Intelligent and Sustainable Manufacturing - Journal

Articles (58) All Articles

Open Access

Article

21 January 2026

Milling Mechanism of Sheet Fiberglass Plastic by a Tungsten Carbide Tool with Diamond and Diamond-like Wear-Resistant Coatings

The study focuses on identifying the specific mechanisms of the FR4 fiberglass composite milling process using tungsten carbide end mills with wear-resistant diamond-like and diamond coatings. The processing was carried out at cutting speeds from 115 to 300 m/min and feed of 0.075 and 0.15 mm/tooth. At the same time, the vibroacoustic signal was recorded in three formats: changes in the RMS value and the amplitude of the acoustic emission in the low-frequency and high-frequency ranges, as well as the parameter K_f, which is the ratio of the RMS amplitudes of the signals in the low-frequency and high-frequency ranges. It is shown that the coating material has a predominant effect on the surface roughness. The minimum roughness value was R_A = 0.2 µm for the case of a diamond-coated tool. In addition, the coating improves processing performance by increasing the cutting speed for tools with DLC by 1.3 times and for tools with diamond coating by 1.7 times, provided that the R_A increases slightly but does not exceed 0.36 µm. When processed with an uncoated instrument, the mill captures the fiber, bends it and breaks it into bundles, creating grooves. The mechanism of glass fiber destruction by a DLC mill is similar, with the difference that the length of the fragmented fiber sections is noticeably reduced due to reduced friction. The mechanism of cutting fiberglass with a diamond-coated milling cutter is significantly different. There are characteristic scratches on the worn sections of the fiber, and there are no signs of destruction of the composite between the matrix and the fiber. Studies of vibration signals have shown that frequency ranges up to 20 kHz and from 33 to 48 kHz are informative enough to diagnose the fiberglass milling process. The most significant values of the K_f parameter were observed at large amplitudes of low-frequency vibrations, typical for processing with uncoated and DLC milling cutters. The lowest K_f values were obtained using diamond-coated milling cutters. A correlation was found between the values of the K_f parameter and the roughness values of the treated end surface of the fiberglass plate.

Sergey V. Fedorov*

Evgeny E. Ashkinazi

Mikhail P. Kozochkin

Artem A. Ershov

Artem P. Litvinov

Enver S. Mustafaev

Sergey N. Grigoriev

Vitaly I. Konov

Intell. Sustain. Manuf.

2026,

(1), 10002;

DOI: 10.70322/ism.2026.10002

Open Access

Article

21 January 2026

An Industry 4.0-Based Data Visualization Framework for Improved Manufacturing Data Analysis—A Case Study

The proliferation of Industry 4.0 technologies in manufacturing has created an unprecedented opportunity to leverage Big Data for process optimization and efficiency improvements. However, the sheer volume of data can also lead to critical information being overlooked, potentially hindering productivity and competitiveness. This paper presents a straightforward Industry 4.0-based data visualization framework designed to transform raw manufacturing data into actionable insights. Specifically, this work focuses on the analysis of Overall Equipment Effectiveness (OEE) data. The framework utilizes a practical dashboard tool to enable manufacturers to perform in-depth data analysis and identify areas for improvement in real-time. Such a framework enables prompt intervention when corrective actions are needed, ultimately increasing efficiency and reducing production downtime. The framework was successfully implemented at a tire manufacturing company on a single machine within a short period of time. The results highlighted the effectiveness of data visualization in identifying specific operational losses and informing strategic decision-making. This work emphasizes the critical role of technology and proper policies in leveraging data to optimize production processes and drive continuous improvement in Industry 4.0 environments.

Ahmad Elhabashy*

Sohaila Elsayed

Ahmed A. Abdelwahed

Hadi Fors

Intell. Sustain. Manuf.

2026,

(1), 10001;

DOI: 10.70322/ism.2026.10001

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

Article

16 December 2025

Design and Implementation of an Autonomous Smart Food Delivery Robot for Commercial Environments

The integration of robotics into service environments is transforming how labor-intensive tasks are managed, particularly during peak hours with staff shortages and long wait times. This research presents a fully autonomous, modular food-delivery robot designed to enhance operational efficiency and improve service experience. The system combines artificial intelligence, facial recognition, smartphone-based order management, Arduino, ESP32, ESP32-CAM, and Python to navigate indoor environments and deliver food directly to recipients, supported by a secure handover mechanism. Experimental results indicate that the robot performs waiter-like delivery reliably, maintaining mobility and structural integrity across various surfaces by using lightweight materials and motors that have been optimized. Through the use of a motion coordination algorithm, responsive navigation can be achieved, while a simple user interface can be operated by anyone with minimal training. According to these results, automation reduces the need for manual labor, increases the speed of service, and ensures consistency in the delivery process. Additionally, the system provides a practical framework for future research and potential applications beyond food delivery, such as surveillance, environmental monitoring, and disaster response. Future work will focus on scaling for real-world deployment and integration advanced AI navigation to enhance autonomy, adaptability, and overall operational performance.

Mohammed Amer*

Amr Hamdan

Haitham Nairat

Nedal Shadouf

Zaki Majjad

Alya' Dababat

Intell. Sustain. Manuf.

2026,

(1), 10034;

DOI: 10.70322/ism.2025.10034

Open Access

Article

09 December 2025

Mechanical Characterization of Ship Building Grade A Steel by Rapid Cooling in Different Liquid Media

Steel is an essential component used to build marine vessels due to its endurance of the sea’s harsh conditions, including corrosion and dynamic stresses, therefore, different grades of mild steel are used in shipbuilding. It provides the strength, ductility, and weldability necessary for structural integrity, consisting of carbon, manganese, etc., as alloying elements. In this research, different quenching media were employed to assess variations in mechanical properties. This process ultimately triggered alterations in the microstructure of the steel. Two types of media, such as vegetable oil (Canola) and Polyvinylpyrrolidone polymer (PVP), were studied in comparison with simple heat-treated steel. Mechanical characterization comprised of tensile testing, hardness and impact testing to evaluate major changes in strength and ductility. Furthermore, a microscope was used to interpret the microstructure. To guarantee consistency in testing, samples were prepared in accordance with ASTM guidelines. The yield strength of as-received steel was increased from 298 MPa to 358 MPa and 370 MPa because of rapid cooling action in PVP and oil, respectively. A significant increase in Ultimate tensile strength was achieved due to the variety of quenching media; however, ductility was seriously compromised because of the excessive hardness of the material. Impact energy analysis revealed a notable reduction, which is linked with degradation in toughness.

Atif Shazad*

Muhammad Hateem Arif

Muhammad Laique

Muhammad Uzair

Muhammad Waqar

Intell. Sustain. Manuf.

2026,

(1), 10033;

DOI: 10.70322/ism.2025.10033

Open Access

Article

25 November 2025

Dissimilar Joining of 316L and A131 Steel by Shield Metal Arc and Tungsten Inert Gas Welding to Evaluate Bending and Tensile Behavior

In this paper, the effect of filler metal and type of welding on the strength and ductility of dissimilar welding of two different grades of stainless steel was investigated. One of the benefits of stainless steel is its corrosion resistance, which is often necessary for equipment longevity in these facilities. During shipbuilding, as required, stainless steel 316L needs to be welded to the shipbuilding-grade carbon steel A131. In these applications, welding between the two should demonstrate superior strength during vessel construction. To provide a clear illustration, experimental work was needed to allow a careful selection of the joining procedure and filler metal or electrode. The current research work includes a comparative experimental analysis of dissimilar-metal welding (SS-316L & A131 steel). The reasons for choosing these two materials are their greater corrosion resistance and high strength in humid environments. Furthermore, two different welding methods (SMAW & TIG) with varying filler metals were employed in the experiment. The ultimate tensile strength and yield strength of the SMAW welds using E308-16 filler metal were the highest among all, while the TIG welds with ER308L showed superior bending strength. Observations suggest that SMAW with the E308-16 electrode exhibits superior tensile strength, while TIG joints with ER 308L filler provide better bending strength for the welding of SS-316L and shipbuilding (SB) grade A131 steels.

Maaz Akhtar*

Fahad Rehman

Muhammad Muzamil

Atif Shazad

Mohsin Sattar

Intell. Sustain. Manuf.

2026,

(1), 10032;

DOI: 10.70322/ism.2025.10032

Open Access

Review

14 November 2025

Advancements in Hybrid Abrasive Flow Finishing: Fundamentals, Technological Developments, and Industrial Applications in Precision Manufacturing

Hybrid-Based Abrasive Flow Finishing (HAFF) represents a significant evolution in precision manufacturing, particularly in addressing the inherent limitations of traditional finishing techniques when dealing with complex geometries and challenging materials. HAFF achieves remarkable precision in managing particle motion by blending state-of-the-art energy inputs and mechanical reinforcements, including sonic vibrations, electromagnetic influences, and beam-guided supports, which accelerate the pace of material extraction and elevate the overall finish of surfaces. This paper comprehensively reviews various HAFF approaches, including energy-assisted methods (e.g., electrochemical, ultrasonic, and laser), force-assisted techniques (e.g., magnetic, hydrodynamic, and vibration), and hybrid energy-force integrated systems. Recent advancements, such as cryogenic-assisted, rotational-assisted, and magnetorheological-assisted AFF, are also discussed in this review. Recent studies from 2023 to 2025 highlight improvements in material removal rates of up to 80% and reductions in surface roughness of over 90% across various HAFF variants, underscoring the timeliness of these developments. Incorporating diverse power sources and mechanical aids into HAFF allows for exact oversight of particle interactions, speeding up the removal of excess material, refining the exterior finish, and broadening its utility across detailed designs and tough-to-process substances. Despite significant progress, challenges persist in scaling HAFF processes for industrial applications, improving cost efficiency, and implementing effective real-time monitoring systems. The future trajectory of HAFF research will focus on the development of innovative abrasive media, advanced automation technologies, artificial Intelligence techniques, and sustainable manufacturing practices. This study examines all existing HAFF technology solutions and evaluates product applications for aerospace, automotive, medical equipment, and micro-manufactured devices. The discussion highlights the industries that require more advanced technological investigations.

Abdul Wahab Hashmi

Yebing Tian*

Hongjie Sun

Arsalan Ahmad

Chunjin Wang

Dazhong Wang

Mamilla Ravi Sankar

Intell. Sustain. Manuf.

2025,

(2), 10031;

DOI: 10.70322/ism.2025.10031

Open Access

Article

12 November 2025

Topological Optimization for Environmental Sustainability in Civil Engineering Structures Design

The increasing demand for sustainable and cost-efficient construction highlights the need to minimize material consumption in civil engineering structures without compromising safety or performance. This study investigates the optimization of steel purlin cross-sections in metal buildings as a means to enhance structural efficiency and environmental sustainability. Finite Element Analysis (FEA) and the Solid Isotropic Material with Penalization (SIMP) method were employed to identify optimal material distributions and evaluate the effects of varying cross-section geometries. Both rectangular and IPE purlin sections were analyzed under realistic loading conditions to compare stress, deformation, and weight performance before and after optimization. The results demonstrate that substantial reductions in material mass, up to approximately 25–30%, can be achieved while maintaining nearly identical stress and displacement responses. These findings confirm that structural optimization effectively reduces both construction costs and environmental impact. The study concludes by recommending the adoption of topology and cross-section optimization techniques in the design of steel structures, particularly in public projects, to promote resource efficiency and sustainable construction practices.

Theofilos Mavroudis

Amalia Moutsopoulou

Markos Petousis*

Georgios E. Stavroulakis

Nectarios Vidakis

Intell. Sustain. Manuf.

2025,

(2), 10030;

DOI: 10.70322/ism.2025.10030

Open Access

Review

07 November 2025

Value Engineering in the Era of Industry 4.0: From Gap Analysis to Research Methodologies and Strategic Framework

Traditional Value Engineering (VE) has long focused on optimizing the function-to-cost ratio but faces limitations in digitalized industrial contexts. Conventional VE lacks integration with advanced technologies, empirical validation in smart environments, and alignment with sustainability and circular economy objectives. The emergence of Industry 4.0—driven by cyber-physical systems, IoT, big data analytics, digital twins, and artificial intelligence—has transformed industrial ecosystems, necessitating a redefinition of VE practices. This study employs a systematic literature review and structured gap analysis to examine the evolution, applications, and challenges of VE across manufacturing, construction, supply chain, and service sectors. The analysis identifies three key deficiencies in conventional VE: (i) absence of integrated digital frameworks, (ii) limited empirical validation in smart environments, and (iii) weak incorporation of sustainability and circular economy principles. To address these gaps, Value Engineering 4.0 (VE 4.0) is proposed as a function-driven, data-intelligent, and human-centric methodology. It is structured around a six-component strategic framework: (1) digital foundations for technological readiness and organizational alignment; (2) smart VE processes leveraging AI, IoT, and advanced analytics for predictive, connected decision-making; (3) an enhanced Job Plan integrating AR/VR, NLP, and blockchain for improved speed, accuracy, and lifecycle alignment; (4) a phased implementation roadmap; (5) real-time DMAIC integration for continuous optimization; and (6) enablers covering leadership, skills, infrastructure, and cybersecurity. VE 4.0 provides both a research agenda and a practical roadmap, enabling organizations to innovate, enhance resilience, and achieve sustainable competitiveness in Industry 4.0 ecosystems.

Attia Hussien Gomaa*

Intell. Sustain. Manuf.

2025,

(2), 10029;

DOI: 10.70322/ism.2025.10029

Open Access

Article

29 September 2025

Multivariant Time-Series Forecasting Methodology for Product Demand Using Deep Learning and Large Language Models

Accurate demand Soothsaying is a crucial element in force chain operation and business planning. Traditional statistical ways don’t consider the nonlinear, dynamic, and interdependent nature of variables that drive product demand, including deal history, prices, seasonality, elevations, request changes, and profitable pointers. This design presents a sophisticated soothsaying frame for guidance from an artificial intelligence system, integrating soothsaying using deep literacy models together with large language models(LLMs), that can negotiate both accurate soothsaying and give practicable intelligence. The deep literacy infrastructures used in this study include Long Short Term Memory(LSTM), Reopened intermittent Units(GRU), and other Motor models for timeseries soothsaying, which optimize temporal dependences and the complex cross-variable relations. To further increase interpretability of the vaticinations, LLMs are useful agents to convert the specialized cast affair into a completely automated and enhanced mortal-readable textbook and reports to develop intelligence for decision timber. Prophetic modeling and naturally generated reporting lead to better delicacy and practicable intelligence for their businesses. This intelligence empowers businesses to create better procurement processes, improve inventory management, and develop more resilient supply chains relevant to today’s business environment.

Dhanashri Pawar

Annu Kumari Gupta

Pranav Baitule

Atharva Kashirsagar

Pratik Desai

Seema Vanjire*

Intell. Sustain. Manuf.

2025,

(2), 10028;

DOI: 10.70322/ism.2025.10028

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.

VishnuVijay Kumar

KhaledShahin

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.

LuckmanAborahYeboah

AyinawuAbdul Malik

PeterAgyemangOppong

PrinceSarfoAcheampong

JosephArko Morgan

RoseAkua AdwubiAddo

BorisWilliams Henyo

StephenTakyiTaylor

WolalormMakafuiZudor

SamuelOsei-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.

ShuguoHu

ChangheLi

BenkaiLi

MinYang

XiaomingWang

TengGao

WenhaoXu

Yusuf SuleimanDambatta

ZongmingZhou

PeimingXu

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.

AttiaHussienGomaa

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 HussienGomaa

Intell. Sustain. Manuf.

2025,

(2), 10020;

DOI: 10.70322/ism.2025.10020

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.

HamidMattiello

CarstenDomann

Intell. Sustain. Manuf.

2024,

(2), 10011;

DOI: 10.35534/ism.2024.10011

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.

QinglongAn

JieYang

JunliLi

GangLiu

MingChen

ChangheLi

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

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.

GuquanGu

DazhongWang

ShujingWu

ShuZhou

BuxinZhang

Intell. Sustain. Manuf.

2024,

(1), 10006;

DOI: 10.35534/ism.2024.10006

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.

LuckmanAborahYeboah

PeterAgyemangOppong

AyinawuAbdul Malik

PrinceSarfoAcheampong

JosephArkoMorgan

RoseAkua AdwubiAddo

BorisWilliams Henyo

Intell. Sustain. Manuf.

2025,

(1), 10010;

DOI: 10.70322/ism.2025.10010

Open Access

Review

13 February 2024

3D Printing Technology for Rapid Response to Climate Change: Challenges and Emergency Needs

Providing rapid, efficient, inexpensive, and resilient solutions is an eminent and urgent need for emergency relief conditions, mainly and increasingly driven by the impacts of climate change. Under such disastrous circumstances, the current practice involves preparation, dispatching and managing significant amounts of materials, resources, manpower, and transportation of basic needs, which can be hindered remarkably by infrastructure damage and massive loss of lives. However, an emerging technology known as 3D printing (3DP) can play a significant role and rapidly bring unlimited innovative solutions in such conditions with much lesser resources to meet the necessities of large populations affected. Considering the recent progress of 3DP technology and applications in different industrial and consumer sectors, this study aims to provide an analysis of the status and current progress of 3DP technology in various fields to understand and present its potential for readiness and response to disasters, emergency and relief need driven by climate change. Secondly, this study also presents a sustainability assessment of 3DP technology for such cases to evaluate economic, environmental, and social impacts. Finally, policies and strategies are suggested to adapt 3DP technology in different sectors to prepare for large-scale emergencies.

Shoukat AlimKhan

AnsAl Rashid

JasimMuhammad

FawadAli

MuammerKoç

Intell. Sustain. Manuf.

2024,

(1), 10004;

DOI: 10.35534/ism.2024.10004

Open Access

Review

29 December 2023

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

QinglongAn

JieYang

JunliLi

GangLiu

MingChen

ChangheLi

Intell. Sustain. Manuf.

2024,

(1), 10002;

DOI: 10.35534/ism.2024.10002

Open Access

Review

28 March 2024

Digital Twins Enabling Intelligent Manufacturing: From Methodology to Application

ShuguoHu

ChangheLi

BenkaiLi

MinYang

XiaomingWang

TengGao

WenhaoXu

Yusuf SuleimanDambatta

ZongmingZhou

PeimingXu

Intell. Sustain. Manuf.

2024,

(1), 10007;

DOI: 10.35534/ism.2024.10007

Open Access

Review

23 February 2024

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

GuquanGu

DazhongWang

ShujingWu

ShuZhou

BuxinZhang

Intell. Sustain. Manuf.

2024,

(1), 10006;

DOI: 10.35534/ism.2024.10006

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

MinkaiChen

YanbinZhang

BoLiu

ZongmingZhou

NaiqingZhang

HuhuWang

LiqiangWang

Intell. Sustain. Manuf.

2024,

(1), 10003;

DOI: 10.35534/ism.2024.10003

Open Access

Review

14 January 2025

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

VishnuVijay Kumar

KhaledShahin

Intell. Sustain. Manuf.

2025,

(1), 10002;

DOI: 10.70322/ism.2025.10002

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

CanLiu

YongZhang

LidaZhu

QiangLi

XinShu

ShaoqingQin

Dazhong Wang

Wentian Shi

Intell. Sustain. Manuf.

2025,

(1), 10001;

DOI: 10.70322/ism.2025.10001

Open Access

Review

19 July 2024

Solid Additives to Increase the Service Life of Ceramic Cutting Tool: Methodology and Mechanism

With the development of the manufacturing industry, there is an increasing demand for high-efficiency processing, high-precision processing, and high-temperature processing. The characteristics of ceramic tools, such as high hardness and wear resistance, make them suitable for high-precision processing. Additionally, their excellent high temperature resistance perfectly meets the requirements of high temperature processing. However, ceramic tools have a relatively low strength and are prone to breakage, which limits their application in some high-strength machining fields. Their low toughness and brittleness also lead to easy cracking and reduced tool life, resulting in frequent tool changes that further limit processing efficiency. Therefore, improving the service life of ceramic tool materials is crucial to enhance processing efficiency and achieve significant economic benefits. With the development of material science, solid additives with toughening and strengthening properties have greatly improved the performance of ceramic tool materials and given ceramic tools new life-enhancing properties, such as lubrication and repair. By utilizing the combined action of one or more solid additives and employing surface coating technology, the service life of ceramic cutting tools is significantly extended. This makes the application of ceramic tools in industrial cutting more and more widely, and the demand is also growing rapidly. However, the mechanism and methods of various solid additives to increase the life of ceramic tool materials have not been systematically reviewed. The analysis of the composition and functional properties of ceramic tool materials was used as a basis to summarize the mechanism by which various solid additives improve the service life of ceramic tool materials, and to provide points for attention in their use. The aim is to assist researchers in designing and preparing new ceramic tool materials that can meet processing requirements. Finally, the research status, challenges, and prospects of enhancing the service life of ceramic cutting tools with solid additives are summarized, providing a foundation for further research.utf-8

YuxinShi

BiaoZhao

WenfengDing

Intell. Sustain. Manuf.

2024,

(2), 10009;

DOI: 10.35534/ism.2024.10009

Open Access

Review

13 February 2024

3D Printing Technology for Rapid Response to Climate Change: Challenges and Emergency Needs

Shoukat AlimKhan

AnsAl Rashid

JasimMuhammad

FawadAli

MuammerKoç

Intell. Sustain. Manuf.

2024,

(1), 10004;

DOI: 10.35534/ism.2024.10004

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

FatemehGhafari

EhsanShourangiz

ChaoWang

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

DambattaYusufSuleiman

QianmengLi

BenkaiLi

YanbinZhang

Bo Zhang

Danyang Liu

Wenqiang Zhang

Zhigang Zhou

Yuewen Feng

Qingfeng Bie

Xianxin Yin

Lesan Wang

ChangheLi

Intell. Sustain. Manuf.

2025,

(1), 10005;

DOI: 10.70322/ism.2025.10005

Intelligent and Sustainable Manufacturing Open Access

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