Advanced Manufacturing Technology Research Articles

Determinants of Renewable Energy Development: Evidence from the EU Countries

Sustainable development of the global economy can be achieved with the help of renewable energy (RE). The paper investigates the determinants of RE development in order to boost its adoption. The determinants of RE deployment were analyzed using random-effects GLS regression for the panel data from 27 EU member states in 2011–2020.The results confirm that economic development and high employment in advanced technology manufacturing are drivers of the RE sector, whereas unemployment growth affects RE deployment negatively. Our results show that active political participation and economic freedom promote RE; however, the level of corruption and democracy does not have a statistically significant impact on it. Favorable geographical location was proved to be a determinant of RE development. The hypothesis that plenty of natural resources discourage countries to develop RE was disproved. The major policy implications for RE promotion include the importance of economy deregulation, open market development and educational transformations. Following the results, prospects for further research were outlined.

Device Processing Challenges for Miniaturized Sensing Systems Targeting Biological Fluids

This article presents a review of device processing technologies used in the fabrication of biomedical systems, and highlights the requirements of advanced manufacturing technology. We focus on biomedical systems that perform diagnostics of fluidic specimens, with analytes that are in the liquid phase. In the introduction, we define biomedical systems as well as their versatile applications and the essential current trends. The paper gives an overview of the most important biomolecules that typically must be detected or analyzed in several applications. The paper is structured as follows. First, the conventional architecture and construction of a biosensing system is introduced. We provide an overview of the most common biosensing methods that are currently used for the detection of biomolecules and its analysis. We present an overview of reported biochips, and explain the technology of biofunctionalization and detection principles, including their corresponding advantages and disadvantages. Next, we introduce microfluidics as a method for delivery of the specimen to the biochip sensing area. A special focus lies on material requirements and on manufacturing technology for fabricating microfluidic systems, both for niche and mass-scale production segments. We formulate requirements and constraints for integrating the biochips and microfluidic systems. The possible impacts of the conventional microassembly techniques and processing methods on the entire biomedical system and its specific parts are also described. On that basis, we explain the need for alternative microassembly technologies to enable the integration of biochips and microfluidic systems into fully functional systems.

Soft and Hard Total Quality Management Practices Promote Industry 4.0 Readiness: A SEM-Neural Network Approach

Industry 4.0 (I4.0) is a technological development in the manufacturing industry that has revolutionized Total Quality Management (TQM) practices. There has been scant empirical research on the multidimensional perspective of TQM. Thus, this study aims to empirically examine the effect of the multidimensional view of TQM (soft and hard) on I4.0 readiness in small and medium-sized (SMEs) manufacturing firms. Based on the sociotechnical systems (STS) theory, a framework has been developed and validated empirically through an online survey of 209 Malaysian SMEs manufacturing firms. Unlike the existing TQM studies that used structural equation modeling (SEM), a two-stage analysis was performed in this study. First, the SEM approach was used to determine which variable significantly affects I4.0 readiness. Second, the artificial neural network (ANN) technique was adopted to rank the relative influence of significant predictors obtained from SEM. The results show that the soft and hard TQM practices have supported the I4.0 readiness. Moreover, the results highlight that hard TQM practices have mediating role between soft TQM practices and I4.0 readiness. The ANN results affirmed that customer focus is considered an important TQM factor for I4.0 managerial readiness, advanced manufacturing technology for operational readiness and top management commitment for technology readiness. In a nutshell, the SEM-ANN approach uniquely contributes to the TQM and I4.0 literature. Finally, the findings can help managers to prioritize firms’ soft and hard quality practices that promote I4.0 implementation, especially in emerging economies.

Study on Chip Formation Mechanism of Single Crystal Copper Using Molecular Dynamics Simulations

Nano-cutting is an important development direction of the modern manufacturing technology. However, the research on the mechanism underlying nano-cutting lags far behind the practical application, which restricts the development of this advanced manufacturing technology. The chip formation process is the basic process of nano-cutting, and it is of key importance for the mechanism research of nano-cutting. In this paper, the nano-tensile behavior of single crystal copper was studied based on the molecular dynamics simulations. The toughness and brittleness characteristics of the copper at different temperatures were analyzed. Then, the molecular dynamics simulations of nano-cutting for single crystal copper with different toughness and brittleness were studied. The crystal structure, cutting force, stress–strain distribution and atomic motion characteristics were systematically investigated. The nano-chip formation mechanism of single crystal copper was revealed. The results show that the chip is formed through two ways, namely the shear and extrusion. The material near the free surface of the workpiece undergoes continuous shear slip and periodic long-distance slippage along the primary shear direction, forming the block chip in which the FCC and HCP structures are orderly distributed. The material near the tool-chip interface is extruded by the tool, block chip and stagnation zone to form the flowing chip with amorphous structure. As the temperature increases, the occurrence frequency of long-distance slippage in the block chip increases, while the slippage degree decreases. Besides, with the increase in temperature, the thickness of block chip formed by shear slip decreases, while the thickness of flowing chip formed by extrusion increases.

Programmable 4D Printing of Photoactive Shape Memory Composite Structures.

4D printing is an advanced manufacturing technology combining additive manufacturing with smart materials. Based on light-active shape memory composites, smart medical structures with remote control capability, therapeutic function, and biocompatibility are hopefully fabricated by 4D printing. Here, a multifunctional composite with good mechanical properties, biocompatibility, and light-active shape memory performance is prepared by incorporating gold nanoparticles into a shape memory polyurethane matrix. The composites demonstrate a rapid and stable light-thermal effect, which can achieve localized and controlled breast tumor ablation, providing an approach to hyperthermia treatment for cancer cells. By directly bioprinting the composite melt, a series of 4D-printed structures are manufactured accurately in a convenient, clean, and safe way, which show a fast autonomous light-driven shape recovery process. The examples of a 4D-printed soft tissue scaffold and intraluminal scaffold can expand from a conveniently insertional shape to an expanded shape under light exposure. The proposed strategies provide great inspiration for customized multifunctional light-thermal therapeutic structures for minimally invasive treatment.

Cross-efficiency for advanced manufacturing technology selection: A multi-task approach

Advanced manufacturing technologies (AMTs) are more and more used by firms to perform repetitive tasks in the production processes. As opting for an ATM represents an important investment for firms, several methodologies have been suggested to help firm decision-makers selecting the best one. A popular concept in that context is the cross-efficiency technique. In short, it endogenously selects the best ATM by computing scores using linear programmings. In this paper, we extend the cross-efficiency technique by adding a new feature: we model ATMs as multi-task processes. The multi-task approach presents two main advantages. One, it naturally gives the option to allocate inputs/costs and indicators/attributes to every task, yielding to a more realist modelling of the AMT processes. Two, AMTs can be compared for every task separately, increasing the discriminatory power of the selection process. As a consequence, the overall performances can be better understood, and, in particular, the reasons for declaring a specific AMT to be best can be investigated. We demonstrate the usefulness of our approach by considering a numerical example and two applications. In each case, we demonstrate the practical and managerial usefulness of our approach.

Multi-Station Multi-Axis Hybrid Layered Manufacturing (MSMA-HLM)

Additive manufacturing is advanced manufacturing technology in which material is added layer by layer. The hybrid approach with conventional and additive processes is utilized for making the component faster and cost-effective. Hybrid Layered Manufacturing (HLM) is the process in which a 3D component is made by adding and subtracting material layer by layer. HLM is basically for a metallic component in which material is added by depositing metal in wire form through an arc, LASER, EBM, and a small amount of material is removed by machining and thus making the system hybrid. There are various levels of hybridization in terms of approach, material, layering, joining process, kinematics and operations. A complete setup of HLM is developed with multiple stations and with a simultaneous five-axis system named as Multi-Station Multi-Axis Hybrid layered Manufacturing (MSMA-HLM). MSMA-HLM has its application in aerospace, automobile, marine, medical, etc. The various case studies with the HLM process are also demonstrated in this paper with cost and time compared with conventional manufacturing. The need for multiple stations during the HLM process is explained in this paper. The preheating, hammering, and inspection units are the add-ons in the manufacturing process for making defect-free components.

Application of Artificial Immune Systems in Advanced Manufacturing

In recent years, the application of Advanced Manufacturing Technologies (AMT) in industrial processes represents the introduction of different Advanced Manufacturing Systems (AMS), which encourage enterprises to improve their core competitiveness and maintain sustainable development when facing the increasing demand for personalized product customization. More recently, AMT led to a new Internet revolution, mostly known as 4th Industrial Revolution. Considering the development and deployment of Artificial Intelligence to enable smart and self-behaving industrial systems, autonomic approaches allow the system to adapt itself, eliminating the need for human intervention for management. This paper presents a systematic literature review regarding Artificial Immune Systems (AIS) approaches to tackle multiple AMS problems requiring levels of autonomy. First, a systematic review of current industrial AIS applications in manufacturing environments is presented. Then, a conceptual framework is proposed to bridge the gap between research in the AIS field and the manufacturing industry while discussing key challenges and opportunities to be addressed by future research. This study aims to build a body of knowledge for researchers and manufacturers regarding AIS solutions under Advanced Manufacturing while suggesting directions for understanding the requirements for designing and managing autonomic industry applications supported by AIS. • Presentation of a systematic review of AIS methods application in AMS. • Summary of the empirical evidence of the benefits of applying AIS algorithms in AMS. • Exploration of the readiness level and autonomy of AIS applications in AMS. • Outline the key areas where future research can improve the use of AIS in AMS.

The Relationship Between the Implementation Levels of Industry 4.0 Technologies and Advanced Manufacturing Technologies - PROOF READING

The Relationship Between the Implementation Levels of Industry 4.0 Technologies and Advanced Manufacturing Technologies - PROOF READING

Topic discovery innovations for sustainable ultra-precision machining by social network analysis and machine learning approach

Ultra-precision machining (UPM) is an advanced manufacturing technology that experiences increasing demand. Therefore, it is necessary to minimize the environmental impacts from its enormous consumptions of resources. Achieving sustainable UPM is still a challenge is it involves complicated influencing relationships among relevant factors like energy consumption, and human health, which could affect sustainable performance. And some influencing relationships between two parameters have not been fully studied yet, which are named as undiscussed two-parameter relationships. Therefore, this paper proposed a new topic discovery model based on social network analysis (SNA) and machine learning approach to discover the undiscussed two-parameter relationships with high potential value in the sustainable UPM research field. By using the link prediction metrics obtained by SNA and principal components analysis in this study, the interactive relationships among the parameters of sustainable ultra-precision machining are determined to discover the potential values of undiscussed two-parameter topics. Then, the k-means algorithm is applied to classify the topics based on the similarity of the metrics results to present the potential value distribution of the undiscussed topics in sustainable UPM. From the metrics results, the topic of the relationship between environmental damage and resource waste was found to be the most valuable potential two-parameter topic in the area of sustainable UPM. This paper also contributes to showing the potential value distribution of undiscussed two-parameter relationships and predicting the sustainable development trend in the UPM sectors.

Design and Implementation of an HCPS-Based PCB Smart Factory System for Next-Generation Intelligent Manufacturing

The next-generation intelligent smart factory system that is proposed in this paper could improve product quality and realize flexible, efficient, and sustainable product manufacturing by comprehensively improving production and management innovation via its digital network and intelligent methods that reflect the characteristics of its printed circuit board (PCB) manufacturing design and on-site implementation. Intelligent manufacturing systems are complex systems that are composed of humans, cyber systems, and physical systems and aim to achieve specific manufacturing goals at an optimized level. Advanced manufacturing technology and next-generation artificial intelligence (AI) are deeply integrated into next-generation intelligent manufacturing (NGIM). Currently, the majority of PCB manufacturers are firms that specialize in processing orders from leading semiconductor and related product manufacturers, such as Samsung Electronics, TSMC, Samsung Electro-Mechanics, and LG Electronics. These top companies have been responsible for all product innovation, intelligent services, and system integration, with PCB manufacturers primarily playing a role in intelligent production and system integration. In this study, the main implementation areas were divided into manufacturing execution system (MES) implementation (which could operate the system using system integration), data gathering, the Industrial Internet of Things (IIoT) for production line connection, AI and real-time monitoring, and system implementation that could visualize the collected data. Finally, the prospects of the design and on-site implementation of the next-generation intelligent smart factory system that detects and controls the occurrence of quality and facility abnormalities are presented, based on the implementation system.

The study of the roundness and cylindricity deviations of parts produced with the use of the additive manufacturing

The paper is dedicated to the evaluation of the accuracy of rotary parts produced with the use of advanced manufacturing technology. The authors investigated the impact of the layer thickness of the applied material and the orientation of the model when printing using the PolyJet method™ on the geometrical quality of manufactured products. To analyze the influence of the assumed factors on the geometrical quality of the holes, a novel evaluation method has been developed. The proposed method takes into account parameters such as roundness deviation, profile irregularity coefficient, dominant harmonic component of the roundness profile, cylindricity deviation, diameter error, and surface topography parameters. The study presented in this paper had two main objectives. The former was to analyze the impact of the layer thickness of the applied material and the orientation of the model when printing using the PolyJet method™ on the geometrical quality of rotary parts. The latter objective was to test a novel, multi-parametric method of evaluation of the accuracy of produced parts in practice. The results obtained by the authors prove that the new evaluation method can be useful in the assessment of the accuracy of manufactured products.

Characterization of Epoxy-Based Rapid Mold with Profiled Conformal Cooling Channel.

Based on the experience of the foundry industry, reducing the demolding time is the key for mass production of wax patterns with sophisticated geometries. Integration of numerical simulation and rapid tooling technology for decreasing the time to market is essential in advanced manufacturing technology. However, characterization of epoxy-based rapid molds with a profiled conformal cooling channel (PCCC) using computer-aided engineering simulation of the epoxy-based rapid mold with PCCC was not found in the literature. In this study, epoxy-based rapid molds with PCCC were characterized numerically and experimentally. The cooling performance of wax injection molds with two different kinds of cross-sections of the cooling channel was investigated. Four pairs of injection molds with PCCC were implemented using four different kinds of material formulations. It was found that the cooling performance of the PCCC was better than a circular conformal cooling channel (CCCC) since the PCCC maintained a more uniform and steady cooling performance of injection-molded product than CCCC. Epoxy resin added with 41 vol.% Cu powder seems to be a cost-effective empirical material formulation in terms of cooling time and material costs. This empirical material formulation provided an injection mold with low material cost and good cooling performance simultaneously compared to an injection mold fabricated with commercial material. The cooling performance could reach 88% of that of the injection mold fabricated with commercial material. The material cost of making the injection mold was only about 60% of that of the injection mold fabricated with commercial material. The coolant flow rate had no significant effect on the cooling time, whereas the cooling time of the wax pattern was affected by coolant temperature significantly.

Rapid Heat Control for Thermoplastic Injection Tooling Using Lattice Structures as Heat Exchanger

Since conventional cooling systems with channels are not adequate to achieve a high aspect quality with a short cycle time, a better concept has to be used to control the fast variation of temperature in the mold, close to the injected part. Recently, with advanced manufacturing technologies like 3D-printing, rapid heat cycle molding are developing, using for example lattice structures as heat exchanger inside the mold. Our work proposes an experimental study to analyze the influence of four lattice structures that were specifically designed for this industrial application. An instrumented bench was developed at the laboratory scale, to test the thermal efficiency of the lattice. The material and geometry of the lattice structures were selected based on their thermomechanical properties and their efficiency as a heat-exchanger. The instrumentation of the bench consists in measuring the flow rate and the pressures in the fluid, and also the temperatures at various locations. This allows us to determine the performances of the lattice structure. The results show that the denser the lattice structure, the better, whether considering the mechanical resistance or the thermohydraulic performances. The key element to understand this phenomenon is the average velocity of the fluid flowing inside the lattice structure, accelerating when the porosity decreases and thus bringing a more intense heat exchange.

RETRACTED ARTICLE: Terahertz fading model for wireless nanosensor networks in advanced medical manufacturing technologies

RETRACTED ARTICLE: Terahertz fading model for wireless nanosensor networks in advanced medical manufacturing technologies

Driving Factors and Mechanisms of AMT Application Levels for Equipment Manufacturing Enterprises: Based on Programmatic Grounded Theory

As a major part of the global manufacturing industry attaining technological upgrades, the adoption and application of advanced manufacturing technology (AMT) plays a vital role in the development of enterprises. Thus, it is of the utmost significance to examine the driving factors that affect AMT application levels in equipment manufacturing enterprises. Through extensive interviews, the use of the qualitative research method of grounded theory, and the three-stage coding of the interview data from intelligent manufacturing pilot demonstration enterprises and projects, this study identified the key influencing factors for the AMT application levels of equipment manufacturing enterprises. We obtained 46 concepts and extracted 18 key categories and 6 main categories. Then, the logical relationships between the main categories were established. Finally, a driving factor model for the AMT application levels of equipment manufacturing enterprises was constructed. The results reveal that the driving factors that affect the AMT application levels of equipment manufacturing enterprises can be summarized as capability factors (technical capability, market capability, and management capability), motivation factors (material incentives and development incentives), and opportunity factors (external stakeholders). Overall, this study proposed a mechanism from the three aspects of ability, motivation, and opportunity.

(Invited) From Nano-Bulk Interplayed Composites to Industrial Standard Devices: A Length Scale Evolution of Heterogeneous Functional Materials for Solid Oxide Electrochemical Cells at Intermediate Temperatures

Heterogeneous functional materials play very important roles in solid oxide electrochemical cells in intermediate temperatures (400-600oC). At this temperature regime, the solid oxide electrochemical cells can compromise the disadvantages from lower and higher temperature counterparts by adopting more cost-effective catalysts and materials as the cell components while mitigating the fast degradation to achieve optimal reaction kinetics. More importantly, it allows many nano-sized catalysts to be functioning that can be ultimately integrated into the real device through advanced manufacturing technologies. At Idaho National Laboratory, we developed a series of strategies to accommodate heterogeneous functional materials for a range of applications, including hydrogen production via water electrolysis, CO2 conversion and ammonia electrosynthesis using protonic ceramic electrochemical cells (PCECs). The special emphasis is placed on the effect of structure, composition, morphology, and defects of these materials on electrochemical performance of PCECs and respective product for a given feedstock.

The impact of advanced manufacturing technology (AMT) application on product innovation performance: a model of mediated moderated effect

PurposeDrawing on the integration of the knowledge-based theory and the resource orchestration theory, this study aims to develop a moderated mediation model on how design/manufacturing/administrative advanced manufacturing technology (AMT) influences product innovation performance. The authors hypothesized that the absorption capacity could mediate the AMT-innovation performance link and that design–manufacturing integration (DMI) could positively moderate the mediating effect of the absorption capacity.Design/methodology/approachTo test the hypothesis, the authors conducted a mail survey of equipment manufacturing firms and obtained 302 valid responses for data analysis. Both hierarchical regression and bootstrapping analysis were conducted to empirically test the research model.FindingsIt is revealed that the absorption capacity partially mediated the effect of AMT on innovation and that DMI enhanced the mediated effect. Specifically, the mediating effect of the absorption capacity was more substantial and significant when DMI was high. However, the mediating effect of the absorption capacity was weaker and insignificant when DMI was low.Originality/valueOverall, this study contributes to the AMT theory on innovation by identifying the absorption capacity and DMI as two key factors that elucidate why and under what conditions AMT affects innovation. Moreover, this study advises managers that besides developing AMT, firms should cultivate a strong DMI, which directs the absorption capacity toward converting the valuable knowledge in firms’ capital equipment into increased innovation performance.

A Two-Step Fuzzy MCDM Method for Implementation of Sustainable Precision Manufacturing: Evidence from China

Despite that products of precision manufacturing are widely used in many fields involving the national economy, precision manufacturing processes are more unfriendly to the environment, resources and social development than general manufacturing. Hence, the implementation of sustainable precision manufacturing (SPM) is of great strategic significance. There is no literature identifying and ranking the drivers of implementation of SPM and the impact on sustainability owing to the application of advanced manufacturing technologies in SPM has not been explored. To resolve these problems, drivers of SPM are identified based on combined support of prior studies and six groups of experts consisting of 71 individuals from six precision manufacturing enterprises. The drivers are calculated and ranked by a two-step fuzzy MCDM method which integrated the fuzzy AHP (fuzzy analytic hierarchy process) and fuzzy TOPSIS (fuzzy technique for order of preference by similarity to ideal solution) algorithms. The evaluation of drivers is based on the basic principles of sustainable development (environmental criterion, social criterion and economic criterion). The paper concludes that technological innovation, government support and current legislation are the most critical drivers during SPM implementation. Additionally, the result of sensitivity verification of the proposed method conducted proves the robustness and correctness of the algorithm and results.

Bone Tissue Engineering through 3D Bioprinting of Bioceramic Scaffolds: A Review and Update.

Trauma and bone loss from infections, tumors, and congenital diseases make bone repair and regeneration the greatest challenges in orthopedic, craniofacial, and plastic surgeries. The shortage of donors, intrinsic limitations, and complications in transplantation have led to more focus and interest in regenerative medicine. Structures that closely mimic bone tissue can be produced by this unique technology. The steady development of three-dimensional (3D)-printed bone tissue engineering scaffold therapy has played an important role in achieving the desired goal. Bioceramic scaffolds are widely studied and appear to be the most promising solution. In addition, 3D printing technology can simulate mechanical and biological surface properties and print with high precision complex internal and external structures to match their functional properties. Inkjet, extrusion, and light-based 3D printing are among the rapidly advancing bone bioprinting technologies. Furthermore, stem cell therapy has recently shown an important role in this field, although large tissue defects are difficult to fill by injection alone. The combination of 3D-printed bone tissue engineering scaffolds with stem cells has shown very promising results. Therefore, biocompatible artificial tissue engineering with living cells is the key element required for clinical applications where there is a high demand for bone defect repair. Furthermore, the emergence of various advanced manufacturing technologies has made the form of biomaterials and their functions, composition, and structure more diversified, and manifold. The importance of this article lies in that it aims to briefly review the main principles and characteristics of the currently available methods in orthopedic bioprinting technology to prepare bioceramic scaffolds, and finally discuss the challenges and prospects for applications in this promising and vital field.