Pub Date : 2026-02-28Epub Date: 2026-01-26DOI: 10.1016/j.jmapro.2026.01.076
Shuhan Li , Xinqiang Lan , Zemin Wang
Extrusion-based additive manufacturing of powder-binder feedstocks offers a cost-effective route for indirectly fabricating metallic components. However, the sintering step remains a major bottleneck, typically requiring lengthy, powder-specific optimization that can exceed the effort spent on printing parameter tuning. This study overcomes this challenge by establishing a direct correlation between macroscopic shrinkage and microscopic porosity, enabling rapid assessment of sintering quality. For H13 steel, densification proceeds through solid-phase sintering at 1000–1350 °C and liquid-phase sintering at 1400–1450 °C. Thermodynamic analysis and experimental results confirm that by increasing the sintering temperature and avoiding excessive liquid-phase sintering (1300–1400 °C), both SSAM-5 and SSAM-10 powders (with medium particle size of 5.3 μm and 11.8 μm) can achieve ideal porosities of 0.45% and 0.96% after 1–3 h of holding. Macroscopic shrinkage was observed after sintering and approached a theoretical limit as porosity decreased. A quantitative model linking shrinkage to porosity was developed, enabling the immediate assessment of internal densification using easily accessible macroscopic data.
{"title":"Revealing the sintering behavior of H13 steel in semi-solid additive manufacturing through the correlation of shrinkage and porosity","authors":"Shuhan Li , Xinqiang Lan , Zemin Wang","doi":"10.1016/j.jmapro.2026.01.076","DOIUrl":"10.1016/j.jmapro.2026.01.076","url":null,"abstract":"<div><div>Extrusion-based additive manufacturing of powder-binder feedstocks offers a cost-effective route for indirectly fabricating metallic components. However, the sintering step remains a major bottleneck, typically requiring lengthy, powder-specific optimization that can exceed the effort spent on printing parameter tuning. This study overcomes this challenge by establishing a direct correlation between macroscopic shrinkage and microscopic porosity, enabling rapid assessment of sintering quality. For H13 steel, densification proceeds through solid-phase sintering at 1000–1350 °C and liquid-phase sintering at 1400–1450 °C. Thermodynamic analysis and experimental results confirm that by increasing the sintering temperature and avoiding excessive liquid-phase sintering (1300–1400 °C), both SSAM-5 and SSAM-10 powders (with medium particle size of 5.3 μm and 11.8 μm) can achieve ideal porosities of 0.45% and 0.96% after 1–3 h of holding. Macroscopic shrinkage was observed after sintering and approached a theoretical limit as porosity decreased. A quantitative model linking shrinkage to porosity was developed, enabling the immediate assessment of internal densification using easily accessible macroscopic data.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"160 ","pages":"Pages 359-370"},"PeriodicalIF":6.8,"publicationDate":"2026-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146080407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-28Epub Date: 2026-01-21DOI: 10.1016/j.jmapro.2026.01.051
Hao Cui , Tao Zhou , Yin Yuan , Cheng Zhang , Feilong Du , Zebin Su , Jing Deng , Pengfei Tian , Zhiguo Feng , Lin He
When milling high-hardness H13 hardened die steel, issues such as excessive milling force and severe tool wear often occur. Research shows that thermally assisted processing can reduce the mechanical stress of the milling process, but it also activates the thermal damage mechanism of the tool and workpiece accordingly. Therefore, the research proposes a multi-energy field processing method for heat-cold source assisted milling and hardened mold steel integrating thermal softening effect (Induction Heating) and clean cooling lubrication effect (Cryogenic Minimum Quantity Lubrication, CMQL). The research first adopted a research method combining simulation with experimental verification to conduct thermal simulation analysis, revealing the control laws of external heat and cold fields on the surface temperature fields of tools and workpieces, and determining the effective milling depth. Afterwards, the heat-cold source multi-energy field synergistic assisted milling experimental platform was built, and the action mechanism of the heat-cold source synergistic working conditions on milling H13 steel was fully revealed. Research show that compared with dry machining, in the HCSAM environment, the main cutting resistance increases by 13.37% and 7.58% respectively when P = 20 kW and 50 kW, while it decreases by 22.3% when P = 80 kW. The application of CMQL enhances heat dissipation from the tool surface, which in turn suppresses the development of a built-up layer and mitigates tool wear. Meanwhile, induction heat will promote the transformation of chip fracture from brittle to ductile, causing the maximum reduction in surface roughness Ra to reach 12.1%. In addition, compared with dry and HCSAM environments (preheating temperatures of 200 °C and 300 °C), the HCSAM environment with a preheating temperature of 550 °C induces grain coarsening and homogenization in the surface and near-surface areas, reduces the work hardening effect, but simultaneously increases the surface residual stress. This study reveals the application potential of heat-cold source synergistic assisted milling (HCSAM) in multi-energy field machining, which can provide an effective solution for high-performance milling of H13 hardened die steel.
{"title":"Research on the mechanism of heat-cold source synergistic assisted milling of hardened die steel","authors":"Hao Cui , Tao Zhou , Yin Yuan , Cheng Zhang , Feilong Du , Zebin Su , Jing Deng , Pengfei Tian , Zhiguo Feng , Lin He","doi":"10.1016/j.jmapro.2026.01.051","DOIUrl":"10.1016/j.jmapro.2026.01.051","url":null,"abstract":"<div><div>When milling high-hardness H13 hardened die steel, issues such as excessive milling force and severe tool wear often occur. Research shows that thermally assisted processing can reduce the mechanical stress of the milling process, but it also activates the thermal damage mechanism of the tool and workpiece accordingly. Therefore, the research proposes a multi-energy field processing method for heat-cold source assisted milling and hardened mold steel integrating thermal softening effect (Induction Heating) and clean cooling lubrication effect (Cryogenic Minimum Quantity Lubrication, CMQL). The research first adopted a research method combining simulation with experimental verification to conduct thermal simulation analysis, revealing the control laws of external heat and cold fields on the surface temperature fields of tools and workpieces, and determining the effective milling depth. Afterwards, the heat-cold source multi-energy field synergistic assisted milling experimental platform was built, and the action mechanism of the heat-cold source synergistic working conditions on milling H13 steel was fully revealed. Research show that compared with dry machining, in the HCSAM environment, the main cutting resistance increases by 13.37% and 7.58% respectively when <em>P</em> = 20 kW and 50 kW, while it decreases by 22.3% when <em>P</em> = 80 kW. The application of CMQL enhances heat dissipation from the tool surface, which in turn suppresses the development of a built-up layer and mitigates tool wear. Meanwhile, induction heat will promote the transformation of chip fracture from brittle to ductile, causing the maximum reduction in surface roughness <em>Ra</em> to reach 12.1%. In addition, compared with dry and HCSAM environments (preheating temperatures of 200 °C and 300 °C), the HCSAM environment with a preheating temperature of 550 °C induces grain coarsening and homogenization in the surface and near-surface areas, reduces the work hardening effect, but simultaneously increases the surface residual stress. This study reveals the application potential of heat-cold source synergistic assisted milling (HCSAM) in multi-energy field machining, which can provide an effective solution for high-performance milling of H13 hardened die steel.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"160 ","pages":"Pages 158-184"},"PeriodicalIF":6.8,"publicationDate":"2026-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146036893","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-28Epub Date: 2026-01-28DOI: 10.1016/j.jmapro.2026.01.086
Chuanqi Liu , Yugang Miao , Ji Liu , Yuyang Zhao , Yuhang Yang , Yifan Wu , Zhiqiang Gao
Functionally graded materials (FGMs) offer a pathway to reconcile conflicting requirements of strength, ductility, and corrosion resistance in structural applications. Here we report the fabrication of FeCoCrNiMo0.2 high-entropy alloy (HEA)/ER120S-G steel gradient structures using an arcing-wire powder hybrid additive manufacturing (AWPH-AM) approach. By continuously varying the wire–powder feed ratio, we achieve in situ control of phase evolution, grain orientation, and passive-film chemistry across the compositional gradient. Microstructural analysis reveals a progressive transition from acicular ferrite to FCC-dominated solid solutions, accompanied by Mo-induced grain-boundary precipitation at high HEA fractions. Mechanical testing shows a trade-off between strength and ductility: steel-rich layers exhibit ultimate tensile strengths approximately1200 MPa with limited elongation, whereas intermediate layers achieve elongation above 30% owing to stable FCC solid solutions. At higher HEA content, precipitation of Mo-rich phases enhances hardness but induces brittle fracture. Electrochemical testing demonstrates a systematic improvement in corrosion resistance with increasing HEA fraction, culminating in the formation of a self-healing Cr2O3–MoOx composite passive film that provides superior protection in chloride environments. This work establishes AWPH-AM as a versatile platform for the design of FGMs, and demonstrates composition–microstructure-property coupling as a strategy to balance strength, ductility, and corrosion resistance in demanding marine and energy applications.
{"title":"Microstructure, mechanical properties and corrosion resistance of FeCoCrNiMo0.2/ER120s-G gradient structures fabricated by arcing-wire powder hybrid additive manufacturing","authors":"Chuanqi Liu , Yugang Miao , Ji Liu , Yuyang Zhao , Yuhang Yang , Yifan Wu , Zhiqiang Gao","doi":"10.1016/j.jmapro.2026.01.086","DOIUrl":"10.1016/j.jmapro.2026.01.086","url":null,"abstract":"<div><div>Functionally graded materials (FGMs) offer a pathway to reconcile conflicting requirements of strength, ductility, and corrosion resistance in structural applications. Here we report the fabrication of FeCoCrNiMo<sub>0.2</sub> high-entropy alloy (HEA)/ER120S-G steel gradient structures using an arcing-wire powder hybrid additive manufacturing (AWPH-AM) approach. By continuously varying the wire–powder feed ratio, we achieve in situ control of phase evolution, grain orientation, and passive-film chemistry across the compositional gradient. Microstructural analysis reveals a progressive transition from acicular ferrite to FCC-dominated solid solutions, accompanied by Mo-induced grain-boundary precipitation at high HEA fractions. Mechanical testing shows a trade-off between strength and ductility: steel-rich layers exhibit ultimate tensile strengths approximately1200 MPa with limited elongation, whereas intermediate layers achieve elongation above 30% owing to stable FCC solid solutions. At higher HEA content, precipitation of Mo-rich phases enhances hardness but induces brittle fracture. Electrochemical testing demonstrates a systematic improvement in corrosion resistance with increasing HEA fraction, culminating in the formation of a self-healing Cr<sub>2</sub>O<sub>3</sub>–MoO<sub>x</sub> composite passive film that provides superior protection in chloride environments. This work establishes AWPH-AM as a versatile platform for the design of FGMs, and demonstrates composition–microstructure-property coupling as a strategy to balance strength, ductility, and corrosion resistance in demanding marine and energy applications.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"160 ","pages":"Pages 553-570"},"PeriodicalIF":6.8,"publicationDate":"2026-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146080390","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-28Epub Date: 2026-01-24DOI: 10.1016/j.jmapro.2026.01.053
Yang Sun , Shuoshuo Qu , Yuying Yang , Dongkai Chu , Peng Yao
Zirconia Toughened Alumina ceramics (ZTAs) are widely used in biomedical fields such as artificial joints due to their excellent wear resistance and biocompatibility. However, their high hardness and brittleness lead to poor surface quality and severe wheel wear during grinding. This study proposes laser pre-ablation assisted grinding (LPAG), utilizing a picosecond laser to fabricate vertical textures, checkerboard textures, and parallel textures on the surface of ZTAs to assist the grinding process. Further, by conducting multi-gradient grinding depth experiments, a laser-grinding parameters collaborative optimization model was established. Experimental results demonstrate that LPAG can significantly reduce grinding forces, with the vertical texture structures showing particularly outstanding performance. The maximum reductions in normal grinding force and tangential grinding force reached 82.4% and 95.6%, respectively. When the grinding depth is 0.6 μm, the surface roughness increases in the order of parallel textures, checkerboard textures, and vertical textures. The surface roughness of parallel-textured workpieces after grinding can reach 103.7 nm, whereas the surface roughness of vertical-textured workpieces is comparable to that of non-laser-ablated workpieces. Grinding of non-laser-ablated workpieces generates extensive fractured pits, while the laser-ablated workpieces exhibit dense pores in the heat-affected zone (HAZ) after grinding. By increasing the material removal depth, the HAZ area fraction can be reduced to 7.9%. When the grinding depth decreases from 0.5 μm to 0.1 μm, the surface roughness of vertical-textured workpieces after grinding is reduced from 103.2 nm to 58.1 nm, with the normal grinding force and tangential grinding force decreasing by an average of 29.4% and 61.1%, respectively. Under grinding depths below 0.2 μm, the vertical-textured workpieces exhibit extensive ductile removal, significantly improving the grinding quality. This study demonstrates the feasibility of LPAG combined with gradient parameter optimization to achieve high-efficiency and low-damage machining of ZTAs.
{"title":"Laser pre-ablation assisted grinding process and material removal mechanisms of ZTA ceramics","authors":"Yang Sun , Shuoshuo Qu , Yuying Yang , Dongkai Chu , Peng Yao","doi":"10.1016/j.jmapro.2026.01.053","DOIUrl":"10.1016/j.jmapro.2026.01.053","url":null,"abstract":"<div><div>Zirconia Toughened Alumina ceramics (ZTAs) are widely used in biomedical fields such as artificial joints due to their excellent wear resistance and biocompatibility. However, their high hardness and brittleness lead to poor surface quality and severe wheel wear during grinding. This study proposes laser pre-ablation assisted grinding (LPAG), utilizing a picosecond laser to fabricate vertical textures, checkerboard textures, and parallel textures on the surface of ZTAs to assist the grinding process. Further, by conducting multi-gradient grinding depth experiments, a laser-grinding parameters collaborative optimization model was established. Experimental results demonstrate that LPAG can significantly reduce grinding forces, with the vertical texture structures showing particularly outstanding performance. The maximum reductions in normal grinding force and tangential grinding force reached 82.4% and 95.6%, respectively. When the grinding depth is 0.6 μm, the surface roughness increases in the order of parallel textures, checkerboard textures, and vertical textures. The surface roughness of parallel-textured workpieces after grinding can reach 103.7 nm, whereas the surface roughness of vertical-textured workpieces is comparable to that of non-laser-ablated workpieces. Grinding of non-laser-ablated workpieces generates extensive fractured pits, while the laser-ablated workpieces exhibit dense pores in the heat-affected zone (HAZ) after grinding. By increasing the material removal depth, the HAZ area fraction can be reduced to 7.9%. When the grinding depth decreases from 0.5 μm to 0.1 μm, the surface roughness of vertical-textured workpieces after grinding is reduced from 103.2 nm to 58.1 nm, with the normal grinding force and tangential grinding force decreasing by an average of 29.4% and 61.1%, respectively. Under grinding depths below 0.2 μm, the vertical-textured workpieces exhibit extensive ductile removal, significantly improving the grinding quality. This study demonstrates the feasibility of LPAG combined with gradient parameter optimization to achieve high-efficiency and low-damage machining of ZTAs.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"160 ","pages":"Pages 345-358"},"PeriodicalIF":6.8,"publicationDate":"2026-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146080409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-28Epub Date: 2026-01-24DOI: 10.1016/j.jmapro.2026.01.072
Brandon Jones , Jyhwen Wang , Bruce Tai , Albert E. Patterson
This study explores the debinding and sintering behavior of copper powder material extrusion (PME) parts with a polylactide (PLA) binder. PME, sometimes known as toolless powder injection molding, is an extrusion-based additive manufacturing (AM) method that produces green parts with high powder loadings (around 90% by weight). These parts require debinding and sintering to be useful, similar to those produced by many traditional methods that use powder and binder as their feedstock. A design-of-experiments (DOE) approach was employed to evaluate the effects of different debinding ramp rates, crucible materials, and ballast types. The processing envelope used in the study reflects the simplified, low-complexity debinding and sintering workflow that is one of the common features of PME, rather than more complex ones focused on optimizing metallurgy. The data showed that the debinding with the alumina ballast produced better mechanical properties, while the sintering with a talc ballast at optimized ramp speeds led to greater density and strength of the parts. The highest ultimate tensile strength (UTS) achieved was 63.98 MPa with a sintered density of 67.55%. The results outline a realistic performance envelope for copper PME processed under these constraints, both revealing and taking advantage of key tradeoffs between debinding strategy, thermal history, and final part integrity. Microscopy analysis revealed that part quality depended heavily on debinding and sintering conditions, with talc ballast producing more consistent surface integrity for sintered parts.
{"title":"Debinding and sintering of copper powder material extrusion parts with a polylactide binder","authors":"Brandon Jones , Jyhwen Wang , Bruce Tai , Albert E. Patterson","doi":"10.1016/j.jmapro.2026.01.072","DOIUrl":"10.1016/j.jmapro.2026.01.072","url":null,"abstract":"<div><div>This study explores the debinding and sintering behavior of copper powder material extrusion (PME) parts with a polylactide (PLA) binder. PME, sometimes known as toolless powder injection molding, is an extrusion-based additive manufacturing (AM) method that produces green parts with high powder loadings (around 90% by weight). These parts require debinding and sintering to be useful, similar to those produced by many traditional methods that use powder and binder as their feedstock. A design-of-experiments (DOE) approach was employed to evaluate the effects of different debinding ramp rates, crucible materials, and ballast types. The processing envelope used in the study reflects the simplified, low-complexity debinding and sintering workflow that is one of the common features of PME, rather than more complex ones focused on optimizing metallurgy. The data showed that the debinding with the alumina ballast produced better mechanical properties, while the sintering with a talc ballast at optimized ramp speeds led to greater density and strength of the parts. The highest ultimate tensile strength (UTS) achieved was 63.98 MPa with a sintered density of 67.55%. The results outline a realistic performance envelope for copper PME processed under these constraints, both revealing and taking advantage of key tradeoffs between debinding strategy, thermal history, and final part integrity. Microscopy analysis revealed that part quality depended heavily on debinding and sintering conditions, with talc ballast producing more consistent surface integrity for sintered parts.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"160 ","pages":"Pages 332-344"},"PeriodicalIF":6.8,"publicationDate":"2026-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146080408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-28Epub Date: 2026-01-28DOI: 10.1016/j.jmapro.2026.01.034
Kuan-Chieh Lu , Zhiqiao Dong , Chenhui Shao
Ultrasonic metal welding (UMW) is a solid-state joining process widely used in industrial applications. However, its sensitivity to tool wear, surface contamination, and material variability presents persistent challenges for ensuring weld quality. Existing online monitoring systems often emphasize predictive accuracy while neglecting practical constraints such as hardware cost, data acquisition rate, and computational latency. To overcome this gap, this paper develops a systematic framework for cost- and time-efficient sensor and feature selection in UMW monitoring. The proposed method integrates signal decomposition, feature importance analysis, cost-aware genetic algorithm optimization, and a separability-analysis-based adaptation mechanism to identify an optimal subset of sensors, features, and time segments that balance predictive accuracy with resource efficiency. Extensive case studies using a multi-sensor data acquisition system demonstrate that the framework achieves high monitoring accuracy in both weld quality prediction and mixed tool and sample surface condition classification while reducing the feature pool by 96.8%–99.4%. Even under reduced sampling frequency (6.25 kHz) and shortened time windows (0.3 s), the model maintains strong predictive performance. Furthermore, the separability-analysis-based adaptation accurately recognizes new fault types using only three samples, reducing retraining data requirements by 90%. Overall, the proposed framework provides a new, scalable solution for cost- and time-efficient UMW monitoring and establishes a foundation for adaptive, lightweight monitoring systems applicable to other manufacturing processes.
{"title":"Sensor and feature selection for cost- and time-efficient online monitoring of ultrasonic metal welding","authors":"Kuan-Chieh Lu , Zhiqiao Dong , Chenhui Shao","doi":"10.1016/j.jmapro.2026.01.034","DOIUrl":"10.1016/j.jmapro.2026.01.034","url":null,"abstract":"<div><div>Ultrasonic metal welding (UMW) is a solid-state joining process widely used in industrial applications. However, its sensitivity to tool wear, surface contamination, and material variability presents persistent challenges for ensuring weld quality. Existing online monitoring systems often emphasize predictive accuracy while neglecting practical constraints such as hardware cost, data acquisition rate, and computational latency. To overcome this gap, this paper develops a systematic framework for cost- and time-efficient sensor and feature selection in UMW monitoring. The proposed method integrates signal decomposition, feature importance analysis, cost-aware genetic algorithm optimization, and a separability-analysis-based adaptation mechanism to identify an optimal subset of sensors, features, and time segments that balance predictive accuracy with resource efficiency. Extensive case studies using a multi-sensor data acquisition system demonstrate that the framework achieves high monitoring accuracy in both weld quality prediction and mixed tool and sample surface condition classification while reducing the feature pool by 96.8%–99.4%. Even under reduced sampling frequency (6.25 kHz) and shortened time windows (0.3 s), the model maintains strong predictive performance. Furthermore, the separability-analysis-based adaptation accurately recognizes new fault types using only three samples, reducing retraining data requirements by 90%. Overall, the proposed framework provides a new, scalable solution for cost- and time-efficient UMW monitoring and establishes a foundation for adaptive, lightweight monitoring systems applicable to other manufacturing processes.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"160 ","pages":"Pages 498-508"},"PeriodicalIF":6.8,"publicationDate":"2026-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146080395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-28Epub Date: 2026-01-21DOI: 10.1016/j.jmapro.2026.01.026
Mohammad Taghian , Ali Pilehvar Meibody , Abdollah Saboori , Luca Iuliano
Powder Bed Fusion (PBF) is a critical enabling technology in metal additive manufacturing (AM) to produce high-performance components deployed in extreme environments, including aerospace, energy, and biomedical applications. However, internal defects, such as lack of fusion porosity, gas-entrapped pores, and keyhole-induced voids continue to impose limitations on structural integrity, fatigue life, and process reliability. Achieving defect-free manufacturing under demanding performance requirements necessitates advanced detection and control strategies. Several recent reviews have addressed either in-situ monitoring techniques or machine-learning-based quality analytics in PBF, but typically in isolation. By contrast, this work provides an integrated review of defect detection across the PBF process chain, with emphasis on in-situ sensing, ex-situ characterization, machine learning-based classification, and mechanistic, numerical, and simulation approaches across micro-, meso-, and macro-scales. Particular focus is placed on computational models that capture critical physical phenomena at different scales, providing insight into defect formation and mitigation in PBF processes. The article also identifies current research gaps and outlines future directions for developing robust defect detection frameworks that support the qualification of AM components for mission-critical and extreme applications. These insights contribute to advancing the state-of-the-art in high-reliability additive manufacturing and accelerating its industrial adoption.
{"title":"Toward closed-loop quality assurance in powder bed fusion additive manufacturing: Defect detection, machine learning, and computational modeling","authors":"Mohammad Taghian , Ali Pilehvar Meibody , Abdollah Saboori , Luca Iuliano","doi":"10.1016/j.jmapro.2026.01.026","DOIUrl":"10.1016/j.jmapro.2026.01.026","url":null,"abstract":"<div><div>Powder Bed Fusion (PBF) is a critical enabling technology in metal additive manufacturing (AM) to produce high-performance components deployed in extreme environments, including aerospace, energy, and biomedical applications. However, internal defects, such as lack of fusion porosity, gas-entrapped pores, and keyhole-induced voids continue to impose limitations on structural integrity, fatigue life, and process reliability. Achieving defect-free manufacturing under demanding performance requirements necessitates advanced detection and control strategies. Several recent reviews have addressed either in-situ monitoring techniques or machine-learning-based quality analytics in PBF, but typically in isolation. By contrast, this work provides an integrated review of defect detection across the PBF process chain, with emphasis on in-situ sensing, ex-situ characterization, machine learning-based classification, and mechanistic, numerical, and simulation approaches across micro-, meso-, and macro-scales. Particular focus is placed on computational models that capture critical physical phenomena at different scales, providing insight into defect formation and mitigation in PBF processes. The article also identifies current research gaps and outlines future directions for developing robust defect detection frameworks that support the qualification of AM components for mission-critical and extreme applications. These insights contribute to advancing the state-of-the-art in high-reliability additive manufacturing and accelerating its industrial adoption.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"160 ","pages":"Pages 50-81"},"PeriodicalIF":6.8,"publicationDate":"2026-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146001852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-28Epub Date: 2026-01-28DOI: 10.1016/j.jmapro.2026.01.068
Xiaocheng Tian , Yufeng Li , Youshuo Zhang , Yan He
Optimizing the process parameters of the melt-casting solidification process for energetic materials (MCSPEM) is crucial for improving the quality and efficiency of melt-casting forming systems. The influence of melt-casting process parameters on shrinkage volume (SV) and solidification time (ST) exhibited a highly nonlinear correlation, with significant interactive effects among variables. However, existing process parameters control primarily relies on manual experience, lacking quantitative characterization and co-optimization of MCSPEM parameters concerning SV and ST, leading to inconsistent quality and low efficiency. Therefore, this paper proposed a multi-objective optimization approach to identify the optimal MCSPEM parameters based on adaptive clustering local Kriging (ACLK) and NSGA II-MOHHO algorithm. Firstly, the nonlinear associations of MCSPEM parameters (i.e., pouring temperature, mold preheating temperature, riser insulation temperature and time, jacket insulation temperature and time) with SV and ST were accurately established using the ACLK model. Secondly, a bi-objective optimization model involving SV and ST was established under the process constraints. Thirdly, a hybrid NSGA II-MOHHO algorithm was developed to tackle the bi-objective optimization model, integrating NSGA II's strengths in solution diversity with MOHHO's advantages in adaptive exploration-exploitation switching. Finally, the EWM-TOPSIS method was applied to obtain the optimal MCSPEM parameters from the Pareto front. Case results show that compared with the empirical scheme, the proposed method reduced SV and ST by 54.02% and 16.68%, respectively. This method can recommend the optimal configuration of MCSPEM process parameters and provide quantitative SV and ST information to guide technicians in accurately optimizing and controlling forming defects and efficiency.
{"title":"Melt-casting parameters optimization of energetic materials for minimizing shrinkage and solidification time via adaptive clustering local Kriging and NSGA II-MOHHO","authors":"Xiaocheng Tian , Yufeng Li , Youshuo Zhang , Yan He","doi":"10.1016/j.jmapro.2026.01.068","DOIUrl":"10.1016/j.jmapro.2026.01.068","url":null,"abstract":"<div><div>Optimizing the process parameters of the melt-casting solidification process for energetic materials (MCSPEM) is crucial for improving the quality and efficiency of melt-casting forming systems. The influence of melt-casting process parameters on shrinkage volume (SV) and solidification time (ST) exhibited a highly nonlinear correlation, with significant interactive effects among variables. However, existing process parameters control primarily relies on manual experience, lacking quantitative characterization and co-optimization of MCSPEM parameters concerning SV and ST, leading to inconsistent quality and low efficiency. Therefore, this paper proposed a multi-objective optimization approach to identify the optimal MCSPEM parameters based on adaptive clustering local Kriging (ACLK) and NSGA II-MOHHO algorithm. Firstly, the nonlinear associations of MCSPEM parameters (i.e., pouring temperature, mold preheating temperature, riser insulation temperature and time, jacket insulation temperature and time) with SV and ST were accurately established using the ACLK model. Secondly, a bi-objective optimization model involving SV and ST was established under the process constraints. Thirdly, a hybrid NSGA II-MOHHO algorithm was developed to tackle the bi-objective optimization model, integrating NSGA II's strengths in solution diversity with MOHHO's advantages in adaptive exploration-exploitation switching. Finally, the EWM-TOPSIS method was applied to obtain the optimal MCSPEM parameters from the Pareto front. Case results show that compared with the empirical scheme, the proposed method reduced SV and ST by 54.02% and 16.68%, respectively. This method can recommend the optimal configuration of MCSPEM process parameters and provide quantitative SV and ST information to guide technicians in accurately optimizing and controlling forming defects and efficiency.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"160 ","pages":"Pages 516-541"},"PeriodicalIF":6.8,"publicationDate":"2026-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146080389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-28Epub Date: 2026-01-30DOI: 10.1016/j.jmapro.2026.01.093
Zhaoxin Hou , Shipeng Li , Han Lv , Hao Li , Xuda Qin , Qing Zhao , Guoyu Fu , Zhengwei Bao , Zhitong Zhou
To address the challenge of monitoring thermo-mechanical damage in CF/PEEK machining, this research establishes a pioneering high-fidelity microscale FE model. The model uniquely incorporates liquid nitrogen precooling and the heat-generation-transfer dynamics across the fiber, matrix, and interface, achieving accurate cutting temperature predictions (errors within 5% at ambient temperature and 12% under cryogenic conditions). The finding results demonstrate that liquid nitrogen cooling (−150 °C) reduces cutting temperatures by 56.4%–60.4%, effectively suppressing thermal damage effects while inducing matrix embrittlement. Under cryogenic conditions(−150 °C), chips across all four fiber orientations exhibit morphology tearing deterioration due to matrix brittleness. During ambient temperature (21 °C) machining, matrix flow forms protective overlayers that reduce fiber damage; conversely, cryogenic machining embrittles the matrix, weakening its rigid support capacity for fibers and exacerbating fiber fracture and interfacial debonding. Surface roughness parameters (Sa/Sz) increase by 31%–85% (0°-135° fiber orientations), with 135° specimens exhibiting the most severe degradation. This study elucidates the synergistic mechanism between temperature and fiber orientation on machining-induced damage in CF/PEEK composites, providing theoretical foundations for optimizing ambient temperature and cryogenic machining processes.
{"title":"Influence of cryogenic temperature on machining mechanisms and surface integrity of CF/PEEK composites based thermo-mechanical coupling analysis","authors":"Zhaoxin Hou , Shipeng Li , Han Lv , Hao Li , Xuda Qin , Qing Zhao , Guoyu Fu , Zhengwei Bao , Zhitong Zhou","doi":"10.1016/j.jmapro.2026.01.093","DOIUrl":"10.1016/j.jmapro.2026.01.093","url":null,"abstract":"<div><div>To address the challenge of monitoring thermo-mechanical damage in CF/PEEK machining, this research establishes a pioneering high-fidelity microscale FE model. The model uniquely incorporates liquid nitrogen precooling and the heat-generation-transfer dynamics across the fiber, matrix, and interface, achieving accurate cutting temperature predictions (errors within 5% at ambient temperature and 12% under cryogenic conditions). The finding results demonstrate that liquid nitrogen cooling (−150 °C) reduces cutting temperatures by 56.4%–60.4%, effectively suppressing thermal damage effects while inducing matrix embrittlement. Under cryogenic conditions(−150 °C), chips across all four fiber orientations exhibit morphology tearing deterioration due to matrix brittleness. During ambient temperature (21 °C) machining, matrix flow forms protective overlayers that reduce fiber damage; conversely, cryogenic machining embrittles the matrix, weakening its rigid support capacity for fibers and exacerbating fiber fracture and interfacial debonding. Surface roughness parameters (Sa/Sz) increase by 31%–85% (0°-135° fiber orientations), with 135° specimens exhibiting the most severe degradation. This study elucidates the synergistic mechanism between temperature and fiber orientation on machining-induced damage in CF/PEEK composites, providing theoretical foundations for optimizing ambient temperature and cryogenic machining processes.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"160 ","pages":"Pages 624-641"},"PeriodicalIF":6.8,"publicationDate":"2026-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146080326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-28Epub Date: 2026-01-22DOI: 10.1016/j.jmapro.2026.01.030
Yan Zhou , Dan Chen , Pengfei Wang , Zhaoxiao Wu , Leqiang Deng , Xue Xiao , Jiuxiang Qin , Chengxiang Li
This study aims to addresses the challenge of electromagnetic pulse welding (EMPW) laminated workpieces (tabs and busbar of lithium-ion batteries (LIBs)) for electric vehicles (EVs), where the tabs and busbar are normally stacked closely together without enough standoff distance that required for EMPW. We propose a novel EMPW method for laminated workpieces based on a gradient through-hole (GTH) structure without standoff distance. When the discharge energy was 15.75 kJ, a 1 mm-thick Al sheet (driver sheet), four layers 0.3 mm-thick Al sheets (tabs), and a 1 mm-thick Cu sheet (busbar) were successfully welded. The mechanical properties and contact resistance of the EMPW welded joint were tested. The influence of discharge energy on the mechanical properties of the joint was also investigated. Scanning Electron Microscope (SEM), Energy Dispersive Spectrometer (EDS), Electron Backscattered Diffraction (EBSD), and Transmission Electron Microscopy (TEM) were used to characterize and analyze the bonding interface microstructure. The results show that a wavy interface is found between the driver sheet and the busbar. The AlCu intermetallic compounds are found, and grain refinement and element interdiffusion occur at the interface. There is no obvious boundary between each layer of tab. Compared with the straight through-hole (STH) structure, the EMPW welded joint obtained by the GTH structure achieves a larger contact surface area, better mechanical properties, and better electrical properties. This study provides a new EMPW method for welding laminated workpieces of the LIBs.
{"title":"Electromagnetic pulse welding of lithium-ion battery laminated workpieces based on a gradient through-hole structure","authors":"Yan Zhou , Dan Chen , Pengfei Wang , Zhaoxiao Wu , Leqiang Deng , Xue Xiao , Jiuxiang Qin , Chengxiang Li","doi":"10.1016/j.jmapro.2026.01.030","DOIUrl":"10.1016/j.jmapro.2026.01.030","url":null,"abstract":"<div><div>This study aims to addresses the challenge of electromagnetic pulse welding (EMPW) laminated workpieces (tabs and busbar of lithium-ion batteries (LIBs)) for electric vehicles (EVs), where the tabs and busbar are normally stacked closely together without enough standoff distance that required for EMPW. We propose a novel EMPW method for laminated workpieces based on a gradient through-hole (GTH) structure without standoff distance. When the discharge energy was 15.75 kJ, a 1 mm-thick Al sheet (driver sheet), four layers 0.3 mm-thick Al sheets (tabs), and a 1 mm-thick Cu sheet (busbar) were successfully welded. The mechanical properties and contact resistance of the EMPW welded joint were tested. The influence of discharge energy on the mechanical properties of the joint was also investigated. Scanning Electron Microscope (SEM), Energy Dispersive Spectrometer (EDS), Electron Backscattered Diffraction (EBSD), and Transmission Electron Microscopy (TEM) were used to characterize and analyze the bonding interface microstructure. The results show that a wavy interface is found between the driver sheet and the busbar. The AlCu intermetallic compounds are found, and grain refinement and element interdiffusion occur at the interface. There is no obvious boundary between each layer of tab. Compared with the straight through-hole (STH) structure, the EMPW welded joint obtained by the GTH structure achieves a larger contact surface area, better mechanical properties, and better electrical properties. This study provides a new EMPW method for welding laminated workpieces of the LIBs.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"160 ","pages":"Pages 254-269"},"PeriodicalIF":6.8,"publicationDate":"2026-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146036899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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