Supply Chain Processes Research Articles

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.

Supply Chain Limitations in the South African Engineering Sector-Supply Chain Professionals Views

The engineering industry has several obstacles as the worldwide economy slows, including macroeconomic hardship, lack of resources, organizational deficiencies, and an overall incapacity to respond to major concerns. In the past few years, they have gotten increasingly intense and serious. Empirical supply chain administration studies identify impediments that hinder the engineering industry in emerging nations, such as South Africa. This research aims to investigate supply chain limitations in the South African engineering industry. The literature was evaluated as well as interviews that were semi-structured and were used to get thoughts from 15 senior supply chain professionals. To examine qualitative data, ATLAS.ti (version 7) software was used for content analysis. The conversations revealed six topics, such as a shortage of capital in supply chains, innovative supply chain process restrictions, supply chain administration changes, supply chain cooperation, supply chain administration, and scheduling administration. engineering companies should use systems to manage their supply chains, integrated options, and collaboration managing project techniques and technology. The findings reveal a shortage of expenditure in supply management processes and the fact that engineering companies are still lacking a strategic perspective on managing their supply chains. However, it seems that supply chain tactics may improve an organization's efficiency and business performance in engineering companies.

Smart manufacturing supply chain process strategy using intelligent computation techniques

Smart manufacturing supply chain process strategy using intelligent computation techniques

Systems Thinking for Supply Chains: Identifying Bottlenecks Using Process Mapping of a Child Health Intervention in the Democratic Republic of the Congo (DRC)

The quality of supply chains in public health interventions in low- and middle-income countries can determine how effectively a program is able to treat its intended population group and subsequently achieve its health targets. We aimed to disentangle where challenges exist hierarchically and administratively through the application of process mapping to the supply chain of an integrated community case management (iCCM) intervention in the Democratic Republic of the Congo (DRC). We conducted a document review, semi-structured key informant interviews, and focus group discussions with program agents involved in supply chain processes of the child health intervention. Enterprise architecture was used to map the intervention’s supply chain and its participatory actors, and detailed bottlenecks of the chain through the application of a health systems framework. The results of this study will be used to inform a system dynamics model of the supply chain of iCCM in DRC. The greatest bottlenecks leading to stockouts at the community level occurred upstream (from national to province and from zone to health facility). While the use of local procurement processes was partially attempted to strengthen systems, parallel supply chain activities compromised sustainable system integration and development. Initial delays in stock dispensation were due to international procurement at the supplier, inducing a trickle-down effect. Inadequate quantification of supply needs and subsequent insufficient product procuration were the single most important steps that led to stockouts. This study demonstrated that the community health supply chain would be most impacted by improvements made in processes at the highest administrative strata, while exposing its delicate dependence on activities at the lowest levels. Visibility of inventory at all levels and improved data quality and use through a transparent tracking system have the potential to significantly reduce stockouts. Future interventions should take care to not develop parallel processes or exclude local health system agents to avoid disruption and ensure sustainable health outcome gains. Causal loop studies and system dynamics can further identify the systems interactions and relationships and their underlying causal mechanisms in need of intervention.

Weather risk hedging mechanism for contract farming supply chain with weather-dependent yield

The stability of contract farming is challenged by the impact of disastrous weather on crop yield. Managing weather risks has become an unavoidable reality for participants in contract farming. In this regard, this paper focuses on investigating weather risk hedging mechanisms for contract farming supply chain in a Newsvendor setting. As a benchmark, we first consider the agricultural production investment decision under the inherent mechanism (i.e. protective price mechanism) of contract farming. Due to the inevitable reduction of farmers’ agricultural investment levels and performance loss caused by disastrous weather under this mechanism, we then systematically propose innovative weather risk hedging mechanisms based on the completeness of both internal risk–benefit sharing mechanism of contract farming in developing economies and its external financial derivatives market. We define them as the operational weather risk hedging (OWRH), financial weather risk hedging (FWRH), and combined weather risk hedging (CWRH) mechanisms, respectively. The research findings are as follows: (1) The OWRH mechanism overcomes the distortion of agricultural investment levels and fosters a community of shared risks and benefits among contract farming participants, to reach the equilibrium with higher profits. Nevertheless, it falls short of externalizing weather risks. (2) The FWRH mechanism transfers disastrous weather risks encountered by contract farming and reverses the trend of decreasing performance as the disastrous weather intensify, yet it fails to resolve the distortion of agricultural investment levels and the internal distribution of profits among stakeholders. (3) The CWRH mechanism mitigates the distortion of investment levels and the decline of contract farming’s performance caused by intensifying weather disaster, improving the anti-risk capacity of contact farming. But it does not always contribute to the optimal profits for contract farming participants, instead, this achievement is only attainable in the face of severe weather. Meanwhile, it imposes higher requirements on the financial environment in developing economies. Furthermore, we provide distinct applicability boundaries for these weather risk hedging mechanisms. The aim is to provide valuable insights into the management of disastrous weather risks faced during the production process of contract farming supply chain in various regions of developing economies.

SeedChain: A Secure and Transparent Blockchain-Driven Framework to Revolutionize the Seed Supply Chain

Farming is a major sector required for any nation to become self-sustainable. Quality seeds heavily influence the effectiveness of farming. Seeds cultivated by breeders pass through several entities in order to reach farmers. The existing seed supply chain is opaque and intractable, which not only hinders the growth of crops but also makes the life of a farmer miserable. Blockchain has been widely employed to enable fair and secure transactions between farmers and buyers, but concerns related to transparency and traceability in the seed supply chain, counterfeit seeds, middlemen involvement, and inefficient processes in the agricultural ecosystem have not received enough attention. To address these concerns, a blockchain-based solution is proposed that brings breeders, farmers, warehouse owners, transporters, and food corporations to a single platform to enhance transparency, traceability, and trust among trust-less parties. A smart contract updates the status of seeds from a breeder from submitted to approved. Then, a non-fungible token (NFT) corresponding to approved seeds is minted for the breeder, which records the date of cultivation and its owner (breeder). The NFT enables farmers to keep track of seeds right from the date of their cultivation and their owner, which helps them to make better decisions about picking seeds from the correct owner. Farmers directly interact with warehouses to purchase seeds, which removes the need for middlemen and improves the trust among trust-less entities. Furthermore, a tender for the transportation of seeds is auctioned on the basis of the priority location locp, Score, and bid_amount of every transporter, which provides a fair chance to every transporter to restrict the monopoly of a single transporter. The proposed system achieves immutability, decentralization, and efficiency inherently from the blockchain. We implemented the proposed scheme and deployed it on the Ethereum network. Smart contracts deployed over the Ethereum network interact with React-based web pages. The analysis and results of the proposed model indicate that it is viable and secure, as well as superior to the current seed supply chain system.

The Valorization of Wastes and Byproducts from Cruciferous Vegetables: A Review on the Potential Utilization of Cabbage, Cauliflower, and Broccoli Byproducts.

The management of vegetable waste and byproducts is a global challenge in the agricultural industry. As a commonly consumed vegetable crop, cruciferous vegetables marked higher amounts of wastage during their supply chain processes, with a significant contribution from cabbage, cauliflower, and broccoli. Therefore, the sustainable and resource-efficient utilization of discarded materials is crucial. This review explores potential applications of cruciferous vegetable waste and byproducts, spotlighting cabbage, cauliflower, and broccoli in food, medicinal, and other industries. Their significance of being utilized in value-added applications is addressed, emphasizing important biomolecules, technologies involved in the valorization process, and future aspects of practical applications. Cabbage, cauliflower, and broccoli generate waste and low-processing byproducts, including leaves, stems, stalks, and rot. Most of them contain high-value biomolecules, including bioactive proteins and phytochemicals, glucosinolates, flavonoids, anthocyanins, carotenoids, and tocopherols. Interestingly, isothiocyanates, derived from glucosinolates, exhibit strong anti-inflammatory and anticancer activity through various interactions with cellular molecules and the modulation of key signaling pathways in cells. Therefore, these cruciferous-based residues can be valorized efficiently through various innovative extraction and biotransformation techniques, as well as employing different biorefinery approaches. This not only minimizes environmental impact but also contributes to the development of high-value-added products for food, medicinal, and other related industries.

Drivers of supply chain adaptability: insights into mobilizing supply chain processes. A multi-country and multi-sector empirical research

AbstractSupply chain (SC) adaptability (SC-Ad) implies that SC processes should change and adapt to anticipated structural and market changes. However, when these changes are related to shifts from exploitative to explorative focuses, companies face an inflexibility problem because of involved uncertainties, creating a barrier to obtaining SC-Ad. This research proposes to overcome this barrier by integrating new combinations of the product/market strategy and SC processes and securing their fit over time. To get it, this study proposes two SC-Ad drivers (related to the SC process (ASCOS) and new product development competences (PDC)), which secure the aforementioned fit by reducing its uncertainties and thus ensuring a SC-Ad that responds to emerging competitive changes. Measurement and structural models were assessed following PLS-SEM. ASCOS and PDC’ relative importance was analyzed using the importance/performance/analysis procedure. PLS, PLS-predict, and CVPAT were used to analyze model’s in-sample and out-of-sample predictive capacity. ANOVA was used to compare SC-Ad, ASCOS and PDC in different plant groups. Results suggest that ASCOS and PDC are SC-Ad’s drivers, and that the plants with highest SC-Ad values are those with the higher ASCOS and PDC’ values. This expand knowledge about SC-Ad drivers, which represents an important literature gap. In an indirect way, some new light is also added to the topic of ambidextrous management. The adequate generalizability of these results is supported by a) a wide multi-country, multi-informant, and multi-sector sample of 268 plants, b) a good out-of-sample model predictive capacity c) no heterogeneity issues.

Comparative Analysis of Fake Product Identification System Using Blockchain Technology

Fictitious products have emerged as a substantial challenge in the manufacturing sector, inflicting adverse consequences on a company's financial health, reputation, and overall prosperity. Thankfully, blockchain technology provides an effective remedy for discerning fake items and verifying the legitimacy of authentic ones, all within a decentralized and widely distributed digital ledger. Quick Response (QR) codes serve as pivotal tools in the fight against fictitious goods, as each product is now furnished with a QR code that acts as a direct bridge to the blockchain system, essentially bestowing each item with a digital identification card. QR code scanners communicate with the blockchain to promptly validate whether a product is genuine or fictitious. Moreover, customers can harness this technology to track a product's journey through the supply chain and authenticate ownership details, akin to a digital breadcrumb trail that securely preserves product information and unique codes as database blocks. Considering the globalized business landscape and the perpetual advancements in technology, industrial manufacturers and distributors are wholeheartedly committed to optimizing their supply chain processes, ensuring they remain one step ahead of fictitious product proliferation and fortifying their operations against the dissemination of spurious items. In this paper we compare Different Fake product identification Methods like Barcodes, QR Codes, RFID Tags, Serial numbers with methods using Blockchain technology which is having high security, transferability & traceability throughout Supply Chain.

Economic Supply Chain Management System of Farm Products Industry Based on the Belt and Road Under the Background of Big Data

Under the strategic background of "One Belt, One Road", the future farm products industry will also become part of the country's core competitiveness. Promoting the transformation of enterprises in the supply chain is conducive to cultivating the country's core competitiveness and creating good output conditions for my country's manufacturing industry. Under the national strategy of "One Belt, One Road", the agricultural product industry is facing new development opportunities. This paper analyzes the background, significance and existing basic problems of the "One Belt, One Road". Starting from the economic development of the national agricultural product industry, it uses the cluster analysis algorithm to analyze the current overall economic situation of the agricultural product industry, points out the current problems in the industry, and believes that the future farm The product industry is facing greater pressure for transformation and upgrading. Finally, combined with the strategic background of "One Belt One Road", from the perspectives of society, government and enterprises, analyze its supply chain process, extract relevant problems, and put forward relevant countermeasures and suggestions from the perspective of intra-chain, extra-chain and their interactive integration .

Integrated management of abatement technology investment and resource extraction

As the need for increased renewable energy generation to meet climate goals grows, so does the demand for critical minerals in the industrial sector. This raises concerns about the availability of supply and the reliability of investment in critical minerals. Based on this, the study proposes an analytical framework for the integrated management of mineral extraction and renewable energy investments. Different from the previous strategy of separate management, this study has established an integrated model that utilizes new energy technology as the downstream application of emission reduction technology. It also utilizes copper, zinc, aluminum, rare earth elements, and other materials as the upstream raw material supply. In terms of minimizing costs, the entire supply chain process is optimized to achieve an empirical case. In addition, considering the significant uncertainty in the process of reducing emissions from new energy technologies, this study also incorporated a forward control stochastic programming method to model and solve it. We obtained confidence intervals for optimal technological investment paths and metal mining paths under various scenarios. Our findings indicate that: (1) Biomass, as a renewable energy technology with the lowest resource demand, should be prioritized for development. However, there is significant uncertainty surrounding the installed capacity of photovoltaics. (2) Copper ore reserves have little impact on the development of renewable energy technologies, while zinc ore and aluminum ore have a greater impact on wind energy and photovoltaics, respectively. (3) By optimizing the cut-off ratio of raw ore under a specific amount of ore storage, we can ensure the availability of materials needed for downstream energy technology.