Improve Process Performance Research Articles

Anaerobic sludge digestion enhancement with bioelectrochemical and electrically conductive materials augmentation: a state of the art review.

Excess biological sludge processing and disposal have a significant impact on the energy balance and economics of wastewater treatment operations, and on receiving environments. Anaerobic digestion is probably the most widespread in-plant sludge processing method globally, since it stabilizes and converts biosolids organic matter into biogas, allowing partial recovery of their embedded chemical energy. A considerable number of studies concerning applicable techniques to improve biogas production, both in quantity and quality, include pre-treatment strategies to promote biosolids disintegration aimed at the release and solubilisation of intracellular energy compounds, inorganic/biological amendments aimed at improving process performance, and sludge thermal pre-treatment. As for in-process amendments, iron, micro and macro-nutrients, ashes from waste incineration and nanoparticles addition have been studied for the improvement of enzymatic reactions. Recently, use of electrically conductive materials has been credited with the possibility to accelerate and stabilize the conversion of organic substrates to methane. The possibility of increasing both biogas generation and its relative biomethane content by interfacing anaerobic digestion with bioelectrochemical systems was also postulated. This review addresses the research gap surrounding the integration of anaerobic digestion with novel technologies, particularly bioelectrochemical systems, to enhance biogas production and methane enrichment. While existing studies focus on pre-treatment and in-process amendments, the feasibility, mechanisms, and benefits of such integration remain underexplored. By critically evaluating the current state of the art, this review identifies the potential of bioelectrochemical integration to improve energy recovery and process stability, while highlighting key challenges and research needs for advancing these technologies toward practical implementation.

Comparative analysis of the wear behaviour of TiN/TiAlN, TiAlVN, and TiAlYN coated tools in milling operations of Inconel 718

Abstract Milling is widely used in the aeronautical and aerospace industries, due to the possibility of producing parts with good dimensional stability and surface quality. Because of its exceptional mechanical qualities and limited thermal conductivity, Inconel 718 is a nickel superalloy that is regarded as a challenging material to process. Due to the flexibility of milling, this is the most commonly used process for machining INCONEL alloys. However, high levels of tool wear can be observed. Coatings can be deposited on the cutting tools to improve process performance. Nonetheless, doping elements such as yttrium and vanadium when added to TiAlN-based coatings can increase the coating's resistance. Furthermore, multilayer coatings tend to be very promising resistance to crack propagation. Thus, this work intends to compare three coatings deposited via PVD, in terms of the quality of the machined surface and wear resulting from the process: TiAlVN, TiAlYN, and TiN/TiAlN. The cutting speed (Vc), feed per tooth (fz), and cutting length (Lcut) were varied. It was possible to verify that the multilayer coating had better results, in terms of average roughness (Ra) and in measuring wear (VB3) and its characterisation. On the other hand, the TiAlVN coating showed the worst results. It was concluded that due to the TiN layer, the TiN/TiAlN coating has better resistance to crack propagation, as its adhesion to the substrate is good and there is no delamination.

Synthesis of Black Seed Oil-loaded-, Alginate-based, pH-sensitive Beads Using Electrospraying Technique.

Black seed oil (BSO), derived from the seeds of the Nigella sativa plant, has garnered attention for its potential anti-cancer properties, particularly in the context of colon cancer. Its active compound, thymoquinone, may help inhibit cancer cell growth and induce apoptosis in colon cancer cells. Additionally, black seed oil's anti-inflammatory and antioxidant effects could contribute to a healthier gut environment, potentially reducing cancer risk. Therefore, this study synthesized pH-sensitive alginate beads to deliver BSO into the colon in a controlled-release manner without releasing the drug at pH 1.2 (stomach), thus providing a well-defined release pattern at pH 6.8. The use of electrospray technology improves process performance by making it easier to formulate small, homogeneous beads with a higher rate of swelling and diffusion in the gastrointestinal medium. The formulated beads were characterized by an ex-vivo mucoadhesive strength test, bead size, sphericity factor (SF), encapsulation efficiency (EE), scanning electron microscope (SEM), in vitro swelling behavior (SB), and in vitro drug release in acidic and buffer media. All these manufactured beads demonstrated modest sizes of 0.58 ± 0.01 mm and spherical shape of 0.03 ± 0.00 mm in this testing. The formulation showed promising floating and releasing properties in vitro. With a very low cumulative percentage of beads, the oil EE of 90.13% ± 0.93% was high, and the release study demonstrated more than 90% in pH 6.8 with good floating nature in the stomach. Additionally, the beads were evenly spaced throughout the intestine. The electrospraying approach used in this protocol can be reproducible, yielding consistent outcomes. Therefore, this protocol can be used for large-scale production for commercialization purposes.

Research on wire electrochemical micromachining with a unidirectional traveling wire and horizontal electrolyte flushing

Wire electrochemical micromachining (WECMM) technology is well-suited for the processing of small parts, offering advantages such as high machining accuracy and the absence of a recast layer on the machined surface. However, the narrow width of the slit in WECMM makes the removal of electrolytic products a challenging process, which in turn results in a reduction in processing efficiency. To address this challenge, this paper proposes WECMM with a unidirectional traveling wire and horizontal electrolyte flushing. This approach aims to enhance the mass transfer efficiency of WECMM through the use of a unidirectional traveling wire, thereby optimizing the processing efficiency of WECMM. The experiment was conducted on 510 µm thick 9Cr18Mo stainless steel using 15 µm tungsten wire as the cathode. The experimental results demonstrate that the maximum feed rate (MFR) of a unidirectional traveling wire WECMM can reach 3.6 µm/s, thereby achieving comprehensive improvement in processing performance. Ultimately, two kinds of intricate microstructures based on four-layer workpieces were fabricated, resulting in a surface roughness Ra of only 0.052 µm.

Optimizing Milling Processes through FEA: An In-depth Analysis of Cutting Tool Geometric Parameters and Their Impact on Performance of milling.

Abstract In the rapidly advancing world of manufacturing, the optimization of cutting processes is of paramount importance for enhancing efficiency and product quality. This work underscores the necessity of employing Finite Element Analysis (FEM) for a comprehensive understanding and improvement of cutting processes. By leveraging DEFORM we create a detailed 2D simulation of the milling process, allowing for an unprecedented inspection of the procedure in a virtual environment. Central to our investigation is the variation of geometric parameters of the cutting tool within the FEM simulation model, offering insights into how minute alterations can significantly affect the outcome of the milling process. The study systematically analyzes the impact of the milling tool’s geometric parameters on various process parameters, including chip formation and cutting forces. This analysis is critical for identifying optimization opportunities in tool design and process settings. Furthermore, we delve into the stress-strain state of the cutting zone, a factor crucial for understanding the material behavior under operational conditions and ensuring the structural integrity of the final product. Through our findings, we demonstrate that strategic modifications in the geometric parameters of the cutting tool can lead to substantial improvements in process performance. This research not only contributes to the body of knowledge on milling processes but also provides practical recommendations for engineers and manufacturers striving to optimize their cutting operations through the application of FEM.

Industry 4.0 and Sustainability: Analysis of Impacts and Proposed Guidelines

Objective: To survey the impacts of implementing new technologies with the Industry 4.0 concept in a large building materials and related products company and propose sustainable guidelines to minimize negative impacts. Theoretical Framework: Industry 4.0 technologies provide improvements in the product manufacturing process and industry performance through the use of data, but it is necessary to consider the integration of business with social, environmental and governance issues. Method: The methodological approach is a single case study, qualitative in nature, applied and exploratory in purpose. In developing the method, a list of impacts caused by the implementation of Industry 4.0 technologies was created from the theoretical framework, which gave rise to a questionnaire applied to the building materials and related products company by means of a field survey. Results and Discussion: 11 impacts were “observed” by the interviewee, 45 impacts, i.e. the majority of them, were classified as “not observed” and 10 impacts were considered to be “not applicable” to existing technologies due to the fact that the company is a retailer. After analyzing the impacts, sustainable guidelines were suggested for each negative impact. Research Implications: It can be concluded that in most of the literature searched, the economic pillar of sustainability was the most commonly found, thus highlighting the lack of analysis focused on environmental and social issues in the implementation of Industry 4.0 technology in the building materials industry. Originality/Value: It was observed that with regard to sustainability, the building materials and related products company has several very important practices, however, no studies applied to other companies were found in the scientific literature, a fact that makes the proposed work very important.

Preparation of low-sensitivity explosive composite spheres via oil-in-oil emulsion

In order to reduce mechanical sensitivity and improve process performance of TKX-50, spherical TKX-50/TATB composite was prepared via the oil-in-oil emulsion method with TKX-50 (Dihydroxylammonium 5,5′-bistetrazole-1,1′-diolate) and TATB (1,3,5-triamino-2,4,6-trinitrobenzene) as raw materials. Based on the experimental results, the ideal circumstances for the emulsion to stabilize were obtained. The SEM results of spherical TKX-50/TATB composite exhibited an excellent spherical structure and size distribution. Furthermore, the SEM, XRD, and FT-IR results of spherical TKX-50/TATB composite demonstrated composite effect of the two basic materials was good. Compared to raw TKX-50 and TATB, the activation energies of spherical TKX-50/TATB composite decreased by 32.75 kJ mol−1 and 33.61 kJ mol−1, respectively. The TKX-50/TATB physical mixture was compared with spherical TKX-50/TATB composite, which had a higher bulk density and flowability. The impact sensitivity H50 of spherical TKX-50/TATB composite was 66.1 cm, which was 50.6 cm higher than that of raw TKX-50, and its friction sensitivity was reduced from 32 % to 24 % compared with that of raw TKX-50.

Organizational performance evaluation and management of processes: a s systemic analysis

To analyze how the articles that take the processes into account evaluate the contexts that they propose to improve and then to point out ways in that research field. This qualitative research using secondary data has used the Knowledge Development Process - Constructivist (PROKNOW-C) as a structured way of searching scientific articles and, under the constructivist performance evaluation view, analyze the articles.18 articles were pointed as adhered to the research which involved performance evaluation and improvement of processes in a universe of 5,183 international articles, dispersed in 5 databases. When analyzing the 18 articles, it was concluded that half of them were using generic approaches with application in specific contexts. For the remaining articles, it was noticed that few works use cardinal scales and a model that allows the integration between the criteria used. Finally, it was observed how the improvement of processes is performed in the light of performance evaluation. The research contemplated a universe of articles in 5 databases: Isiknowledge, Scopus, Ebsco, Emerald and Willey. A status quo analysis of how the set of 18 articles performs the performance evaluation was carried out and it was given continuity of how the works using process improvement can take into account the performance evaluation.

Multiple deep learning by majority-vote to classify haploid and diploid maize seeds

The maize plant is a crucial global staple, integral to food security. To ensure sustainable maize production, the development of high-yielding and resilient maize varieties is essential. This study proposes a majority voting-based decision support system for classifying haploid and diploid maize seeds using deep features from Convolutional Neural Networks (CNNs). Key variables include the accuracy, sensitivity, specificity, F-score, and Matthew's correlation coefficient (MCC) of the classification models. Experimental results showed impressive performance with accuracy, sensitivity, specificity, F-score, and MCC values of 90.96 %, 94.53 %, 86.40 %, 92.15 %, and 81.96 %, respectively. These results underscore the efficiency of the proposed method in accurately distinguishing between haploid and diploid seeds. The implementation of this decision support system in agricultural practices can significantly reduce the labour-intensive and time-consuming task of manual seed classification by experts. This system provides a cost-effective solution compared to existing expensive and complex methods, enhancing productivity, quality, and sustainability in maize breeding programmes. The ability to rapidly and accurately identify haploid seeds accelerates the breeding process, contributing to the development of new maize varieties with desirable traits such as higher yields and disease resistance. Future research should explore the integration of this decision support system with automation and robotics to further streamline the seed classification process. Additionally, investigating the applicability of this approach to other crops could broaden its impact. Further studies should also focus on enhancing the resolution of maize seed images and utilising more advanced hardware to improve processing performance. Finally, expanding the dataset with diverse maize varieties could refine the model's accuracy and generalisability.

Enhancing automated fiber placement process monitoring and quality inspection: A hybrid thermal vision based framework

Automated Fiber Placement (AFP) has revolutionized composite manufacturing, yet quality assurance remains challenging due to the significant impact of emerging defects on part quality and the current reliance on time-consuming manual inspection protocols. This paper presents a comprehensive hybrid framework that enhances AFP process monitoring and quality inspection by integrating thermal vision with innovative methodologies. Our framework combines model-based and data-driven algorithms across three modules to address key AFP inspection tasks, including in-situ monitoring, dynamic tow identification, defect detection, segmentation, localization, and quantitative lay-up quality evaluation. The setup-independent spatial–temporal analysis algorithm estimates tow boundaries with sub-pixel accuracy. An optimized SVM classifier, trained on an extensive AFP defect database, achieves a defect detection accuracy of 96.4% and an F1-score of 96.43%, meeting industry standards. The active contours-based segmentation and localization module provides critical qualitative traits such as defect shape, size, and location. Moreover, the novel Defect Area Percentage (DAP) metric enables precise quantitative defect impact evaluation at both the course and tow levels. By consolidating qualitative and quantitative outcomes, the system offers real-time high-level feedback for informed decision-making, significantly improving process performance and reducing machine downtimes. This proactive approach advances AFP process monitoring and quality inspection and positions our framework as a promising solution for next-generation composite manufacturing.

Hospital process performance and the adoption of medical devices: An organization-based view.

Over the past two decades, there has been a growing scholarly interest in the adoption of technology in healthcare. While numerous studies have delved into the effects of specific technologies on the performance of different organizational units and medical specialties, the findings have often been divergent. Unlike the established literature, our approach focuses on the organization's perspective to analyze how technology impacts process performance in hospital settings. More precisely, we compiled a tailored dataset from 56 healthcare organizations in Italy and conducted a comprehensive analysis of panel data from 2016 to 2019, utilizing Ordinary Least Squares (OLS) regression as our main analytical tool. The data shows a clear relationship between an organization's use of medical devices and its overall process performance. Our research highlights the importance of achieving substantial improvements in process performance by strategically integrating new technologies and devices. Policymakers are encouraged to consider introducing incentives to drive hospitals to invest in innovative technologies. Furthermore, monitoring expenditures on new devices could serve as a valuable metric for assessing the extent of technology adoption within clinical practices.

Nutrients removal in overloaded WWTP by intermittently aerated IFAS: Effects of biofilm carrier and intermittent aeration cycle

Updating of the current Urban Waste Water Treatment Directive (91/271/EEC) will demand stricter regulations for nutrients removal. In this frame, wastewater treatment plants (WWTPs) of small-to-medium potential will face new challenges for achieving process intensification. Integrating intermittent aeration (IA) and integrated fixed-film activated sludge (IFAS) technologies could be a promising solution to meet such requirements. This study analyzed how IA cycles affected nutrients removal in IFAS reactors with different biofilm carriers (e.g., plastic and sponge media). The plants responses to different carbon/nitrogen/phosphorous (C/N/P) ratios were evaluated while operating under low sludge retention time (SRT) to simulate overloaded conditions.A short IA cycle (1 h) with an aeration/not aeration ratio of 2:1 enabled high organic carbon and nitrification performances when operating at high C/N/P (11.8/1/1), whereas low denitrification and phosphorous removal yields were obtained because of the short not-aerated phase. Decreasing C/N ratio (8.8/1/1) without changing the IA cycle resulted in nitrification worsening because of the reduced metabolic kinetics of biofilm. Under such load conditions, a higher IA cycle (2 h) was necessary to improve process performance. A longer not-aerated phase was also positive for denitrification and phosphorous removal because of the establishment of anoxic and anaerobic environments within the bulk and inner biofilm layers. Besides, results suggested that sponge carriers offered advantages over plastic ones, enabling a higher biofilm retention capacity, better nutrient removal, as well as robustness and resilience to operating condition changes. This would result in simpler management systems for implementing the IA process, thus reducing process complexity and costs.

Decoding the task specificity of post-error adjustments: Features and determinants

Errors typically trigger post-error adjustments aimed at improving subsequent reactions within a single task, but little work has focused on whether these adjustments are task-general or task-specific across different tasks. We collected behavioral and electrophysiological (EEG) data when participants performed a psychological refractory period paradigm. This paradigm required them to complete Task 1 and Task 2 separated by a variable stimulus onset asynchrony (SOA). Behaviorally, post-error slowing and post-error accuracy exhibited task-general features at short SOAs but some task-specific features at long SOAs. EEG results manifest that task-general adjustments had a short-lived effect, whereas task-specific adjustments were long-lasting. Moreover, error awareness specifically conduced to the improvement of subsequent sensory processing and behavior performance in Task 1 (the task where errors occurred). These findings demonstrate that post-error adjustments rely on both transient, task-general interference and longer-lasting, task-specific control mechanisms simultaneously, with error awareness playing a crucial role in determining these mechanisms. We further discuss the contribution of central resources to the task specificity of post-error adjustments.

High-resolution 3D printable inks based on functional polymeric ionic liquids for applications in carbon dioxide valorization

This study investigates the use of epoxy-functionalized acrylate-based 3D printable ink for creating high-resolution functionalized devices, exploring the possibility to further functionalize those for chemical engineering applications. In fact, the control of the epoxy-functionalized surface enables the formation of active surfaces, and this study employs supported Ionic Liquids with catalytic properties as a proof of concept. Ionic liquids (ILs) and polymeric derivatives represent a promising path to generate multifunctional complex 3D structures, playing advanced roles in multiple applications. The fine-tuning of the functionalization methodology and formulation enhances the resolution of acrylate-based resins, allowing the production of highly detailed structures that can significantly boost catalytic efficiency. Through a comparison with commercial resins, the developed formulation demonstrates superior resolution capabilities, positioning it as an effective alternative for use in vat photopolymerization technologies. Additionally, controlling the level of functionalization and accessibility of the ILs' active sites through the control of the surface area of the reactor has led to improved process performance in terms of yield and space-time yield (STY) in the CO2 cycloaddition to epoxide reaction.

Well-designed flame retardants for epoxy resin composites that simultaneously improve heat resistance, mechanical properties and fire safety

Epoxy resin (EP) flammability severely limits its application in some industrial fields, while flame retardant epoxy resin (FREP) often suffers from the problem of not being able to balance flame retardant properties with mechanical properties. To solve the problem, in this work, HDP, a reactive flame retardant was succeeded in synthesizing by the one-pot method using protocatechuic aldehyde (PH), 2,4-diamino-6-phenyl-1,3,5-triazine (DPT), and 9,10-dihydro-9-oxa-10-phosphaphenanthrene-10-oxide (DOPO) as reactive monomers, was used to improve the flame retardancy of EP. And evaluated the effect of HDP on the curing reaction, heat resistance and mechanical property of EP. The introduced of four phenolic hydroxyl groups and two secondary amine groups enhanced the compatibility of the flame retardant HDP in EP and improved process performance. The apparent activation energy (Ec) was reduced by 8.1 %, facilitating the curing of EP/DDM. When 5 wt% of HDP (with only 0.36 wt% phosphorus content) was added to EP, the flexural strength and modulus of FREP increased by 21.0 % and 14.9 %, respectively, and the Tg increased by 9.0 % compared to EP. Cone calorimeter test (CCT) data showed that compared to EP, samples of EP/HDP-5 showed a 14.5 % and 21.6 % reduction in total heat release (THR) and total smoke production (TSP), respectively, and a 13.7 % increase in coke yield (CY). EP/HDP-5 has a high limited oxygen index (32.5 %) and passes the UL-94 V-0 classification. The excellent char formation and flame retardancy was owed to the dual role of the condensed and gas phases of FREP in the combustion process.

A Review on Laser Beam Shaping Application in Laser Powder Bed Fusion

Laser powder bed fusion (L‐PBF) is extensively adopted in the aerospace and automobile industries for producing metallic components. The L‐PBF process involves rapid melting and solidification of metallic powders using a laser source to produce dense parts. Most industrial L‐PBF systems use a fiber‐based laser source that emits a Gaussian beam distribution. However, the conventional Gaussian beam used in L‐PBF processes presents inherent limitations that can impact the quality and properties of the final products. This review aims to provide a theoretical background of laser beam shaping techniques and explores the application of alternative beam shapes in L‐PBF. It investigates how different beam profiles affect the melt pool geometry, process stability, productivity, mechanical properties, microstructure, and surface roughness of fabricated parts. Additionally, it discusses different types of beam‐shaping techniques and elements utilized to generate distinct beam shapes. Furthermore, different constraints and limitations that hinder the full exploitation of beam shaping are critically discussed. By analyzing the impact of beam shaping in L‐PBF, this review provides insight into optimizing the AM process, enhancing part quality, and improving processing performance. It will also help readers to overview the research gaps, challenges, and promising future directions in laser beam shaping applications in L‐PBF.This review comprehensively covers and presents the current research trend of laser beam shaping applications in L‐PBF. It delves into the opportunities, challenges, limitations, and futures prospects of beam shaping applications. Furthermore, presents the methods and techniques used to modulate the laser beam profile, including spatial and temporal.This article is protected by copyright. All rights reserved.

Periodic on-off operations of the self-cycling ethanol fermentation process: Stability analysis and optimal operation strategies

Fuel ethanol is highlighted for being renewable and carbon neutral, but a multi-scale challenge exists that hampers its role as a future energy substitute, and with the breakthrough of cellulose pretreatment and enzyme hydrolysis technology, fermentation itself has become one of the main limiting factors for process enhancement. To tackle the problem, this paper studies periodic operation strategies to improve process performance and avoid possible instabilities. Firstly, superiority by periodic operation over the corresponding steady-state operation is verified. Then, to settle the problem of possible instabilities under impulsive control, stability of state-impulsive control is conducted and for the studied case, any self-cycling fermentation starts from batch mode with 50 % discharge-and-refill portion exhibits superior repeatability property, which allows continuous fermentation to operate under very slow overall dilution rate to cope with the extreme slow fermentation rate. Finally, on-off operation problem is formulated that is governed by a multidimensional nonlinear system, affine to the manipulated variable that is under the isoperimetric constraint; with the use of Pontryagin maximum principle, the optimal synthesis of the optimal strategies under integral constraint is computed out, and a practically plausible on-off operation strategy for ethanol fermentation is formulated with guaranteed periodic stability and optimality.

Improving big data analytics data processing speed through map reduce scheduling and replica placement with HDFS using genetic optimization techniques

Big Data Analytics (BDA) is an unavoidable technique in today’s digital world for dealing with massive amounts of digital data generated by online and internet sources. It is kept in repositories for data processing via cluster nodes that are distributed throughout the wider network. Because of its magnitude and real-time creation, big data processing faces challenges with latency and throughput. Modern systems such as Hadoop and SPARK manage large amounts of data with their HDFS, Map Reduce, and In-Memory analytics approaches, but the migration cost is higher than usual. With Genetic Algorithm-based Optimization (GABO), Map Reduce Scheduling (MRS) and Data Replication have provided answers to this challenge. With multi objective solutions provided by Genetic Algorithm, resource utilization and node availability improve processing performance in large data environments. This work develops a novel creative strategy for enhancing data processing performance in big data analytics called Map Reduce Scheduling Based Non-Dominated Sorting Genetic Algorithm (MRSNSGA). The Hadoop-Map Reduce paradigm handles the placement of data in distributed blocks as a chunk and their scheduling among the cluster nodes in a wider network. Best fit solutions with high latency and low accessing time are extracted from the findings of various objective solutions. Experiments were carried out as a simulation with several inputs of varied location node data and cluster racks. Finally, the results show that the speed of data processing in big data analytics was enhanced by 30–35% over previous methodologies. Optimization approaches developed to locate the best solutions from multi-objective solutions at a rate of 24–30% among cluster nodes.

Enhancing Efficiency and Stability in Carbon-Based Perovskite Solar Cells by Double Passivation with Ultralow-Cost Coal-Derived Graphene and Its Derivatives.

Coal-derived carbon nanomaterials possess numerous superior features compared to other classic carbon, such as readily accessible surfaces, tunable pore structure, and facile and precise surface functionalization. Therefore, the controllable preparation of coal-derived carbon nanomaterials is anticipated to be of great significance for the performance improvement and commercialization process of carbon-based perovskite solar cells (C-PSCs). In this study, we successfully synthesized highly stable and commercially valuable graphene oxide (GO) and reduced graphene oxide (rGO) utilizing coal. Compared to traditional methods and commercial graphene, the chemical oxidation and pyrolysis process used in this study is mild and simple, offering the advantages of controlled composition and the absence of other impurities. GO or rGO was incorporated into the top of the SnO2 electron transport layer (ETL) of C-PSCs. Under optimized conditions and ultraviolet-ozone (UVO) irradiation, the ultimate power conversion efficiency (PCE) increased from the unmodified 12.4 to 14.04% (based on rGO) and 15.18% (based on GO), representing improvements of 22 and 31%, respectively. The improved photovoltaic performance is mainly owing to enhanced charge transport capabilities, denser interfacial contacts, improved carrier separation properties, increased conductivity, and abundance of hydrophilic functional groups in GO, which can form more stable hydrogen bonds with SnO2. After being stored at room temperature and ambient humidity for 30 days, the modified, unpacked devices retained 87% of the highest power conversion efficiency (PCE). This study introduces a practical and manageable method to enhance the performance of C-PSCs by using functional carbon nanomaterials derived from coal.

Investigation of sustainability failures of ISO 9001 quality management system – a case of Botswana

PurposeThis study aims to investigate causes of sustainability failures of ISO 9001 Quality Management Systems in Botswana.Design/methodology/approachThe research employed qualitative and quantitative methods, including literature review and secondary data analysis to understand trends relating to Botswana, and a survey to identify gaps leading to certification sustainability failures, focusing on; motives for certification, causes of decertification and issues in the certification process.FindingsISO 9001 adoption in Botswana is slow, with low acceptance rate in the public sector at 13% compared to the private sector at 87%. Termination rates have been high at 55% over two decades. Manufacturing dominates certification with 45% of total certification. While micro and small companies struggle to sustain certification, often failing within 2 years, medium-sized companies demonstrate better sustainability, lasting beyond 6 years. Product/service quality and process improvement drive certification while decertification is influenced by management factors, financial constraints, and process management. The study recommends a model for effective integration of ISO 9001.Originality/valueIntegrated systems are crucial for consistent process performance and continual improvement in all sectors for sustainable organizational success. Although the ISO 9001 Quality Management System has shown positive impacts globally, the impact of its adoption in Botswana remains questionable with high failure rates post implementation. There appears to exist a significant gap in development, implementation, and maintenance of the QMS. The public domain has no evidence of any past investigation on causes of sustainability failures of ISO 9001 post certification. The current study sought to close that knowledge gap.