Today's Supply Research Articles

Analysis of Food Supply Chain Process by Block Chain Based Approach

The developments in technology and the emergence of new technologies have increased the expectations for the supply chain to have a more efficient, traceable and transparent structure. Although the legal regulations and standards of blockchain technology have not been clearly revealed yet, it is thought that it will solve many problems with its application in the food supply chain. In this context, the use of blockchain technology in the food supply chain, its advantages and disadvantages and today's application examples were examined by making a literature review. As a result of the study, it has been seen that blockchain technology provides significant added value to the food supply chain and is a solution to many problems of today's traditional supply chain.

Honey Badger Algorithm Based DVR Controllers for Improved Power Quality‏ in a Microgrid Combined of (Wind System\ Grid\Nonlinear Load)

Power quality (PQ) is crucial in today's energy supply networks, where even little voltage fluctuations can have a big impact on how well household appliances and technologies operate. The suggested dynamic voltage regulator (DVR) approach helps to create a new generation power grid that is more dependable and effective. In this study, the honey badger optimizer (HBO) is used to optimize the controllers of the DVR for improving PQ via voltage control. The efficacy of the optimized DVR is further increased by its integration with a microgrid (MG) wind supply. The suggested technique makes use of a low-complexity control approach for voltage regulation to adjust for harmonic distortion, swells, and voltage dips in the addressed system. The technique accomplishes voltage improvement, bus stabilization, energy-efficient utilization, and harmonic distortion reduction by using the DVR in conjunction with an MG wind supply. Various voltage disturbances, such as balanced and unbalanced swell and sag, voltage imbalance, notching, various fault states, and power system harmonic distortion, are taken into consideration to show the approach's usefulness. The findings indicate PQ enhancement, demonstrating that the load voltage roughly matches the nominal value.

Risk Management in Global Supply Chains: Addressing Vulnerabilities in Shipping and Logistics

This paper explores the critical aspects of risk management in global supply chains, with a specific focus on vulnerabilities within shipping and logistics. The interconnected nature of today's supply chains exposes them to various risks, ranging from natural disasters and geopolitical tensions to operational challenges and cybersecurity threats. The paper outlines a comprehensive framework for risk identification, assessment, and mitigation, emphasizing the importance of proactive strategies in addressing potential disruptions. Diversification of suppliers and transportation routes, technological investments, insurance coverage, and enhanced collaboration are highlighted as key mitigation measures. Through case studies, the paper examines successful risk management practices and draws insights from failures. Additionally, it delves into emerging trends, such as technological advancements and climate change adaptation, providing a forward-looking perspective on evolving risks. The conclusion underscores the dynamic nature of global supply chain risks and advocates for continuous improvement in risk management practices to ensure resilience and sustainability.
 Keywords: Risk Management, Global, Supply Chains, Vulnerabilities, Shipping and Logistics.

E-FARMER Agriculture and Rural Development Using Block Chain Technology

The efficiency, validity, and health of many essential criteria in the food and agricultural supply chain are receiving more attention as a result of the globalisation of industrial and agricultural production. Due to the increasing risks to food safety and corruption, there is a great need for effective traceability solutions. These solutions serve as crucial quality management tools, guaranteeing the safety of the products across the agricultural supply chain. Block chain is a cutting-edge technological approach that yields groundbreaking results for commodity traceability in food supply chains and agriculture. Today's agricultural supply chains are intricate ecosystems that involve a number of stakeholders, making it challenging to validate a number of important needs, mostly related to yield monitoring, crop growth stages, compliance with quality standards, and the nation of first origin. In order to manage crop prices and traceability, this study suggests a system that levitates the block chain and efficiently executes business operations across the agricultural supply chain. The suggested framework method improves effective science and safety with high integrity and dependability by doing away with the necessity for intermediaries, centralised authorities, and records of the transactions. All transactions are first recorded, after which they are kept in the immutable ledger of the block chain and connected to a decentralised network. This ensures a robust, dependable, and effective supply chain ecosystem with a high degree of traceability and transparency. Keywords: Blockchain technology, Agriculture, Supply chain, Traceability, Food safety.

Evaluation and prioritization of barriers to the implementation of the eco-regenerative supply chains using fuzzy ZE-numbers framework in group decision-making

<p>In today's supply chain management, there is a growing emphasis on transitioning to environmentally sustainable practices. This paper aimed to identify and rank the barriers to the implementation of eco-regenerative supply chains. A novel integrated approach was proposed based on stepwise weighted assessment ratio analysis (SWARA) and the multi-attributive border approximation area (MABAC) method using ZE-fuzzy numbers. This approach aimed to address some of the limitations of the failure mode and effects analysis (FMEA) method, including lack of thorough prioritization and inability to make decisions about the importance of various failure factors in an uncertain environment. By combining fuzzy sets and considering the reliability levels of two distinct groups of decision-makers and experts, this proposed method offers a comprehensive evaluation framework. Following the determination of the risk priority number (RPN) by the FMEA method, risk factors were evaluated using ZE-SWARA, and barriers were ranked using the ZE-MABAC method to identify critical barriers and propose corrective actions. Furthermore, sensitivity analysis was conducted in this study to demonstrate the viability of the proposed method. This research contributes to the advancement of eco-regenerative supply chain management practices by offering a systematic and innovative approach to addressing environmental concerns and improving decision-making processes in uncertain environments.</p>

Development of SCOR Database for Digitalisation of Supply Chain Customer Feedback Analysis

High-level customer service, with improved quality at a lower cost, is imperative in today's global supply chain, where customers have myriad options across borders. This is in line with the primary objective of supply chain management, which is to enable and deliver high-level customer service with lower costs, reduce lead time, and improve the quality of products/services. The Supply Chain Operations Reference (SCOR) model based on KPI metrics enables an increase in the quality of products/services by monitoring and digitalising involved processes. The current paper suggests the structure of the SCOR database for Supply Chain process improvement by applying the best practices of the SCOR for Business Processes improvement. We recommend the Bayesian Belief Network (BBN) and Case-Based Reasoning (CBR) methods to estimate the influence of these improvements on Supply Chain efficiency through key performance indicators before implementation. Integrating the methods proposed in this article focuses on an approach that minimises supply chain failures, decreases failure elimination time, understands consumer needs, and offers more accurate price proposals and lead times to improve customer satisfaction. Accordingly, the integrated SCOR-based Business Process Modelling (BPM) was not previously combined with BBN to identify the most efficient ways to improve the reliability of a Supply Chain by applying best practices, which impacts the entire supply chain. Our research is limited to SME companies in electronics manufacturing, but our ambition is to develop a universal framework suitable for broader areas. The study aims to analyse how the customers see the company by combining the CDA (Customer Delivery Accuracy) and Customer Complaints measures and find the optimal way to improve business processes by applying best practices. Still, it is limited to SCOR reliability performance metrics.

Does Resilience Matter for Supply Chain Performance in Disruptive Crises with Scarce Resources?

AbstractIn today's disruptive world, firms and supply chains are facing massive disruptions, primarily owing to resource scarcity. We develop a model supported by the resilience and resource‐based theories to assess supply chain decision‐makers in the United States. We validate the model by employing partial least squares structural equation modeling and fuzzy set qualitative comparative analysis. We find that supply chain agility and flexibility can support supply chain resilience, which in turn sustains supply chain performance. Furthermore, we find a mediation effect of supply chain resilience in the relationship between agility and supply chain performance, as well as between flexibility and supply chain performance. Furthermore, the findings suggest that supply chain performance under severe disruptions can be achieved when supply chains are resilient based on the combination of agility and flexibility. Our study contributes to the supply chain resilience and resource‐based theory literature by identifying that resource configuration plays a decisive role in resilience and performance in severe disruptions due to resource scarcity. Our findings suggest that not all resilience‐related resources are necessary to build resilience and support performance. Therefore, when confronted by a disruptive crisis, managers, practitioners and policymakers should identify the best resource configurations to create resilience and support performance.

Cooperation, coordination, or collaboration? A structured review of buyers' partnerships to support sustainable sourcing in supply chains.

The growing need of today's global supply chains for a paradigm shift to sustainability requires all supply chain members to establish partnership relationships. However, the existing literature fails to provide a comprehensive understanding of these partnerships. The present research contributes to understanding the nature and structure of the buyers' partnerships for enhancing sustainable sourcing. A structured review methodology is adopted to collect information about supply chain partnerships from the literature on sustainable sourcing. Then, a content analysis is conducted on the collected information using a comprehensive partnership framework, i.e., theMcNamara framework. The framework suggests ten interconnected facets to characterize the structure of a partnership and classifies the nature of partnerships into three categories called cooperation, coordination, and collaboration. The findings indicate that cooperative partnerships are not effective for promoting sustainable sourcing as they lack the exchange of resources between the participating organizations. In contrast, coordinative partnerships are mainly effective for tactical and operational initiatives to address reactive, end-of-pipe solutions for sustainable sourcing. Finally, collaborative partnerships should be mainly initiated at the strategic level to design proactive solutions for sustainable sourcing. Some practical implications are provided to facilitate the transition of supply chains to sustainability. Some open questions for future research are also provided.

Economic damages of food-safety incidents in complex markets: 2018 E. coli outbreak and romaine lettuce

Food-safety incidents are costly for everyone in the leafy greens industry. However, it is challenging to estimate the size and distribution of these costs in today's complex supply chains. Extensive use of formal contracts in markets such as leafy greens obscures prices and other terms of trade from the public view. Using proprietary data on prices and sales from a major leafy greens processor operating in the retail and food-service sectors, we are able to separately estimate short-run damages associated with the November 2018 romaine Escherichia coli advisory for growershippers, processors, retailers, and food-service operators. Due to fixed prices in grower-processor contracts, growers were only minimally impacted by the advisory. Processors, meanwhile, lost approximately $55.3 million from price and quantity impacts. Retailers incurred $14.1 million in losses after pulling product from distribution channels and shelves. Foodservice operators were less impacted because lower prices offset losses from destroying potentially contaminated products. Moving forward, the best way to mitigate losses during food-safety incidents is fast and efficient traceability.

Medical supply chain integrated with blockchain and IoT to track the logistics of medical products.

Nowadays blockchain technology plays a vital role in creative developments and important discoveries in the world. Blockchain develops secure and trustworthy platforms for data sharing in various application areas such as secure sharing of medical data, Anti-money laundering, tracking systems, Supply chain, and logistics monitoring, Crypto-currency exchange, etc. Today's Supply chain in the healthcare sector faces many problems like security, transparency, tampering with medical products, counterfeit drugs, more paperwork, high cost, and more time-consuming process while transporting medical equipment from manufacture to end-users. To overcome these problems, we introduce Novel Approach for Integrated IoT (Internet of Things) With Blockchain in Health Supply Chain (NAIBHSC) approach. By using this approach, we can eliminate all supply chain-related issues between suppliers and end-users. The goal of this research is by combining Blockchain technology with IoT to develop a smart health supply chain management system. This approach provides security, privacy, trust, visibility, decentralized tracking and tracing of the medical product, avoids counterfeit drugs, avoids the damage to medical components, authentication, reduces the cost, and provides the status of the products during the shipment process between manufacturers to end-user. In this approach, we conduct a series of experiments on a different group of users. The experimental results show that compare to existing approaches our proposed NAIBHSC approach gives better response time that is the average Transaction Per Second (TPS) for a group of 500 users is 100 milliseconds, reduces the latency time that is average latency time for 500 users group has 403 milliseconds, and improves the overall performance of the smart health supply chain management system.

Toward Understanding Today's Supply Chain Problems: A System Thinking Approach

Toward Understanding Today's Supply Chain Problems: A System Thinking Approach

Toward understanding today's supply chain problems: a system thinking approach

Toward understanding today's supply chain problems: a system thinking approach

A mixed methods approach to analyze and predict supply disruptions by combining causal inference and deep learning

In today's complex supply networks, disruptions caused by diverse events represent major unknown operational conditions and risk factors requiring research on supply chain risk management. Hereby, operations management (OM) researchers are traditionally focusing on defining analytical and mathematical risk mitigation strategies characterized by a variety of different constraints, such as capacities, timeliness, or relations, leading to limited transferability into practice. Given the complexity of modern supply chains we argue that a data-driven approach to supply chain risk management enhances the assessment and comparability of risk mitigation strategies. Thereby an approach that allows conclusions about causal relationships between supply chain interventions and potential outcomes is of particular importance. Inspired by deep learning as well as causal learning theory and following a design science research approach, we design an analytical model that can predict supply disruptions based on external and internal data and quantify causal effects on delivery reliability. The model is evaluated in a single case study using data from a large first tier automotive supplier. The results show that the model has a high predictive performance and can learn causalities from observed data and analyze interventions effecting supply disruptions. The identification of causal relationships offers the potential to identify lacking supplier relationships and consequently bundle supply chain risk management activities. Building on the empirical and analytical insights, we discuss implications for both theory and practice.

Efficacy of Electronic Monitoring

The use of electronic performance monitoring is becoming increasingly widespread in conjunction with the digitalization of today's supply chains, yet the efficacy of these systems to improve desired performance outcomes is still highly uncertain. This study examines the effect of a federal regulation mandating the adoption of electronic data logging devices for commercial truck drivers in late 2017 and the efficacy of this regulatory effort in improving safety through an analysis of motor vehicle fatalities pre- and post-mandate. Results of a difference in difference estimation show the ELD mandate failed to reduce motor vehicle fatalities, and, in fact, may have increased overall fatality rates. These findings suggest that the expected benefits of electronic monitoring are likely to be highly contingent on proper design and implementation and a failure to consider the broader effects may lead to negative outcomes.

Streamlined approach for assessing embedded consumption of lithium and cobalt in the United States

AbstractIn today's complex global supply chains, time and data intensive analyses are required to understand global flows of mineral commodities from mine to consumer, particularly for mineral commodities in products (electronics, automobiles, etc.) that contain multiple parts with many mineral commodities. National and regional analyses require additional time and data to incorporate international trade flows. However, data limitations and time constraints often prohibit global and national material flow analyses for minor metals. Here we present a methodological approach to circumvent these constraints by utilizing readily available industry‐level global data from the United Nations Statistics Division and national industrial data to estimate total requirements for a mineral commodity. We apply this approach to lithium and cobalt use in the United States for the year 2018 and distinguish between apparent raw material consumption versus inferred embedded consumption of lithium and cobalt materials in all forms. The results show that more than half of the United States’ total requirements for both lithium and cobalt is in parts and products that were manufactured outside the United States. In large part, this is due to limited US manufacturing capability for lithium‐ion battery materials and cells and the United States’ high import reliance for electronics that use those batteries.

A Critical Review of Off Shoring Decision Making and Operationality in SMEs

In today's global supply chains, which are complex, innovative, and competitive, outsourcing and offshoring have emerged as one of the most important and essential strategic initiatives. Among the long-term business initiatives taken by companies, this is one of the most prominent trends. Despite disagreements about outsourcing's effects on businesses, the practice continues in many companies. Companies of all sizes are increasingly relocating some of their manufacturing and sourcing operations overseas. Despite this, there is a dearth of research that focuses on offshoringdecision-makingprocedure as pertains to Small Medium-sized Enterprises (SMEs). We surveyed French SMEs to learn how company size affects the outsourcing process, and we found that SMEs offshore a comparable share of procurement to larger organizations, though they tend to focus on fewer countries. We also showed that smaller businesses are not as well-equipped to make informed decisions about offshoring as larger ones are because they have less information about foreign countries.

Generation of Power Quality Disturbances Required for the Performance Assessment of Different Power Quality Monitoring Algorithms using Multiple Approaches

This paper presents multiple approaches for the generation of Power Quality Disturbances (PQDs) and the development of the dataset required for evaluating the effectiveness of various PQDs detection and classification algorithms. In today's power networks, power quality is an important issue. Three PQDs, namely the voltage sags, swells, and interruptions, are considered under study in this research paper. In today's electricity grid, these PQDs are thought to be more prevalent and common. Today's end-users demand high-quality supply for the operation of their sensitive equipment. The utility must keep an eye on PQ and take the required actions to maintain it in order to deliver a supply of high quality. The creation of reliable and efficient PQ monitoring algorithms is a major goal for many budding researchers. The PQD signals or dataset of PQDs are required for the development and performance assessment of these PQ monitoring algorithms. The different approaches available for the generation of PQDs and dataset are discussed in detail in this research paper. This research work focuses on generating PQDs through the use of MATLAB programming, simulation of PQD models in the MATLAB Simulink environment, and experimental methodology. This paper will serve as a useful resource for budding researchers working in the PQ domain.

Capture, Storage, and Release of Oxygen by Metal–Organic Frameworks (MOFs)

AbstractOxygen is a critical gas for medical and industrial settings. Much of today's global oxygen supply is via inefficient technologies such as cryogenic distillation, membranes or zeolites. Metal–organic frameworks (MOFs) promise a superior alternative for oxygen separation, as their fundamental chemistry can in principle be tailored for reversible and selective oxygen capture. We evaluate the characteristics for reversible and selective uptake of oxygen by MOFs, focussing on redox‐active sites. Key characteristics for separation can also be seen in MOFs for oxygen storage roles. Engineering solutions to release adsorbed oxygen from the MOFs are discussed including Temperature Swing Adsorption (TSA), Pressure Swing Adsorption (PSA) and the highly efficient Magnetic Induction Swing Adsorption (MISA). We conclude with the applications and outlooks for oxygen capture, storage and release, and the likely impacts the next generation of MOFs will have on industry and the broader community.

Capture, Storage, and Release of Oxygen by Metal-Organic Frameworks (MOFs).

Oxygen is a critical gas for medical and industrial settings. Much of today's global oxygen supply is via inefficient technologies such as cryogenic distillation, membranes or zeolites. Metal–organic frameworks (MOFs) promise a superior alternative for oxygen separation, as their fundamental chemistry can in principle be tailored for reversible and selective oxygen capture. We evaluate the characteristics for reversible and selective uptake of oxygen by MOFs, focussing on redox‐active sites. Key characteristics for separation can also be seen in MOFs for oxygen storage roles. Engineering solutions to release adsorbed oxygen from the MOFs are discussed including Temperature Swing Adsorption (TSA), Pressure Swing Adsorption (PSA) and the highly efficient Magnetic Induction Swing Adsorption (MISA). We conclude with the applications and outlooks for oxygen capture, storage and release, and the likely impacts the next generation of MOFs will have on industry and the broader community.

Comparative Life Cycle Evaluation of the Global Warming Potential (GWP) Impacts of Renewable Natural Gas Production Pathways

Renewable natural gas (RNG) sources are being considered in future energy strategy discussions as potential replacements for fossil natural gas (FNG). While today’s supply of RNG resources is insufficient to meet U.S. demands, there is significant interest in its viability to supplement and decarbonize the natural gas supply. However, the studies compare the life cycle global warming potential (GWP) of various RNG production pathways are lacking and focus mostly on a singular pathway. This effort is an attempt to close this gap and provide a comparison between the life cycle GWP of three major RNG pathways and the FNG pathway. The three RNG pathways evaluated are anaerobic digestion (AD), thermal gasification (TG), and power-to-gas (P2G) using various feedstocks. The functional unit is 1 MJ of compressed RNG ready for injection into the natural gas transmission network. The results show that RNG production is not always carbon neutral or negative. Depending on the pathway, the GWP impact of RNG production can range from −229 to 27 g CO2e/MJ compressed RNG, with AD of animal manure and AD of municipal solid waste being the least and the most impactful pathways, respectively, compared to the 10.1 g CO2e/MJ impact for compressed FNG.