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The life-cycle duration (TLC) is typically assumed constant in pavement life-cycle analysis. The added scientific value of this paper is that (TLC) is considered a variable parameter to be estimated from the performance curve using a variable terminal condition rating. A variable (TLC) requires using the equivalent annual value (EAV) instead of the net present value for cost estimation. The life-cycle performance (LCP) curve is constructed using two routine maintenance cycles separated by one major rehabilitation action. The time parameters associated with LCP curve are estimated from the inverse performance function based on the initial, present and terminal condition ratings. The equivalent annual cost and performance associated with a particular LCP curve are used to compute cost/performance (C/P) ratio for optimal maintenance and rehabilitation (M&R) plan selection. The EAV represents the costs of two routine maintenance cycles and one major rehabilitation action. Sample results obtained from three case studies have indicated the reliability of the proposed LCA approach in yielding optimal M&R plans. At the project-level, the optimal M&R plan associated with 7 m/km terminal IRI value resulted in (0.949) minimal (C/P) value. However, the optimal M&R plan with 3.25 terminal PSI yielded (1.50) minimal (C/P) value.

In a world where climate change and sustainability are at the forefront, innovative solutions are more pressing than ever. In the production process of distillates, the critical stage is the cooking of agave for thermal hydrolysis of fructans. This stage determines the efficiency of the process, incurs the highest production cost, and has a detrimental impact on the environment. In this study, we investigate the saccharification of agave fructans in fresh juice using fructanases produced in situ by Kluyveromyces marxianus as an alternative to traditional agave cooking. furthermore, we explore both sequential and simultaneous alcoholic fermentation processes using a native mixed culture to improve the overall yield and obtain a distillate with enjoyable sensory characteristics. The results show that saccharification and simultaneous fermentation allow for obtaining a fermented product containing an average of 7% alcohol. Gas chromatography and mass spectrometry analysis shows that the distillate is essentially an ethanol – water mixture with a broad profile and high concentration of volatile compounds. The composition of the distilled product provides a well-balanced sensory experience that is highly valued by consumers. Hence, for the first time, a novel, efficient, low-cost, and sustainable process for producing agave distillates has been successfully designed.

The increasing demand for coffee in Indonesia and abroad, accompanied by value creation from applying sustainability principles for coffee brands or outlets, leads to potential opportunities for coffee product entrepreneurs. Through the development of an online platform that entrepreneurs can directly access to eliminate links in the supply chain, coffee entrepreneurs have the opportunity to compete through national and international markets. Therefore, this study examined the effectiveness of digital platform applications in increasing the supply chain competitiveness of agricultural micro, small, and medium enterprises (MSME) products in Indonesia, especially coffee products. The conceptual model in this study examines the relationship between digital platform capability and organisational agility, specifically addressing when and how digital platform can help MSME exporters increase their organisation’s agility. This research uses theory of capability dynamism and the partial least squares structural equation modelling (PLS-SEM) method to test the proposed model and estimate the relationship between constructs. Consequently, this research develops strategies for the supply chain stakeholders using the why-how-laddering method for managerial implications. The study’s findings show that organisational agility can be supported by improving digital platform capability, and nine strategic recommendations can be applied to increase coffee exporters’ digital platform capability and organisational agility, respectively.

The increasing prominence of autonomous vehicles underscores the critical need for precise and prompt lane detection to ensure safe and reliable transportation. This paper aims to enhance autonomous vehicle performance by developing an advanced real-time lane detection system using the YOLOV5 Segmentation Large Model. The methodology utilises LabelMe for dataset annotation and employs rigorous pre-processing techniques such as resizing, augmentation, noise addition, greyscale conversion, enhanced exploration size, and image rotation. YOLOv5 architecture is extensively employed for in-lane instance segmentation. The proposed model achieves high performance with a pixel accuracy of 89%, a processing speed of 48 frames per second, and mAP@0.5 scores of 0.885 for the bounding box and 0.731 for the mask. These results demonstrate the model’s effectiveness in various conditions. This paper introduces an innovative approach to autonomous vehicle lane detection, leveraging the YOLOV5 Segmentation Large Model for unparalleled precision and recall rates. This paper makes a significant contribution to the advancement of autonomous vehicle technology, emphasising the critical role of reliable and timely lane detection in strengthening the dependability and safety of transportation systems.

The digital transformation of Vietnam is a crucial strategic priority for the country’s rapid and sustainable development. This article presents a new method that combines the neutrosophic analytical hierarchy process (NAHP) with the technique for order of preference by similarity to ideal solution (TOPSIS) to analyse the impact of critical success factors (CSFs) on digital transformation. The NAHP was employed to ascertain the weights of the criteria, which serve as the most important indications of success in digital transformation. After obtaining the criteria weights, the alternatives were ranked based on their performance relative to the criteria provided by the TOPSIS technique. With the success of digital transformation activities, firms have substantial acceptance of the reliability of technological, organisational, and environmental (TOE) factors. The study investigated several factors, including leadership, organisational culture, technology infrastructure, and customer-centricity. The proposed methodology required evaluation by implementing a practical case study involving TOE critical factors in the Vietnamese digital transformation sector. Several methodologies and multi-criteria approaches have been developed to assess the key factors that contribute to the successful digital transformation of enterprises. The findings highlighted the validity of the hybrid NAHP-TOPSIS methodology in determining CSFs necessary for achieving objectives relevant to digital transformation.

The Pakistani aerospace industry is embracing digitalisation (within a year), utilising budgets of less than 5% of the company’s annual revenue; however, no industry claims that these technologies have been adopted to a large extent across their R&D, production/manufacturing, MRO, and services/distributor functions. According to 67% of respondents, there are no regulations, laws, or other government policies pertaining to Industry 4.0. Technological preparedness in the form of suitable software and hardware was highlighted as the main critical success factor, while Cybersecurity and cloud computing were identified as essential implementation tools. The originality and value of this study lie in it being the first study of its type on Industry 4.0 within the Pakistani aerospace sector. This research will serve as a strategic tool for policymakers, industry leaders, and stakeholders to guide informed decision-making and propel the aerospace sector towards sustainable growth and competitiveness.

In September 2015, the United Nations launched the 2030 Agenda for Sustainable Development, followed by the adoption of the ‘Space2030’ Agenda in October 2021, highlighting the importance of space and Earth Observation (EO) data in monitoring progress towards these goals. This research examines the benefits of EO evolution, spurred by New Space initiatives, within socioeconomic sustainability and development. Key Performance Indicators (KPIs) are introduced to assess the socioeconomic impacts related to Sustainable Development Goal 8 (SDG8) targets 8.2 and 8.3. Findings show that the EO evolution enhances job opportunities (KPI1) and increases job deployment rates per investment (KPI2). Furthermore, this trend democratises access to the space market, significantly boosting participation of Small and Medium Enterprises (SMEs) (KPI3).

Despite significant advancement in conventional desalination technologies, their widespread application is still constrained by high energy demands, high capital costs, and the associated greenhouse gas (GHG) emissions. The main objective of this study is to evaluate the potential and challenges of renewable energy desalination in the Middle East. The study also compared the production of energy and water, and emissions reductions of hypothetical 100 MW renewable energy plants in Kuwait, coupled with reverse osmosis (RO) desalination units. The wind-RO plant is estimated to produce 68 million cubic metres on an annual basis, while the CSP-RO and PV-RO plants produced 44 and 37 million cubic metres of fresh water, respectively. These estimates, however, only account for 5% to 9% of the annual fresh water demand in the reference case. Meeting 100% of the fresh water demand would require a 1000 MW to 2000 MW renewable energy capacity. Overall, the intermittent nature of renewable energy sources is a fundamental barrier to the large-scale transition to renewable energies for desalination. The results of this study indicate that the CSP’s relatively small footprint (compared to wind plants) and higher capacity factor make it an ideal compromise among the proposed plants.

This study examines the relationship between extreme weather conditions and the S&P500 return index, representing the U.S. stock market. The literature review and analysis show extreme weather events can impact the S&P500 return index. This effect is observed in two ways. First, extreme weather events create a market anomaly in the U.S. stock market, indicating that prices move in a way that cannot be explained by a rational model. Second, extreme weather events create financial uncertainty and have a negative impact on firms’ future cash flows. These findings suggest that investors and financial markets should be more cautious about extreme weather events. In addition, the impact of extreme weather on the U.S. stock market is weak. This can be explained in two ways. First, extreme weather events are predictable and seasonally recurring. Second, the American stock market is close to the efficient market hypothesis.

Bottom ash (BTA), a byproduct of burning coal in electric power plants, is often considered waste. Managing significant quantities of bottom ash remains a challenge. Laterite, commonly used in road construction, may not meet the required standards in some regions, necessitating the transport of higher-quality laterite from distant locations. This practice increases construction costs. This research explores the use of bottom ash and cement as replacements for laterite in pavement materials. The proportion of bottom ash used varied from 10 to 50% by dry weight of the laterite, while the cement contents were 1, 3, 5, and 7% by dry weight of the laterite-bottom ash mixture. The experiments included unconfined compressive strength, splitting tensile strength, California bearing ratio, and durability against wetting-drying cycles. The results indicate that the stabilised laterite significantly increases strength values—2 to 14 times greater than those of unstabilised laterite, with 20% bottom ash replacement yielding the best results. Microstructural analyses confirmed the strength test outcomes. Replacing laterite with bottom ash and cement proves to be a sustainable method for road construction, offering cost-effectiveness, conservation of natural resources, pollution reduction, and enhanced energy efficiency in accordance with the standards of the Department of Highways of Thailand.

This study aimed to enhance the efficiency of by-product raw materials from the sugar industry for use as fuel. The approach involved developing an equation to calculate the higher heating value (HHV) for each type of raw material using a regression method. Additionally, a simplex-centroid mixture design (SCMD) was employed to estimate the lower heating value (LHV) based on the mixing ratios by weight of sugarcane trash leaves (SCL), sugarcane bagasse (SCB), and filter cake (FTC). The results demonstrated that the developed model accurately estimated the HHV for each raw material. The ultimate analysis showed high statistical appropriateness, with an R2 of 0.83. The standard error of estimation was 0.74 MJ/kg, and the mean absolute error was 0.76%. Furthermore, the SCMD effectively estimated the LHV of the SCL, SCB, and FTC mixture ratios, achieving an R2 of 99.77%. The evaluation and validation of the prediction equation revealed a mean absolute error of 7.57% and a mean bias error of 6.31%. The findings of this study can be used to enhance the combustion efficiency of sugar industry by-products for use as fuel by selecting the optimal mixing ratio for each type of raw material.

Water, a vital resource for ecosystems and human populations, is facing increasing nitrate contamination due to agricultural runoff, industrial discharge and improper waste disposal. The present study focuses on the efficacy of nitrate removal through adsorption using fuller’s earth (FE) and modified fuller’s earth (acid-treated) (MFE) as adsorbents. The impact of initial pH (2.0–7.0), contact time (5–240 min), adsorbent dosage (1–30 g/L), initial nitrate concentration (50–250 mg/L) and temperature (30–50°C) on nitrate removal using fuller’s earth were studied. The maximum nitrate removal was observed at pH 2.0, and equilibrium was reached in 120 min at 30℃. The Freundlich isotherm best fit the equilibrium data. The maximum nitrate uptake of fuller’s earth and modified fuller’s earth were 84.75 mg/g and 85.47 mg/g, respectively. Nitrate removal by FE and MFE followed a second-order kinetic equation. Thermodynamic studies showed spontaneity and the exothermic nature of the nitrate adsorption process. ∆H° values were −44.96 and −42.63 kJmol−1 for FE and MFE and ΔS° was −85.11 and −74.52 Jk−1mol−1 for FE and MFE, respectively. FE, known for its exceptional adsorption capacity owing to its porous structure and high ion-exchange capacity, has demonstrated a remarkable affinity for nitrate ions in batch studies.

Microplastics (MPs) present a pressing environmental concern, posing formidable challenges to their effective elimination from water systems. Bioadsorbents offer a promising, eco-friendly, and cost-effective alternative to traditional removal methods. This review analyzes 206 research papers (2016-January 2024) to explore recent advances in bioadsorbent design and application for microplastic removal. We examine the sources and ecological impacts of MPs, then delve into the most studied bioadsorbents: biochar (51.9%), biomass-derived activated carbon (7.4%), synthetic sponges/aerogels (25.9%), and graphene-based materials (14.8%). The review critically analyzes factors influencing MP adsorption by these materials, including MP type and size, adsorbent properties, and experimental conditions. Reported removal efficiencies ranged from 31% to 100%, with polystyrene (52%) being the most common test polymer. Finally, the intricate mechanisms of MP-bioadsorbent interaction are discussed. We highlight key challenges and future research directions for optimising and scaling up bioadsorbent-based MP removal, acknowledging the early stage of this promising and sustainable approach.

The European Union (EU) has set ambitious recycling targets for plastic packaging waste of 50% and 55% by the end of 2025 and 2030, respectively. Austria’s recycling rate is currently below 30%, necessitating significant improvements in collection, sorting, and recycling efficiencies. To enhance the sorting efficiency, understanding the composition and condition of waste is crucial. Our study focuses on the identification of the recyclable content of polyethylene (PE) films in Upper Austrian waste streams for plastics recycling. This involved the manual sorting of three waste streams through various steps. As a result, the occurrences of monolayer PE films in the post-consumer waste streams were obtained. Based on the apprehended data, a circularity indicator (CI), which is a rough estimation of material circularity that takes into account the losses in both quantity and quality when reprocessing materials, together with a sensitivity analysis was calculated for Austria, which revealed that reducing demand and increasing the amount of recycled materials is more beneficial to the CI than improving energy efficiency. This research fills knowledge gaps on the availability of PE film waste in the various waste streams and can be used as a basis for enhancing the recycling rate in PE film recycling.

Zambia has recently faced prolonged load shedding due to reduced hydroelectricity generation caused by unfavourable rainfall patterns. To tackle this issue and satisfy increasing energy demands, the government aims to explore alternative energy sources like wind energy. However, the uncertainty surrounding the economic feasibility of implementing wind power projects in Zambia poses a significant challenge. This study evaluates the economic feasibility of eight proposed wind farm sites using net present value (NPV), simple payback period (SPP), internal rate of return (IRR), and levelized cost of electricity (LCOE). By examining energy yield analysis (EYA), wind speed, and financial indicators, the study identifies the most economically viable wind farm site(s). The results reveal that the Lusaka wind farm is the most economical, with an energy yield analysis of 386 GWh, wind speed of 8 m/s, NPV of USD 316 million, SPP of 2.9 years, IRR of 82%, and LCOE of 0.182 USD/kWh. An economic sensitivity analysis, varying the average electricity tariff, also points to Lusaka as the most financially viable site. Consequently, policymakers are advised to develop cost-reflective feed-in tariff (FiT) schemes and power purchase agreements to establish electricity tariffs that encourage investment from independent power producers in Zambia.

Electric vehicles (EVs) have played a significant role in sustainability, and EVs fire accidents have raised doubts in recent years. To solve the mobile analytical equipment limitation in EVs fire accident and help staff receive prompt results at on-spot inspection, we provide a lightweight but accurate Transformer that can ideally adapt to the mobile environment. First, we built on the simple Segformer and extended it to aggregate the representations of amorphous objects, such as fire traces, in image recognition. Second, we used shunt-based self-attention (SSA) to enhance the model for capturing multi-scale contextual information and help distinguish the deformed level of EVs after combustion. Third, we redesigned a simple multi-level information aggregation (MIA) decoder to obtain the relationship between pixels in the channel dimensions by a weighted aggregation. Furthermore, to foster image trace recognition, we put forwards and evaluated the accuracy of models on electric vehicle fire traces (EVFTrace), a dataset of images of burnt EVs. On EVFTrace, the mean intersection over union (mIoU) achieves 72.24%. The float point operations (Flops) and parameters (Params) achieve 114.83 G and 89.5 M. Our model shows excellent efficiency and accuracy for burnt EVs segmentation tasks.

The paper proposes a method to size a standalone hybrid PV/MHP/BES (photovoltaic/micro-hydro/battery energy storage) system. The proposed method is simple and easy to use. The size and location decoupled proposed approach can effectively size cost-effective systems. The method exploits variable renewable energy (VRE) resources adjustable complementarity proposing a CMACVRE (VRE Adjusted Complementarity Critical Month) term to size the hybrid system. By reducing capital investment and enhancing load sharing between VRE resources, the method inherently sizes cost-effective systems that minimise SnD gaps and operational expenses. The results show that the proposed method cannot only size a Homer Pro comparable system but can optimise a Homer Pro sized system further. Additionally, that the system sized by Homer Pro employing the proposed approach with adjustable complementarity delivers better results than the system sized by Homer Pro without it. The results show that the sized hybrid system meets load demand even considering ± 10% uncertainty. A North American site produces 4,069 kWh vs. 3,686 kWh of the energy required yearly; the Southeast Asian site produces 656 kWh vs. 607 kWh of the required; and the European site produces 12,982 kWh vs. 12548 kWh of the required, each considering −10% uncertainty.

The progress of technology in our current world continues to advance each day, benefiting human beings in various ways. One significant development in recent time is the emergency of automated vehicles, which have the potential to revolutionise transportation. These vehicles utilise electric power, sensors, cameras and sound navigators to carry out their intended operations without causing environmental pollution. Currently, there are several autonomous companies, primarily located in California, cities like San Francisco (Cruise), Palo Alto (Tesla), Fremont (Pony.ai), Santa Monica (Motional), Mountain View (Waymo), and Foster city (Zoox). This paper aims to review the utilisation level and performance of autonomous vehicles, specially focusing on the goals set for 2023. By analysing various research studies and company profiles, this paper aims to provide insights into the current status of autonomous vehicles and their practical applications. It employs quantitative and statistical methods to extract valuable information from these studies. Also, this paper examines the state of the art in autonomous vehicles and the impact of gaps in machine learning algorithms, from perception to execution. The data used for this study are obtained from research reviews and updated profile of different companies. The assessment reveals a significant increase in research and development activities related to autonomous and automated vehicles across various disciplines since 2010. Specifically, the number of research studies on autonomous driving vehicles has increased from 302 to 2718, while studies on automated vehicles have increased from 1379 to 6085. In the Engineering discipline alone, there have been 601 studies on autonomous driving vehicles and 341 studies on automated vehicle-related research, which have increased to 2685 and 1865, respectively in the specified time.

Fuel cell hybrid electric vehicles employ fuel cells along with batteries or ultracapacitors as power sources, and energy management systems can control their power split. This study investigates energy management strategies for lightweight plug-in extended-range fuel cell hybrid electric vehicles to optimise fuel economy, extend component lifespans, and enhance vehicle efficiency. Comparisons between power follower and dynamic programming-based strategies are conducted, focusing on incorporating PEMFC health constraints to prolong stack durability via on-off binary mode operation. Using the New European Driving Cycle, performance evaluation is conducted on a parallel architecture featuring a 16-kW motor, regenerative braking system, eight 420-Wh batteries in series, and six 1-kW fuel cell stacks. Dynamic programming strategies demonstrated potential improvements, with savings in hydrogen consumption of 62–72 L per driving cycle and SOC levels of 3.9%. Moreover, optimised battery lifespan enabled the system to achieve approximately 18,087 -18,745 charge/discharge cycles. Implementing PEMFC health constraints facilitated reductions in average accumulated active time to 205 seconds per driving cycle and startup/shutdown cycle frequency to 36.5 cycles per hour, promoting enhanced system durability and operational efficiency.

Coastal erosion presents a significant environmental threat globally, including in the Northern Java coastal area of Indonesia. As employing hard structures is not an environmentally sustainable practice, nature-based solutions, such as mangrove forests, have emerged as a global trend offering sustainable coastal protection. However, safeguarding young seedlings from wave and current forces remains challenging. Given that temporary structures, such as synthetic geo-bag dikes, considered for protection pose environmental challenges as they degrade slowly, the use of natural fibres such as ramie, unique to Indonesia as a strategic raw commodity, is a sustainable alternative. The study examined ramie fibres (0.28 mm thick) as an eco-friendly geo-bag material through laboratory tests, biodegradability burial tests, and comparisons with other natural fibres. Despite alkali treatment, the strength of ramie fibre did not meet standard geotextile parameters, and its degradability rendered it unsuitable for the expected service life. Ramie would need specific treatments to become a viable alternative for geo-bags. In conclusion, further research is needed to explore how ramie can serve as a sustainable geo-bag material.

To overcome the drawbacks of a single-stage evaporative cooler, an indirect-direct type evaporative cooler was proposed and fabricated. An alternative arrangement of mild steel plates wherein unmixed heat transfer occurs between air and water to form an indirect evaporative cooler. This is followed by a packing arrangement made of biomass-based coconut coir that forms a direct evaporative cooler. Experiments were conducted by varying the air and water flow rates, and the performance of the coconut coir was compared with that of a commercially available celdek packing. Experimental results indicated that a combination of an indirect-direct evaporative cooler helped cool air without an appreciable increase in air-specific humidity. The performance of the coconut coir is slightly lower than that of the Celdek coir in terms of the drop in DBT and wet-bulb effectiveness. A maximum wet bulb effectiveness of 0.78 and 0.63 was achieved for the celdek and coconut coir packings, respectively. The maximum performance was attained at an air velocity of 6 m/s and a water flow rate of 3 LPM. Owing to the different advantages of coconut coir over celdek packings, it is recommended to use coconut coir as an alternative packing in indirect-direct evaporative coolers.

The Maximum Power Point Tracking (MPPT) technique in the solar energy field optimises the performance of solar panels in different atmospheric conditions and variable loads. In this study, we present a new method that uses unsupervised learning (K-means clustering) to identify the atmospheric clusters of solar irradiance and cell temperature (G, T) and delimit homogeneous atmospheric zones or clusters to reduce the search space of the optimal parameters ([Formula: see text], [Formula: see text], and [Formula: see text]). The data collected for one year is segregated into 12 clusters; in every cluster, 04 regions are defined based on every cluster’s centroid ([Formula: see text], [Formula: see text]). A local search of the reference voltage/Duty cycle per cluster region is initiated for every sensed (G, T). Variable atmospheric conditions and resistive loads are tested. The results show that the efficiency of the DC/DC converter is 97.5% with a settling time (4.013 ms/5.577 ms) compared to the Perturb and Observe (P&O) the conventional tracking method and the Particle Swarm Optimisation (PSO), both applied locally inside a cluster and a deviation of 2% from the global maximum.

This study examines how green supply chain management (GSCM) in emerging markets affects firms’ waste disposal practices in Thailand’s dynamic economy. Using partial least squares structural equation modelling (PLS-SEM), we examined 320 Thai SMEs’ survey data to understand GSCM. The research reveals two key findings: A strong positive correlation exists between green supplier initiatives and green manufacturing processes, with suppliers’ sustainable efforts accounting for 27.2% of the variance in green practices (r-square = 0.272). This shows how much green supplier engagement affects manufacturing. Green distribution plays a significant role in promoting customer cooperation in the green economy, explaining 48.9% of the variance in customer engagement with sustainable practices (r-square = 0.489). Green supplier and distribution practices significantly impact waste disposal, but green manufacturing and customer cooperation fall short of anticipated impacts. Green supplier cooperation is essential for green manufacturing but does not directly lead to effective waste disposal, suggesting a disconnection and the potential for more integrated approaches. Green distribution helps meet customer demand for sustainable practices. This divergence suggests a potential oversight in GSCM implementation, emphasizing the need to integrate GSCM considerations into emerging market firms’ strategic frameworks and strategic policy interventions to improve waste disposal practices through GSCM adoption.

This study assessed the performance and emissions characteristics of a single cylinder, 2-stroke motorcycle spark ignition engine (Esoo 150 cc) utilising clay-catalytically produced distilled waste plastic pyrolysis oil (DWPPO) fuel. The clay catalyst and fuel properties were analysed using established standard testing procedures. The engine performance and exhaust gas emissions were determined for various fuel blends and compared with those of commercial gasoline at various parameters. Results showed that distilled pyrolysis fuel properties (kinematic-viscosity: 6.4 × 10–7 m2/s; caloric-value: 47.82 MJ/kg) were enhanced compared to kinematic viscosity of 1.92 × 10–6 m2/s and caloric value of 44.41 MJ/kg for Crude Waste Plastic Pyrolysis Oil. Notably, chemical composition of distilled fuel collected within a temperature range of 90°C-180°C closely resembled those of pure gasoline. It was also shown that 50% Distilled Waste Plastic Pyrolysis Oil (D50WPPO) significantly improved the brake power, brake thermal efficiency and reduction in brake specific fuel consumption while operating at full load conditions with various DWPPO-Gasoline blends and pure gasoline. Unburned hydrocarbon emissions reduced by 40% when the engine was fuelled with D50WPPO. The study concluded that DWPPO can potentially be employed as a substitute of conventional gasoline without any engine modifications.

ABSTRACTThe development of machines explores the development of a manufacturing system. This perspective offers challenges adjacent to the materials, the product that wants to be manufactured, the technical considerations that must be covered during implementation and the manner of delivering the products to the user. This article addresses the design and development of machines, on the one hand the redesign of a multifunctional platform, and on the other hand a 3D food printer. The second is emphasised, since its main objective is to help the food problems that exist today. The design phases, aspects considered for its implementation such as food safety, the choice of the substrate, the functionality of the food, transportation and the pre- and post-processes required. In this manner, the selection and innovation of materials constitutes a primary source of innovation and research in the integral development of a 3D food printer. The main source of value of these both cases lie in customisation. The experiences of a multidisciplinary research team in the development processes are compiled and the design and creation process are shown, in order to contribute to deal with design and development to tackle fundamental problems of society.

In response to concerns about depleting natural resources, organisations are developing eco-friendly products and services. This study examines the role of manufacturing industries and services in sustainable resource utilisation, focusing on the Micro, Small, Medium Enterprises (MSME) sector, a significant contributor to global Gross Domestic Product (GDP). Using Life Cycle Assessment (LCA) methodology, the research identifies hotspots within the production processes of three companies manufacturing bathroom fittings, specifically the ‘Wall mixer’ component used in households and hotels. The study calculates In response to concerns about depleting natural resources, organisations are developing eco-friendly products and services. This study examines the role of manufacturing industries and services in sustainable resource utilisation, focusing on the MSME sector, a significant contributor to global GDP. Using Life Cycle Assessment (LCA) methodology, the research identifies hotspots within the production processes of three companies manufacturing bathroom fittings, specifically the ‘Wall mixer’ component used in households and hotels. The study calculates CO2 equivalents for each phase of the product lifecycle, identifying average gate-to-gate process values across the companies. This comparison reveals specific hotspots, with a significant one identified, leading to recommendations for industries to prioritise this issue for immediate energy savings. The primary focus is to establish an initial benchmarking system to reduce CO2 equivalents in cradle-to-gate or gate-to-gate systems. Implementing these measures is expected to reduce the carbon footprint, energy consumption, and raw material usage, ultimately enhancing profitability for the three companies. equivalents for each phase of the product lifecycle, identifying average gate-to-gate process values across the companies. This comparison reveals specific hotspots, with a significant one identified, leading to recommendations for industries to prioritise this issue for immediate energy savings. The primary focus is to establish an initial benchmarking system to reduce CO2 equivalents in cradle-to-gate or gate-to-gate systems. Implementing these measures is expected to reduce the carbon footprint, energy consumption, and raw material usage, ultimately enhancing profitability for the three companies.

ABSTRACTPro-environmental behaviour is worth researching to understand the relationship between consumer behaviours and environmentally friendly consumptions. This research aims to investigate the impact of citizen science on pro-environmental citizenship behaviour when environmental attitude, environmental knowledge, and environmental awareness intermediaries in an emerging market like Thailand. The sample of 394 Thai citizens was collected from main provinces in different regions of Thailand, including Bangkok, Khon Kaen, Lamphun, and Phuket. PLS-SEM was employed to test the study hypotheses by applying the structural equation modelling approach to analyse the collected data. The main findings show that there was a positive impact of citizen science on citizen environmental attitude, citizen environmental awareness, and citizen environmental knowledge towards pro-environmental citizenship behaviour. The study also reveals that these mediated relationships play a pivotal role in translating environmental consciousness into actionable behaviours that support sustainable use and consumption. Furthermore, increased citizen environmental awareness plays a crucial role in recognising the urgency and importance of engaging in sustainable practices. Awareness acts as a catalyst, prompting individuals to reflect on their consumption patterns and lifestyle choices, ultimately leading to more environmentally friendly behaviours. Marketers may implement it with green marketing strategies by increasing more favourable to sustainable products within consumers.

Solid oxide fuel cells (SOFCs) could have great application potential and technological development. However, there are no studies that have quantitatively and rigorously estimated the environmental impacts in the future scenario. This study fills this gap through an innovative approach consisting of patent-based technological forecasting and prospective life cycle assessment (LCA). The analysis of the 58 selected patents reveals that future SOFCs could have (on average) +53% specific power which could lead to a 56% mass reduction compared to current SOFC. The prospective LCA shows an average global warming potential (GWP) reduction of 50%. The future tubular layout is more sustainable than planar one by about 15%. GWP decreases with increasing specific power and in cells with smaller sizes and thicknesses. Finally, the ductile future SOFCs, dedicated to mobile applications and dynamic loads, have a GWP greater than future stationary SOFCs, but still equal to half of the current SOFCs. All these results therefore confirm the potential of the patented SOFC developments on environmental sustainability, arguing in favour of their industrial development and a more massive application in the future.

ABSTRACTThe metallurgical industry simultaneously represents both one of the most crucial sectors of the industry and a sector with significant emissions. Alongside methods to mitigate the harmful impact on the environment, we need to consider reducing the hazardous, toxicological impact on the human organism. In this article, we explore the life cycle of two steel production methods: BF-BOF and EAF. The results of our research indicate that the EAF method has a lesser impact on the human organism. Our goal is to identify the key processes that constitute the primary source of emissions of hazardous substances in each of these two pathways. We investigated the distribution of the impact of production processes in each of the two aforementioned methods. In traditional steel production using oxygen converters, the primary source of emissions is the production of pig iron in blast furnaces. In the second case, it was the used electricity. For this study, we applied the LCA methodology, which enables determining the impact of the investigated process throughout its entire life cycle. In the conclusion, possible options for mitigating the harmful impact of each case are discussed.

ABSTRACTThis study presents the development of an event-driven hybrid control for position and force tracking applied on a mobile robotic manipulator for metal recycling tasks. The suggested controller operates in a sequenced strategy starting from a fixed spot, moving the mobile device towards a targeted zone ([Formula: see text]) from where the i-th piece-to-be-recycled is attainable (considering the arm manipulation). Once the event of entering the zone is completed, the mobile robot is fixed at a position, and the end-effector of the robotic arm is enforced towards the piece-to-be-recycled. When the end-effector touches the piece in a given spot ([Formula: see text]), the hybrid control changes to the force tracking intending to carry the piece towards the spot ([Formula: see text]) where it ill be processed. Each piece location is identified based on a vision-based system that applies deep learning tools using convolutional neural networks. A multi-physics numerical simulation illustrated the application of the developed controller in a realistic scenario, showing all the elements of the event-driven operation. To validate the suggested controller, the comparison with a robust control that works on a wide range of carrying mass confirms the operational improvement of the event-driven hybrid position and force design.

ABSTRACTThis study aimed to fabricate thin, porous layers of 17-4 PH stainless steel with a defined porosity using laser powder bed fusion (LPBF). The central composite design (CCD) approach was utilized to examine the effect of process parameters on porosity. Three different methods were employed to measure the porosity of 17-4 PH stainless steel samples, i.e. theoretical analysis, buoyancy, and X-ray computed tomography (X-CT). A statistical quadratic regression model is generated that correlates with LPBF parameters to forecast porosity with high prediction accuracy. The maximum obtained porosity is 51.25% ± 0.33% with a laser power of 60 W, a scanning speed of 1800 mm/s, and a hatch spacing of 0.115 mm, which resulted in an average pore size of 24.8 ± 0.38 µm. Permeability was also analysed, as the volume energy density decrease ranges from 19.30 to 14.22 J/mm3, the permeability coefficient increases from 1.39 to 9.41 × 10−11 m2. In addition, it is observed that the minimum energy density to fabricate the 17-4 PH SS with the highest porosity and free of defects and fragmentation is 14.2 J/mm3.

ABSTRACTSmartphones are indispensable tools for daily tasks; nevertheless, their short lifespan of about two years contributes to a disproportionate increase in environmental waste. Although current initiatives explore reusing specific smartphone components, such as metallic parts, the scope of these efforts still needs to be expanded, necessitating more comprehensive strategies to address the growing waste generation. Additionally, end-users play a pivotal role in determining the fate of obsolete smartphones and in adopting sustainable disposal practices to mitigate environmental damage after the devices are no longer useful to them. This proposal describes the scope to obtain a circular economy approach at a macro-level environmental impact. The strategy aims to employ obsolete smartphones while reducing environmental im pacts and facilitating efficient device disposal. The authors employ the S4 framework to support sustainable product development at a macro-level, emphasising sensing, smart, sustainability, and social dimensions. However, it is essential to note that the current solution applies only to smartphones with functional features, including intact displays, operational batteries, accessible cameras and sensors, and functional power systems, obtaining a level three according to the S4 framework, which describes limited human intervention.

ABSTRACTThe goal of this study is to create a dynamic model that can accurately forecast the estimated time of arrival of a bus at a specific bus stop using data obtained from the global positioning system (GPS) in Addis Ababa, Ethiopia. Both operators and customers use accurate and timely bus arrival information. In turn, it helps determine the correct placement of charging stations when green-energy vehicles are introduced in the urban mass transit system. A plethora of machine learning models have been used for prediction. Additionally, we tailored an ensemble method based on the average prediction. The performances of these machine learning methods were estimated and compared using conventional measures, such as Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and R-squared (R2) values. The results showed that the performance of the Random Forest technique used in this study was impressive, with MAE of 0.137, MSE of 0.054, RMSE of 0.233, and R2 value of 0. 999. The findings demonstrate that the proposed method is reliable for predicting the arrival times of urban and rural buses. Next, in order to position the charging points for Electric Vehicles (EV) along specific bus routes, self-organising map (SOM) is employed to optimise EV charging point placement locations, and the result signify better performance than the kNN and DBSCAN clustering approaches.

ABSTRACTBlending biodiesel at different ratios leads to fluctuations in properties such as oxygen content, cetane number, speed, density, and calorific value, affecting performance and emissions. Therefore, studying the combustion process of biodiesel is necessary. This study describes the construction of a CVCC (Constant volume combustion chamber) model to study the fuel combustion process and the impact of temperature on the characteristic parameters of the combustion process. Fuels used for simulations included diesel fuel and B10 biodiesel derived from palm oil. The calculated results from the model are compared with experimental data to verify, analyse, and evaluate the combustion process in CVCC. Analysis of the influence of combustion chamber temperature shows that increasing the temperature from 300K to 450K leads to a decrease in the mixing time of the mixture, a decrease in the spray length, an increase in the fuel evaporation rate, and the combustion process occurs. Faster, the peak pressure appears earlier and higher, and the heat transfer rate is faster. Pressure increases faster during the delayed combustion phase. At the same time, increasing the oxygen concentration from 10% to 20% also leads to an increase in pressure rate, reaching an earlier peak, and the combustion process occurs faster.

ABSTRACTWe introduce the innovative concept of Sustainable Laser Energy Consumption (SLEC, ε) that promotes sustainable metal additive manufacturing practices while maintaining productivity and tailored densification in the Selective Laser Melting (SLM) process. This study focuses on deriving analytical expressions through dimensional analysis and Buckingham’s π theorem to predict bulk density with high precision across studied materials: In718, W, AlSi10Mg, Ti6Al4V, and SS316L. This approach provides valuable insights and allows the setting of an appropriate combination of scanning speed and hatch distance for a range of laser power, enabling sustainable manufacturing of SLMed components with tailored density. Furthermore, the mathematical expression introduced as SLEC facilitates the tradeoff between energy consumption and productivity, promoting a greener and more sustainable future of metal additive manufacturing. Furthermore, the underlying fractal nature of SLM is explored through the investigation of the influence of fractal structures, present in the powder bed, on densification that provides information on how powder morphology and homogeneity (i.e. fractal dimension and lacunarity) of the powder bed are linked to a sustainable SLM process.

ABSTRACTThe use of electric cooking appliances, also referred to as eCooking devices, presents a practical and sustainable solution for achieving universal access to clean cooking facilities by 2030. A choice modelling analysis on the factors that influence the selection of an eCooker in Ghana has been conducted to facilitate market expansion for organisations seeking to offer clean cooking services. The study utilised Analytical Hierarchy Process (AHP), Fuzzy-TOPSIS, and Data Envelopment Analysis (DEA) methodologies to assess and rank electric cookers based on crucial factors such as kWh consumption rate, cooking efficiency, affordability, time-saving features, ergonomics, space utilisation capabilities, compatibility with cookware types, ease of cleaning and maintenance procedures, accessibility, among others. The rate of consumption was identified as the most critical factor, emphasising the significance of energy efficiency in the decision-making process. The analysis showed that the induction stove was optimal, considering both Fuzzy-TOPSIS and DEA evaluations. Although the induction stove may consume a considerable amount of electricity, its efficiency, performance, and other attributes make it the preferred choice. This study presents a systematic approach to assessing and ranking electric cooking stoves in Ghana, offering valuable insights for both consumers and policymakers.

ABSTRACTWith global supply chains facing increasing complexity and uncertainty, mitigating sustainable supply chain risks (SSCRs) has become an important research topic. Industry 5.0 (I5.0) is a supplement to, and re-development of, Industry 4.0, but no research on improving supply chain resilience (SCRE) through I5.0 drivers to mitigate SSCRs currently exists. Therefore, we developed a QFD approach to investigate the relationship between SSCRs, SCRE, and I5.0 drivers. This study utilises the FDM-FDISM-ANP-TOPSIS method, considers China’s largest private logistics enterprises as the object of empirical analysis, and establishes a sustainable supply chain identification system and SCRE evaluation index system for logistics enterprises through two-stage House of Quality. The findings reveal that 20 key I5.0 significantly bolster 17 SCRE, thereby mitigating 13 SSCRs by QFD-MCDM framework. These I5.0 drivers play a pivotal role in enhancing SCRE of logistics enterprises. This study contributes to the field of supply chain risk resilience in sustainable engineering by integrating the perspectives of SSCRs, SCRE and I5.0. It underscores the necessity for managers in logistics enterprises to develop SCRE solutions that incorporate both SSCRs and I5.0 considerations. Furthermore, our findings offer valuable insights for other industries aiming to bolster their supply chain competitive advantages in an increasingly complex global landscape.

ABSTRACTScientific advances and technological requirements to develop carbon fibre-reinforced polymers (CFRP) with excellent strength-to-weight ratios led to the high consumption of CFRP composites. The mechanical recycling of CFRP is a simpler, more economical, and environmentally responsible solution for effectively recovering this structural material that contains epoxy resin and carbon fibre. CFRP laminates were placed on a Computer Numerical Control (CNC) and milling cutting at 1100, 1800, and 2500 rpm. The recovered CFRP particles were mixed with acrylonitrile butadiene styrene (ABS) using the melt intercalation approach. Recovered CFRP particles increased the molecular mobility and reduced the thermal stability of ABS. The main differences between the ABS and the composites were a more pronounced necking region in the ABS than in the composites and a notable reduction in strain. The strain of the ABS was 27.58%, while in the composites, it was 4.29, 4.02, and 3.51%, depending on the cutting speed. Thus, ductility decreased up to 87% in the composites. This work’s successful CFRP mechanical recycling method provides epoxy powder, individual carbon fibres, and CFRP particles, opening a research field of great economic and environmental relevance in developing new materials.

ABSTRACTTechnologies from Industry 4.0 enhance human skills and capabilities in production. These advanced manufacturing and digital technologies unlock opportunities to integrate individuals with unique abilities into industrial environments, helping to attain social sustainability. However, the validation process with end-users in real-world manufacturing tasks ensures the technology is robust and aligned with individual needs. However, the topic is in its early stages, and only a few papers concerning validation have emerged in journals. This paper presents a systematic review utilising the PRISMA methodology to examine validated technologies proposed to empower differently-abled workers in the manufacturing sector. The supporting technologies were identified and sorted into four categories: collaborative robots, augmented reality, assistive technology, and gamification. Within the reviewed papers, quantitative and qualitative evidence emerged, showcasing how individuals with challenges proficiently employed technology to complete assembly tasks, elevate their working speed, and reduce the error rate. Nevertheless, there remains a lack of information concerning usability, intuitiveness, and ergonomic considerations. Furthermore, there’s an ongoing requirement for long-term studies, standardised methodologies, and statistical assessments conducted by a representative cross-section of participants. Beyond its influence on organisational social responsibility, this research aims to transcend the realm of cultivating a potential new workforce for manufacturing companies.

ABSTRACTThis study examines attitudes and perceptions towards biodegradable disposable products, as well as the willingness to pay for them in the southern region of Jalisco. Surveys were conducted among residents to explore their consumption patterns and the reasons influencing their purchasing decisions. The results highlight that only one in three individuals in this region shows a preference for biodegradable disposables, with a stronger inclination among women and those with higher educational levels. Despite a general interest in environmental preservation and a willingness to adopt biodegradable products, these factors were found to have no significant impact on the final purchasing decision. These findings suggest that governmental initiatives to promote the adoption of biodegradable disposables have not yet achieved significant adherence among the local population. This study provides valuable insights into current challenges in adopting sustainable practices and emphasises the need for more effective strategies to drive changes in consumer behaviour in the region.

ABSTRACTThe concept of Industry 4.0, as a means to move forward in the industrial ecosystem, has reached an important turning point. Where do we stand now in terms of industrial innovation and transition? This opinion paper provides an overview of the situation in the Netherlands, a reflection on what has been achieved by the Industry 4.0 paradigm, and the necessary way forward to solidify its implementation. Tentative results reveal that the pervasiveness of Industry 4.0 applications is sector-specific. This work provides industrial stakeholders and academics with useful suggestions and a possible path to move towards better integration of Industry 4.0 in company reality. In this opinion paper, we employ a mixed methods research methodology to argue that, based on our findings on industrial adaptation in The Netherlands, Industry 4.0 is the outcome of an evolutionary process and not of a revolution, as it is often claimed.

ABSTRACTA substantial amount of wastewater is generated during the extraction of oil and gas. Wastewater that is generated as a result of oil and gas extraction activities is known as produced water (PW), and managing PW is one of the greatest challenges faced by the oil and gas industry. Effective management of PW requires an understanding of the complex impact it may have on both oil production and water treatment operations. Here, a numerical model has been applied to a real-world case study, that of Kuwait Oil Company (KOC), to examine the relationships among various input and output factors in PW supply chain management. Specifically, the numerical model is a multi-objective optimisation model for the management of PW supply chains that takes into account economic as well as environmental objectives. A global sensitivity analysis has also been performed to assess the economic and operational factors that can influence the management of PW in KOC. The findings of this study show that the operational costs, treatment costs and environmental impacts can be assessed and used to guide the management of the PW supply chain in KOC.

ABSTRACTEthiopia has the potential to be 100% renewable. Its renewables are capable to solve its energy poverty and energy shortage in East Africa. The country’s climate resilient green economy strategy considers energy as key enabler for vibrant economy. The objective of this paper is to identify key challenges of the energy sector by studying 12 years of electricity generation data, 2012 to 2023, and to analyze the sector’s performance with a special emphasis on hydropower. In this study, both quantitative and qualitative methods were employed to draw performances indicators. The quantitative results showed that the country achieved 30% of its energy development plan with a deteriorating performance from 94% to 40%. This performance works for hydropower too, which dominants the electricity development and supply. The declining performance comes from government’s monopoly in the sector, financial deficit due to ongoing internal crises and technical unavailability of power plants. This performance has greatly influenced expansion of industries, access to electricity, unemployment, and other economic activities. The authors advise the government, stakeholders, and development partners to consider the recommendations given in this paper to boost the energy sector development and keep the country in healthy economic pace by all measures.

ABSTRACTManaging sustainable and digital transformations in the water industry is a challenge. The identification of freshwater resources for green hydrogen production is necessary for the energy transition away from fossil fuels such as oil and gas. This can be achieved through the sustainable flood retention basin (SFRB) concept for identifying optimal locations for the retention of surface water. This unbiased concept helps in conflict resolution between stakeholders with water rights. Moreover, it serves as a simple tool to produce a digital water supply atlas based on dimensionless parameters with the short names’ population density, location advantage, precipitation, groundwater level, water rights, SFRB, excess running water and proximity to networks. While the first five parameters can be determined during a desk study, the last three parameters require site visits for verification purposes. Germany was used as a representative case study country to demonstrate the proposed methodology to obtain a water atlas based on mapped weighted values. The Kaiserstuhl in Germany served as a worked calculation example indicating well above average potential for water storage using existing retention basins. The water atlas can be used to supplement a (green) hydrogen atlas, supporting decision-makers in building hydrogen infrastructure.

ABSTRACTThis study analyzes the impact of energy efficiency and renewable energy use on carbon emissions in G7 countries. The period examined covers the years 1971–2023. There are two important results. The first is the cointegration relationship between the variables. Accordingly, there is a long-run cointegration relationship between energy efficiency, renewable energy use and carbon emissions. The second is the direction and strength of this long-run relationship. When energy efficiency increases, carbon emissions decrease. This result is consistent with general expectations. On the other hand, there is a positive relationship between renewable energy consumption and carbon emissions. This result is not consistent with general expectations. The existence of a positive relationship between renewable energy consumption and carbon emissions is an issue that needs to be discussed.

ABSTRACTVehicle safety relies on the capacity of vehicle systems to decrease the likelihood of biomechanical injuries to both vehicle occupants and pedestrians. This can take the form of active or passive measures applied to the materials and their geometry in the event of an impact. Nevertheless, due to the nonlinear behaviour of materials and deformation, a distinct collapse process emerges that requires analysis; this analysis can be virtual or through experimental tests. While observed performance can be ascertained through experimental designs, executing such a design for every parameter combination can be time-consuming and costly. This study employs a Long Short-Term Memory (LSTM) to predict the energy absorbed and crushing force of thin-walled aluminium 6063 T5 tubes subject to different collapse triggers and heat treatments. The LSTM model is constructed using experimental data derived from experiments that consider trigger shape, area, trigger position, furnace duration, cooling temperature, and heat treatment soaking method. The LSTM model achieved a Root Mean Square Error (RSME) of 0.56 and 0.0025 for crushing force and energy absorption, respectively. LSTM proves to be a valuable tool for predicting results in nonlinear analysis, particularly in the context of crush behaviour. Also, a comparison of the LSTM and finite element analysis (FEA) predictive performance is presented.

ABSTRACTAdditive Manufacturing (AM) processes have the capability to promote a more rational use of resources, reduce generated waste, as well as repair damaged components to extend their lifespan. With the aim of contributing to a more efficient and environmentally friendlier manufacturing process, this research work investigates the energy consumption of the Laser Directed Energy Deposition process (DED-LB) through the introduction of new parameters in its characterisation, which are energy and mass efficiency. First, the energy efficiency of the laser generator itself has been characterised. Based on the results obtained, it was possible to conclude that pulsed laser operation strategies allow a reduction in consumption of up to 9% compared to a continuous laser operation mode. Second, a design of experiments was carried out to relate the energy and mass efficiency of the deposition process to the input parameters: laser power, feed rate, and mass rate. The parameter that most influences the energy efficiency of the process is the mass rate, where high rates are advisable to maximise its value. On the other hand, it is concluded that an increase in the mass rate or a reduction in the feed rate results in an increase in the mass efficiency

ABSTRACTThe growing diversity and volume of e-waste products are emerging as significant and complex challenges from environmental, economic, and recycling perspectives. This surge not only hampers the effective management and conservation of precious resources and strategically important materials (SIMs) but also intensifies the problem. Addressing this pressing global issue necessitates a holistic and intelligent decision-making model capable of effortlessly handling the vast variety and volume of e-waste products. This paper introduces a novel multi-criteria decision support system (DSS) that combines AI visual recognition with a multi-fuzzy model to precisely determine the optimal End-of-Life (EoL) recovery route. Additionally, the functionality of the proposed DSS is showcased through a pilot implementation and case study examples, emphasising the advantages of a fully automated, reliable, and efficient EoL management for e-waste.

ABSTRACTThe study examines changes in the role of CEE, Germany and China in cross-sectoral connections. The paper aims to understand the flows in the servitization of manufacturing among three economies. It tried to answer the question of how strong links are in the servitization of manufacturing and whether there are any visible trends in value-added flows within this triangle.

ABSTRACTThe use of non-toxic and eco-friendly natural dyes on textiles has received much attention due to the increased environmental awareness to avoid some hazardous synthetic dyes. In the present study, an eco-friendly approach was developed to impart colour and antibacterial properties to cotton fabrics dyed with Justicia schimperiana leaf extract as a non-toxic natural colourant. The solvent method of extraction and exhaust dyeing method was used for this study. Copper sulphate, ferrous sulphate, and alum were applied in a simultaneous -mordanting process as a mordanting agent. The effects of shade percentage, dyeing temperature, and dyeing time on the obtained colour strength of the fabrics were investigated. Optimisation of dyeing conditions was carried out using Box Behnken design of expert software. An optimum level of 3. 28 colour strength (K/S) was observed in the sample treated with a shade percentage of 50 (% o.w.f), 72 °C dyeing temperature, and 45 minutes of dyeing time. Antibacterial properties of treated fabrics were evaluated against common pathogenic bacteria, Staphylococcus aureus (Gram-positive) and Escherichia coli (Gram-negative). The results indicated the treated fabrics possessed desirable antibacterial properties. The washing and rubbing fastness of the dyed fabrics were also reported.