Supply Chain Processes Research Articles

HCSRL: hyperledger composer system for reducing logistics losses in the pharmaceutical product supply chain using a blockchain-based approach

Blockchain technology uses a secure and decentralised framework for transaction management and data sharing within supply chains. This is particularly crucial in the pharmaceutical industry, where product authenticity and traceability are paramount. Blockchain plays a pivotal role in preventing product loss and counterfeiting, while simultaneously enhancing transparency and efficiency throughout the supply chain. The research introduces a step-by-step approach to implementing a proof-of-concept (PoC) for Supply Chain Risk Management (SCRM) through blockchain technology. This PoC involves simulating a supply chain process to assess feasibility and measure key performance indicators. Engaging stakeholders and gathering feedback is integral to refining the blockchain-based SCRM system. The study rigorously evaluates the performance of the SCRM blockchain across various test scenarios, featuring differing numbers of organizations and clients. Multiple fabric networks are employed to assess the system’s scalability and performance under diverse conditions. The results of these comprehensive tests inform practical deployment decisions and highlight areas for potential optimization and further development. So this research provides valuable insights into the application of blockchain in pharmaceutical supply chains, offering a roadmap for implementation and improving supply chain security, efficiency, and transparency.

Innovative biorefinery approaches for upcycling of post-consumer food waste in a circular bioeconomy context

Owing to the significant amounts produced each year, food waste is a critical issue that affects the economy, society, and environment. An estimated US$ 1 trillion food is wasted annually because of the supply chain and harvesting processes, which lose around one-third of the net production. This significant loss has sparked global concern, there is an urgent need for sustainable approaches to reduce food waste or to propose an economical route for its utilization. Major concerns associated with its improper management include environmental degradation and the exacerbation of greenhouse gases. This review provides a comprehensive understanding of the recent advances in measures to minimize food waste (FW) and its chemical and biotransformation into valuable products. Food waste comprises mainly carbohydrates, proteins, and oils; the former two components are commonly used as microbial feedstock, leaving behind the residual oil fraction which poses a greater environmental risk. Microbial transformation of these hydrophobic materials present in food waste into value-added products proves to be a sustainable and economical strategy. Thus, this study proposes an integrated biorefinery strategy for holistic valorization of FW, whereby all its components were used to produce value-added compounds such as biofuels, bioplastics, nutraceuticals, and biomaterials using microbial biocatalysis. Compared to conventional methods, an integrated biorefinery will be more sustainable and uplift the microbial processes by switching from ‘pure’ to food waste-derived substrates and thereby pave ways to achieve ‘green’ transition.

A Study on Designing and Managing the Supply Chain Process and its Impact on Business Performance to Gain a Long-Term Competitive Advantage

Abstract: This study aims to understand factors that improve business performance and gain a competitive advantage. It compares the operations and supply chain procedures of automakers like General Motors, Toyota, and Ford to assess their management efficiency ratios. The research examines the cash conversion cycle, cash conversion cycle, receivables turnover, inventory turnover, and total asset turnover. General Motors leads in quickly turning sales into profits, with shorter collection periods and lower inventory holdings. The study also highlights the complex interplay between financial success, competitive advantage, and operational excellence in the automobile sector. By utilizing this information, companies can improve their supply chain operations and long-term competitiveness.

The potential of IoT to transform supply chain management through enhanced connectivity and real-time data

This review paper examines the transformative potential of Internet of Things (IoT) technology in supply chain management (SCM). It elucidates how IoT-enabled solutions enhance visibility, efficiency, cost-effectiveness, and risk management across supply chain processes. Despite promising benefits, challenges such as data security, integration complexity, scalability, and technological dependencies are identified. Emerging trends in edge computing, artificial intelligence, machine learning, and blockchain and recommendations for successful implementation are discussed. The paper underscores the significance of IoT adoption for businesses, consumers, and society, envisioning a future marked by interconnected, intelligent, and sustainable supply chains.

Resilience in supply chain management: lessons learned from disruptions like the COVID-19 pandemic

The ravaging impacts of the COVID-19 pandemic on global supply chains and its exposures of the vulnerabilities of the supply chain process has been examined in this paper. Importantly, the failure of supply chain resilience and the post-COVID-19 lessons necessitated the need to examine the need for resilience in supply chain management process. The paper examined the concept of resilience and its application in supply chain management, and covered strategies for developing resilience in supply chain management, which includes: identification and assessment of associated risks, diversification of supply chain channels, enhancing collaborations and effective communication among stakeholders, inventory management and supply chain flexibility, technology adoption and digitalization, scenario planning and simulations, as well as robust continuity planning. The paper also identified the challenges of supply chain resilience building. The paper provides valuable insights into how organizations can better handle future supply chain operations by considering the intrinsic development of resilience, which will enable them to better withstand and quickly recover from future disruptions.

Logistics Performance Index of Africa: An Indicator for Türkiye and Africa Trade Relations?

The logistics performance of countries is important in trade flows. As part of the supply chain process, logistics is the backbone of trade processes. In this direction, the Logistics Performance Index (LPI) put forward by the World Bank can be considered as an indicator. With the LPI, countries have the opportunity to evaluate the effectiveness of their activities in trade and logistics. The aim of the study is to rank and analyze African countries with the integrated Entropy-MOORA Reference Approach using the LPI values for 2023. In order to increase the depth of the study, an evaluation is made based on the trade data between Türkiye and African countries for 2022. The study aims to rank African countries on the basis of six criteria defined by the MOORA Reference Approach and to provide a perspective on the development of Türkiye’s trade relations with African countries in line with trade figures. According to the results of the study, South Africa ranks first, Botswana second, and Libya last in the ranking of LPI countries. Türkiye’s trade volume with the continent, South Africa ranks fifth, Botswana fifty-third, and Libya third. Therefore, there is no correlation between LPI and trade data in current situation.

A STUDY ON RISKS AND THEIR MITIGATION IN SUPPLY CHAIN PROCESS WITH SPECIAL REFERENCE TO JSW ISPAT SPECIAL PRODUCTS LIMITED

This project report examines the various risks inherent in the supply chain of JSW Ispat Special Products Limited and outlines the strategies used to mitigate these risks. The purpose of the research is to find out, through in-depth analysis, how these supply chain risks affect the efficiency of the facility's operations and overall efficiency. The report is comprehensive and includes the results of extensive literature reviews, primary research and detailed data analyses. The main risks identified are supply disruptions, logistical challenges, market instability and regulatory changes. Mitigation strategies such as multifaceted sourcing, improved inventory management, robust logistics planning and compliance frameworks are discussed in detail. The results of this study not only highlight critical supply chain vulnerabilities, but also provide practical insights and recommendations to improve resilience and efficiency. Ultimately, this study contributes to a deeper understanding of supply chain dynamics and provides practical solutions to optimize supply chain processes at JSW Ispat Special Products Limited. Keywords: Supply chain, risk mitigation, JSW Ispat, Supply disruptions, Logistics challenges

Structural Optimization of Trusses in Building Information Modeling (BIM) Projects Using Visual Programming, Evolutionary Algorithms, and Life Cycle Assessment (LCA) Tools

The optimal structural design is imperative in order to minimize material consumption and reduce the environmental impacts of construction. Given the complexity in the formulation of structural design problems, the process of optimization is commonly performed using artificial intelligence (AI) global optimization, such as the genetic algorithm (GA). However, the integration of AI-based optimization, together with visual programming (VP), in building information modeling (BIM) projects warrants further investigation. This study proposes a workflow by combining structure analysis, VP, BIM, and GA to optimize trusses. The methodology encompasses several steps, including the following: (i) generation of parametric trusses in Dynamo VP; (ii) performing finite element modeling (FEM) using Robot Structural Analysis (RSA); (iii) retrieving and evaluating the FEM results interchangeably between Dynamo and RSA; (iv) finding the best solution using GA; and (v) importing the optimized model into Revit, enabling the user to perform simulations and engineering analysis, such as life cycle assessment (LCA) and quantity surveying. This methodology provides a new interoperable framework with minimal interference with existing supply-chain processes, and it will be flexible to technology literacy and allow architectural, engineering and construction (AEC) professionals to employ VP, global optimization, and FEM in BIM-based projects by leveraging open-sourced software and tools, together with commonly used design software. The feasibility of the proposed workflow was tested on benchmark problems and compared with the open literature. The outcomes of this study offer insight into the opportunities and limitations of combining VP, GA, FEA, and BIM for structural optimization applications, particularly to enhance structural efficiency and sustainability in construction. Despite the success of this study in developing a workable, user-friendly, and interoperable framework for the utilization of VP, GA, FEM, and BIM for structural optimization, the results obtained could be improved by (i) increasing the callback function speed between Dynamo and RSA through specialized application programming interface (API); and (ii) fine-tuning the GA parameters or utilizing other advanced global optimization and supervised learning techniques for the optimization.

Manajemen Risiko Pada Aktivitas Distribusi Pangan KJP Di Kepulauan Seribu Menggunakan Metode House Of Risk

PD PSJ is a company engaged in the distribution of foodstuffs and basic needs, especially the people of Jakarta. Along with the government's program related to the procurement of KJP cheap foodstuffs, the KJP food distribution process is in collaboration with PD PSJ. KJP food distribution activities are carried out throughout the DKI Jakarta area, including the Thousand Islands. In the process, there were several obstacles experienced by the officers. To reduce the risk of a late KJP food distribution supply, management carried out several policies related to risk management. The House of Risk (HOR) method is one of the methods to identify several activities and risks that can occur in the supply chain process of goods. This research applies the HOR method to obtain recommendations for improvements in the process of distributing KJP goods. The results of data processing and analysis using the HOR method obtained the greatest recommendation for improvement is to conduct training to field officers and improve communication both internally and externally.

Challenges and Opportunities for Sustainable Supply Chain Management

Green supply chain management (GSCM) is an advanced management approach that comprehensively considers the environmental impact, resource utilization efficiency, and enterprise income throughout the entire supply chain process. Compared to traditional supply chain management, GSCM exhibits higher complexity in terms of management and network characteristics. It emphasizes sustainable development for both society and enterprises, incorporating ecological and environmental protection design principles from raw material sourcing to waste material recycling, thereby achieving optimized environmental outcomes through enhanced cooperation within and between organizations. In essence, green supply chain management practices encompass green design, green procurement, green manufacturing, green packaging, green materials usage, and green recycling initiatives. The critical distinction between a green supply chain and a traditional one lies in the former's consideration not only of optimizing and coordinating the supply chain under conventional economic cost constraints but also recognizing the negative impacts of economic activities on the environment as significant factors warranting investigation. By embedding environmental awareness into supply chain management processes, it seeks to achieve a balanced approach that harmonizes the economy with environmental concerns. The proposition of adopting a green supply chain aligns with the developmental trajectory of economic globalization and free trade while meeting demands for environmentally friendly products and promoting greener trade.

Blockchain self-update smart contract for supply chain traceability with data validation

Abstract A sustainable supply chain management strategy reduces risks and meets environmental, economic and social objectives by integrating environmental and financial practices. In an ever-changing environment, supply chains have become vulnerable at many levels. In a global supply chain, carefully tracing a product is of great importance to avoid future problems. This paper describes a self-updating smart contract, which includes data validation, for tracing global supply chains using blockchains. Our proposal uses a machine learning model to detect anomalies on traceable data, which helps supply chain operators detect anomalous behavior at any point in the chain in real time. Hyperledger Caliper has been used to evaluate our proposal, and obtained a combined average throughput of 184 transactions per second and an average latency of 0.41 seconds, ensuring that our proposal does not negatively impact supply chain processes while improving supply chain management through data anomaly detection.

Secure pharmaceutical supply chain using blockchain in IoT cloud systems

Supply Chain Management (SCM) systems require time sequencing, coordination and tracking the movement of goods and processes. Internet of Things (IoT) and Blockchain technologies are useful to develop a secure automated SCM. IoT devices with in-built sensors and actuators help to keep track of the state, location, temperature or other parameters of an entity, and control the automation of routine as well as hazardous tasks. Blockchain technology supports time-stamping, authentication, process coordination, non-repudiation, commercial transactions, and also provides security for transactions and storage. The pharmaceutical SCM demands accurate, immediate and secure control system. Additionally, the supply chain process data from IoTs is stored and processed in Cloud by Analytics applications, for business planning and improvement. An efficient and secure IoT-Cloud-Blockchain based system for both SCM automation and analytics has been proposed in this work. It leverages a hierarchical IoT, Mist, Edge, Fog, Cloud computing (IMEFC) architecture to enhance Communication-Response-Compute-Security-Storage (CRCSS) in the system. Blockchain technology provides security for the SCM transactions and data. The efficiency of the Blockchain is measured in terms of upload time, download time and transaction fees for Bitcoin, Ethereum and Filecoin platforms. The Filecoin blockchain platform is quicker and cost-effective for larger file sizes, compared to Ethereum and Bitcoin, making it suitable for Pharmaceutical SCM systems.

A Novel Hybrid Gray MCDM Model for Resilient Supplier Selection Problem

The current business climate has generated considerable uncertainty and disrupted supply chain processes. Suppliers have frequently been identified as the primary source of hazards responsible for supply chain disruptions. Using a strategic approach to supplier selection that prioritizes providers with resilience features, mitigating the risk exposure inherent in supply chains is possible. This study proposes a comprehensive gray multiple-criteria decision making (MCDM) method incorporating resilience attributes to supplier selection. To determine criteria weights, the gray PSI and gray BWM methodologies were used, and to evaluate and prioritize resilient providers, the gray MCRAT and gray COBRA methodologies were applied. According to the results obtained by the suggested methodology, the supplier that demonstrated the greatest degree of resilience was determined to be the provider categorized as SPIR 4. The sequential sequence of the SPIR numbers is as follows: SPIR 5, SPIR 1, SPIR 3, SPIR 2, and SPIR 6. The data demonstrate that the developed approach produced accurate results.

Enhancing quality assessment of live Pacific oysters (Crassostrea gigas) using flexible sensors real‐time monitoring physiological signals

AbstractShell‐closing strength (SCS) is commonly used to assess oyster vigor and quality as an important physiological stress indicator of the oyster organism. In this study, a quality decision support system based on flexible wireless sensor network and web services was designed and developed to explore the application of SCS in the rapid assessment of vitality and quality. Based on physiological and environmental information collected by flexible wireless sensor networks, this study proposes a novel quantitative vitality assessment method to identify oyster life decline cycles and processes. Meanwhile, TVB‐N, TVC, and pH were selected as quality indicators, and a back‐propagation artificial neural network (BP‐ANN) was used to predict and evaluate oyster quality indicators. The results showed that the root mean square errors (RMSE) for TVB‐N, TVC, and pH were 0.4624, 0.8827, and 0.1941; the coefficients of determination (R2) were 0.8919, 0.8578, and 0.6249. Therefore, the rapid assessment of oyster vitality and quality based on a flexible wireless sensor network is a reliable and effective means.Practical applicationsThis study aims to explore the application of live oyster SCS for rapid quality evaluation. In this article, a quality decision support system based on a flexible wireless sensor network (WSN) and web services is developed to improve the quality and health of live oysters in the supply chain. The use of the multi‐sensor system enables the monitoring and collection of environmental and physiological signals of live oysters throughout the supply chain process. The evaluation of the quality of live oysters using physiological and environmental information collected by flexible wireless sensor networks is a reliable and efficient method. This will provide an effective and reliable quality evaluation and management for the oyster industry.

Research on Supply Chain Risk Prevention and Control of Medical Products Enterprises

This paper firstly analyzes the mode, development background and development status of the medical products supply chain, and finds that the medical products market shows an expanding trend, which requires the prevention and control of supply chain risks. Secondly, this paper identifies the risk factors existing in its current development, mainly supply risk, logistics risk, demand risk, information risk and cooperation risk, and analyzes the five types of risk in detail, points out the risk factors existing in each risk, and enumerates the impacts of each risk on each link of the medical products supply chain. Again, this paper combines the relevant risk factors to propose specific supply chain management countermeasures from three aspects, namely: using innovative digital supply chain models, optimizing internal supply chain processes, and improving the standardized management of medical products production. Finally, the whole paper is summarized and relevant conclusions are drawn, aiming to provide some references for giving full play to the role of medical products supply chain.

Leveraging artificial intelligence for enhanced supply chain optimization

This study provides a comprehensive review of the integration of Artificial Intelligence (AI) into Supply Chain Management (SCM), focusing on its impact on operational efficiency, strategic innovation, and sustainability. Employing a systematic literature review and content analysis methodology, the research synthesizes findings from peer-reviewed articles and conference papers published between 2013 and 2023. The study identifies key advancements in AI technologies, such as machine learning, natural language processing, and robotics, and their applications across various supply chain processes including demand forecasting, inventory management, and logistics optimization. Key findings reveal that AI significantly enhances supply chain efficiency by improving decision-making, reducing costs, and optimizing resource allocation. However, challenges such as data privacy concerns, ethical considerations, and the need for skilled personnel emerge as critical factors influencing AI adoption in SCM. The future outlook for AI-enhanced supply chains is promising, with potential for further innovation and resilience, albeit contingent upon addressing existing challenges. The study concludes with strategic recommendations for practitioners and policymakers, emphasizing the importance of fostering a culture of innovation, developing digital competencies, and creating supportive regulatory frameworks for AI integration. Directions for future research include exploring the long-term impacts of AI on supply chain sustainability, ethical implications of autonomous systems, and the interplay between AI and emerging technologies. This research contributes to the academic discourse on AI in SCM, offering insights for enhancing supply chain operations in the digital age.

Exploring the impact of supply chain integration and agility on commodity supply chain performance

The aim of this research was to explore the influence of supply chain integration (SCI) on commodity supply chain performance (SCP) with the mediating role of supply chain agility (SCA). The research methodology employed a correlational approach using structural equation modeling. 131 employees from active companies in the agricultural commodity supply chain (SC) sector in Iran participated in the study. Analysis of the data was carried out utilizing Partial Least Squares Structural Equation Modeling (PLS-SEM) employing SMARTPLS software. The results indicate that customer integration (CI), supplier integration (SI), and internal integration have a positive and significant impact on SCA and commodity SCP. Additionally, the influence of SCA on commodity SCP is positive and significant. SCA plays a positive and significant mediating role in the impact of CI, SI, and internal integration on commodity SCP. Therefore, it can be concluded that companies that possess CI, SI, and internal integration in their commodity SC process demonstrate more satisfactory performance in the commodity SC.

A study on Optimizing supply chain management to ensure efficient delivery of salon products and equipment to all locations in Groom India salon and spa private limited

This study aims to optimize the supply chain management of Groom India Salon and Spa Private Limited to ensure efficient delivery of salon products and equipment to all its locations. The research will begin by evaluating the current end-to-end supply chain processes, identifying bottlenecks, and exploring digital solutions for real-time tracking and inventory management. By implementing software tools to enhance visibility and coordination, the study seeks to reduce delivery lead times, achieve cost savings through optimized inventory levels, and improve customer satisfaction and loyalty. The methodology will involve a combination of qualitative and quantitative analysis, including interviews with key stakeholders, data collection on current processes and performance metrics, and simulation modelling to test various optimization scenarios. The study aims to provide actionable insights and recommendations for enhancing the supply chain management of Groom India Salon and Spa Private Limited, ultimately contributing to its overall operational efficiency and customer service excellence.

The impact of procurement strategies on supply chain sustainability in the pharmaceutical industry

In today's society, there is a major role that procurement is playing in sustainability because of great requirements and demand for improvement in some supply chain processes and procurement practices. It helps in making rational decisions that encompass economic, social, and environmental parts of society. Corporate sustainability requires such abilities to impact external firms in the process of supply chain. In the Economic advancement markers worldwide, public and neighbourhood levels advance sustainability approaches are advised, as they represent the advancement in the supply chain process. By implementing procurement strategies in the pharmaceutical industry elements of supply chain sustainability can improve environmental, social a financial impact on society. It is a cross-sectional study. The present study was conducted in the urban areas of Karachi, Pakistan. Data collection will be through questionnaires and surveys. It is designed for information collection so it can be used to determine the improvement and impact of sustainability on procurement strategies in supply chain sustainability.

Optimizing Palm Oil Biomass Supply Chain Logistics through Multi-Objective Location-Routing Model

Malaysia can convert agricultural wastes (biomass) into biofuel to reduce fossil fuel dependency and solve the disposal problem. As one of the largest palm oil producers, Malaysia has an abundance of palm oil biomass, but the biomass has high humidity, low energy density, and is scattered geographically. Establishing collection facilities with pretreatment operations is suggested to collect the biomass and improve its quality. Nevertheless, the facility placement and vehicle routing decisions significantly affect the total cost and operational efficiency. Hence, this study develops a model to address the location-routing problem and quantifies the pretreatment operation to customize the process in the biomass supply chain. This research also addresses sustainability from all dimensions through multi-objective optimization. The model minimizes costs, reduces negative social impacts by considering population densities, and measures environmental performance through CO2 emissions. The study first optimized each objective function separately and then conducted a multi-objective optimization using a weighted sum approach. Optimizing each objective function individually will achieve the best outcome for each dimension, but enhancing one objective would impair the others. However, multi-objective optimization shows some compensation for the performances where economic, social, and environmental indicator values decreased by 0.36%, 6.58%, and 15.28%, respectively. The results demonstrate that the model adjusts the locational and routing decisions based on different goals.