Intelligent and Sustainable Manufacturing - Journal

Articles (84) All Articles

Open Access

Review

27 October 2026

Intelligent Vibration Monitoring and Chatter Control in Sustainable Machining: From Physics-Based Models to Machine Learning and Digital Twins

Chatter is a persistent self-excited vibration problem in machining that affects productivity, surface quality, tool life, energy consumption, and process sustainability. This review examines the evolution of intelligent chatter management and evaluates its implications for sustainable machining. The review considers the transition from analytical stability prediction and stability-lobe methods to sensor-based monitoring, machine learning, physics-informed approaches, adaptive control, and digital twins, with particular attention to deployment readiness and sustainability evidence. The literature indicates that productivity and surface-quality effects of chatter are well established, whereas direct evidence concerning energy use, material waste, carbon emissions, life-cycle impacts, and component durability remains comparatively limited. Data-driven approaches offer strong potential for real-time monitoring but face challenges related to transferability, changing process conditions, and validation across different machines, tools, materials, and geometries. A clear gap is identified between technology maturity and sustainability-evidence maturity. To address this gap, the review introduces the Sustainability Evidence Level (SEL) framework for organizing and assessing sustainability evidence according to whether reported benefits are measured, modelled, or scenario-assumed. The review highlights the need for future studies to integrate intelligent chatter management with measurable resource-use, productivity, durability, and environmental indicators.

Mehmet Çevik*

Latif Tibet Aktaş

Fatma Kömürcü

Muhammet Mustafa Bahşı

Ebubekir Atan

Intell. Sustain. Manuf.

2026,

(2), 10028;

DOI: 10.70322/ism.2026.10028

Open Access

Review

22 October 2026

Robotic Assisted Grinding and Polishing: From Perception, Control to Decision Strategies

As high-end equipment continues to evolve towards extreme dimensions and complex configurations, the processing accuracy and adaptive requirements of grinding and polishing techniques have greatly increased. Traditional processing methods are no longer sufficient to meet the manufacturing requirements of high-end precision components. Robot-assisted intelligent grinding and polishing is a core technology for solving the precise processing of complex curved surfaces and flexible production. Although existing research has made considerable progress in individual modules such as perception detection, dynamic control, and process optimization, robot-assisted grinding and polishing is not merely the combination of robots and tools. Here, this paper takes the “perception-control-decision” collaborative logic as the main line, systematically elaborates the multi-source information fusion perception system, force-position intelligent control strategy, processing decision and path planning optimization methods for robot grinding and polishing, analyzes the multi-module collaborative mechanism, sorts out its typical applications in aerospace, automotive, and semiconductor fields, summarizes the current technical bottlenecks and looks forward to future development directions. The research aims to provide theoretical support and practical references for the technical upgrade and engineering application of robot intelligent grinding and polishing systems.

Wenbo Cong

Cong Mao

Zhuming Bi

Wentao Wang*

Intell. Sustain. Manuf.

2026,

(2), 10027;

DOI: 10.70322/ism.2026.10027

Open Access

Review

22 October 2026

Research Trends and Emerging Applications of Cardiovascular Treatment-Related Medical Devices: A Bibliometric and Narrative Review

Cardiovascular diseases are associated with high morbidity, disability, and mortality, and their long-term prevention and management increasingly depend on precise intervention, continuous monitoring, and individualized treatment. These needs have accelerated the development of treatment-related medical devices, including interventional devices, implantable systems, monitoring platforms, and intelligent assistive technologies. However, rapid growth in this field has fragmented the evidence in terms of data sources, analytical tools, research topics, and methodological pathways, leaving an insufficiently clear understanding of the knowledge structure, hotspot evolution, and development directions. To address these issues, this study combines bibliometric analysis and knowledge mapping with a structured narrative discussion of cardiovascular treatment-related medical devices. The bibliometric dataset comprised English-language articles and reviews indexed in the Web of Science Core Collection from 2015 to 2025, while representative studies published mainly between 2023 and 2026 were also considered in the application-oriented discussion to highlight recent technological and clinical developments. The review addressed several dimensions, including literature data sources, analytical tool application, keyword evolution, institutional distribution, and representative device applications. Specifically, this study first summarizes the database sources, search strategies, and literature screening procedures, thereby clarifying the main pathways and basic characteristics of data acquisition in this field. It then reviews the use of commonly used bibliometric tools in publication trend analysis, collaboration network analysis, co-citation analysis, and topic identification, while comparing their advantages and limitations in visualization and knowledge mining. Furthermore, based on annual publication output, high-frequency keywords, keyword co-occurrence, clustering structures, burst terms, and institutional distribution patterns, this study systematically analyzes research hotspots, frontier directions, major research forces, and evolutionary patterns in the field. Finally, the overall development status of cardiovascular treatment-related medical device research is discussed from the perspectives of knowledge base, hotspot migration, methodological system, and recent application pathways represented by transcatheter intervention, left atrial appendage occlusion, conventional and leadless pacing, implantable cardioverter-defibrillators, wearable cardioverter-defibrillators, pulsed field ablation, renal denervation, and intelligent monitoring. The results indicate that bibliometric analysis based on clearly defined boundary conditions can reveal the research landscape, institutional distribution characteristics, hotspot directions, and methodological evolution pathways of this field. These findings may inform topic refinement, technical route optimization, and methodological selection in future studies. With the integration of multisource heterogeneous data, artificial intelligence-based analytical tools, and application-oriented device innovation, cardiovascular medical devices are likely to advance toward more intelligent, precise, and data-driven development. The narrative component also considers device configuration, materials, mechanical loading, manufacturing, bench testing, failure modes, standards, and long-term clinical translation.

Ruiyu Zhou

Lan Dong

Yusuf Suleiman Dambatta

Jingang Sun

Teng Gao

Cong Sun

Peng Yao

Runze Li

Min Yang*

Intell. Sustain. Manuf.

2026,

(2), 10026;

DOI: 10.70322/ism.2026.10026

Open Access

Review

19 October 2026

AI-Driven Sustainable Procurement Management in Supply Chains: A Systematic Literature Review, Research Gap Analysis, and Future Directions

Artificial intelligence (AI) is transforming procurement through intelligent automation, predictive analytics, real-time decision support, and data-driven supplier management, creating new opportunities to advance sustainable supply chain performance. Yet, research on AI-driven sustainable procurement management remains fragmented across the AI, procurement, and sustainable supply chain domains, limiting theoretical integration and a systematic understanding of how AI-enabled capabilities can generate sustainability value. This study addresses this gap through a systematic literature review (SLR) of peer-reviewed studies published between 2011 and 30 June 2026. The review synthesizes the evolution and intellectual structure of the field across AI technologies and capabilities, procurement applications, sustainability dimensions, supply chain resilience, theoretical perspectives, methodological approaches, and contextual conditions. The findings show that existing research is primarily concentrated on technology adoption, process automation, predictive analytics, and operational efficiency, while comparatively limited attention has been directed toward the organizational, relational, and governance mechanisms that shape the translation of AI capabilities into sustained and multidimensional sustainability outcomes. The research-gap analysis identifies important deficiencies in end-to-end procurement integration, AI capability maturity, data governance and interoperability, predictive sustainability risk management, responsible supplier management, human–AI collaboration, explainability and accountability, contextual boundary conditions, and comprehensive sustainability measurement. In response, the study develops an integrative future research agenda that moves beyond technology adoption toward capability development, responsible AI governance, resilient procurement ecosystems, and measurable sustainability value creation. By integrating fragmented streams of research and clarifying the relationships among AI capabilities, procurement processes, and sustainable supply chain outcomes, this study advances the conceptual foundations of AI-driven sustainable procurement management. It provides a structured basis for cumulative scholarship and evidence-informed managerial practice.

Attia Hussien Gomaa*

Intell. Sustain. Manuf.

2026,

(2), 10025;

DOI: 10.70322/ism.2026.10025

Open Access

Article

24 September 2026

Gradient Fabrication of Cu-Zn Alloy Coating and Synergistic Anti-Corrosion Mechanism of Carbon Layer

Due to their dense microstructure and excellent thickness controllability, copper films are widely utilized in flexible electronics and energy storage device systems. Their interfacial stability in electrochemical environments becomes the critical factor limiting device cycle life and safety. However, in fluorine-containing electrolyte environments, copper is susceptible to severe HF-induced corrosion, generating unstable products such as CuF₂, which can lead to structural degradation and functional failure. The results indicated that the film with a low Zn content (Cu-Zn (9.5:0.5 wt%)) exhibited deteriorated corrosion resistance due to a significant micro-galvanic effect. Its corrosion current was as high as 6.87 × 10⁻⁵ mA·cm⁻². By contrast, the high-Zn-content film (Cu-Zn (9:1 wt%)) formed a composite passivation film that increased charge transfer resistance to 1.22 × 10⁴ Ω·cm² and reduced the corrosion current to 2.08 × 10⁻⁵ mA·cm⁻². The introduction of an additional carbon layer resulted in optimal stability of the Cu-Zn (9:1 wt%)@C composite film, with the corrosion current decreasing to 6.14 × 10⁻⁶ mA·cm⁻² and the structure remaining intact after corrosion. Multi-scale characterization revealed that the addition of zinc to the alloy enhanced the film’s intrinsic passivation capability, while the carbon layer provided an external barrier effect through physical isolation, charge regulation, and stress relief. This synergy effectively suppressed the formation of by-products. In summary, the Cu-Zn (9:1 wt%)@C composite film demonstrated the greatest corrosion resistance, establishing a theoretical foundation and engineering approach for the design of highly stable metallic films for use in intricate electrochemical environments.

Keke Jiang

Yongqiang Fu

Ying Fu

Yanbin Zhang

Xing Zhao

Xuesong Chang

Tiewei Liu

Dongzhou Jia*

Xiaoqiang Wu*

Intell. Sustain. Manuf.

2026,

(2), 10024;

DOI: 10.70322/ism.2026.10024

Open Access

Article

18 September 2026

Surface Finish Improvement of Selective Laser Melted Aluminium Alloy by Surface Mechanical Attrition Treatment

Surface mechanical attrition treatment (SMAT) has been used to treat the surfaces of an aluminium alloy manufactured by selective laser melting (SLM). SMAT involved impacting the SLM sample surface with spherical balls at a frequency of 30 Hz for 10 min to 30 min, which induced plastic deformation of the sample surface, leading to a change in surface finish and surface hardness. The surface finish, morphology, hardness, and structural features have been investigated. The results show that SMAT is very effective in improving the surface finish of the SLM aluminium alloy surface. After 30 min of treatment, the roughness value (R_a) was reduced by 87%, from 19.4 μm to 2.6 μm. SMAT also has the benefit of increasing the surface hardness of SLM aluminium alloy from 125 HV_0.1 to 160 HV_0.1, and generating a strain hardened layer of about 300 μm thick at the subsurface, and thus has the potential of improving wear resistance. In addition, SMAT induced a compressive residual stress of around 100 MPa on the treated surface, which would be beneficial in improving the fatigue properties of SLM aluminium alloy. The mechanisms underlying surface smoothing, hardness increase, and the evolution of compressive residual stress in SMAT are discussed in terms of severe surface plastic deformation and strain hardening.

Yong Sun*

Congcong Zhao

Huaping Tang

Yunjie Bi

Intell. Sustain. Manuf.

2026,

(2), 10023;

DOI: 10.70322/ism.2026.10023

Open Access

Article

11 September 2026

Granulation of Fine Eggshell Powder to Produce Feedstock Powder for Binder Jetting Additive Manufacturing: Effects of Spraying Pressure and Slurry Feed Rate

Eggshell powder is a sustainable calcium carbonate-based material with potential as a feedstock for binder jetting additive manufacturing. However, its irregular particles exhibit poor flowability and powder spreading characteristics. Although spray freeze drying granulation has previously been shown to improve the properties of eggshell powder, the influence of process variables on the resulting granules remains insufficiently understood. This study investigates the effects of spraying pressure and slurry feed rate on the properties of granulated eggshell powder. One-factor-at-a-time experiments were conducted to identify feasible ranges of these process variables, and a full factorial design of experiments with two replications was employed to evaluate the main and interaction effects of spraying pressure and slurry feed rate on particle size and flowability of granulated eggshell powder. Spraying pressure had a statistically significant effect on particle size, whereas slurry feed rate did not significantly affect particle size within the investigated range. Increasing spraying pressure resulted in smaller granules. Powder flowability was evaluated using both the Hausner ratio and repose angle. Both measures showed a significant interaction between spraying pressure and slurry feed rate, indicating that powder flowability depends on the combined effects of these two variables. The findings suggest that spraying pressure is the key variable governing particle size, while the combined influence of spraying pressure and slurry feed rate must be considered when controlling powder flowability. The resulting process–property relationships provide a basis for selecting spray freeze drying conditions for converting eggshell waste into more suitable granulated feedstock for binder jetting additive manufacturing.

Md Shakil Arman*

Fahim Khan

Zhijian Pei

Mostafa Meraj Pasha

Intell. Sustain. Manuf.

2026,

(2), 10022;

DOI: 10.70322/ism.2026.10022

Open Access

Article

10 September 2026

Performance-Based Topology Optimization of Main Steel Girders in Composite Bridges with Multi-Criteria Environmental Sustainability Evaluation

The rising need for economical and ecologically friendly bridges calls for practical solutions that do not compromise the strength, utility, and safety of the structures. The steel-concrete bridge system uses steel girders that carry most of the weight. Thus, an optimal arrangement of girders is necessary for structural efficiency and economic advantage. This study investigates the structural optimization of steel main girders for composite bridges to obtain optimum structural weight and economy. To investigate the coupled behavior of steel girders and concrete decks under realistic conditions, Finite Element Modeling (FEM) is used. In this approach, alternative sizes or configurations for the steel girder are evaluated to predict tensile and compressive stresses as well as deflections. This involves a comparison between the material savings and cost benefits of optimized or conventional designs/configurations. The optimization approaches used in designing composite bridges seem effective at reducing steel mass without affecting bridge performance in terms of stresses and deflections. This study shows that cross-sectional and topology optimization result in a bridge that is more economical, using less steel than previous bridges. Optimization techniques are suggested for designing and building bridges, especially large-scale projects, because of their importance in providing cost-effective and energy-efficient solutions.

Theofilos Mavroudis

Amalia Moutsopoulou*

Markos Petousis*

Nectarios Vidakis

Intell. Sustain. Manuf.

2026,

(2), 10021;

DOI: 10.70322/ism.2026.10021

Open Access

Review

21 August 2026

How Does the Mechanical Structure of a Dexterous Hand Drive Embodied Intelligence

Robotic dexterous hands, as the primary end-effectors through which embodied agents interact with the physical world, directly determine grasp stability, manipulation accuracy, environmental adaptability, and human–robot interaction safety. Research on dexterous hand mechanical structures has expanded rapidly and become increasingly interdisciplinary, so conventional narrative reviews can no longer capture its knowledge base, research drivers, and the evolution of hotspots. A systematic framework that combines bibliometric quantification with mechanism-oriented synthesis is therefore needed. This study presents a bibliometric review of dexterous hand mechanical structures based on Web of Science Core Collection publications from 2016 to 2025, combining bibliometric statistics, collaboration-network analysis, keyword co-occurrence, cluster analysis, and trend synthesis to reveal the field’s research landscape, intellectual structure, and technological evolution. Publications increased steadily, rising from 64 in 2016 to 252 in 2025, with marked acceleration after 2022. China leads in publication volume, whereas the United States, Germany, and the United Kingdom show strong citation impact and international collaboration. Core journals concentrate on robotics, mechatronics, sensing, soft robotics, and rehabilitation engineering, and keyword evolution shows a shift from prosthetic hands and basic mechanism design toward compliant structures, soft actuation, tactile perception, and dexterous manipulation. Based on keyword clustering, three principal research streams are identified: body configuration and degree-of-freedom (DoF) evolution, drive and transmission structure design, and soft/compliant structure expansion. The central challenge of dexterous hand design is no longer the accumulation of DoFs but the coordinated optimization of DoF allocation, actuation mapping, contact stability, and compliant adaptation under strict constraints of space, energy, and reliability. Tendon-driven, internally integrated, and underactuated architectures emphasize lightweight dexterity, precision control, and adaptive grasping, respectively, while soft continuum, rigid–soft hybrid, and variable-stiffness structures are reshaping dexterous hands from rigid execution mechanisms into physically intelligent interaction systems. Overall, the field has entered a stage of interdisciplinary system integration, with its core mission shifting from building complex mechanical hands to constructing perceptive, adaptive, and controllable end-effectors. Future work should strengthen task-oriented structural optimization, hybrid actuation, rigid–soft coupling, integrated flexible sensing and closed-loop control, and unified performance evaluation, accelerating the transition from laboratory prototypes to standardized assessment and large-scale deployment.

Hao Wu

Jixin Liu

Xiaotian Zhang

Guang Wang

Zhaopeng Hao

Qingan Yin

Zhenjing Duan

Guohao Jiang

Dezhi He

Guofeng He

Guoqing Wang

Aiguo Qin

Kaixu Zhang

Teng Gao

Mingzheng Liu*

Intell. Sustain. Manuf.

2026,

(2), 10020;

DOI: 10.70322/ism.2026.10020

Open Access

Review

10 August 2026

Bibliometric Analysis of Humanoid Robot Joint Modules: Structural, Control, Interaction and Biomimetic

As an intelligence paradigm, embodied intelligence emphasizes that intelligent capabilities emerge from the dynamic interaction between an intelligent agent and its physical embodiment, and are realized through a continuous closed-loop process integrating perception, decision-making, action, and feedback. With the rapid development of embodied intelligence, humanoid robots have become increasingly important in intelligent manufacturing, service, and human-robot collaboration. Joint modules, as the core units responsible for perception, decision-making, and actuation, determine the motion performance, interaction capability, and intelligence level of humanoid robots. Research directions in this field remain fragmented, technological pathways are diverse, and systematic summaries of evolutionary patterns are lacking. First, publication trends, country and institutional collaboration networks, and major research contributors were analyzed. Research on humanoid robot joint modules has entered a phase of rapid growth since 2018, indicating a shift from early exploratory studies toward engineering and large-scale applications. Second keyword co-occurrence, clustering analysis, and burst detection were used to identify research hotspots and evolutionary features, research focus gradually shifted from traditional electromechanical actuation to compliant actuation, intelligent control, multimodal perception, and embodied intelligence. Furthermore, key technologies of joint modules were systematically summarized and reviewed from four aspects: structural design and performance optimization, motion control, human-robot interaction, and biomimetic actuation for human-like performance enhancement. Joint modules gradually evolved toward structural integration, intelligent control, natural interaction, and human-like system characteristics. Technical bottlenecks in current humanoid robot joint modules were analyzed, and future research directions were proposed to provide technical support and theoretical guidance for both industrial applications and academic research in humanoid robotics.

Changhe Ji

Jingjie Dai

Yusuf Suleiman Dambatta

Guang Wang

Guohao Jiang

Dezhi He

Xianfeng Zhao

Shouhai Chen

Kaixu Zhang

Yihang Fan

Huhu Wang

Xing Zhao

Xiaoming Wang

Xiaohan Sun

Changhe Li*

Intell. Sustain. Manuf.

2026,

(2), 10019;

DOI: 10.70322/ism.2026.10019

Open Access

Review

14 January 2025

Artificial Intelligence and Machine Learning for Sustainable Manufacturing: Current Trends and Future Prospects

Artificial Intelligence (AI) and Machine Learning (ML) are transforming manufacturing processes, offering unprecedented opportunities to enhance sustainability and environmental stewardship. This comprehensive review analyzes the transformative impact of AI technologies on sustainable manufacturing, focusing on critical applications, including energy optimization, predictive maintenance, waste reduction, and circular economy implementation. Through systematic analysis of current research and industry practices, the study examines both the opportunities and challenges in deploying AI-driven solutions for sustainable manufacturing. The findings provide strategic insights for researchers, industry practitioners, and policymakers working towards intelligent and sustainable manufacturing systems while elucidating emerging trends and future directions in this rapidly evolving field.

Vishnu Vijay Kumar*

Khaled Shahin

Intell. Sustain. Manuf.

2025,

(1), 10002;

DOI: 10.70322/ism.2025.10002

Open Access

Review

02 April 2025

Wide-Bandgap Semiconductors: A Critical Analysis of GaN, SiC, AlGaN, Diamond, and Ga₂O₃ Synthesis Methods, Challenges, and Prospective Technological Innovations

The increasing demand for high-performance Wide-Bandgap (WBG) semiconductors, including GaN, SiC, and emerging Ultrawide-Bandgap (UWBG) materials such as Ga₂O₃ and diamond, has driven significant advancements in epitaxial growth techniques. However, achieving scalability, defect-free growth, and sustainability remains a major challenge. This review systematically evaluates Molecular Beam Epitaxy (MBE), Metal-Organic Chemical Vapor Deposition (MOCVD), Hydride Vapor Phase Epitaxy (HVPE), and other novel growth and hybrid growth techniques, emphasizing energy efficiency, defect control, and environmental impact. Industry 4.0-driven AI-based process optimization and closed-loop recycling have emerged as transformative strategies, reducing waste and improving manufacturing efficiency. Key findings reveal that HVPE enables rapid defect-free GaN fabrication, Hot-Filament CVD enhances SiC growth with superior thermal properties, and Atomic Layer Epitaxy (ALE) achieves sub-nanometer precision crucial for next-generation quantum and RF applications. Despite these advancements, p-type doping in UWBG materials, substrate compatibility, and thermal management remain unresolved challenges. Future research must focus on scalable eco-friendly epitaxy, novel doping mechanisms, and policy-driven sustainability efforts. This review provides a comprehensive roadmap for sustainable WBG semiconductor manufacturing, bridging materials innovation, energy efficiency, and industrial adoption to support the next generation of power electronics and optoelectronics.

Luckman Aborah Yeboah*

Ayinawu Abdul Malik

Peter Agyemang Oppong

Prince Sarfo Acheampong

Joseph Arko Morgan

Rose Akua Adwubi Addo

Boris Williams Henyo

Stephen Takyi Taylor

Wolalorm Makafui Zudor

Samuel Osei-Amponsah

Intell. Sustain. Manuf.

2025,

(1), 10011;

DOI: 10.70322/ism.2025.10011

Open Access

Review

28 March 2024

Digital Twins Enabling Intelligent Manufacturing: From Methodology to Application

Digital twin technology develops virtual models of objects digitally, simulating their real-world behavior based on data. It aims to reduce product development cycles and costs through feedback between the virtual and real worlds, data fusion analysis, and iterative decision-making optimization. Traditional manufacturing processes often face challenges such as poor real-time monitoring and interaction during machining, difficulties in diagnosing equipment failures, and significant errors in machining. Digital twin technology offers a powerful solution to these issues. Initially, a comprehensive review of the research literature was conducted to assess the current research scope and trends. This was followed by an explanation of the basic concepts of digital twins and the technical pathway for integrating digital twins into intelligent manufacturing including outlining the essential technologies for creating a system of interaction between the virtual and real worlds, enabling multimodel fusion, data sensing, algorithm-based prediction, and intelligent decision-making. Moreover, the application of digital twins in intelligent manufacturing throughout the product life cycle was detailed, covering product design, manufacturing, and service stages. Specifically, in the manufacturing phase, a model based on heat conduction theory and visualization was used to construct a time-varying error model for the motion axis, leading to experiments predicting the time-varying error in the hole spacing of a workpiece. These experiments achieved a minimum prediction error of only 0.2 μm compared to the actual error. By compensating for time-varying errors in real time, the variability in the hole spacing error decreased by 69.19%. This paper concludes by summarizing the current state of digital twins in intelligent manufacturing and projecting future trends in key technologies, application areas, and data use, providing a basis for further research.

Shuguo Hu

Changhe Li*

Benkai Li

Min Yang

Xiaoming Wang

Teng Gao

Wenhao Xu

Yusuf Suleiman Dambatta

Zongming Zhou

Peiming Xu

Intell. Sustain. Manuf.

2024,

(1), 10007;

DOI: 10.35534/ism.2024.10007

Open Access

Article

19 June 2025

Advancing Total Productive Maintenance in Smart Manufacturing: From Methodology to Implementation

The rapid advancement of Industry 4.0 technologies has catalyzed the development of intelligent tools and methodologies to enhance operational efficiency, reliability, and productivity across modern industrial enterprises. Total Productive Maintenance (TPM), a foundational approach in manufacturing, traditionally improves equipment reliability, reduces downtime, and drives continuous improvement through proactive employee involvement. However, in the context of Smart Manufacturing, traditional TPM reveals significant limitations—chiefly its reliance on manual data collection, reactive maintenance, and limited real-time insight. This paper explores TPM’s evolution, key innovations, and cross-industry applications while highlighting challenges in adopting Industry 4.0 technologies. It proposes a comprehensive TPM 4.0 framework integrating Lean Six Sigma’s DMAIC methodology with advanced digital tools for systematic failure mode classification, risk-based maintenance prioritization, and real-time performance optimization. Leveraging IIoT-enabled condition monitoring, Digital Twin simulations, and machine learning-driven predictive analytics, the framework supports real-time anomaly detection, cognitive diagnostics, and adaptive maintenance planning—substantially improving Overall Equipment Effectiveness (OEE), cost efficiency, and system resilience. Additionally, federated learning promotes scalable, privacy-preserving AI collaboration, while blockchain enhances data security and transparency, mitigating cybersecurity risks. By merging traditional TPM with AI-driven automation and digital sustainability, TPM 4.0 establishes a foundation for self-optimizing, cyber-resilient maintenance ecosystems, accelerating the transition to autonomous manufacturing. Although conceptual, this framework offers a practical roadmap for smart manufacturing transformation, with future validation planned through case studies and pilot projects.

Attia Hussien Gomaa*

Intell. Sustain. Manuf.

2025,

(2), 10019;

DOI: 10.70322/ism.2025.10019

Open Access

Article

23 June 2025

Asset Management Excellence: A Roadmap for Integrating Lean Six Sigma and ISO 55001 to Achieve Operational Excellence

Asset Management Excellence (AME) has become essential for sustaining operational efficiency and long-term competitiveness in today’s digitally driven and increasingly complex industrial landscape. This study introduces an integrated roadmap that aligns Lean Six Sigma (LSS)—specifically the DMAIC methodology—with ISO 55001 standards to enhance asset reliability, optimize lifecycle performance, and support continuous improvement. The proposed model embeds principles such as lifecycle value optimization, risk-based decision-making, and sustainability. It leverages proven tools, including Failure Mode and Effects Analysis (FMEA), Root Cause Analysis (RCA), Statistical Process Control (SPC), predictive maintenance, and real-time monitoring to enable proactive, data-driven asset management. This integration supports efficiency, reduces variability, and extends asset life. Performance is measured through key indicators such as Mean Time Between Failures (MTBF), Overall Equipment Effectiveness (OEE), and lifecycle cost-efficiency. These metrics enable organizations to monitor progress, validate improvements, and ensure alignment with strategic objectives. The study also addresses common implementation challenges across financial, organizational, workforce, technological, and structural domains. It proposes targeted mitigation strategies, including phased implementation, cost-benefit analyses, stakeholder engagement, digital readiness assessments, and capacity-building programs to enhance adoption and long-term sustainability. While conceptual, the roadmap offers a practical, scalable approach to embedding LSS within asset management systems. It fosters a transition from reactive to proactive practices, enhancing resilience, sustainability, and strategic value. Future research will validate the framework through sector-specific case studies and pilot implementations.

Attia Hussien Gomaa*

Intell. Sustain. Manuf.

2025,

(2), 10020;

DOI: 10.70322/ism.2025.10020

Open Access

Article

16 December 2025

The Jevons Paradox and Vernon’s Product Life Cycle: Evidence from Primary–Secondary Price Differentials in Copper and Aluminium (2002–2021) with 2024–2025 Market Context

This study examines how efficiency improvements associated with Jevons’ Paradox and product-system maturation, as described by Vernon’s Product Life Cycle (PLC), jointly influence the long-term pricing relationship between primary and recycled copper and aluminium. Using author-provided nominal annual USD price series for 2002–2021, the analysis derives descriptive indicators most notably the recycled-to-primary (R/P) price ratio to characterize structural shifts consistent with PLC-driven secondary integration. Recent market conditions in 2024–2025, including tight physical availability, low inventories, regional premia, and recurrent episodes of backwardation, are incorporated as qualitative context without merging with the historical dataset. Results indicate a sustained narrowing of R/P discounts for both metals by 2021. The combined Jevons–PLC interpretation suggests that efficiency-driven service expansion and supply-side tightness increase the relative value of secondary material, supporting long-term convergence between primary and recycled streams.

Antonio Alonso-Jimenez*

Manuel Regueiro y González-Barros

Enrique Álvarez

Luis Alonso Castillo

Intell. Sustain. Manuf.

2026,

(1), 10035;

DOI: 10.70322/ism.2025.10035

Open Access

Review

01 April 2025

Sustainable Manufacturing and Applications of Wide-Bandgap Semiconductors—A Review

Wide-bandgap (WBG) semiconductors such as silicon carbide (SiC) and gallium nitride (GaN) are revolutionizing high-power electronics due to their superior thermal conductivity, breakdown voltage, and energy efficiency. These materials are critical in electric vehicles, renewable energy systems, and high-frequency applications like 5G infrastructure. However, their production processes are resource-intensive and present significant environmental challenges. This review evaluates recent advancements in sustainable WBG semiconductor manufacturing, focusing on low-energy epitaxial growth, closed-loop recycling, and the mitigation of toxic by-products. Additionally, it highlights the role of Industry 4.0 innovations, such as AI-driven process optimization and IoT-based resource management, in enhancing sustainability. The review identifies research gaps in cost reduction, alternative WBG materials like Gallium Oxide (Ga₂O₃) and Diamond, and scalable green manufacturing solutions. It underscores the necessity for industry-wide collaboration and regulatory frameworks to drive the adoption of eco-friendly semiconductor fabrication. The findings of this study provide a roadmap for advancing sustainability in WBG semiconductor production, ensuring their long-term viability in the transition toward energy-efficient technologies.

Luckman Aborah Yeboah*

Peter Agyemang Oppong

Ayinawu Abdul Malik

Prince Sarfo Acheampong

Joseph Arko Morgan

Rose Akua Adwubi Addo

Boris Williams Henyo

Intell. Sustain. Manuf.

2025,

(1), 10010;

DOI: 10.70322/ism.2025.10010

Open Access

Review

23 February 2024

Research Status and Prospect of Ultrasonic Vibration and Minimum Quantity Lubrication Processing of Nickel-based Alloys

Nickel-based alloys has important application value in modern industrial field, but there are a lot of problems that are difficult to solve in traditional processing, and it is a typical difficult-to-process material. In order to improve the machinability of nickel-based alloys, scholars try to use a variety of non-traditional processing methods to explore and study the processing of nickel-based alloys. In these studies, ultrasonic vibration assisted processing technology and minimum quantity lubrication (MQL) processing technology can achieve remarkable results. The intermittent separation cutting characteristics of ultrasonic vibration assisted processing technology can improve the processing quality by changing the tool path, while minimum quantity lubrication processing technology can improve the lubrication effect of cutting, combining ultrasonic vibration assisted MQL processing leverages the benefits of both methods, resulting in improved machinability and expanded application of nickel-based alloys. Summarize the current research status on the machining mechanism of nickel-based alloys assisted by ultrasonic vibration and micro lubrication, and anticipate its developmental trends. This provides a reference for future research on the efficient machining mechanisms and practical applications of nickel-based alloys.

Guquan Gu

Dazhong Wang*

Shujing Wu

Shu Zhou

Buxin Zhang

Intell. Sustain. Manuf.

2024,

(1), 10006;

DOI: 10.35534/ism.2024.10006

Open Access

Article

09 May 2025

Modeling and Assessing Economical Feasibilities for Waste to Energy Conversion/Incineration Process in Context of Municipal Solid Waste

At the time of the study, most of the municipal waste, including solid municipal waste, in the city of St. Petersburg and in the connected larger Leningrad region is processed by landfilling. This sort of waste processing in open landfills causes environmental damage, uncontrollable landfill fires, bad and dangerous odors, nearby rivers/streams, groundwater pollution, CH₄ and CO₂ emissions, to mention a few. Additionally, landfilling is a waste of energy and material resources present in the content dumped into landfills. In this context, Waste-to-Energy (WtE) incineration is a process that we use to recover the energy the materials have back to usable form, which we use in the form of heat and electricity. Even though a lot of resources and energy are available in the (municipal solid) waste, it does not mean that recovering it would always make sense. Our study analyses and estimates the profitability of a WtE incineration plant(s) in the city of St. Petersburg and the connected Leningrad region. With the available data and following analysis, we have concluded that the WtE incineration is economically feasible in this specific region and city areas, given that the implementations follow more traditional (economically less expensive and easier) technical and process model solutions. As a note of results stability, it needs to be pointed out that the changes in estimates of gate fees, cost of electricity and heat, and so on do impact the economic feasibility a lot, and larger scale changes in the assumed revenues would have a high impact on the outcome of repeatability of the results.

Teppo Vartiainen

Timo Kärri

Paulo Afonso

Ari Happonen*

Intell. Sustain. Manuf.

2025,

(2), 10015;

DOI: 10.70322/ism.2025.10015

Open Access

Article

28 August 2024

Overcoming SME Legal and Regulatory Challenges and Fostering Sustainable Collaboration and 7PS Engineering in the Digital Age through Integrating the X.0 Wave Theory & SME 5.0 Concept

Technological innovations, education, business and society change quickly and often unpredictably. The fusion of artificial intelligence (AI), machine learning, augmented reality (AR), virtual reality (VR) and augmented reality (XR) opens a new era in which work, production, communication and thought processes are massively transformed. In this context, the challenge arises: How can small and medium-sized enterprises (SMEs) adapt to this accelerated change? This study highlights a path forward and introduces the concept of “SME 5.0” or “Hybrid SME” or “SME of Tomorrow” as a comprehensive solution to address the complexities of the digital age. In this integrated exploration of the X.0 Wave Theory and SME 5.0 Concept, the framework for human civilization’s evolution and technological shifts converges with a practical roadmap for small and medium-sized enterprises (SMEs) navigating the dynamic digital landscape. Acknowledging transformative waves in technology, economics, and societal structures within the X.0 Wave Theory, the study accentuates the ongoing nature of these shifts. It advocates for a long-term perspective, urging policymakers and industry leaders to consider potential future scenarios to devise strategies fostering innovation, competitiveness, and privacy safeguards. Simultaneously, the study introduces SME 5.0 as a holistic solution for SMEs, aligning with the transformative success envisioned by the X.0 Wave Theory. Proposing the Seven Pillars of Sustainability (7PS) framework tailored to SMEs, the concept emphasizes digitalization and sustainable technology. The title, “Harmonizing the X.0 Wave Theory and SME 5.0 Concept”, encapsulates the synergy between theoretical underpinnings and practical solutions. The subtitle, “Fostering Sustainable Collaboration, 7PS Engineering, and Overcoming Legal Challenges in the Digital Age”, provides a glimpse into the study’s focus on practical implications, sustainability, engineering, and legal considerations for SMEs in the rapidly evolving digital era.

Hamid Mattiello*

Carsten Domann*

Intell. Sustain. Manuf.

2024,

(2), 10011;

DOI: 10.35534/ism.2024.10011

Open Access

Review

14 January 2025

Artificial Intelligence and Machine Learning for Sustainable Manufacturing: Current Trends and Future Prospects

Vishnu Vijay Kumar*

Khaled Shahin

Intell. Sustain. Manuf.

2025,

(1), 10002;

DOI: 10.70322/ism.2025.10002

Open Access

Review

29 December 2023

A State-of-the-art Review on the Intelligent Tool Holders in Machining

In the manufacturing process, in addition to the properties of material itself, the quality of a product is directly related to the cutting process. Cutting force and cutting heat are two crucial factors in cutting processing. Researchers can analyze various signals during cutting process, such as cutting force signal, vibration signal, temperature signal, etc., which can regulate force and temperature, optimize the cutting process, and improve product quality. Therefore, it is very important to pay attention to various signals in cutting process. Meanwhile, good-quality signal data sets will greatly reduce time, resource and labor costs for subsequent use or analysis of researchers. Therefore, how to collect high-quality signals effectively and accurately is the first step. At present, researchers prefer to use various sensors to collect signals. With the advancement of science and technology, intelligent tool holder appears in researchers’ vision. It integrates multiple systems such as sensors, data collection, data transmission, and power supply on the tool holder. It replaces traditional wired sensors, and it is highly interactive with CNC machine tools. This paper will carry out a systematic review and prospect from three aspects: the structural design of the intelligent tool holder, the signal monitoring technology of the intelligent tool holder, and the tool condition monitoring of the intelligent tool holder.utf-8

Qinglong An*

Jie Yang

Junli Li

Gang Liu

Ming Chen

Changhe Li

Intell. Sustain. Manuf.

2024,

(1), 10002;

DOI: 10.35534/ism.2024.10002

Open Access

Review

23 February 2024

Research Status and Prospect of Ultrasonic Vibration and Minimum Quantity Lubrication Processing of Nickel-based Alloys

Guquan Gu

Dazhong Wang*

Shujing Wu

Shu Zhou

Buxin Zhang

Intell. Sustain. Manuf.

2024,

(1), 10006;

DOI: 10.35534/ism.2024.10006

Open Access

Review

28 March 2024

Digital Twins Enabling Intelligent Manufacturing: From Methodology to Application

Shuguo Hu

Changhe Li*

Benkai Li

Min Yang

Xiaoming Wang

Teng Gao

Wenhao Xu

Yusuf Suleiman Dambatta

Zongming Zhou

Peiming Xu

Intell. Sustain. Manuf.

2024,

(1), 10007;

DOI: 10.35534/ism.2024.10007

Open Access

Article

31 January 2024

Design of Intelligent and Sustainable Manufacturing Production Line for Automobile Wheel Hub

The wheel hub is an important part of the automobile, and machining affects its service life and driving safety. With the increasing demand for wheel productivity and machining accuracy in the automotive transport sector, automotive wheel production lines are gradually replacing human production. However, the technical difficulties of conventional automotive wheel production lines include insufficient intelligence, low machining precision, and large use of cutting fluid. This paper aims to address these research constraints. The intelligent, sustainable manufacturing production line for automobile wheel hub is designed. First, the machining of automotive wheel hubs is analyzed, and the overall layout of the production line is designed. Next, the process equipment system including the fixture and the minimum quantity lubrication (MQL) system are designed. The fixture achieves self-positioning and clamping functions through a linkage mechanism and a crank–slider mechanism, respectively, and the reliability of the mechanism is analyzed. Finally, the trajectory planning of the robot with dual clamping stations is performed by RobotStodio. Results show the machining parameters for a machining a wheel hub with a diameter of 580 mm are rotational speed of 2500 rpm, cutting depth of 4 mm, feed rate of 0.5 mm/r, and minimum clamping force of 10881.75 N. The average time to move the wheel hub between the roller table and each machine tool is 27 s, a reduction of 6 s compared with the manual handling time. The MQL system effectively reduces the use of cutting fluid. This production line can provide a basis and reference for actual production by reasonably planning the wheel hub production line.utf-8

Minkai Chen

Yanbin Zhang*

Bo Liu

Zongming Zhou

Naiqing Zhang

Huhu Wang

Liqiang Wang

Intell. Sustain. Manuf.

2024,

(1), 10003;

DOI: 10.35534/ism.2024.10003

Open Access

Review

08 January 2025

A Review of Ultrasonic Vibration-Assisted Grinding for Advanced Materials

Ultrasonic vibration-assisted grinding (UVAG), which superimposes high-frequency, micro-amplitude ultrasonic vibration onto conventional grinding (CG), offers several advantages, including a high material removal rate, low grinding force, low surface roughness, and minimal damage. It also addresses issues such as abrasive tool clogging, thereby enhancing machining efficiency, reducing tool wear, and improving the surface quality of the workpiece. In recent years, the rapid development of advanced materials and improvements in UVAG systems have accelerated the progress of UVAG technology. However, UVAG still faces several challenges in practical applications. For example, the design and optimization of the ultrasonic vibration system to achieve high-precision, large-amplitude, and high-efficiency grinding remain key issues. Additionally, further theoretical and experimental studies are needed to better understand the material removal mechanism, the dynamics of grinding force, abrasive tool wear, and their effects on surface quality. This paper outlines the advantages of UVAG in machining advanced materials, reviews recent progress in UVAG research, and analyzes the current state of ultrasonic vibration systems and ultrasonic grinding characteristics. Finally, it summarizes the limitations of current research and suggests directions for future studies. As an emerging machining technology, UVAG faces challenges in many areas. In-depth exploration of the theoretical and experimental aspects of high-precision, large-amplitude, and high-efficiency ultrasonic vibration systems and UVAG is essential for advancing the development of this technology.utf-8

Can Liu

Yong Zhang

Lida Zhu*

Qiang Li

Xin Shu

Shaoqing Qin

Dazhong Wang

Wentian Shi

Intell. Sustain. Manuf.

2025,

(1), 10001;

DOI: 10.70322/ism.2025.10001

Open Access

Review

09 July 2025

Muti-Energy Field-Assisted Grinding of Hard and Brittle Materials: Tools, Equipment and Mechanisms

Hard, brittle and difficult-to-machine materials are prone to surface cracks, subsurface damage and other defects in the traditional grinding process, accompanied by low processing efficiency and severe tool wear. As a new type of processing technology, energy field-assisted grinding provides a new approach for the efficient and high-quality processing of hard and brittle materials. This paper reviews the latest research progress of muti-energy field-assisted grinding from aspects such as the types and selection of grinding tools, processing equipment and physical-chemical coupled mechanisms. Firstly, micro-grinding tools are classified based on different surface structures and coating materials, with the aim to enhance processing efficiency, improve the surface quality and geometric accuracy of workpieces, and reduce tool wear. Secondly, the processing mechanisms, parameter selection and current difficulties faced by four energy field-assisted grinding methods, including laser-assisted grinding, electrochemical-assisted grinding, magnetic-assisted grinding and ultrasonic field-assisted grinding, are discussed under both chemical and physical effects. Thirdly, different equipment and auxiliary devices developed for energy field-assisted grinding have been introduced, providing reliable platforms for the distribution design and efficient regulation of the energy field. Finally, the cutting-edge progress, main challenges and development trends of energy field-assisted grinding are prospected, illustrating the great potential of this technology in fields such as aerospace, electronics, and optical components.utf-8

Wentao Wang

Zhiyuan Zhou

Qing Wang

Baixuan Gao

Cong Mao*

Intell. Sustain. Manuf.

2025,

(2), 10022;

DOI: 10.70322/ism.2025.10022

Open Access

Article

01 April 2024

Cost Effectiveness of the Industrial Internet of Things Adoption in the U.S. Manufacturing SMEs

This research paper explores the financial adoption challenges of the Industrial Internet of Things (IIoT) in industry. Previous studies have mainly concentrated on designing affordable IIoT devices, reducing operational costs, and creating conceptual frameworks to assess the financial impact of IIoT adoption. The objective of this paper is to investigate whether IIoT adoption’s financial benefits outweigh the initial costs in small and medium-sized enterprises (SMEs). The data from the Industrial Assessment Centers (IAC) database were analyzed, focusing on 62 U.S. manufacturing SMEs across 10 states and 25 Standard Industrial Classifications (SICs), evaluating projected IIoT implementation costs and anticipated cost savings. Results from the analyses reveal that statistically, the difference between implementation costs and savings is significant at a 95% confidence level. Practically, this indicates that SMEs, despite facing high initial costs, can expect these investments to be counterbalanced by substantial savings. From an engineering perspective, this finding raises awareness among SMEs that, beyond overcoming financial barriers, IIoT technologies serve as a strategic enhancement to operational efficiency and competitive positioning. This study acknowledges the limitations including reliance on estimated projections and a narrow industry focus. Future research should broaden the sample and explore the lifecycle costs of IIoT.utf-8

Fatemeh Ghafari

Ehsan Shourangiz

Chao Wang*

Intell. Sustain. Manuf.

2024,

(1), 10008;

DOI: 10.35534/ism.2024.10008

Open Access

Review

18 February 2025

Digital Twin and Artificial Intelligence in Machining: A Bibliometric Analysis

The past decade has witnessed an exodus toward smart and lean manufacturing methods. The trend includes integrating intelligent methods into sustainable manufacturing systems purposely to improve the machining efficiency, reduce waste and also optimize productivity. Manufacturing systems have seen transformations from conventional methods, leaning towards smart manufacturing in line with the industrial revolution 4.0. Since the manufacturing process encompasses a wide range of human development capacity, it is essential to analyze its developmental trends, thereby preparing us for future uncertainties. In this work, we have used a Bibliometric analysis technique to study the developmental trends relating to machining, digital twins and artificial intelligence techniques. The review comprises the current activities in relation to the development to this area. The article comprises a Bibliometric analysis of 464 articles that were acquired from the Web of Science database, with a search period until November 2024. The method of obtaining the data includes retrieval from the database, qualitative analysis and interpreting the data via visual representation. The raw data obtained were redrawn using the origin software, and their visual interpretations were represented using the VOSviewer software (VOSviewer_1.6.19). The results obtained indicate that the number of publications related to the searched keywords has remarkably increased since the year 2018, achieving a record maximum of over 80 articles in 2024. This is indicative of its increasing popularity. The analysis of the articles was conducted based on the author countries, journal types, journal names, institutions, article types, major and micro research areas. The findings from the analysis are meant to provide a bibliometric explanation of the developmental trends in machining systems towards achieving the IR 4.0 goals. Additionally, the results would be helpful to researchers and industrialists that intend to achieve optimum and sustainable machining using digital twin technologies.utf-8

Dambatta Yusuf Suleiman*

Qianmeng Li

Benkai Li

Yanbin Zhang

Bo Zhang

Danyang Liu

Wenqiang Zhang

Zhigang Zhou

Yuewen Feng

Qingfeng Bie

Xianxin Yin

Lesan Wang

Changhe Li*

Intell. Sustain. Manuf.

2025,

(1), 10005;

DOI: 10.70322/ism.2025.10005

Open Access

Article

25 February 2025

Thermal Characterization Study of Double End Face Grinding Powder Metallurgy Stainless Steel 316L

Double end face grinding machining is a highly efficient surface grinding technique. And grinding temperature is an important factor affecting the surface quality of workpieces. However, it is difficult to monitor the surface temperature of the workpiece in real time because of the covered contact between the grinding wheel and the upper and lower surfaces of the workpiece during the machining process. This paper aims to conduct a mechanistic analysis and experimental investigation of the machining process to address this challenge. Initially, the paper conducts an analysis of the kinematic mechanism, modal analysis, and the grinding force mechanism specific to the double end face grinding process. Afterwards, the mechanisms leading to the generation of grinding heat and the associated heat transfer mechanisms are explored in depth. The paper then proceeds to solve the instantaneous temperature field during double end face grinding by the finite element method (FEM). Furthermore, the micro and macro profile heights of the machined workpiece surfaces are measured and analyzed. The results show that the machined workpiece surface shows a high center and low edge. This is due to the fact that the temperature at the edge of the workpiece is higher than the center during machining, resulting in more material removal. Through these investigations, the study is able to determine the optimal process parameters for the machining process. This in turn improves machining efficiency and product conformity. And these findings not only guide practical production processes but also provide a foundation for future theoretical research in this area.utf-8

Yue Lu

Junchao Feng

Cong Sun*

Kaiyuan Lin

Guanlong Wang

Xin Wang

Intell. Sustain. Manuf.

2025,

(1), 10006;

DOI: 10.70322/ism.2025.10006

Intelligent and Sustainable Manufacturing Open Access

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