Digital Manufacturing Research Articles

3D printers and their use in prosthetic dentistry

In recent years, the use of computer-aided design and computer-aided manufacturing (CAD/CAM) has increased considerably in addition to the traditional methods used in routine. CAD/CAM technology has many advantages. However, despite these advantages, it has a very important disadvantage such as material waste. Today, the technology that overcomes this problem is the additive manufacturing method with three-dimensional printers. This method has recently replaced the traditional subtractive computer-aided design and manufacturing technology in prosthodontics. The use of 3D printers has been increasing in recent years due to its advantages such as ease of production, time saving and material saving, freedom of design, error-free and faster production. It is also predicted that the use of this technology will increase in the future and will be the main method for digital manufacturing. The aim of this review is to evaluate the production methods of 3D printers, the areas of use in prosthodontics, the advantages and disadvantages of 3D production methods, and to review the purposes of use, materials used and developments in prosthodontics.

Manufacturing of PEEK orthodontic baseplate and 3D-printed alloy components from an intraoral scan.

This paper demonstrates a digital manufacturing technique of a removable orthodontic appliance from an intraoral scan. An intraoral scan was made for the maxillary and mandibular arches. 3Shape Orthodontics Appliance Designer produced the virtual Hawley retainer, consisting of alloy components (Adam Clasps and Fitted Labial bow) and a base plate. The base plate design was modified to adapt to inserting the alloy components, which were combined using cold-cured acrylic. The finished Hawley retainer was assessed intraorally. The described technique emphasizes the design specifications of digitally designed and manufactured removable orthodontic appliances. A combination of additive and subtractive techniques was successfully employed to manufacture the alloy components and base plate. This novel method provides an alternative approach to manufacturing removable appliances with computer-aided design (CAD)/computer-aided manufacturing (CAM) technologies. The described process offers a precursor to digital manufacturing of other developed designs of dental appliances.

BrepMFR: Enhancing machining feature recognition in B-rep models through deep learning and domain adaptation

Feature Recognition (FR) plays a crucial role in modern digital manufacturing, serving as a key technology for integrating Computer-Aided Design (CAD), Computer-Aided Process Planning (CAPP) and Computer-Aided Manufacturing (CAM) systems. The emergence of deep learning methods in recent years offers a new approach to address challenges in recognizing highly intersecting features with complex geometric shapes. However, due to the high cost of labeling real CAD models, neural networks are usually trained on computer-synthesized datasets, resulting in noticeable performance degradation when applied to real-world CAD models. Therefore, we propose a novel deep learning network, BrepMFR, designed for Machining Feature Recognition (MFR) from Boundary Representation (B-rep) models. We transform the original B-rep model into a graph representation as network-friendly input, incorporating local geometric shape and global topological relationships. Leveraging a graph neural network based on Transformer architecture and graph attention mechanism, we extract the feature representation of high-level semantic information to achieve machining feature recognition. Additionally, employing a two-step training strategy under a transfer learning framework, we enhance BrepMFR's generalization ability by adapting synthetic training data to real CAD data. Furthermore, we establish a large-scale synthetic CAD model dataset inclusive of 24 typical machining features, showcasing diversity in geometry that closely mirrors real-world mechanical engineering scenarios. Extensive experiments across various datasets demonstrate that BrepMFR achieves state-of-the-art machining feature recognition accuracy and performs effectively on CAD models of real-world mechanical parts.

3D auxetic linkage based on Kirigami

The structural design of 3D auxetic linkages is a burgeoning field in digital manufacturing. This article presents a novel algorithm for designing 3D auxetic linkage structures based on Kirigami principles to address existing limitations. The 3D input model is initially mapped to a 2D space using conformal mapping based on the BFF method. This is followed by 2D re-meshing using an equilateral triangle mesh. Subsequently, a 3D topological mesh of the auxetic linkage is calculated through inverse mapping based on directed area. We then introduce new basic rotating and non-rotating units, employing them as the initial structure of the 3D auxetic linkage in accordance with Kirigami techniques. Lastly, a deformation energy function is defined to optimize the shape of the rotating units. The vertex coordinates of the non-rotating units are updated according to the optimized positions of the rotating units, thereby generating an optimal 3D auxetic linkage structure. Experimental results validate the effectiveness and accuracy of our algorithm. Quantitative analyses of structural porosity and optimization accuracy, as well as comparisons with related works, indicate that our algorithm yields structures with smaller shape errors.

Surfaces of coastal biogenic structures: exploiting advanced digital design and fabrication strategies for the manufacturing of oyster reef and mussel bed surrogates

Coastal biogenic structures, formed by ecosystem engineering species, often feature rough surfaces characterized by intricate topographies and highly three-dimensional reliefs. Their surfaces are shaped by waves and tidal currents and reciprocally influence the ambient hydrodynamics, reflecting an equilibrium. Despite their significance, the impact of these surfaces on the ambient hydrodynamics remains underexplored due to limited knowledge of accurately replicating their complex topographies in experimental setups. The recent advent of advanced digital manufacturing presents an efficient means to manufacture highly complex, three-dimensional surrogate models for experimental modeling. This work explores the accurate replication of rough coastal biogenic structures for experimental modeling on the examples of an oyster reef and a mussel bed, utilizing a flexible design methodology and, for the first time, particle bed 3D printing with Selective Cement Activation (SCA) as a fabrication and manufacturing method. A workflow is proposed, which includes an iterative surrogate model development based on in-situ topographical features, requirements of the experimental setup, and parameters of the particle bed 3D printer with SCA. The results demonstrate the effectiveness of the methodology in achieving highly accurate surrogate surfaces of complex coastal biogenic structures by validation against a set of topographical features relevant to hydraulic roughness. Particle bed 3D printing with SCA proved to be a suitable method to manufacture complex surrogate surfaces for experimental modeling, offering advantages such as independence of production time from surface complexity. However, challenges persist in achieving exact comparability between the manufactured surrogate surface and the real coastal biogenic structures, particularly for surfaces with very high complexity. Nonetheless, the manufactured generic surrogate surfaces enable detailed investigations into the influence of complex coastal biogenic structures on the ambient hydrodynamics, thereby enhancing the understanding of the processes governing wave energy dissipation attenuation, turbulence production, and vertical mixing – critical for efficient application as a nature-based solution on coastal protection or restoration efforts.

A 3D printed ultra-short dental implant based on lattice structures and ZIRCONIA/Ca2SiO4 combination

Additive Manufacturing (AM) enables the generation of complex geometries and controlled internal cavities that are so interesting for the biomedical industry due to the benefits they provide in terms of osseointegration and bone growth. These technologies enable the manufacturing of the so-called lattice structures that are cells with different geometries and internal pores joint together for the formation of scaffold-type structures. In this context, the present paper analyses the feasibility of using diamond-type lattice structures and topology optimisation for the re-design of a dental implant. Concretely, a new ultra-short implant design is proposed in this work. For the manufacturing of the implant, digital light processing additive manufacturing technique technology is considered. The implant was made out of Nano-zirconia and Nano-Calcium Silicate as an alternative material to the more common Ti6Al4V. This material combination was selected due to the properties of the calcium-silicate that enhance bone ingrowth. The influence of different material combination ratios and lattice pore sizes were analysed by means of FEM simulation. For those simulations, a bio-material bone-nanozirconia model was considered that represents the final status after the bone is integrated in the implant. Results shows that the mechanical properties of the biocompatible composite employed were suitable for dental implant applications in dentistry. Based on the obtained results it was seen that those designs with 400 μm and 500 μm pore sizes showed best performance and led to the required factor of safety.

The Application of 3D Printing Formwork Technology in Concrete Building Materials

Concrete 3D printing technology is a prime example of contemporary digital manufacturing, showcasing its efficiency and automation in the realm of construction. Compared to traditional construction methods, the characteristics of labor-saving and formwork-free in 3D printing technology have brought changes to the construction personnel structure and forming process. Enhancing the flexibility of concrete materials and 3D printing technology are two major areas of concentration, along with promoting the wider application of 3D printing in the construction industry. An extensive review of the advancements in concrete 3D printing technology is given in this paper. The mechanical, printable, buildable, and rheological properties of concrete materials that are suitable for 3D printing are also discussed. The study also shows how 3D printing formwork technology is frequently used in decorative elements and atypically shaped projects. The goal is to offer informative analysis and practical tools for further research and advancements in 3D printed concrete technology. The study's overall findings emphasize how important it is to improve 3D printing technology's compatibility with concrete materials. By tackling essential performance criteria and exploring creative uses, we can unlock the complete potential of concrete 3D printing, which will result in notable progress within the construction sector.

The coupling and coordination of digital economy and manufacturing transformation and upgrading for industry 5.0 in Hebei Province

In the context of the widespread application of digital technologies such as the Internet, big data, artificial intelligence, and cloud computing, digital transformation in the manufacturing sector has become an important engine to promote high-quality economic development in Hebei Province. This paper aims to objectively analyze the current situation of industrial integration between the Beijing-Tianjin-Hebei digital economy and the manufacturing industry and conduct level measurement so as to promote the in-depth integration and development of the digital economy and manufacturing industry in Hebei Province, so that the manufacturing enterprises in Hebei Province can rebuild their competitive advantages in future development, finally realize digital transformation, and promote the high-quality development of the manufacturing industry in Hebei Province. Therefore, it is very important to carry out empirical research on the integrated development of the digital economy and manufacturing industry in Hebei Province. First of all, this paper constructs the index evaluation system of the digital economy and manufacturing industry, respectively, takes the relevant data of the Beijing-Tianjin-Hebei region in the past five years as data samples, uses the entropy weight-TOPSIS method to measure the level of digital economy development and manufacturing industry transformation, and uses the coupling coordination degree model to measure the level of industrial integration of the two. The final results show that: (1) The development level of the digital economy in Hebei Province fluctuates greatly, and there is still a certain gap with Beijing and Tianjin, but the future development potential of the digital economy is huge. (2) The transformation level of manufacturing industry in Hebei Province shows a trend of fluctuation and rise on the whole, and the development trend is good, and the gap between Hebei Province and developed regions is gradually narrowing. (3) The integration of the digital economy and manufacturing industry in Hebei Province has a good development trend, but there is still a certain gap with Beijing and Tianjin, and there are problems of inadequate, unstable, and unbalanced industrial integration. Finally, based on the research conclusions, suggestions are put forward to promote the coordinated development of the Beijing-Tianjin-Hebei region, improve the level of digital economy and manufacturing integration of industrial convergence development, raise the level of digital infrastructure construction, and raise the level of science and technology innovation. This paper reveals the mechanism of the digital economy affecting the high-quality development of the manufacturing industry, studies the whole process of digitalization, information technology, and intelligence integration into the development of the manufacturing industry, and fully releases the positive effect of the digital economy driving the high-quality development of the manufacturing industry, which has important theoretical and practical significance for promoting the high-quality development of the manufacturing industry and formulating relevant industrial policies.

The coupling and coordination of digital economy and manufacturing transformation and upgrading for industry 5.0 in Hebei Province

In the context of the widespread application of digital technologies such as the Internet, big data, artificial intelligence, and cloud computing, digital transformation in the manufacturing sector has become an important engine to promote high-quality economic development in Hebei Province. This paper aims to objectively analyze the current situation of industrial integration between the Beijing-Tianjin-Hebei digital economy and the manufacturing industry, and conduct level measurement, so as to promote the in-depth integration and development of the digital economy and manufacturing industry in Hebei Province, so that the manufacturing enterprises in Hebei Province can rebuild their competitive advantages in the future development, finally realize digital transformation, and promote the high-quality development of the manufacturing industry in Hebei Province. Therefore, it is very important to carry out empirical research on the integrated development of digital economy and manufacturing industry in Hebei Province. First of all, this paper constructs the index evaluation system of digital economy and manufacturing industry respectively, takes the relevant data of Beijing-Tianjin-Hebei region in recent five years as data samples, uses entropy weight-TOPSIS method to measure the level of digital economy development and manufacturing industry transformation, and uses the coupling coordination degree model to measure the level of industrial integration of the two. The final results show that: (1) The development level of digital economy in Hebei Province fluctuates greatly, and there is still a certain gap with Beijing and Tianjin, but the future development potential of digital economy is huge. (2) The transformation level of manufacturing industry in Hebei Province shows a trend of fluctuation and rise on the whole, and the development trend is good, and the gap between Hebei Province and developed regions is gradually narrowing. (3) The integration of digital economy and manufacturing industry in Hebei Province has a good development trend, but there is still a certain gap with Beijing and Tianjin, and there are problems of inadequate, unstable and unbalanced industrial integration. Finally, based on the research conclusions, suggestions are put forward to promote the coordinated development of Beijing-Tianjin-Hebei region, improve the level of digital economy and manufacturing integration of industrial convergence development, raise the level of digital infrastructure construction, and raise the level of science and technology innovation. This paper reveals the mechanism of digital economy affecting the high-quality development of manufacturing industry, studies the whole process of digitalization, information technology and intelligence integration into the development of manufacturing industry, and fully releases the positive effect of digital economy driving the high-quality development of manufacturing industry, which has important theoretical and practical significance for promoting the high-quality development of manufacturing industry and formulating relevant industrial policies.

Appraising the Feasibility of 3D Printing Construction in New Zealand Housing

The construction industry in New Zealand is significantly impacted by the importance of housing, particularly as urbanisation continues to grow in major cities. Modern construction methods, such as offsite construction and building automation, evolving into digital manufacturing and construction in the industry, have become prominent. Despite the global recognition of 3D printing technology, its adoption in the construction industry in New Zealand is still relatively limited. This study aims to examine the feasibility of 3D printing construction in response to current market challenges, innovation, and the 2050 net-zero carbon goal. Utilising Building Information Modelling (BIM) and Life Cycle Assessment (LCA) approaches, this study investigated the environmental impacts of three housing types: 3D printing (3DP), light steel framed (LSF), and timber. This study used cradle-to-cradle as the system boundary. The results indicate that the 3DP house emits 20% fewer carbon emissions than the traditional timber house and 25% less than the LSF house. Additionally, the 3DP house exhibits a 19% lower annual electric energy consumption than the timber house. Therefore, in response to the growing housing demand in New Zealand, the construction industry must innovate and embrace digital and advanced construction methods, including the adoption of 3D printing.

Digital Twin-Driven Multi-Factor Production Capacity Prediction for Discrete Manufacturing Workshop

Traditional capacity forecasting algorithms lack effective data interaction, leading to a disconnection between the actual plan and production. This paper discusses the multi-factor model based on a discrete manufacturing workshop and proposes a digital twin-driven discrete manufacturing workshop capacity prediction method. Firstly, this paper gives a system framework for production capacity prediction in discrete manufacturing workshops based on digital twins. Then, a mathematical model is described for discrete manufacturing workshop production capacity under multiple disturbance factors. Furthermore, an innovative production capacity prediction method, using the “digital twin + Long-Short-Term Memory Network (LSTM) algorithm”, is presented. Finally, a discrete manufacturing workshop twin platform is deployed using a commemorative disk custom production line as the prototype platform. The verification shows that the proposed method can achieve a prediction accuracy rate of 91.8% for production line capacity. By integrating the optimization feedback function of the digital twin system into the production process control, this paper enables an accurate perception of the current state and future changes in the production system, effectively evaluating the production capacity and delivery date of discrete manufacturing workshops.

When manufacturers turn into digital platform providers: A transformation model to understand the platformization pathway

Platformization has arrived in manufacturing. However, to enter the digital platform business manufacturers need to make a fundamental shift from product thinking to platform thinking. To master this shift, firms have to take the platformization pathway, which describes the process when manufacturers turn into digital platform providers. However, little is known about platformization on the firm level from a transformation perspective. Our study attempts to close this gap and develops a transformation model that frames the platformization pathway when established manufacturers become platform leaders. For this purpose, we adopt the concept of ambidexterity and develop a theoretical framework to conceptualize and investigate the transformation process as a result of sequential transitions and balancing between explorative and exploitative activities. Moreover, we use interviews from 29 large manufacturers and conduct an inductive case study analysis to identify the different stages, the contextual factors and the dynamics of transformation. By combining the theoretical framework and the results of our case study analysis, we develop a formal transformation model that contributes to understanding the manufacturers' platformization pathway. Our results also aim to support manufacturers in designing their strategies so they can turn into leading digital platform providers.

Managing digital manufacturing transformation: assessing the status-quo and future prospects in North Indian industries

PurposeThe use of technology in 4th industrial revolution is at its peak. Industries are trying to reduce the consumption of resources by effectively utilizing information and technology to connect different functioning agents of the manufacturing industry. Without digitization “Industry 4.0” will be a virtual reality. The present survey-based study explores the factual status of digital manufacturing in the Northern India.Design/methodology/approachAfter an extensive literature review, a questionnaire was designed to gather different viewpoints of Indian industrial practitioners. The first half contains questions related to north Indian demographic factors which may affect digitalization of India. The latter half includes the queries concerned with various operational factors (or drivers) driving the digital revolution without ignoring Indian constraints.FindingsThe focus of this survey was to understand the current level of digital revolution under the ongoing push by the Indian government focused upon digital movement. The analysis included non-parametric testing of the various demographic and functional factors impacting the digital echoes, specifically in Northern India. Findings such as technological upgradations were independent of type of industry, the turnover or the location. About 10 key operational factors were thoughtfully grouped into three major categories—internal Research and Development (R&D), the capability of the supply chain and the capacity to adapt to the market. These factors were then examined to understand how they contribute to digital manufacturing, utilizing an appropriate ordinal logistic regression. The resulting predictive analysis provides seldom-seen insights and valuable suggestions for the most effective deployment of digitalization in Indian industries.Research limitations/implicationsThe country-specific Industry 4.0 literature is quite limited. The survey mainly focuses on the National Capital Region. The number of demographic and functional factors can further be incorporated. Moreover, an addition of factors related to ecology, environment and society can make the study more insightful.Practical implicationsThe present work provides valuable insights about the current status of digitization and expects to facilitate public or private policymakers to implement digital technologies in India with less efforts and the least resistance. It empowers India towards Industry 4.0 based tools and techniques and creates new socio-economic dimensions for the sustainable development.Originality/valueThe quantitative nature of the study and its statistical predictions (data-based) are novel. The clubbing of similar success factors to avoid inter-collinearity and complexity is seldom seen. The predictive analytics provided in this study is quite elusive as it provides directions with logic. It will help the Indian Government and industrial strategists to plan and perform their interventions accordingly.

Bridging Nanomanufacturing and Artificial Intelligence-A Comprehensive Review.

Nanomanufacturing and digital manufacturing (DM) are defining the forefront of the fourth industrial revolution-Industry 4.0-as enabling technologies for the processing of materials spanning several length scales. This review delineates the evolution of nanomaterials and nanomanufacturing in the digital age for applications in medicine, robotics, sensory technology, semiconductors, and consumer electronics. The incorporation of artificial intelligence (AI) tools to explore nanomaterial synthesis, optimize nanomanufacturing processes, and aid high-fidelity nanoscale characterization is discussed. This paper elaborates on different machine-learning and deep-learning algorithms for analyzing nanoscale images, designing nanomaterials, and nano quality assurance. The challenges associated with the application of machine- and deep-learning models to achieve robust and accurate predictions are outlined. The prospects of incorporating sophisticated AI algorithms such as reinforced learning, explainable artificial intelligence (XAI), big data analytics for material synthesis, manufacturing process innovation, and nanosystem integration are discussed.

Computer Vision Approach in Monitoring for Illicit and Copyrighted Objects in Digital Manufacturing

We propose a monitoring system for detecting illicit and copyrighted objects in digital manufacturing (DM). Our system is based on extracting and analyzing high-dimensional data from blueprints of three-dimensional (3D) objects. We aim to protect the legal interests of DM service providers, who may receive requests for 3D printing from external sources, such as emails or uploads. Such requests may contain blueprints of objects that are illegal, restricted, or otherwise controlled in the country of operation or protected by copyright. Without a reliable way to identify such objects, the service provider may unknowingly violate the laws and regulations and face legal consequences. Therefore, we propose a multi-layer system that automatically detects and flags such objects before the 3D printing process begins. We present efficient computer vision algorithms for object analysis and scalable system architecture for data storage and processing and explain the rationale behind the suggested system architecture.

Overview of clinical and laboratory evaluation results of the effectiveness of digital methods for knowledge-based fabrication of complete removable acrylic dentures

This article provides an overview of the conceptual studies of modern digital technologies for the fabrication of complete removable acrylic dentures. Analysis of data of subtractive and additive methods of digital manufacturing shows the advantages of digital CAD/CAM methods over traditional methods. The use of known prepolymerized acrylic blocks in the subtractive milling method has enabled achieving high physical and mechanical properties, optimal spatial accuracy, and minimal thickness of the fabricated dentures. Moreover, residual monomer volume reduction in solid polymer blocks has allowed the high biological inertness and safety of the fabricated structures for prosthetic bed tissues and the patient’s body. Layer-by-layer printing of removable dentures by fused polymer deposition modeling technology results in high spatial accuracy of constructing structures of any degree of complexity and reduced total production time of removable dentures.
 Despite the intensity of implementation of digital CAD/CAM technologies in the practice of complete removable denture manufacturing, the search for alternative methods of modernization of the known traditional means and methods continues. However, we believe that automation and digitalization of the clinical and laboratory manufacturing of complete removable acrylic dentures has clear prospects for the total replacement of compression pressing and hot polymerization techniques of acrylates. In summary, the potential prospect in the future is a global reassessment of traditional concepts for the fabrication of complete removable dentures, considering the formation of an innovative digital CAD/CAM philosophy and the introduction of computer intelligent systems.

Development of Cyber Physical System Based Manufacturing System Design

Cyber Physical System (CPS) is Informatics and computer science. Cyber physical manufacturing system is a new research field. In the fields of computer science and manufacturing science and technology Promote the Fourth Industrial Revolution known as Industry 4.0. CPS is generally focused. About the integration of the physical world and cyberspace. It`s the integration of communication, Computational, control, and physical elements. Currently, CPS is Science, government and industry. Systematic literature review on cyber. The physical system of the manufacturing system is not available. The purpose of the chapters in this bookis to gain insight into manufacturing systems and develop cyber-physical systems. Physical systems for intelligent manufacturing. CPS is written using the concept of CPS. A 5-tier architecture system for manufacturing systems. Continuous Key Release. It also describes the technology of cyber physical manufacturing systems. Combined with manufacturing, CPS enables intelligent manufacturing and provides technical support for manufacturing upgrades and conversions. This can be summarized in three aspects: internet-based manufacturing, process intelligence, and product intelligence. Future manufacturing is said to be personalized manufacturing based on cyber physical systems, intelligent manufacturing, digital manufacturing, and network-based manufacturing. CPS continues to transform the manufacturing trends of the industry, creating even more amazing value for future global manufacturing scenarios

Experimental and statistical study on the effect of process parameters on the quality of continuous fiber composites made via additive manufacturing

Ongoing research in additive manufacturing towards structural and industrial application has led to the use of commingled roving as a manufacturing feedstock for printing high fiber volume fraction composites. The prospects of using this technology for high performance applications necessitates the need for a comprehensive experimental investigation into the effects of processing parameters on the quality of an additively manufactured composite printed from commingled roving feedstock. In this work, transverse flexure and void fraction matrix pyrolysis testing are both performed to evaluate composite quality. The transverse flexure test is a testing approach that evaluates the quality of the interfacial fiber-matrix bond while the void fraction test estimates the void content in the printed composite. A full observational study consisting of 27 different test combinations is done to investigate the effects of three different process parameters namely, temperature, pressure, and print speed across three different levels. Composite samples were made from commingled roving of E-glass and amorphous PET using an in-house built continuous fiber composite digital manufacturing system. Least squares regression analysis is performed to study the main, interaction and quadratic effects of process parameters. A statistical regression model having an R2 adjusted value of 80.1% is generated from the transverse flexure study, which is used to explain main and interaction effects and also predict performance. Response surface plots are also generated and are used to optimize process parameters which can subsequently be of help in scaling up composite manufacturing. Results show that all three process parameters are highly statistically significant at the 0.01 level of significance. Pressure * Temperature and Pressure * Printspeed are significant interaction terms. Pressure plays a weightier role when print speed is increased or temperature is decreased as it closes more voids that would ordinarily have been introduced because of drop in polymer melt viscosity. Micrographic analysis is also performed.

The influence of the raster angle on the dimensional accuracy of FDM-printed PLA, PETG, and ABS tensile specimens

3D printing is a rapidly advancing method in digital manufacturing techniques and produces objects in layers. Fused Deposition Modelling (FDM) is a 3D printing technology where the material is melted in a hot nozzle and then placed on a build platform to create a prototype layer by layer. In this study, the effects of different raster angles (0°, 45°, 90°, 45°/-45°, 0°/90°) on dimensional accuracy for PLA, PETG and ABS materials produced using FDM were investigated. The results show that PETG generally shows higher dimensional deviations compared to PLA and ABS, and samples with a scan angle of 90° generally have lower deviation percentages than other angles. Width deviations (approximately 1.5% on average) were lower than thickness deviations (approximately 9.5% on average). Analysis of the cross-sectional areas shows that all samples are above the theoretical area (41.6 mm2). PETG samples with a scan angle of 45°/-45° exhibit the largest cross-sectional area (46.78 mm2), while ABS samples with a scan angle of 90° exhibit the smallest (45.46 mm2). This study is important to understand the impact of material selection and raster angle on dimensional accuracy, and it is recommended to account for cross-sectional deviations and calculate the stress based on the actual cross-sectional area to achieve more accurate results in applications requiring precise measurements. These data offer valuable information for those interested in 3D printing and its professionals and can lead to further research in this field, so that printing techniques can be further developed and product quality can be improved.

A Review of Game Theory Models to Support Production Planning, Scheduling, Cloud Manufacturing and Sustainable Production Systems

Cyber-physical systems, cloud computing, the Internet of Things, and big data play significant roles in shaping digital and automated landscape manufacturing. However, to fully realize the potential of these technologies and achieve tangible benefits, such as reduced manufacturing lead times, improved product quality, and enhanced organizational performance, new decision support models need development. Game theory offers a promising approach to address multi-objective problems and streamline decision-making processes, thereby reducing computational time. This paper aims to provide a comprehensive and up-to-date systematic review of the literature on the application of game theory models in various areas of digital manufacturing, including production and capacity planning, scheduling, sustainable production systems, and cloud manufacturing. This review identifies key research themes that have been explored and examines the main research gaps that exist within these domains. Furthermore, this paper outlines potential future research directions to inspire both researchers and practitioners to further explore and develop game theory models that can effectively support the digital transformation of manufacturing systems.