International Journal of Advanced Manufacturing Technology最新文献

{"title":"Simultaneous dimension and tolerance design for robot manipulator considering cost and positioning accuracy reliability.","authors":"Zhiwei Zhao, Yan Jin, Paul Goodall, Andrew West, Mark Price","doi":"10.1007/s00170-026-17862-8","DOIUrl":"10.1007/s00170-026-17862-8","url":null,"abstract":"<p><p>Tolerance allocation is an important design step for determining robot accuracy and directly affecting manufacturing cost. However, existing methods typically consider dimension synthesis first before tolerances are allocated, which neglects the manufacturability constraints arising from the dependency between part size and achievable tolerance grades. This often leads to costly iterations between design and manufacturing and increasing manufacturing cost. To address this issue, an integrated tolerance allocation and dimensional synthesis method of robot design is proposed for optimizing both positioning accuracy reliability and manufacturing cost. The method simultaneously optimizes joint dimensions and corresponding tolerances by formulating a cost function that captures the relationship between dimensional parameters, robot end-effector accuracy reliability, tolerance-grade rules, and manufacturing cost. Additionally, a matrix-based Monte Carlo simulation (MCS) method is introduced to accelerate evaluation workspace-wide reliability under tolerance uncertainty. NSGA-II multi-objective optimization algorithm is employed to find the Pareto front of the optimal solutions. A case study of a surgical robot is taken to demonstrate the effectiveness of the proposed approach. Results show that the proposed method can reduce 22% of manufacturing cost while achieving better positioning accuracy reliability compared to the traditional tolerance allocation method, and the speed of matrix-based MCS method is improved by 400 times compared to the point-based MCS method.</p>","PeriodicalId":50345,"journal":{"name":"International Journal of Advanced Manufacturing Technology","volume":"143 11-12","pages":"6509-6522"},"PeriodicalIF":3.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13183741/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147984093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reinforced scan: a reinforcement learning enabled optimal laser scan path planning in laser powder bed fusion additive manufacturing.","authors":"Chaoran Dou, Jihoon Chung, Raghav Gnanasambandam, Yuhao Wu, Jianzhi Li, Zhenyu James Kong","doi":"10.1007/s00170-025-17144-9","DOIUrl":"10.1007/s00170-025-17144-9","url":null,"abstract":"<p><p>Additive Manufacturing is an innovative technology that fabricates parts layer by layer. However, in Laser Powder Bed Fusion (LPBF), printed metal parts often exhibit residual stresses, deformations, and other defects due to non-uniform temperature distribution during the printing process. To mitigate these issues, an optimized scan sequence within each layer can improve thermal uniformity. Traditional optimization methods, which rely on domain knowledge and employ trial-and-error or heuristic approaches, often fail to achieve optimal solutions due to the complex nature of the problem. One major challenge in improving scan strategies lies in the vast search space required to optimize the scan sequence for individual scan tracks within each layer, making it difficult to identify the best solution. To overcome this challenge, this work proposes an innovative scan strategy, Reinforced Scan, that leverages reinforcement learning to intelligently determine the optimal scan sequence. The method introduces a novel reward function that accounts not only for temperature variance but also for the spatial uniformity of the temperature field. By structuring the optimization problem into multiple hierarchical levels, the approach significantly reduces computational demand and enhances the manageability of the optimization process. The effectiveness of the proposed Reinforced Scan is validated through Netfabb™ Local Simulation and real-world laser scanning experiments on a Ti-6Al-4V thin plate. Its performance is compared against conventional heuristic scan sequences. Both simulation and experimental results demonstrate that Reinforced Scan achieves superior outcomes, notably reducing residual stress compared to traditional methods.</p>","PeriodicalId":50345,"journal":{"name":"International Journal of Advanced Manufacturing Technology","volume":"142 9-10","pages":"5257-5273"},"PeriodicalIF":3.1,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12904886/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146203628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Influence of different lubrication strategies on surface quality and geometric accuracy in incremental sheet forming of stainless steel.","authors":"Aditya Vedanthu, Sabino Ayvar Soberanis, Chris M Taylor, Pete Crawforth, David Curtis","doi":"10.1007/s00170-026-18677-3","DOIUrl":"10.1007/s00170-026-18677-3","url":null,"abstract":"<p><p>Incremental Sheet Forming (ISF) has gained significant attention as a flexible and cost-effective manufacturing method for producing low to medium volume and customised sheet metal components. However, its industrial uptake remains limited by gaps in knowledge related to surface quality and geometric accuracy, which are strongly governed by tribological conditions at the tool-sheet interface. This study experimentally compares five distinct lubrication strategies - Hydro slide (HG32) oil, flood emulsion coolant, minimum quantity lubrication (MQL) using soybean oil, supercritical CO₂ (scCO₂), and hybrid scCO₂ + MQL during 25 ISF trials of 1 mm thick stainless-steel grade 304 sheets formed into an 84 mm × 84 mm square pyramid geometry. Process performance was evaluated using vertical forming forces, a friction indicator derived from tangential (in-plane) and vertical force measurements, surface roughness parameters (Ra and Rz) measured using the Alicona optical topography functionality, and geometric accuracy using full field 3D scanning. The results showed that HG32 consistently produced the lowest vertical forming forces but resulted in the poorest surface quality, characterised by pronounced surface smearing, higher friction indicator values, and increased Ra and Rz roughness parameters. The higher friction indicator values suggest a greater contribution of tangential forces relative to vertical forces, suggesting increased tool-sheet friction and reduced lubrication effectiveness. In contrast, MQL achieved the best overall surface quality, a lower friction indicator value suggesting more favourable tool-sheet sliding conditions and improved lubrication effectiveness and the most stable geometric performance, despite generating higher forming forces than HG32. Full field deviation mapping showed that geometric deviations were concentrated along diagonal regions for all lubrication strategies. Overall, the findings provide a detailed process quality dataset and clear guidance on selecting lubrication strategies to balance force demand, surface quality, and dimensional accuracy in ISF of hard to form stainless-steel parts.</p>","PeriodicalId":50345,"journal":{"name":"International Journal of Advanced Manufacturing Technology","volume":"145 9-10","pages":"7107-7129"},"PeriodicalIF":3.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13545147/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148898404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fabrication and characterisation of Ti and DLC coatings on metamaterial-architecture-inspired 3D-printed polymer substrates.","authors":"Ely Dannier V-Niño, José Luis Endrino, Andrés Díaz Lantada, Iván Fernández Martínez, Hugo Armando Estupiñán Duran, Saurav Goel","doi":"10.1007/s00170-026-17551-6","DOIUrl":"10.1007/s00170-026-17551-6","url":null,"abstract":"<p><p>This research explores the fabrication and characterisation of metamaterial-architecture-inspired 3D-printed polymer substrates with complex geometries, subsequently functionalized with titanium (Ti) and diamond-like carbon (DLC) coatings deposited by direct current magnetron sputtering. In this context, the term <i>metamaterial-architecture-inspired</i> refers exclusively to the engineered surface geometry and does not imply the experimental demonstration of emergent metamaterial properties. Polymeric substrates were fabricated via laser stereolithography using both an industrial (SLA-3500) and a low-cost (Form 1+) printing system, employing photoreactive resins in a layer-by-layer process. Ti and DLC thin films were subsequently deposited, and the resulting surfaces were characterised using reflected light optical microscopy and Raman spectroscopy to assess geometrical fidelity, coating conformity, and chemical-structural stability. Uniform coatings were successfully achieved on complex three-dimensional microtextures using both SLA systems. Substrates printed with the SLA-3500 exhibited well-defined layers and an average increase in valley curvature of approximately 2.8%, whereas Form 1 + printed samples showed a higher deviation of about 17.7% relative to the original design. Raman spectroscopy confirmed the presence of characteristic D and G bands at 1396 cm⁻¹ and 1589 cm⁻¹ in DLC-coated samples on both Accura^®60 and Clear FLGPCL 02 substrates, indicating graphitic carbon domains while preserving the chemical integrity of the underlying polymer. Ti-coated surfaces exhibited increased broadband intensity between 1200 and 1420 cm⁻¹, attributed to resin-metal interactions. Despite minor variations in spectral intensity, no significant shifts in vibrational frequencies were observed, demonstrating comparable molecular stability of both substrate systems following coating deposition. These results establish a reliable framework for the fabrication and surface functionalization of architected polymer substrates, enabling future investigations into structure-property relationships and application-specific functional performance.</p>","PeriodicalId":50345,"journal":{"name":"International Journal of Advanced Manufacturing Technology","volume":"142 11-12","pages":"6379-6391"},"PeriodicalIF":3.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12971785/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147437125","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning informed additive manufacturing of stainless steel 410 using cold metal transfer-based metal inert gas welding.","authors":"Swati Singh, Amritbir Singh, Shiva Sekar, Rajab Alsayegh, Shrikrishna Nandkishor Joshi, Saurav Goel","doi":"10.1007/s00170-026-18086-6","DOIUrl":"10.1007/s00170-026-18086-6","url":null,"abstract":"<p><p>This study investigates the use of machine learning to predict bead geometry in cold metal transfer (CMT)-based wire-arc additive manufacturing (WAAM) of SS410 martensitic stainless steel. A dataset comprising 50 experimentally deposited single beads was developed indigenously to model the relationship between key process parameters and the resulting bead aspect ratio. Multiple regression and advanced tree-based ensemble models, including Random Forest, XGBoost, Extra Trees Regressor and Cat-Boost Regressor (CBR), were implemented to capture the influence of wire feed rate, deposition rate (torch travel speed), current and voltage on bead morphology. Comparative evaluation of the models, supported by independent validation demonstrated that the CBR model provides the most accurate prediction of aspect ratio among other models investigated in this study. Feature importance analysis indicated that welding current is the dominant parameter governing bead geometry, followed by voltage. Microstructural characterisation of the thick walls produced using the optimal process parameters revealed a progressive increase in δ-ferrite content with build height, associated with heat accumulation during multilayer deposition. Correspondingly, the ultimate tensile strength and yield strength decrease by 14% and 12.7%, respectively. These findings highlight the potential of machine-learning-based frameworks for predicting and optimising process-geometry relationships in WAAM, while also indicating the need for future AI-assisted strategies to control phase evolution and mitigate the formation of detrimental microstructural constituents in martensitic stainless steels.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s00170-026-18086-6.</p>","PeriodicalId":50345,"journal":{"name":"International Journal of Advanced Manufacturing Technology","volume":"144 5-6","pages":"3875-3892"},"PeriodicalIF":3.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13260246/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148254266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mechanisms and advances in field assisted machining of SiC.","authors":"Peixiong Wang, Wenbin Zhong, Maomao Wang, Haodong Zhao, Wenrui Wu, Peixuan Yan, Wenhan Zeng, Xiangqian Jiang","doi":"10.1007/s00170-026-17695-5","DOIUrl":"10.1007/s00170-026-17695-5","url":null,"abstract":"<p><p>Silicon carbide (SiC) has become an increasingly important material for optical and semiconductor applications owing to its exceptional properties. However, its extreme hardness and brittleness pose significant challenges to traditional machining processes, leading to severe tool wear, low material removal rates, and suboptimal surface finishes. To overcome these issues, advanced field-assisted techniques like laser-assisted machining have emerged as promising solutions. This review provides a comprehensive overview of the mechanisms and recent advances in field-assisted machining processes of SiC, with a particular emphasis on laser-assisted machining. Critical research gaps are identified and a potential processing roadmap is outlined to pave the way for high-quality and efficient machining of SiC.</p>","PeriodicalId":50345,"journal":{"name":"International Journal of Advanced Manufacturing Technology","volume":"143 9-10","pages":"4691-4711"},"PeriodicalIF":3.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13095921/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147787854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigating the potential of auxetic structures in tibial insert toward multi-range load-carrying knee implant.","authors":"Ahmed ElZefzafy, Abdul Wasy Zia","doi":"10.1007/s00170-026-18816-w","DOIUrl":"10.1007/s00170-026-18816-w","url":null,"abstract":"<p><p>The artificial tibial insert degrades within the human body over service time as a metallic femoral surface continues articulating against it. The degradation rate depends on gait patterns and mainly on the human body weight, as tibial inserts normally lack subject-specific customisation. This article investigates the feasibility of gyroid, square anti-chiral, and triangular auxetic structures for tibial insert applications. The mechanical performance of new tibial designs is compared against a conventional (bulk) tibial insert through computational and experimental studies. The preliminary stress-strain and deformation behaviours are studied with ANSYS Workbench. Whereas the Instron machine is used for experimental studies to test the 3D printed conventional and auxetic structure-based tibial inserts designed in this work. The experimental studies are performed under a wide range of quasi-static and cyclic loading conditions to understand their mechanistic performance and suitability for knee joint functionality. Among gyroid, square anti-chiral and triangular auxetic structures, the triangular design has demonstrated exceptional load-bearing capabilities up to 20 kN, an adequate deflection up to 2.3 mm, along with 34.8% reduction in component weight. The enhanced elastic recovery supported by auxetic structures can provide knee safety under impact loads. In addition, it is perceived that the auxetic structures-based tibial insert provides tunable effective stiffness, demonstrating the significance of auxetic lattice design and their suitability for a wider range of body weights to ensure mechanical stability, medical safety, and implant longevity.</p>","PeriodicalId":50345,"journal":{"name":"International Journal of Advanced Manufacturing Technology","volume":"145 11-12","pages":"8403-8412"},"PeriodicalIF":3.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13562339/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148957254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel hybrid explainable artificial intelligence modelling approach for smart manufacturing.","authors":"Puthanveettil Madathil Abhilash, Xichun Luo, Qi Liu, Yi Qin","doi":"10.1007/s00170-025-17157-4","DOIUrl":"10.1007/s00170-025-17157-4","url":null,"abstract":"<p><p>Modelling complex manufacturing processes presents significant challenges related to accuracy and explainability. Physics-based models, while interpretable and generalizable, often suffer from reduced accuracy due to simplifications and incomplete system understanding. On the other hand, purely data-driven models are typically more accurate but lack transparency, limiting their trust and adoption in critical manufacturing applications. Existing hybrid approaches attempt to address these issues but often retain black-box AI components that compromise interpretability. In this study, we propose a novel hybrid modelling framework that intrinsically integrates physics-based models with explainable AI, to correct for modelling inaccuracies. This approach offers both high accuracy and transparent, traceable decision-making. Its effectiveness is demonstrated through a case study predicting the real-time position of cutting tools from accelerometer signals during ultra-precision diamond turning.</p>","PeriodicalId":50345,"journal":{"name":"International Journal of Advanced Manufacturing Technology","volume":"143 1-2","pages":"421-437"},"PeriodicalIF":3.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12975863/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147445570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deriving proxy life cycle assessment datasets for manufacturing machines through data clustering.","authors":"Nathan Dodd, Lenny Koh, Rachael Rothman","doi":"10.1007/s00170-026-18236-w","DOIUrl":"10.1007/s00170-026-18236-w","url":null,"abstract":"<p><p>Conducting Life Cycle Assessments (LCAs) for machines and tools in manufacturing is often time-intensive and hampered by difficulties in accessing suitable datasets. It is, nevertheless, important to consider the life cycle impacts of the machines and tools in a manufacturing process to identify hot spots, evaluate the relative importance of their impacts and develop strategies for further environmental improvements. This core novelty of this study is in the investigation of whether heterogeneous life cycle assessment (LCA) inventory and impact data for manufacturing machines can be meaningfully clustered, and whether the resulting groupings can be interpreted and operationalised as generalised proxy life cycle inventory datasets. It further evaluates the practical usefulness of these cluster-derived proxy datasets for supporting screening-level LCA and early-stage sustainability decision-making in manufacturing contexts. Three proxy LCA categories were developed, capturing broad similarities between machines while retaining sufficient detail for high-level sustainability assessments. The resulting machine proxy data provides a practical tool for streamlining LCA decision-making, allowing practitioners to estimate life cycle impacts from production to end-of-life even in the absence of detailed datasets. Validation against individual ecoinvent datasets showed that these generalised categories produce reasonably accurate approximations within typical uncertainty ranges, supporting exploratory analyses and screening applications. However, they are not intended to replace full LCAs for specific machines where precise assessment is required. Future work could enhance the proxy datasets by incorporating real-time operational data and regional variations, potentially using machine learning to refine impact estimates dynamically. Industrial integration of these datasets, such as in digital twin models or automated LCA platforms, would enable rapid, scalable sustainability assessments, supporting more informed decision-making in machine selection, procurement, and operational planning.</p>","PeriodicalId":50345,"journal":{"name":"International Journal of Advanced Manufacturing Technology","volume":"144 9-10","pages":"6515-6532"},"PeriodicalIF":3.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13275540/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148297190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A decision support model for efficient garment reprocessing for a sustainable circular business model.","authors":"Hariketan Patel, Gokula Vasantha, Jonathan Corney, John Quigley, Hanane El-Raoui, Rachel Sales, Michael Cusack, Anthony Burns, Andrew Rough","doi":"10.1007/s00170-025-17164-5","DOIUrl":"10.1007/s00170-025-17164-5","url":null,"abstract":"<p><p>The rapidly growing fashion business has intensified environmental, and sustainability concerns due to its focus on high-volume production at low costs. The rental-based business models in the circular economy, by promoting an alternative approach to garment ownership, aim to mitigate environmental impact, enhance businesses' competitiveness, and provide user value to customers. The rapid reprocessing of garment rentals offered to customers boosts corporate earnings and mitigates environmental issues. However, considering the complexities of garment reprocessing and fluctuations in rental demand, the objective of this study is to use an open Jackson queueing network with a decomposition approach to analyse the effects of external arrival rates and worker's processing rates on lead processing time and throughput for different garment types. The tradeoff curves provide a sensitivity analysis by varying the external arrival rate and the worker's processing rate to examine their impact on lead time and throughput of garment types. The results based on the workcell utilization demonstrate the tradeoff in throughput of various garment types by varying process parameters in the garments reprocessing. The results indicate that deviations in process parameters beyond certain upper and lower thresholds result in reduced throughput and increased lead time for garment types. The rearrangement of workers in the reprocessing workcell network showed a favourable improvement in the throughput of garment types. The findings significantly benefit the garment sector by offering a methodical approach for efficient processing, consequently improving overall efficiency and sustainability, and promoting circular economy efforts.</p>","PeriodicalId":50345,"journal":{"name":"International Journal of Advanced Manufacturing Technology","volume":"146 3","pages":"1705-1731"},"PeriodicalIF":3.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13582054/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148992292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}