Supply Management Research Articles

A novel hybrid model based on multiple influencing factors and temporal convolutional network coupling ReOSELM for wind power prediction

Highly accurate wind power prediction is important for the operation and management of wind farms, energy utilization and power supply. In recent years, in order to further improve prediction accuracy, some researchers have considered utilizing factors such as wind speed and wind direction to establish prediction models. However, this often results in input redundancy due to a lack of technical means. In this paper, a multivariate prediction model for wind power based on variational mode decomposition (VMD), fuzzy entropy (FE), partial auto-correlation function and cross-correlation function (PACF&CCF, abbreviated as PC), improved artificial hummingbird algorithm (IAHA), temporal convolutional network (TCN), and regularized online sequential extreme learning machine (ReOSELM) is proposed. To address the nonlinearity and non-stationarity of the original wind power time series and decrease computational costs, the VMD combined with FE data preprocessing technique is employed. Considering the information redundancy in the multivariate data, the PC technique is utilized to conduct correlation analysis on the input data and select highly correlated features as inputs. When the input is multivariate and high-dimensional, the ReOSELM model struggles to achieve satisfactory prediction performance. Therefore, a new model based on TCN-ReOSELM is constructed. Additionally, to overcome the drawbacks of manual parameter adjustment, an IAHA algorithm is proposed, which integrates Latin hypercube sampling and chaotic local search strategies, to optimize the crucial parameters of TCN-ReOSELM. The experimental results demonstrate that the multivariate method proposed in this paper reduces the RMSE by 31% compared to the univariate method. Specifically, the proposed VMD-FE-PC-TCN-ReOSELM model reduces the RMSE, MAE, and SMAPE by 60–64%, 55–58%, and 10–36%, respectively, compared to the PC-TCN-ReOSELM model.

Artificial-intelligence-model to optimize biocide dosing in seawater-cooled industrial process applications considering environmental, technical, energetic, and economic aspects

This research introduces an Artificial Intelligence (AI) based model designed to concurrently optimize energy supply management, biocide dosing, and maintenance scheduling for heat exchangers. This optimization considers energetic, technical, economic, and environmental considerations. The impact of biofilm on heat exchangers is assessed, revealing a 41% reduction in thermal efficiency and a 113% increase in flow frictional resistance of the fluid compared to the initial state. Consequently, the pump’s power consumption, required to maintain hydraulic conditions, rises by 9%. The newly developed AI model detects the point at which the heat exchanger’s performance begins to decline due to accumulating dirt, marking day 44 of experimentation as the threshold to commence the antifouling biocide dosing. Leveraging this AI model to monitor heat exchanger efficiency represents an innovative approach to optimizing antifouling biocide dosing and reduce the environmental impact stemming from industrial plants.

An intelligent deep residual learning framework for tomato plant leaf disease classification

Modern agriculture has been fascinated by various advancements in agriculture and the processing of foods and supply management that provision farmers to improve production. The health of plants is essential to improve production and economic growth. Diseases in plants can affect production and create a rigorous impact on the quality and create a hazard to food safety. Hence, detecting and classifying plant leaf diseases is essential to prevent the disease spread across the plants in the agriculture field and to improve productivity. The researchers in existing frameworks utilized artificial intelligence and machine learning techniques to demonstrate noteworthy solutions. However, a few issues exist related to noises in the images, hyperparameter selection problems, and over-fitting problems that influence prediction accuracy. The proposed model jellyfish ResNet(JF-ResNet) works well to achieve a better accuracy level by incorporating jellyfish optimized ResNET for tomato plant leaf disease identification and classification. The performance metrics such as Accuracy, specificity, sensitivity, and F1-Score is used to evaluate the performance of the JF-ResNet model. The proposed model achieves 97.3% accuracy, 95.3% sensitivity, 96.1% specificity, 96.9% recall, 96.4% precision and 97.1% F1-Score.

High-reliability uninterruptible power supply manager for critical virtualization cluster

Information technology servers are complex, delicate, and expensive systems; power grid interruption is one of the possible causes that can lead to hardware damage or logical disk structure damage, with severe consequences. Moreover, a power grid drop causes a sudden interruption of the services managed by a server. Uninterruptible power supplies (UPS) provide backup power when the regular power grid source drops. UPSs can only maintain a server for a short time. Therefore, it is necessary to introduce a blackout manager who can correctly shut down the server activities. Moreover, the manager must be able to restore the servers' status when the electrical grid power returns to its normal state. This paper proposes a possible UPS power manager able to manage servers during a prolonged electrical blackout. The UPS power manager identifies the blackout and keeps the servers safe by saving their state and shutting them down properly. Following the power grid restoration, the UPS power manager restarts the servers and restores their state. The proposed approach has been evaluated on a virtualization cluster used for critical activities at the Politecnico di Torino.

The relationships between ethical codes of conduct, ethical supplier risks, and financial performance: a buyer-supplier perspective

Although ethical codes of conduct are commonly used in supply chain management, the effectiveness of the codes has been questionable and the ethical risks from a supplier are rarely examined in a buyer-supplier dyad. Drawing on the literature on supply management, business ethics, agency theory and stakeholder theory, we propose that both the buyer and supplier should adopt ethical codes of conduct in order to reduce ethical supplier risk and improve their financial performance. A survey of 200 pairs of matched manufacturers and suppliers was conducted from automotive, clothing, food and pharmaceutical industries in China. Structural equation modelling was used to analyse the data. Our findings show that the implementation of buyer (supplier)’s ethical codes positively relate to its financial performance, and the buyer’s ethical codes positively relate to the supplier’s financial performance through ethical supplier risk. Our findings provide new empirical evidence on the critical significance of ethical codes of conduct and the particular role of suppliers in the adoption of this initiative in a supplier-buyer dyad.

Soft Schottky diodes for skin-interfaced electronics enabled by entirely soft components

Soft electronics have achieved significant development, attracting substantial interest due to their promising potential as a dominant form of future electronics. In this rapidly evolving field, the fully soft Schottky diode plays a critical role as a fundamental building block for electronic circuitry systems. These systems, constructed entirely from soft materials, can tolerate various mechanical deformations when interfaced with human skin, making them ideal for use in health monitoring systems and interactive human-machine interfaces. In this study, we introduce a Schottky diode fabricated entirely from soft materials using a facile solution process, further enabling all-printing fabrication systems. Utilizing the mechanical softness of poly(3,4-ethylenedioxythiophene) polystyrene sulfonate-based soft electrode, poly(3-hexylthiophene) nanofibril composite soft semiconductor, and liquid metal, we successfully fabricated a fully soft Schottky diode. This diode exhibits exceptional electrical characteristics even under various mechanical deformations, showcasing the high durability of the device. We have further developed fully soft rectifiers and logic gates, highlighting the versatility of our study. By incorporating these devices with a piezoelectric nanogenerator in a skin-interfaced energy harvesting system, they exhibit sufficient capability for rectification, ensuring a stable power supply as part of a power supply management system. This approach offers substantial potential for future skin-interfaced electronics, paving the way for advanced wearable technology.

Sustainable management of small-town water supply in Nepal: improvement through the multi-stage training mechanism

ABSTRACT In Nepal, a project to sustain a safe water supply for small towns was executed in 68 towns, each with distinctive water sources and topographical situations. This project adopted two approaches to establish a standardized capacity development process for small-town water supplies. The first approach, the Management Model, consists of standard operating procedures (SOPs) and business planning. The second approach, termed the Support Model, entails a comprehensive system for training, monitoring, and evaluating water supply management. Throughout the project, a total of 31 SOPs pertaining to operation, maintenance, and facility rehabilitation manuals were developed. Moreover, four courses consisting of training, basic and on-site training, and interactive workshops were conducted. Consequently, the data deficiency rate reduced significantly by 61%, while 87% of water samples met water quality standards. In contrast, the operating ratio and water production rates improved by 17 and 29%, respectively. The materials produced from these models are expected to contribute to small-town water supply systems beyond the pilot sites. This is due to the versatility of the model for future applications. Although the project was effectively implemented, continuous support for small-town water supply by the Government of Nepal is needed for future sustainability.

Green Supplier Selection Using Fuzzy AHP, Fuzzy TOSIS, and Fuzzy WASPAS: A Case Study of the Moroccan Automotive Industry

The green supplier selection presents numerous challenges, from initial assessment to final selection, which specialists in this field of supplier management often encounter. Among the techniques that aim to meet these challenges that are continually progressing is the creation and development of high-quality decision-making tools. In this study, the assessment of suppliers hinges on both traditional and environmental factors. A framework of multi-criteria decision-making (MCDM) is announced in order to appraise green supplier selection. This framework integrates Fuzzy Analytical Hierarchy Process (AHP) combined with two additional methods: WASPAS (“Weighted Aggregated Sum-Product Assessment”) and TOPSIS (“Technique for Order Preference by Similarity to Ideal Solution”). At the outset, there were five environmental criteria for green supplier selection: “Health and Safety”, “Sustainable Product Design”, “ISO 14001 Certification”, “Investment Recovery”, and “Green Packaging”, along with three conventional criteria including quality, price, and delivery, were pinpointed through a review of literature and expert input to facilitate the MCDM approach. As part of demonstrating the pertinency of the recommended framework, a practical case study of the automotive industry in Morocco is discussed. The results demonstrate that the utilized Fuzzy hybrid methods yield consistent rankings for green suppliers. Additionally, among the four green suppliers, number three obtained the best ranking, which indicates the robustness and performance of the chosen models. Furthermore, this study offers a unified platform for selecting green suppliers under a Fuzzy environment. Therefore, the chosen strategy and its analysis provide relevant data and information to decision-makers for the choice and selection of suppliers. It can also provide and help procurement departments and decision-makers to choose and select the efficient ecological supplier in the global market supply chain.

Steering through the storm: a process framework to guide purchasing and supply managers in navigating low-probability-high-impact disruptions

PurposeThis study seeks to explore the strategies purchasing and supply managers can employ to navigate the challenges presented by low-probability-high-impact (LPHI) disruptions. The core aim is to create a process framework that provides a systematic, step-by-step method to help purchasing and supply managers effectively deal with the chaos triggered by LPHI events.Design/methodology/approachThe study draws on qualitative data collected from eight firms operating within different industries (healthcare, fishing, food retail and manufacturing), where two firms represented each industry. The data underwent a thorough analytical process involving open coding, axial coding and aggregation of categories, resulting in the identification and formulation of overarching themes.FindingsThe analysis unveiled five primary challenges purchasing and supply management (PSM) encountered during the COVID-19 pandemic. These include supply shortages, supplier opportunism, the imperative to build a new supply base, price volatility and the need to make critical decisions based on limited information. It also identified contingent factors that influenced the magnitude of these challenges and approaches applied to address them. Additionally, it identified five responses to the challenges and two contingent factors that affected the responses.Originality/valueThis study extends the existing body of knowledge in purchasing and supply management by developing a process framework tailored to assist purchasing and supply managers in effectively addressing LPHI disruptions. To the best of our knowledge, this is one of the first studies to offer a structured, step-by-step approach that guides PSM professionals in navigating the chaos likely to be caused by such events.

Revisiting circular economy indicators: A circular supply chain perspective

The accurate understanding and measurement of circularity in purchasing and supply management is crucial for organisations aiming to enhance sustainability, reduce costs, and comply with regulations. However, existing circular economy indicators do not account for all circularity dimensions (i.e., C1-monetary, C2-energy and environment, C3-material, C4-temporal and C5-efficiency) and neglect key actors (i.e., collectors, recyclers, manufacturers, users) in the circular supply chain. Consequently, this results in biased decision-making when selecting supply chain partners, hindering the circular economy's progress. This study investigates the effectiveness of circular economy indicators and their constituent circular economy items at the circular supply chain level to better evaluate circular economy accomplishments. Out of the 63 circular economy indicators and 23 circular economy items identified, only three evaluate all five circularity dimensions, while nearly 40 percent fail to consider critical actors within the circular supply chain. Drawing on stakeholder theory, this study proposes a framework for developing an effective circular economy indicator. The proposed framework is validated through a hybrid approach, beginning with the fuzzy analytical hierarchy process to ascertain the weights of circular economy items, followed by the fuzzy technique of order preference similarity to the ideal solution to rank recycling alternatives using the determined weights, and culminating with the linear programming to optimise the circularity based on the established rankings. This research emphasises the importance of covering all circularity dimensions and targeting all circular supply chain actors in aligning the goals of different entities with the broader objectives of the circular economy. It is the first study to provide guidance on developing circular economy indicators and evaluating circular economy performance from a circular supply chain perspective, serving as a solid foundation to achieve circular economy agendas. It affords purchasing and supply practitioners the opportunity to augment decision-making processes, optimise sustainability efforts, and bolster supply chain regulatory adherence and governance.

Analisis Manajemen Persediaan Bahan Baku Pada Pabrik Tahu Ditinjau Dari Perspektif Bisnis Islam

Production problems are a very important problem for business actors because they can affect the profits they earn. The smoothness of production itself is influenced by whether or not the raw materials will be used. In this case, raw material inventory management can help reduce possible risks. Raw material inventory management is the most active element in company operations which is continuously obtained. In this case, researchers use the Safety Stock, Economiq Order Quantity (EOQ) and Reorder point inventory management methods to optimize the purchase of raw material inventory so that it becomes optimal and efficient. In this research, problems were found at the Tofu Factory regarding raw material supplies. In this case, the Tofu Factory always experiences a shortage of raw material stock and experiences waste in the costs incurred. This resulted in the Tofu Factory experiencing delays in deliveries to consumers. The results of the analysis show the use of raw material inventory management methods applied at the Jagabaya tofu factory, namely SafetyStock, Economic Order Quantity (EOQ) and Reorder Point. The implementation of this method is not optimal so this method does not work as it should because of several inhibiting factors. The management of raw material supplies at the Jagabaya tofu factory still does not use a structured method, so that in the production process stock runs out often occur. Therefore, raw material inventory management at tofu factories is only based on estimated sales numbers without clear calculations.

Tuberculosis commodities supply chain performance in the WHO African region: A scoping review.

Procurement and supply chain management [PSM] systems remain a critical pillar for the implementation of Directly Observed Therapy [DOTS] for tuberculosis [TB] and achievement of disease related aspirations such as 'ending TB by 2030'. We conducted a scoping review of literature using the Arksey and O'Malley [2005] framework to summarize and disseminate the results of available evidence in relation to TB commodities supply chain performance in the WHO African Region. We searched three electronic databases complemented by google search using relevant terms and identified 1,586 sources. Twenty-five studies published between 2009 and 2023 met the eligibility criteria, inclusive of 21 peer reviewed publications and four reports. The strengths we found included the existence of pooled procurement mechanisms [PPM], availability of funding through external sources, existence of logistics management information systems [LMIS] and integration of PSM systems into primary health care. The main challenge was frequent stock outs which mainly affected medicines for treating TB in children and those for preventing TB. Stock outs were found to follow a poverty gradient and pervasively inequitable since they disproportionately affected structurally disadvantaged populations and communities. Countries that rely on domestic mechanisms for procurement tend to be more vulnerable to stock outs due to inadequate and unpredictable financing, delayed disbursements of funds, longer procurement lead times and poor supplier management. We concluded that stock outs remain one of the foremost challenges to ending TB by 2030. We recommend leveraging existing performance-enhancing platforms such as PPMs, including utilization of such mechanisms by countries that utilize domestic resources to procure commodities. We recommend the design of people centric supply chains that are sensitive to the differentiated needs of the population to ensure that composite improvements in PSM performance do not mask underlying disparities. Context-relevant research is needed to inform future strategies for improving PSM performance.

Manajemen Supply pada Produk HNI-HPAI Halal Mart di Kabupaten Sambas Perspektif Ekonomi Islam

Islam is a religion that has a universal system that regulates good business and is in accordance with religion. Many companies are switching to an Islamic business system, called sharia economics. Currently, people really like the Islamic business system. Sharia-based companies include PT HPAI (Herbal Penawar al-Wahida Indonesia), which later became HNI-HPAI (Herba Penawar Al-Wahida Indonesia-Halal Network International). This research aims to determine the supporting and inhibiting factors for implementing supply management at the herbal HPAI halal mart in Sambas Regency. In this research, qualitative research was used. The data collection technique is carried out by means of interviews, then analyzed through data reduction, classifying the data, presenting the data and finally drawing conclusions. The data sources in this research consist of 2, namely primary data and secondary data. One of the supporting factors for carrying out herbal medicine supply management in Sambas Regency can involve operational efficiency, product quality and good marketing strategies. Meanwhile, inhibiting factors may include raw material supply instability, regulatory changes, or logistical constraints. The external supporting factor is that many people know the quality of HPAI products, so they are easy to sell because the prices are affordable. The internal inhibiting factor is not having its own way or rules to handle orders for lots of herbal products by consumers and delays in delivery of goods. These delays are due to an overload of goods to be sent by the expedition.

PENGARUH FINANCIAL PERFORMING TERHADAP NILAI PERUSAHAAN YANG DIMODERASI OLEH GREEN SUPPLY CHAIN MANAGEMENT (Studi Kasus Pada Perusahaan Manufaktur Sub Sektor Makanan dan Minuman yang Terdaftar di BEI Periode 2018-2022)

Investors will consider financial performance when choosing an investment. Financial performance can continue to improve with the implementation of the right business strategy, thereby increasing company value. the purpose of this study was to test and analyze the effect of current ratio, return on investment, and green supply chain management on firm value, as well as to test and analyze whether green supply chain management can moderate the effect of current ratio and return on investment on firm value. This research uses quantitative research. The data source in this study was taken from secondary data, namely annual reports obtained from the Indonesia Stock Exchange (IDX). The description of the population in this study is a manufacturing company in the food and beverages sub-sector listed on the Indonesia Stock Exchange (IDX) in 2018-2022. Based on the research results, it is known that CR has a positive and significant effect on firm value, ROI has a positive and significant effect on firm value, GSCM has a positive and significant effect on firm value. Then GSCM is not able to moderate the effect of CR and ROI on firm value. Key words: Current ratio, Return On Investment,Green Supply Management

A literary review on Ayurveda perspective of Pandu in Kaumarabhritya

In traditional science of Indian medical system, Childhood age is described as Kaumaravastha. The basic feature of this age group is to increase immunity, physical & mental strength, management of nutritional supply & control of prevalence of disease in of growing children. Kaumarbhritya not only to help paediatric disease but also describe dietary & daily life routine for paediatric care. The Pandu is one of the common diseases of childhood as early growing life which resembles Anaemia as per modern science. The disease involves vitiation of Dhatus by Pitta predominant Tridosha, which leads to deficiency of Blood (Rakta) Fat (Meda) & Ojas.[2] The condition is associated with laxity (Saithilya) of Dhatus, heaviness (Gaurava). Other predominant features are like diminish Varna (Complexion), Vala (Strength) & Sneha (Smoothness) of the body. There are certain premonitory symptoms which indicate chances of Pandu like Hrudaya Spandana (Palpitation), Roukshya (Dryness), Swedabhava (Loss of sweating) & Shrama (tiredness).[4] The Pandu may arise due to Sevan of Kshara, Amla, Lavana, Asatmya Bhojana. Hence Ayurveda recommended to take Satmya Bhojana & all of the foods which increase the amount of blood. The foods like Kharjura, Kismis, Apple, Pomegranate should be given. The drugs to be used in child should have Madhura Rasa.There are various Ayurveda formulation also available for the management of Pandu such as Navayasa Choorna. Samsodhana Karma also indicated for the management of Pandu Roga. This Article described various Ayurveda perspective of Pandu Roga in children.

SWASTHA: Revolutionizing Medical Supply Management in Sri Lankan Healthcare

SWASTHA: Revolutionizing Medical Supply Management in Sri Lankan Healthcare

Assess The Workload Management Model and Enhanced Quality Control in The Central Sterile Supply Department: A Study Protocol.

Introduction The Central Sterile Supply Department (CSSD) plays a crucial role in ensuring the safety and efficacy of medical instruments and equipment used in healthcare settings. Effective workload management and quality control are essential for maintaining high standards of patient care and minimizing the risk of healthcare-associated infections. This study protocol aims to assess the implementation and impact of a new workload management model and enhanced quality control measures in a CSSD setting. Methods The study will employ a mixed-methods approach, including quantitative analysis of workload data, qualitative interviews with CSSD staff, and observational assessments of workflow and quality control procedures. The workload management model under investigation involves the allocation of resources based on demand patterns and the implementation of scheduling algorithms to optimize staff efficiency. Enhanced quality control measures include the implementation of advanced sterilization technologies, rigorous inspection protocols, and continuous staff training initiatives. Results The study expects to provide insights into the effectiveness of the workload management model in optimizing resource allocation and improving staff productivity. Additionally, it aims to evaluate the impact of enhanced quality control measures on the reliability and safety of instrument sterilization processes. Findings from this study will inform recommendations for further improvements in CSSD operations and contribute to the advancement of best practices in sterile supply management. Conclusion The successful implementation of an effective workload management model and enhanced quality control measures in the CSSD is crucial for maintaining patient safety and ensuring the efficient functioning of healthcare facilities. By systematically evaluating the implementation and impact of these interventions, this study protocol seeks to contribute to the ongoing improvement of CSSD operations and the enhancement of healthcare quality.

Drivers of Sustainable supply chain for sustainable development in industry

This analysis explores the different elements that constitute sustainable supply chains used by companies as genre on the road to sustainable development across different industries. The analysis of a body of literature and empirical data is carried out by a critical objective to determine the fundamental aspects of sustainability practices. The research suggests that we should have the necessary knowledge of these drivers for the stage to be raised of the environmental responsibility, social equity and economic development. Strategies are detailed to enable stakeholders throughout industries in adopting sustainable supply chain methods. Through this process, the long-term resilience of supply chains and the sustainability of the profitable position are promoted. The results are of this type, clarifying the crucial role of sustainable supply chain in reaching the global sustainability targets and promoting sustainability model for the companies and societies all over the world. Through this research we strive to add to the already established supplies chain management literature and aid the change process management in the pursuit of sustainable development in the different industries. Result of the cocreation with this domain has brought up meaningful implications to the literature. One of the new concepts we are proposing is a dynamic setting for a three-level model serving as a tactical plan for strategic sustainable supply management. Our study has contributed a theoretical framework that distinguishes practical facts of supply chain management and is for the purposes of future research and appraisals in terms of UN 17 Sustainable Development Goals

Evaluating Trends of Temperature Index in Gia Lai Province Based on IITA and IPTA Approaches under Climate Change

This study performs historical trend analysis for average, maximum, and minimum temperatures using the integration of the Improved visualization for trend analysis (IITA) and Innovative Polygon Trend Analysis (IPTA) of Şen to evaluate the tendency of extreme temperatures on different time scales (annual, monthly and seasonal) in Gia Lai province from 1980 to 2019 at three stations, including Pleiku, AyunPa, and An Khe. Results recorded over the past four decades, the temperature trend in Gia Lai has been gradually warming. The average temperature in each month of the year ranges from 19 to 28°C, December and January usually have the lowest temperature of the year with a variation lower than 20°C. On the contrary, the months of April, May, and June often have the highest temperatures of the year, with a variation greater than 26°C. The outcomes of this research have provided a general picture of temperature characteristics, useful information for the management and planning of land use, irrigation and water supply in Gia Lai province under unpredictable climate change.

Water, energy and environment nexus: Quantitative assessment for integrated power plants with renewable energy

The population increase and the demand for water and energy, accompanied by the implications of environment pollution for natural and human resources, indicate the critical necessity for a coherent movement towards nexus between water, energy, and environment. Due to the fact that power generation industry is responsible for a significant proportion of water and fuel consumption and Carbon dioxide emissions within the world, in this research, the application of the hybrid renewable system in a thermal power plant has been assessed based on the approach of analyzing the link between energy, water and environment. The design of the solar system and the assessment of carbon balance during the power plant lifetime have been conducted in PVsyst application in 2022. Moreover, ReCipe environmental model has been used for assessing the effect of decrease in carbon emission on the ecosystem. The findings of the research indicate that the replacement of at least 2 % of the nominal capacity of the fossil fuel power plant with the renewable one, prevents the emission of 1431.28 tons of carbon dioxide yearly. This amount equals to 380.34 cubic meters of reserve in fossil fuel consumption and 391.73 tons of crude oil. The results also showed that in addition to preserving natural resources, the hybrid cycle design leads to significant water demand reduction which equals to 3842 cubic meters with the capacity to supply underground water sources. Due to the interests of preserving water and energy resources and decreasing carbon emission in power plant industry, within the framework of nexus approach, management of energy supply by replacing resources and using water and heat recovery technologies and application of energy demand management policies based on energy efficiency and environmental implications is recommended.