Current market requirements force manufacturing companies to face production changes more often than ever before. Reconfigurable manufacturing systems (RMS) are considered a key enabler in today’s manufacturing industry to cope with such dynami...
The emergence of mass personalized production has increased the adaptability and intelligence requirements of welding robots. To address the challenges associated with mass personalized production, this paper proposes a novel knowledge-driven framewo...
Micromachining techniques have been applied widely to many industrial sectors, including aerospace, automotive, and precision instruments. However, due to their high-precision machining requirements, and the knowledge-intensive characteristics of min...
This study investigates data-driven business model innovation (DDBMI) for incumbent manufacturers, underscoring its importance in various strategic and managerial contexts. Employing topic modeling, the study identifies nine key topics of DDBMI. Thro...
The manufacturing industry must maintain high-quality standards while meeting customer demands for customization, reduced carbon footprint, and competitive pricing. To address these challenges, companies are constantly improving their production proc...
The integration of human–cyber–physical systems (HCPSs), IoT, digital twins, and big data analytics underpins Industry 4.0, transforming traditional manufacturing into smart manufacturing with capabilities for real-time monitoring, qualit...
Manufacturers can plan predictive maintenance by remotely monitoring their assets. However, to extract the necessary insights from monitoring data, they often lack sufficiently large datasets that are labeled by human experts. We suggest combining kn...
There is a lack of high correlation and reuse potential among multiple manufacturing data for textiles and apparel. Moreover, the material flow traceability between production workstations is not clear, making it difficult to detect potential product...
Tool wear is critical to quality, productivity, and sustainability in manufacturing processes. Therefore, accurately monitoring and predicting wear is one of the primary goals of smart manufacturing systems. While AI-based approaches have achieved si...
In today’s complex, constantly evolving and innovation-supporting manufacturing systems, knowledge plays a vital role in sustainable manufacturing process planning and problem-solving, especially in the case of Computer-Aided Process Innovation (CAPI...
The construction industry has long been labor-intensive, with slow productivity growth and a significant environmental impact. In this regard, the ever-increasing practices of additive manufacturing (AM) in construction have presented a variety of ad...
The widespread adoption of cyber-physical systems and other cutting-edge digital technology in manufacturing industry production facilities may motivate stakeholders to embrace the idea of Industry 4.0. Some industrial companies already have differen...
Techniques to provide in vitro tissue culture have undergone significant changes during the last decades, and current applications involve interactions of cells and organoids, three-dimensional cell co-cultures, and organ/body-on-chip tools. Efficien...
The industrial manufacturing model is undergoing a transformation from a product-centric model to a customer-centric one. Driven by customized requirements, the complexity of products and the requirements for quality have increased, which pose a chal...
The formulation of robust Welding Procedure Specifications (WPS) is paramount in aviation manufacturing, where quality directly impacts structural integrity and flight safety. Current practices, however, often rely on experiential knowledge and lack...
Safety management is a priority to guarantee human-centered manufacturing processes in the context of Industry 5.0, which aims to realize a safe human–machine environment based on knowledge-driven approaches. The traditional approaches for safe...
Periodic health checks of contouring errors under unloaded conditions are critical for machine performance evaluation and value-added manufacturing. Aiming at breaking the dimension, range and speed measurement limitations of the existing devices, a...
The efficient operation of the maintenance service system is key to achieving sustainable operations, with its core lying in the coordinated scheduling of spare parts production and maintenance personnel, as well as the holistic management of in-warr...
The trend towards socialization, personalization and servitization in smart manufacturing has attracted the attention of researchers, practitioners and governments. Social manufacturing is a novel manufacturing paradigm responding to this trend. Howe...
Additive manufacturing (AM) has impacted the manufacturing of complex three-dimensional objects in multiple materials for a wide array of applications. However, additive manufacturing, as an upcoming field, lacks automated and specific design rules f...
The increasing application of lithium-ion batteries in manufacturing and energy storage systems necessitates high-precision screening of abnormal cells during manufacturing, so as to ensure safety and performance. Existing methods struggle to break d...
The digital transformation of producer services contributes to the development of manufacturing technology innovation through an intermediary role, providing an important policy basis for the effective implementation of China’s innovation-drive...
In manufacturing, convolutional neural networks (CNNs) are widely used on image sensor data for data-driven process monitoring and quality prediction. However, as purely data-driven models, CNNs do not integrate physical measures or practical conside...
Industry 4.0 has introduced a data-driven model of production and management of goods and services. This manufacturing paradigm leverages the potential of the Internet of Things (IoT), but finding the information necessary to drive manufacturing proc...
The present work proposes a holonic-based mechanism for self-learning factories based on a hybrid learning approach. The self-learning factory is a manufacturing system that gains predictive capability by machine self-learning, and thus automatically...
The fourth industrial revolution is the transformation of industrial manufacturing into smart manufacturing. The advancement of digital technologies that make the trend Industry 4.0 are considered as the transforming force that will enable this trans...
Digital Twins (DTs) integrated with Artificial Intelligence (AI) are emerging as transformative tools in smart manufacturing. By bridging the physical and virtual domains, DTs enable real-time monitoring, predictive analytics, and autonomous decision...
The birth of mass production started in the early 1900s. The manufacturing industries were transformed from mechanization to digitalization with the help of Information and Communication Technology (ICT). Now, the advancement of ICT and the Internet...
The images of surface defects of industrial products contain not only the defect type but also the causal logic related to defective design and manufacturing. This information is recessive and unstructured and difficult to find and use, which cannot...
The rapid advancement of digital technologies, referred to as Industry 4.0, has profoundly transformed the manufacturing landscape, necessitating a reevaluation of engineering education. Future engineers must possess diverse skills and competencies t...
Ship manufacturing is a critical backbone industry in China, where the nation leads on a global scale in terms of vessel completions and order volumes. However, the high volume of orders often imposes substantial processing loads, increases the risk...
This paper presents a comprehensive design framework for Enterprise Architecture aimed at facilitating decision-driven analytics in smart factories. The motivation behind this research lies in challenges faced by manufacturing companies, such as skil...
Improving energy efficiency in industrial manufacturing remains challenging despite substantial technical potential. This has resulted in a persistent energy efficiency gap, which is increasingly understood as a socio-technical issue driven by not on...
The concept of Industry 4.0 is defined as a common term for technology and the concept of new digital tools to optimize the manufacturing process. Within this framework of modular smart factories, cyber-physical systems monitor physical processes cre...
Advanced construction techniques, such as additive manufacturing (AM) and modular construction, offer promising solutions to address labor shortages, reduce CO2 emissions, and enhance material efficiency. Despite their potential, the adoption of thes...
Precision manufacturing requires handling multi-physics coupling during processing, where digital twin and AI technologies enable rapid robot programming under customized requirements. However, heterogeneous data sources, diverse domain models, and r...
This paper presents a comprehensive review of optimization practices in the corrugated board industry, which has recently experienced significant interest in using optimization methodologies driven by sustainable demands and increasing computational...
Background: Ongoing challenges such as geopolitical conflicts, trade disruptions, economic sanctions, and political instability have underscored the urgent need for large manufacturing enterprises to improve resilience and reduce dependence on global...
Machine learning has been an emerging scientific field serving the modern multidisciplinary needs in the Materials Science and Manufacturing sector. The taxonomy and mapping of nanomaterial properties based on data analytics is going to ensure safe a...
Intelligent data analytics-based cloud computing is a leading trend for managing a large-scale network in contemporary manufacturing environments. The data and information are shared using the cloud environments and valuable knowledge is driven using...
Cold spray is emerging as an additive manufacturing technique, particularly advantageous when high production rate and large build sizes are in demand. To further accelerate technology’s industrial maturity, the problem of geometric control must be i...
Despite the significant contribution of buyer-driven knowledge transfer activities (BDKTAs) to innovation and operational performance, studies that analyze social sustainability in manufacturing (suppliers) firms are still scarce. This paper examines...
Additive manufacturing (AM) has made rapid progress in most industries; however, the construction sector lags behind, despite substantial potential for growth. This study aims to evaluate recent innovations in AM, with a focus on multi-material addit...
The rapid advancement of artificial intelligence (AI) in the traditional-apparel-manufacturing sector is accelerating innovation and transformation, as cutting-edge AI applications have been increasingly integrated into the industry in recent years....
To support data-driven decision-making in a Manufacturing Execution System (MES) environment, a system that can quickly and accurately analyze a wide range of production, quality, asset, and material information must be deployed. However, existing ME...
China has shifted its focus from export-led growth to technology-driven growth. The “One Belt, One Road” initiative (OBOR) is aimed at promoting economic integration with the rest of the world that might boost China’s ability to upg...
This paper presents a novel ontology-driven digital twin framework specifically designed for aviation maintenance and operations that addresses these challenges through semantic reasoning and explainable decision support. The proposed framework integ...
In metal additive manufacturing (AM), precise temperature field prediction is crucial for process monitoring, automation, control, and optimization. Traditional methods, primarily offline and data-driven, struggle with adapting to real-time changes a...
In the era of the digital economy, how digital transformation (DT) contributes to economic development has become a topic of growing interest. This study focuses on business model innovation (BMI) driven by DT in the manufacturing sector. From this p...
Additive manufacturing has emerged as a key enabling technology for in-space manufacturing, offering the potential to reduce logistics mass, enhance mission autonomy, and support long-duration exploration. The suppression of gravity-driven phenomena...
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