Sustainable Manufacturing Research Articles

Identification and Prioritization of Critical Success Factors of a Lean Six Sigma–Industry 4.0 Integrated Framework for Sustainable Manufacturing Using TOPSIS

The relationship between Lean Six Sigma, Industry 4.0 and sustainable manufacturing has been evaluated only to a limited extent within this domain of the published literature. A DMAIC-DMADV-based framework along with a phase-by-phase implementation path is proposed in this study to integrate Lean Six Sigma and Industry 4.0 technologies for achieving sustainable manufacturing. The paper also focused on identifying and prioritizing the critical success factors for the implementation of the proposed framework. The critical success factors identified through a literature review are ranked using the multi-decision criteria technique TOPSIS, with input from selected experts across various manufacturing companies. The results highlight that the most important enablers set clear sustainability goals, regularly monitor progress and have a skilled workforce. The findings provide actionable guidance for practitioners, and the study contributes to the existing body of knowledge by offering a comprehensive methodology to integrate Lean Six Sigma and Industry 4.0 for sustainable manufacturing. Further research must focus on the validation of the framework in diverse industrial settings and refining the sustainability assessment model to enhance its adaptability.

Enhancing Environmental Sustainability in the Coffee Processing Industry via Energy Recovery and Optimization: A Life Cycle Assessment Case Study

The coffee processing industry is amongst the most energy-intensive industrial sectors, with the roasting process requiring substantial quantities of energy. To enhance sustainability, various energy optimization and recovery methods have been proposed. This study evaluates the environmental benefits of integrating energy recovery techniques in a typical coffee processing industry using a Life Cycle Assessment (LCA) approach. Specifically, two alternative scenarios were compared to a baseline processing line; (i) Scenario A, which involves recycling hot air streams to reduce natural gas consumption, and (ii) Scenario B, which utilizes an Organic Rankine Cycle (ORC) to convert waste heat to electricity. The LCA analysis indicated that Scenario A achieved a 25% reduction in greenhouse gas emissions and an 18% decrease in fossil fuel use. Scenario B demonstrated even greater environmental benefits, with a 40% reduction in greenhouse gas emissions and a 36% decrease in fossil fuel depletion. These findings underline the potential of integrating energy recovery technologies to enhance the sustainability of coffee production, offering valuable insights for industry stakeholders and researchers focused on sustainable manufacturing practices.

The Role of Activity-Based Costing in Reducing Environmental Impact: A Systematic Literature Review

Accounting professionals play a pivotal role in reducing environmental impact through systems like activity-based costing (ABC). This study offers a thorough review of research on ABC and environmental impact, providing insights into the current literature and guiding future developments. It systematically reviews 58 articles published in the Web of Science from 1998 to 2023, using Excel and the R package Bibliometrix for data analysis. The findings indicate a steady increase in research on ABC and environmental impact. Key contributions highlight the advantages of ABC in minimizing environmental impact across industries such as sustainable construction, metallurgy, transportation, and manufacturing. Emerging research directions include developing costing systems to reduce environmental impact, optimizing supply chain cost management models, and applying new technologies to tackle environmental challenges in production processes. Two primary research themes, identified as “motor themes,” are crucial for advancing this field: life-cycle assessment management models, which integrate environmental factors throughout a product or service’s life cycle; and the performance and impact of environmental cost management systems, which evaluate the effectiveness of these systems in reducing ecological footprints while maintaining profitability. These areas are essential for driving future research and innovation at the intersection of cost management and environmental sustainability.

AI-driven Modeling for the Optimization of Concrete Strength for Low-Cost Business Production in the USA Construction Industry

The need to develop ecologically friendly sustainable building materials is made apparent by the worldwide construction industry's substantial contribution to global greenhouse gas emissions. The use of supplemental materials in concrete is one potential solution to lessen the environmental footprint. Thus, the purpose of this work is to use Machine Learning (ML) algorithms to forecast and create an empirical formula for the Compressive Strength (CS) of concrete with supplemental materials. Six distinct ML models—XGBoost, Linear Regression, Decision Tree, k-Nearest Neighbors, Bagging, and Adaptive Boosting—were trained and tested using a dataset that included 359 experimental data of varying mix proportions. The most significant factors used as input parameters are cement, aggregates, water, superplasticizer, silica fume, ambient curing, and supplemental material. Several statistical measures, such as Mean Absolute Error (MAE), coefficient of determination (R2), and Mean Square Error (MSE), were used to evaluate the models. XGBoost model outperformed the other models with R2 values of 0.99 at the training stage. To ascertain how the input parameters affected the outcome, feature importance analysis using Shapely Additive exPlanations (SHAP) was conducted. It was demonstrated that curing age and cement type significantly affected the strength of concrete with high SHAP values. By eliminating experimental procedures, reducing the demand for labor and resources, increasing time efficiency, and offering insightful information for enhancing sustainable manufacturing of concrete, this research advances the low-cost production of concrete in the USA construction industry.

Sustainable additive manufacturing: challenges and opportunities of recycling plastic waste for 3D printing filaments

Sustainable additive manufacturing: challenges and opportunities of recycling plastic waste for 3D printing filaments

Enhanced Sustainability Assessment Framework for Plywood Manufacturing: A Multi-Method Approach Using Delphi Technique, BWM, and S-VSM

Sustainable manufacturing has emerged as a critical priority in addressing the complex environmental, social, and economic challenges of modern industry. This study focuses on the plywood sector, a significant contributor to manufacturing, which faces distinct sustainability issues such as high energy consumption, material inefficiencies, and hazardous working conditions. To address these challenges, the research introduces workload and noise level as critical indicators for assessing sustainability, broadening the scope of traditional evaluation methods. A multi-method framework was employed, integrating the Delphi technique to identify key sustainability indicators, the Best Worst Method (BWM) to assign weights to these indicators, and Sustainable Value Stream Mapping (S-VSM) paired with a Traffic Light System (TLS) to evaluate and visualize the Manufacturing Sustainability Score (MSS). Applied to a plywood manufacturing case study, the framework highlighted areas requiring improvement, particularly in worker well-being and operational safety, while demonstrating the industry's moderate overall efficiency. By offering actionable insights for improving resource use, operational processes, and employee conditions, this framework provides a practical tool for industry managers aiming to enhance sustainability. Furthermore, its adaptability makes it a valuable reference for other manufacturing sectors seeking to implement resource-efficient and sustainable practices. This research not only fills critical gaps in sustainability assessment but also contributes to advancing industry practices by emphasizing holistic and innovative approaches to manufacturing efficiency.

Flexible and Stretchable Vitrimers for Sustainable Electronics.

The rapid increase in electronic waste (e-waste) necessitates sustainable materials that combine functionality with recyclability. Here, we introduce a novel approach for creating flexible vitrimers─reprocessable polymers with dynamic covalent bonds─for use in electronic applications, such as wiring and connectors. By extending polymer chains and employing transesterification reaction, we develop vitrimers that exhibit tunable viscoelastic properties, high stretchability (over 250% tensile strain), and enhanced toughness (up to 466 J/m3). Our vitrimers demonstrate a topological freezing temperature (Tv) of 185-248 °C, adjustable through catalyst concentration and chain length. The materials are synthesized by using a two-step process involving widely available industrial chemicals. Molecular dynamics simulations provide insight into how chain extension and network topology affect viscoelasticity, supporting the experimental findings. Using transesterification, covalent bonding between flexible and rigid vitrimers can be achieved. We prototype a functional USB cable that successfully transfers power and data, showcases repairability, and is recyclable through a solvent-based process. These results highlight the potential of flexible vitrimers in reducing e-waste and advancing sustainable electronic manufacturing.

Revolutionising Industry 5.0: unlocking AI-at-the-Edge for sustainable manufacturing transformation

Revolutionising Industry 5.0: unlocking AI-at-the-Edge for sustainable manufacturing transformation AI REDGIO 5.0 aims to accelerate the digital transformation of manufacturing SMEs by integrating AI-at-the-Edge and Industry 5.0 systems. The project focuses on developing AI-driven solutions that enhance operational efficiency, sustainability and human-centred practices. Through SME-driven experiments and collaboration across regions, it seeks to foster innovation, improve manufacturing processes and promote a sustainable, resilient industry.

Sustainable Manufacturing Through Economics Education and Counselling

Sustainable Manufacturing Through Economics Education and Counselling

Evaluating environmental impacts of bio-based insulation materials through scenario-based and dynamic life cycle assessment

Abstract Purpose Bio-based insulation materials can have a significant impact in achieving net zero target in the construction sector. However, they face challenges due to lack of data on environmental performances and professional perception, hindering their proliferation. This study aims to combine scenario-based and dynamic analyses of environmental performances to provide comprehensive environmental information on bio-based thermal insulation materials. The goal is to empower professionals with robust information, facilitating informed decisions and promoting the selection of bio-based materials. Methods Data on manufacturing, use, recyclability, and technical performance of eleven commercially available natural insulation materials were collected from the literature to create a Life Cycle Inventory (LCI). For each material, a scenario-based life cycle assessment (LCA) was conducted by modelling variation in manufacturing, transportation, end-of-life and material properties, using the UK as the primary case study. Materials were compared to three non-bio-based insulation materials by ranking the thirteen environmental impact categories in EN 15804(2013) + A2(2019) to give an exhaustive overview of their potential benefits and burdens. Additionally, a dynamic LCIA was performed to implement in the analysis both short-and long-term emissions, exploring the impact of biogenic carbon. Results The scenario analysis highlighted that recycled cotton and hemp fibre insulation have the lowest impact across all impact categories, attributed to their sustainable manufacturing processes and minimal impacts at the end-of-life stage. The dynamic LCIA demonstrated that recycled textile insulation has the lowest impact both in the short-term (prior to waste disposal) and the long-term (post-waste disposal), regardless of the chosen end-of-life scenario. Furthermore, it indicated that cotton and hemp fibre have a negligible impact on global temperature changes, achieving a net-zero effect in the short-term and close-to-zero impact in the long-term. Conclusion The novelty of this paper lies in its comprehensive investigation of the environmental impacts of bio-based thermal insulation materials, employing multiple tools to enhance generalizability. These results will support decision-making by providing data ranges to help practitioners identify the most environmentally friendly insulation materials. Additionally, they offer insights into how similar products compare within that range, driving progress in the built environment towards net-zero emissions. Whilst the full dataset and evaluation methods are illustrated through a UK-based case study, this method can be adapted for specific scenarios and projects, due to the transparency of data and methods. This research significantly influences the built environment and promotes net-zero targets within the sector.

Reducing the Environmental Impact of Denim: A Comparative Study of Green and Conventional Manufacturing Practices

Denim manufacturing, from cotton farming to garment production, carries significant environmental impacts. Despite introducing sustainability within the denim industry, the environmental benefits of related practices are not thoroughly assessed and contrasted with conventional manufacturing practices. This study aims to evaluate and compare the environmental impacts of sustainable and traditional denim manufacturing processes in Bangladesh through a Life Cycle Assessment. Adhering to ISO 14040/14044:2006 standards and utilising the ReCiPe 2016 Midpoint (H) assessment, this study investigated key environmental indicators, including terrestrial acidification, eutrophication, land occupation, water consumption, abiotic depletion, and greenhouse gas emissions. Notable findings reveal that yarn and fabric production contribute to 56% of greenhouse gas emissions and 45% of terrestrial acidification, while cotton cultivation accounts for 92% of water consumption and 69% of land use. Compared to traditional methods, green manufacturing practices achieve reductions in greenhouse gas emissions and water use by over 60% and 21%, respectively. These findings underscore the potential for sustainable practices to mitigate the environmental footprint of denim production while highlighting areas for further improvement. This study delivers critical insights for advancing sustainability in the denim industry.

Optimizing Inventory Control Using Min-Max Method for Sustainable Manufacturing Process

Inventory plays an important role in a company's production process, especially in the sustainable manufacturing industry. The inventory of raw materials such as rayon, polyester, and cotton is an essential element that needs to be controlled to maintain a smooth production process. This research aims to plan and control raw materials through the min-max method, with a focus on evaluating inventory control to identify and overcome existing problems in the raw material warehouse at a yarn and textile manufacturing company. The results show that each type of raw material has a different reorder level, which guides the company in avoiding the risk of shortage or excess stock. By applying the right reorder level, the company can improve its production efficiency and inventory management. This research contributes to the practice of inventory control in the sustainable manufacturing industry, which supports operational stability and minimizes resource wastage. The implications of the findings could expand the application of min-max method-based inventory control in other industries to support operational sustainability.

Extraction and Characterization of Antioxidants and Cellulose from Green Walnut Husks

The ultrasound-assisted extraction process with microwave pretreatment was modeled and optimized to maximize the yield of antioxidants from green walnut husks using a response surface methodology with Box–Behnken design. In this design, the ultrasound-assisted extraction time (10–40 min), ultrasound-assisted extraction temperature (40–60 °C), and microwave pretreatment time (20–60 s) were selected as the factors, while the total antioxidant content was defined as the response. The solvent of choice for extracting antioxidants was 50% (v/v) ethanol. After optimization using the desirability function, an ultrasound-assisted extraction time of 23 min, ultrasound-assisted extraction temperature of 60 °C, and microwave pretreatment time of 60 s were proposed as the optimal conditions and their validity was verified. Under these conditions, the experimentally determined total antioxidant content was 3.69 g of gallic acid equivalent per 100 g of dry matter. In addition to phenolics, UHPLC–ESI–MS/MS analysis indicated the presence of lipids, quinones, terpenoids, and organic acids in the extract. After the antioxidant extraction, the solid residue was further processed to isolate cellulose in line with the concept of sustainable manufacturing. The structural characterization and hydration properties of cellulose were analyzed to identify its key features and assess its potential for value-added applications. The results demonstrate that green walnut husks are a valuable and cost-effective agro-industrial byproduct for extracting antioxidants and isolating cellulose. This aligns with the principles of a circular economy and the sustainable production of natural compounds.

Digital Product Passport Design Supporting the Circular Economy Based on the Asset Administration Shell

This paper investigates the design of a digital product passport (DPP) model based on the asset administration shell (AAS) framework to support the circular economy while ensuring cross-industry applicability. In a circular economy, resources are continuously reused, fostering more sustainable manufacturing. The European Commission’s initiatives target this issue, with the DPP playing a critical role in sharing product sustainability information, such as product composition and repairability, throughout its lifecycle. However, a widely applicable DPP approach has yet to be established. This study consolidates existing standards, and scientific literature to develop a data model that aligns with circular economy principles. Using the AAS framework initially developed by the Plattform Industrie 4.0, we mapped the data requirements to submodel templates and addressed gaps in the data needed for real-life implementation. The results demonstrate that the proposed DPP data model is specific enough for practical use cases, such as the upcoming EU battery passport, while remaining flexible enough for application across various industries. The AAS framework’s adaptability and comprehensive data exchange capabilities make it a suitable foundation for developing DPPs that support the transition to a circular economy.

The Effect of Internal and External MQL Methods Used for Environmentally Friendly Manufacturing on Machining Performance in Drilling AA2024 Alloys: A Comparison for ANN And Taguchi Analyzes

In recent years, the interest in sustainable manufacturing has created an increasing demand for the economical and environmentally friendly Minimum Quantity Lubrication (MQL) method. However, there are not enough studies comparing internal and external MQL applications in drilling operations. The aim of this study is to investigate the effects of internal and external MQL application on drilling performance. Using Taguchi L9 experimental design, AA2024 aluminum alloy was drilled under three different cooling conditions (internal MQL, external MQL, dry), three different cutting speeds (100, 125, 150 m/min) and three different feeds (0.10, 0.15, 0.20 mm/rev). Surface roughness (Ra) was determined as the performance criterion, 30 repetitions were made in each experiment and the average Ra values were calculated for each condition. At the end of the experiments, the lowest Ra value (0.5 µm) was obtained in the internal MQL condition where the lowest cutting speed (100 m/min) and feed (0.1 mm/rev) parameters were used. In the external MQL condition, Ra results close to dry cutting were observed. The ANOVA analysis revealed that the control factor with the greatest effect on Ra values was the cooling condition. In addition, tool wear after the 30th hole was examined with SEM images and minimum deformation was observed in the internal MQL. ANN and Taguchi analyses were applied to the Ra data measured in the experiments. It was observed that the measured Ra data were in agreement with the data estimated using the Taguchi approach by 97% and with the data estimated using the ANN approach by 99%.

System Dynamics for Manufacturing: Supply Chain Simulation of Hemp-Reinforced Polymer Composite Manufacturing for Sustainability

System Dynamics for Manufacturing: Supply Chain Simulation of Hemp-Reinforced Polymer Composite Manufacturing for Sustainability

Data-Driven Manufacturing: Leveraging Analytics for Operational Excellence

This comprehensive article explores the transformative impact of data-driven analytics on modern manufacturing operations, emphasizing its role in enhancing operational excellence and innovation. The article examines five key areas: production intelligence, supply chain optimization, sustainable manufacturing analytics, data-driven innovation, and implementation frameworks. Through detailed analysis, the article demonstrates how advanced analytics capabilities are revolutionizing manufacturing processes by enabling predictive maintenance, optimizing supply chains, promoting sustainable practices, and accelerating innovation cycles. The article reveals how manufacturing organizations leverage real-time monitoring, machine learning algorithms, and artificial intelligence to achieve improved operational efficiency, reduced maintenance costs, enhanced product quality, and increased market responsiveness. The article also addresses organizational readiness and technical infrastructure requirements for successfully implementing data-driven manufacturing solutions. By examining technical and organizational dimensions, this study provides valuable insights into how manufacturers can effectively transition to data-driven operations while maintaining competitive advantage in an increasingly dynamic market environment.

Towards a Greener Future: Using DEMATEL-ANP for Sustainable Indonesian Fiber Cement Board Manufacturing Company

The Indonesian fiber cement board industry faces increasing pressure to enhance sustainability due to growing environmental global concerns and regulatory demands. The companies in this sector must address multiple sustainability criteria such as waste management, resource utilization, and compliance with environmental regulations to remain competitive and sustainable. However, identifying which criteria are the most influential in driving overall sustainability outcomes presents a challenge. Previous studies have often examined these criteria in isolation, without considering their interdependencies. To address this gap, this study integrates the Delphi method with DEMATEL and ANP to analyze and prioritize key sustainability criteria for a fiber cement board company. By developing a comprehensive framework, this research aims to provide actionable insights that will help companies enhance their sustainability performance. In this research, PT. XYZ, a well-known fiber cement board manufacturer in Central Java, Indonesia, was used as a case study. The result shows that the DEMATEL-ANP method reveals that waste management, compliance with environmental regulations, and resource and material management are the most critical criteria, with high prominence and influence scores. These findings suggest that focusing on these critical areas first, followed by processing other criteria accordingly, can significantly enhance the company’s sustainability performance.

Impact of Retention Agents on Functional Properties of Recycled Paper in Sustainable Manufacturing

The proper dosing and optimization of retention additives are necessary to ensure the desired benefits without compromising other aspects of the paper manufacturing process. In this study, the effects of a cationic polyelectrolyte based on acrylamide and a cationic derivative of acrylic acid on the different properties of paper containing recycled fibers were investigated. The structural and tensile properties were examined through various analyses to determine the optimal dosage of the retention additive. The results obtained indicate that while the retention agent can enhance papermaking efficiency by improving retention, drainage, and sheet formation, it also negatively impacts the tensile strength and surface smoothness of the recycled paper. This complexity highlights the importance of a balanced approach in optimizing retention aid dosages. Determining the optimum dosage of such an agent requires multiple trials and analyses with varying dosages. This review aims to offer a background for engineers seeking to enhance the competitiveness and reduce production costs of their paper products, as well as for researchers striving to surpass the existing standards and achieve innovative outcomes.

The Integration of Additive Manufacturing into Industry 4.0 and Industry 5.0: A Bibliometric Analysis (Trends, Opportunities, and Challenges)

This bibliographic analysis explores the evolving landscape of additive manufacturing (AM) in the context of Industry 4.0 and the emerging paradigms of Industry 5.0. This research critically examines the key literature and scholarly works to clarify the evolution, challenges, and opportunities presented by integrating AM technologies with digital transformation and advanced industrial practices. The exploration begins by tracing the foundational concepts of Industry 4.0, emphasizing the role of cyber–physical systems, data analytics, and automation in reshaping manufacturing ecosystems. It then moves to the developments of Industry 5.0, focusing on human-centric approaches, collaborative robotics, and sustainable manufacturing strategies that extend beyond automation. The impact of AM technologies across various sectors, from aerospace and automotive industries to healthcare and consumer goods, is central to this analysis. This article synthesizes empirical studies, case analyses, and theoretical frameworks to discern the synergies, challenges, and prospects of integrating AM into Industry 4.0 and the evolving Industry 5.0. Through this bibliographic journey, readers gain insights into the transformative potential of AM as a catalyst for innovation, agility, and sustainability in the digital age. The findings underscore the need for interdisciplinary collaborations, policy frameworks, and technological advancements to harness AM’s full potential within Industry 4.0 and 5.0.