosion, baja densidad y propiedades mecanicas elevadas. Se tiene como objetivo, en el presente trabajo, analizar las propiedades mecanicas de los cuerpos de prueba ABS confeccionados por impresion 3D con diferentes variaciones en la espesura de la capa depositada. Los ensayos de traccion y dureza se realizaron para determinar las propiedades mecanicas del polimero ABS. EnglishThe ...

The ATLAS collaboration has built a detector in the CERN's Large Hadron Collider (LHC). Each year, several petabytes of data will be retrieved from the LHC, by this detector, to be distributed over several countries and analyzed by more than 1700 physicists, from 159 institutes, spread over 37 countries. DQ2 is the name of the distributed data management system for ATLAS which was implemented to overcome this tremendous challenge. Its goal is to be capable of transferring gigabytes of information per second, manage the petabytes of valuable information produced each year by the LHC, provide tools for the thousands of physicists to easily access this data and hide the inherent complexities of interacting with several computing grids and storage elements. Started in 2004, DQ2 has already proven its capacity of transferring ATLAS data, at the required 1.2 gigabytes per second, and reliably manage all ATLAS' data. The central catalogs is one of the most important components of DQ2 since its where the information needed to manage and transfer ATLAS' data is stored. The quantity of users interacting with DQ2, together with the high capacity of the computing centers at ATLAS' disposal, requirements to manage petabytes of data and sustain data transfer in the order of terabytes per day, makes the central catalogs play a vital role to effectively accomplish these goals. On this report, we present some of the work done on the DQ2's central catalogs component, almost from its inception until today. We described some of the available solutions for reliable and scalable databases, discuss many of the problems, solutions and ideas we implemented to overcome memory problems, security issues, client-server interaction, performance, reliability and scalability. We also present some research in the subject of knowledge discovery and data warehousing, as well as the steps accomplished in the implementation of data warehouse namely, the dimensional modeling process, important considerations taken in design of the relational model and the data staging process. This work is the base to integrate a reporting tool, in the central catalogs, to better understand the usage of system. This tool will be a valuable asset since it will help the development team identify priorities, possible misuse and security problems, predict the load of the system during certain ATLAS' activities, future hardware needs, among others.

The major purpose of this research was to carry out assessment on challenges and opportunities of integrating fourth (4 th) industrial technologies on economic development in developing countries. The case study research design was used because a case study is a comprehensive description and analysis of a single situation or a number of specific situations. A self-designed structured questionnaire was used to collect data from 150 respondents selected randomly from academicians, government officials, company directors, and Information Communication Technology (ICT) directors. The researchers collected 150 completed questionnaires from the respondents. Data were analysed using percentage, frequency and statistics. The findings of this research indicate that cybersecurity, and cloud computing technologies and mostly adopted for integration in economic development. General technical challenges, and lack of technical infrastructures such as affordable electricity and internet access are found out to be critical challenges in adopting fourth industrial technologies in developing countries. Facilitating the access to multilevel platforms that offer digital transformation programs for businesses, and connecting people to digital networks and intensely improving the efficiency of organizations was found to be a very good opportunity of integrating 4 th industrial technologies for economic development in developing countries. It is therefore recommended by the researchers that the infrastructures with standard security measures should be built to minimize cyber insecurity. The researchers also recommend that specialized training for technical staff and employees on how to operate and manage 4 th industrial technologies be conducted and the use of secure supported technological policies be implemented as a mechanism to prevent internal and external data loss.

As digital transformation progresses at an unprecedented rate, the necessity to digitize supply chains has become increasingly apparent. This transition underscores the importance of accurately evaluating key  performance indicators (KPIs) to assess these digital initiatives’ impact effectively. This paper offers an in-depth examination of a broad spectrum of KPIs critical for evaluating supply chain digitization. It also focuses on various methodologies for KPI assessment while acknowledging the significant challenges organizations encounter in tracking these metrics. Additionally, this study presents a comprehensive framework designed to help organizations methodically evaluate their digitization efforts. This framework ensures that measurement initiatives align with overarching strategic objectives and promote enhancements in supply chain efficiency through the strategic deployment of digital technologies. By establishing a robust method for tracking and analyzing KPIs, organizations can better understand their performance in a digital context. This exploration is vital for companies striving to leverage digital transformation to maintain competitiveness in an increasingly intricate business landscape.

Modern manufacturing is increasingly characterized by complex processes and the need for real-time, high-fidelity data to enable effective decision-making. A Manufacturing Execution System (MES) serves as a critical link between enterprise-level planning and shop-floor operations, providing functionalities such as production scheduling, electronic batch recording, and quality management. Nevertheless, traditional MES implementations encounter challenges related to data accuracy, integration complexity, and siloed information. The Industrial Internet of Things (IIoT) addresses these gaps by providing automated, sensor-based data generation and improved contextualization for the MES. This paper proposes a methodology for IIoT–MES integration, focusing on system architecture, data collection procedures, and advanced analytics. Results from pilot projects and literature indicate that integrating IIoT with MES significantly enhances process visibility, equipment maintenance, and review-by-exception workflows, ultimately enabling continuous improvement. Key benefits include fewer manual errors, quicker
root-cause analysis, predictive maintenance capabilities, and improved overall equipment effectiveness (OEE). Limitations, such as infrastructure costs and data security concerns, are also highlighted. The paper concludes by outlining potential future directions, including advanced machine learning models and standardized frameworks for broad industry adoption.

New industrial revolution in smart manufacturing is about to occur, propelled by unparalleled accessibility to cutting-edge technology. The Fourth Industrial Revolution, often referred to as Industry 4.0, has ushered in a new era of manufacturing known as smart manufacturing. At its core are technologies like Artificial Intelligence (AI) and Machine Learning (ML) that have revolutionized traditional manufacturing processes. This research article explores the integral role played by AI and ML in transforming conventional manufacturing into smart manufacturing. It delves into their applications, from data-driven decision-making to predictive maintenance, and their integration with the Internet of Things (IoT). The article also examines real-world examples to illustrate the impact of these technologies while addressing challenges and ethical considerations. Furthermore, it envisions future trends and implications for the manufacturing industry in the era of AI and ML. AI guarantees quality control in the manufacturing sector. Intelligent AI programmes are able to track performance, keep an eye on machine output, and identify flaws. They also contribute to lower maintenance expenses. Nowadays, the majority of industrial businesses automate their manufacturing processes with AI.

New industrial revolution in smart manufacturing is about to occur, propelled by unparalleled accessibility to cutting-edge technology. The Fourth Industrial Revolution, often referred to as Industry 4.0, has ushered in a new era of manufacturing known as smart manufacturing. At its core are technologies like Artificial Intelligence (AI) and Machine Learning (ML) that have revolutionized traditional manufacturing processes. This research article explores the integral role played by AI and ML in transforming conventional manufacturing into smart manufacturing. It delves into their applications, from data-driven decision-making to predictive maintenance, and their integration with the Internet of Things (IoT). The article also examines real-world examples to illustrate the impact of these technologies while addressing challenges and ethical considerations. Furthermore, it envisions future trends and implications for the manufacturing industry in the era of AI and ML. AI guarantees quality control in the manufacturing sector. Intelligent AI programmes are able to track performance, keep an eye on machine output, and identify flaws. They also contribute to lower maintenance expenses. Nowadays, the majority of industrial businesses automate their manufacturing processes with AI.

del 17 al 23 de octubre de 2019 titulada "Estructuras Desplegables. De los prototipos al diseño paramétrico". La exposición fue el resultado del trabajo del grupo GRAMMAR (Graphic Analysis and Methodologies for Architectural Research). Composición basada en el módulo de Emilio Pérez Piñero (Patente ES266801/USA3185164) con distintas longitudes de barra. Estados: plegada y desplegada. Modelización: Grasshopper/Kangaroo. Construcción: Impresión 3D con plástico ABS.

The Teaching Factory is an emerging paradigm aiming to enforce skills and competencies of engineers and operators working in the field of manufacturing, through an alignment of the teaching and training activities to the needs of modern factories. In this research work, the Teaching Factory principles are applied to envision ManuLearning, a new interactive and explorative knowledge-based system, which aims at enhancing the workforce skills and competencies within the context of Industry 4.0, while developing an awareness campaign to newest technologies among Small and Medium-sized Enterprises (SMEs). This paper presents this envisioned system by mainly focusing on two key-aspects: (i) the elicitation of its major requirements; (ii) the design of the architecture, which highlights how to concretize the realization of a communication channel between the factory and education systems. Finally, a real case study is introduced in order to demonstrate the correctness and validity of the p...

The automotive manufacturing sector is experiencing a profound transformation driven by Industry 4.0 principles and digital technologies. This comprehensive article examines the evolution of smart manufacturing technologies, their impact on production processes, and the resulting paradigm shift in automotive manufacturing operations. The article explores the implementation of digital twins, advanced manufacturing systems integration, cybersecurity frameworks, and workforce development strategies. The article highlights how these technological advancements have revolutionized production efficiency, quality control, and market responsiveness while addressing the challenges of legacy system integration and cybersecurity. Furthermore, it investigates the future trajectory of automotive manufacturing, focusing on additive manufacturing technologies, artificial intelligence applications, and software-defined vehicle production methodologies.

The automotive manufacturing sector is experiencing a profound transformation driven by Industry 4.0 principles and digital technologies. This comprehensive article examines the evolution of smart manufacturing technologies, their impact on production processes, and the resulting paradigm shift in automotive manufacturing operations. The article explores the implementation of digital twins, advanced manufacturing systems integration, cybersecurity frameworks, and workforce development strategies. The article highlights how these technological advancements have revolutionized production efficiency, quality control, and market responsiveness while addressing the challenges of legacy system integration and cybersecurity. Furthermore, it investigates the future trajectory of automotive manufacturing, focusing on additive manufacturing technologies, artificial intelligence applications, and software-defined vehicle production methodologies.

Centralized supply chains (SCs) are prone to disruption, which makes them a risky choice for medical equipment production. Additive manufacturing (AM) allows for production localization and improvements in SC resilience. However, the comparative competitiveness of a localized SC from the time and cost perspective is still unclear. In this study, we investigate the competitiveness of localized medical part AM SCs against centralized ones by analyzing the responsiveness and cost of each SC. We utilize a real-world case study in which an AM service provider supplies medical parts to university medical centers in the Netherlands to construct six scenarios. We also develop a thorough empirical cost formulation for both central and local AM of patient-specific medical parts. The results of scenario analysis show that when utilizing the currently available AM technology, localized SC configurations significantly reduce the delivery time from about 54 to 27h, but at a 4.3-fold higher cost. Hence, we illustrate that the cost difference between the localized and centralized scenarios can be reduced when state-of-the-art AM machines are utilized, demand volumes increase, and the distances between the SC network nodes expand. Moreover, our scenario analysis confirms that the cost of the measures taken to prevent dust dispersion associated with powderbed fusion AM has a major impact on the total cost of localized AM SCs for medical parts. The results of this study contribute to the understanding of the relevant factors in deciding whether central or localized SC configurations can be used in the AM production of medical parts. Furthermore, this study provides managerial insights for decision-makers at governments and hospitals as well as AM service providers and AM equipment manufacturers.

You as a newly qualified engineer at a leading manufacturing firm, have been tasked with exploring how the latest advancements in industrial technology can be harnessed to enhance the company's production capabilities. The firm, known for its high-quality consumer electronics, has been facing increasing competition from both domestic and international markets. To maintain its competitive edge, management has decided to invest in upgrading their manufacturing processes. You need to investigate the concepts of Industry 4.0, smart factories, and the evolution towards Industry 5.0 and prepare a comprehensive report and strategic roadmap for the company's transition. This assignment requires you to understand the current state of the industry, evaluate the benefits and challenges of these technologies, and propose a phased implementation plan that aligns with the company's goals.

Substantial progress and development in additive manufacturing (AM) technologies have been realised during the last decade but have hardly been implemented on AM systems due to old numerical solutions still used by the AM digital thread, for instance STL (1987) and G-code (ISO 6963, 1982). In this field, more traditional processes like machining have challenged this issue by adopting the Standard for the Exchange of Product model data compliant Numerical Control (STEP-NC) standard that enables advanced and intelligent manufacturing by taking advantage of the full computing performance of numerical controllers in manufacturing machines. This standard integrates the whole digital chain (CAD-CAM-CAPP-CNC-CMM) in a unique file with information on design and manufacturing and enables manufacturing of high-value products directly without numerical data conversion or post-processing. This study presents a new STEP-NC data model for AM technologies developed with the ISO TC184/SC1/WG7 committee. A STEP-NC platform initially developed for machining processes has been adapted to implement and validate the AM data model. It enables AM directly from a STEP-NC file, as well as hybrid manufacturing (AM and machining), and allows integration of several optimisation and simulation modules that extend the possibility of advanced and intelligent AM, for instance inprocess manufacturing optimisation.

Il sistema della conoscenza e delle competenze nella scena internazionale è sempre più frammentato, ed evolve velocemente a causa delle costruzioni tecnologiche come l'internet delle cose e la rivoluzione della società digitale. A questo punto è necessario domandarsi se il Design possa ancora essere considerata una disciplina "del fare" con una forte valenza tecnico-applicativa oppure sta cedendo il passo ad altri saperi più specificatamente tecnologici come le ingegnerie, per ritagliarsi invece nuovi spazi nella dimensione dei cultural studies e human-studies con un approccio prevalentemente criticospeculativo. Una condizione questa, che porta ad un sistema competitivo asimmetrico. Una deriva, una opportunità o una inevitabile evoluzione? Il numero 70 di diid vuole indagare se e quali forme di intersezione "fioriscono" tra Design e altri saperi e come il Design sta ridefinendo i suoi stessi saperi.

O objeto de estudo dessa pesquisa consiste em uma análise experimental de um conjunto de técnicas que subsidiem a reprodução de elementos pré-moldados de argamassa armada utilizados nos Centros de Atenção Integral à Criança e ao Adolescente/CAIC. O arquiteto João da Gama Filgueiras Lima (1932-2014), Lelé, foi o responsável por liderar uma equipe, no início dos anos 1990, que desenvolveu o projeto piloto para os CAICs. A meta inicial do projeto baseava-se na construção de 5.000 unidades para atender aproximadamente seis milhões de crianças por todo país, contudo apenas 7% das construções foram efetivamente implantadas (350), mas enfrentam uma série de dificuldades para a manutenção de sua conservação física. Sendo assim, o objetivo geral dessa pesquisa é investigar técnicas de modelagem e fabricação digital, para o estudo de componentes que apresentaram não conformidades e a fabricação de seus respectivos moldes, visando à facilitação da reprodução desses componentes no contexto das obras que adotam o sistema construtivo dos CAICs. Tirando partido disso, justifica-se inicialmente a abordagem dessa temática ao incorporar o caráter propositivo em estruturas pré-existentes visando salvaguardar esse patrimônio arquitetônico tecnológico da contemporaneidade que adota princípios da modernidade do mestre Lelé. Além disso, a busca de métodos de reprodução de componentes visando a sua substituição na estrutura dos CAICs, tem amparo em recentes iniciativas. A exemplo da recuperação do módulo Iansã, antiga sede do programa de pós-graduação da Faculdade de Arquitetura da Universidade Federal da Bahia/FAUFBA, que teve parte de seus componentes substituídos sem comprometer a integridade do edifício. A abordagem metodológica dessa pesquisa partiu da concepção digital da peça (modelagem paramétrica), que passa pela transição ao modelo físico reduzido para estudos (prototipagem), e finalmente é adaptado para fôrmas que possibilitem sua reprodução na matriz cimentícia (fabricação de moldes). Contudo, esse artigo utiliza enquanto escopo de investigação os processos realizados na etapa de concepção e elaboração dos moldes, que exploram as técnicas de processo subtrativo (usinagem) e conformativo (termoformagem à vácuo). Enquanto resultados foram realizados testes conceituais para produção digital das fôrmas de três componentes (sapata de fundação, segmento da laje de cobertura e a grelha da canaleta de drenagem), após isso deu-se a montagem dos moldes para subsidiar o seu desenvolvimento em pequena escala enquanto contribuição do estudo.

The rapid market changes and strong product individualization create the need for great flexibility of manufacturing management on new foundations, such as the Industry 4.0 model. Digital manufacturing is the basis for Industry 4.0, which has the following dimensions: (a) digital manufacturing based on advanced digital-oriented technologies, (b) smart products (advanced manufacturing model and new characteristics), and (c) smart supply chain of raw materials and delivery of finished products). Bidirectional exchange of information in collaborative manufacturing, using it exchange also for digital platforms of design of the innovative products. In this paper we are show developed model of Serbian digital factory of home cookware and appliance manufacturing for tools lifecycle management (TLM) in workshop for metal forming as a part of MES model.

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

This paper presents an analysis and synthesis of research carried out in the fi eld of digital factory and digital manufacturing. The aim was to present different approaches and concepts, digital manufacturing and digital factory, for the purpose of establishing a common research approach. The engineering model of manufacturing based on digital models of products, processes and resources is the future of manufacturing engineering in this area, and are therefore subject to analysis in this study particularly important. At the end are particularly given to future research directions in the fi eld of digital factory and of manufacturing.

The paper shows the concept of Serbian Industry 4.0 Model based on cyber-physical manufacturing metrology model (CPM 3 ) and an integrated approach to manufacturing quality. The paper presents two directions of research: Virtual optimization of CAI process parameters for the sculptured surface inspection and Intelligent model for Inspection Planning on CMM.