A framework of the risk assessment for the supply chain of hazardous materials

The global effort to curb carbon emissions is accelerating demand for clean energy technologies and the materials they rely on. Demand for these materials will only continue to grow, especially as some nations aim to achieve net zero emissions by 2050. While some major materials like steel, copper, and aluminum are already powering the fossil fuel economy, others are more minor materials with potential supply risks. These risks could jeopardize the ability to reduce greenhouse gas emissions within the desirable timeframe to avoid significant climate change. In some cases, it may be necessary to take action to improve the resilience of material supply chains and mitigate supply risks. Understanding the importance of individual materials to clean energy and the supply risks associated with them is necessary to identify which materials may serve as potential roadblocks to a clean energy future. The U.S. Department of Energy (DOE) issued a series of 13 supply chain deep dive assessment reports on various energy technologies in 2022 in response to President Biden’s Executive Order on America’s Supply Chains (E.O. 14017). These reports emphasized that supply chain bottlenecks can occur at any stage of the value chain from mining and refining to component and even sub-system manufacturing. The bottlenecks are a combination of factors such as material availability, equipment availability, work force availability and quality, logistics, regulatory framework, and market conditions. These bottlenecks were worsened during the global Covid-19 pandemic. Its lingering impacts have hindered capacity expansion for material supply chains and prevented product lead-time recovery. One approach to reduce supply chain risks for the United States is to have a strong domestic manufacturing sector with a diverse set of producers. Boosting responsible domestic production would require leveraging the latest science not only in material extraction but also in developing substitutes, recycling, reuse, and remanufacturing. This report is an updated analysis of previous Critical Materials Strategy (CMS) reports published by the DOE in 2010, 2011, and 2019 based on national and global priorities, technology advancement, and technology adoption trends. Like the CMS reports, this analysis presents the results of a formal material criticality assessment to identify which materials are critical to the continued deployment of clean energy technologies globally. The analysis in this report leveraged the DOE supply chain deep dive assessments to develop the initial list of materials to evaluate. This DOE Critical Materials Assessment (CMA) is conducted independently of criticality assessments performed by other U.S. government agencies, such as that conducted by the U.S. Geological Survey (USGS). This analysis complements the USGS critical minerals determination in three aspects. First, the DOE assessment is performed from a global perspective, while the USGS analysis focusses on the importance of minerals to the U.S. economy. Second, this report focuses on the importance of materials to clean energy technologies, rather than to the economy in general. Lastly, this study is forward looking to 2035 based on clean energy deployment scenarios, whereas the USGS assessment is retrospective. Materials evaluated in this report that do not appear in the USGS Critical Minerals List include copper, uranium, electrical steel, and SiC. A draft version of this report received ~80 public comments related to supporting data and methodological improvement. Those comments have been incorporated as much as possible where appropriate. Highlights of findings from this 2023 CMA include: Rare earth materials (neodymium, praseodymium, dysprosium, and terbium) used in magnets in electric vehicle (EV) motors and wind turbine generators continue to be critical. While dysprosium (Dy) and terbium (Tb) are both heavy rare earth elements that serve the same function in magnets, the criticality of Tb is slightly lower than that for Dy in the short term due to the widespread use of Dy in high-grade magnets and Tb’s present role as a substitute. Similarly, praseodymium (Pr) is critical in the medium term but only near critical in the short term because it is more substitutable in magnets than neodymium (Nd); Materials used in batteries for EVs and stationary storage are now considered to be critical. While cobalt (Co) was found to be critical in this and previous reports, lithium (Li) becomes critical in the medium term due to its broader use in various battery chemistries and the rampant growth of the EV industry. Natural graphite is a new addition in this assessment and is also found to be critical; Platinum group metals used in hydrogen electrolyzers, such as platinum (Pr) and iridium (Ir), are critical due to an increased focus on hydrogen technologies to achieve net zero carbon emissions, while those used in catalytic converters, such as rhodium (Rh) and palladium (Pd), were screened out due to the decreased importance of catalytic converters in the medium term; Gallium (Ga) continues to be critical due to its use in light-emitting diodes (LEDs). In addition, the use of Ga has increased in magnet manufacturing and in semiconductor in forms such as gallium arsenide (GaAs) or gallium nitride (GaN); Major materials like Aluminum (Al), copper (Cu), nickel (Ni), and silicon (Si) move from noncritical in the short term to near critical in the medium term due to their importance in electrification; Electrical steel is near critical due to its use in transformers for the grid and electric motors in EVs.

As an important component of railway intelligent construction, the intelligent management platform for material supply chain is an integrated platform for material management in intelligent construction and an inevitable trend for the continuous development of the full-process information management of railway engineering material supply chain. This paper analyzes and proposes the architecture of the full-process information management system for the material supply chain, and develops an intelligent management platform for the material supply chain. The main functions include the coding and identification system, intelligent supply and demand matching of materials, procurement management, in-transit tracking management, intelligent warehouse management, collaborative dispatching management, and analysis and decision-making management. The research results show that the full-process information management of the railway engineering materials supply chain is oriented towards the main process of project implementation, conducting real-time control over the life cycle of engineering materials, achieving full-process coordinated dynamic management and dispatching command among all participating construction units and supply units, and improving the multi-level and multi-dimensional intelligent analysis capabilities of discrete business data. Support the continuous development of dynamic control throughout the entire process of railway engineering construction materials.

Construction materials play a crucial role in the project delivery process. However, the process of requisition for the materials on construction site if not handled appropriately can adversely affect the performance of quality, cost, and time. Therefore, the study was aimed at developing an automated materials requisition system which will make the supply chain on construction sites seamless and more effective. A use case diagram and an activity block diagram helped to understand the users and functionalities of the material requisition platform. In addition, using different user interface and a database system including a programming language to connect them, the study developed an automated Web-based material requisition system for construction firms using the model view controller (MVC) model. The MVC model comprised of using MySQL, HTML, and PHP, respectively, in the design. The automated materials requisition system was tested by sending material requisition through the supply chain of a construction firm. Result of the automated system was presented via screenshots of the Web-based platform. In conclusion, any construction firm can register on the platform and make use of the automated materials requisition system in order to maximize the productivity and optimize the use of ICT in their materials’ supply chain process.

Introduction to Hazardous Materials Hazard Defined Ancient Hazards The Industrial Age The Recent Past Toxicology and Health Effects of Hazardous Materials Introduction Routes of Exposure Body Response to Toxic Chemicals Varieties of Toxic and Hazardous Effects Specific Contaminant Effects Dose-Response Relationships Allowable Exposure Limits Time Effects and Sensitivities Sources of Health Effects Information Risks and Risk Assessment Introduction Types of Risks The Risk Assessment Process Uncertainties in Risk Assessments California Approaches Criteria for Health Impact and Acceptable Risks Screening Level Calculations Risk Management Air Pollution and Air Toxics Introduction Classifications and Sources Direct Evaporative Emissions Fugitive Emissions Waste-Related Air Toxic Emissions Treatment-Related Emissions Regulatory Approaches Hazardous Air Emission Trends Soils and Groundwater Introduction Principles of Hydrogeology Groundwater Movement Contamination in Groundwater Mitigation and Treatment Treatment Approaches Biological Treatment Methods Physical Treatment Methods Chemical Treatment Methods Combination Systems Natural Methods and Attenuation Transportation of Hazardous Materials Introduction Laws Involved in Hazardous Materials Transportation Hazardous Waste Transportation Regulations Key Elements Practical Aspects of Hazardous Materials Transportation Trends in Transportation Incidents Management of Hazardous Materials Introduction Proactive Hazardous Materials Management General Considerations A Specific Management Approach: The Aerospace Industry Hazardous Materials Planning for the Future Proactive Emergency Planning Waste Characterization and Analytical Methods Introduction Representative Sampling EPA Reference Methods Sampling and Handling Units of Measurement and Physical and Chemical Properties Fundamentals of Chemistry for Sample Analysis Matrices and Detection Limits Analytical Methods and Techniques Waste Treatment and Disposal Introduction Materials Recovery Basic Treatment Principles Treatment Classes Ultimate Residuals Management Appendix A: Federal Regulatory Approaches Appendix B: California Approaches Appendix C: Hazardous Materials Definitions

Background: The supply chain risk management (SCRM) process is aimed at the implementation of strategies that assist in managing both daily and exceptional risks facing the supply chain through continuous risk assessment to reduce vulnerability and ensure continuity.Purpose: The purpose of the study was to determine whether the SCRM process enables supply chain resilience among grocery manufacturers in South Africa. The fast-moving consumer goods (FMCG)-manufacturing industry faces increased risk because of the nature of their products being perishable with a limited shelf life.Method: This study was conducted using a descriptive qualitative research design. Data were collected by means of 12 semi-structured interviews with senior supply chain practitioners within the South African grocery manufacturing industry.Findings: The study found that most firms informally implement SCRM processes of risk identification, assessment, mitigation and monitoring to mitigate disruptions. Furthermore, the findings indicate that the SCRM processes facilitate resilience among grocery manufacturers in South Africa.Conclusion: The managerial implications show that supply chain managers of grocery manufacturers should formalise the SCRM process and develop risk assessment scales to better prioritise risks in order to run a resilient supply chain. The research contributes to the supply chain management field by adding to the scarce literature relating to SCRM as an enabler of supply chain resilience in a South African context.

The transportation volume of hazardous material is increasing, and the potential risk of hazardous material for environment and mankind is enlarging. How to select the best transportation route, insure transportation safety and reach destination rapidly is an important problem for decision department. The transportation route decision-making method of hazardous material is put forward in this paper. A scientific and reasonable transportation route is the essential condition to ensure the hazardous material transportation safety. On the foundation of considering the factors which affecting the hazardous material safety, a new evaluation index system is set up, and a new evaluation model is established based on particle swarm optimization algorithm and BP neural networks. The example shows that the new evaluation index system is scientific and the new evaluation model is feasible. The decision making methods of hazardous material can help the government supervision and management department choose the best route.

Planning is crucial to an organization whether it is required for the execution of manufacture, repair and overhaul, or another aspect of the engineering supply chain. It is particularly important to the aerospace and defence industry because the supply chain for materials, parts and processes may now stretch around the globe. Planning and controlling this invariably complex set of relationships places considerable demands on both human and IT resources. Additionally, other developments are pushing existing planning systems to their limits. Outsourcing is a case in point, where organizations are increasingly focusing on their core business and delegating the responsibility for specialized requirements to external suppliers with more appropriate or cost‐effective resources.

Optimal supply chain design depends on the business context the chain caters for. In this dissertation, we are concerned with attaining and maintaining this alignment between a firm's supply chain portfolio and its business context. Following an introduction in Chapter 1, in Chapter 2 of this dissertation, we analyze the influence of a firm's product types on optimal supply chain design: Academics and practitioners agree that functional products are best delivered via physically efficient supply chains, while innovative products are best delivered via market responsive chains. However, to date, only a few firms have systematically adjusted their supply chain strategies according to this argument. Instead of carrying only one product type, firms deliver a number of both functional and innovative products in parallel complicating the alignment of supply chain portfolios with product portfolios. We address this issue and analyze in detail a firm's optimal supply chain portfolio as a function of its product portfolio. We target the tactical level of decision-making and develop a generic mathematical model to analyze how product portfolios affect the optimal setup of supply chain portfolios. We identify generic problem properties and perform extensive sensitivity analysis to illustrate our findings with numerical examples. Our results indicate that effective supply chain and product portfolio alignment holds the potential for significant cost savings. Because of the large number of factors influencing the optimal set-up, however, profound quantitative analysis is required to exploit the full potential of aligning the supply chain with the product portfolio and to guide implementation. In Chapter 3, we extend our modeling framework and take into account the fact that a firm's products and global business parameters, such as labor rates and transportation costs, evolve over time. Hence, firms need to adapt their supply chain portfolios frequently to stay aligned in the long term. Adapting a well-established supply chain portfolio, however, may involve high costs and expose a firm to unforeseeable risks. We address this issue, differentiating business dynamics into product portfolio dynamics and global business dynamics, and classifying supply chain adaptation into high, medium and low. Building on these classifications, we extend our mathematical model to analyze how much supply chain adaptation a firm actually requires to respond to the business dynamics it faces. Our results indicate that supply chain adaptation may indeed be crucial for a firm to retain its competitiveness. The need for adaptation, however, varies widely across firms: For example, a firm faced with product portfolio commoditization may be required to adapt its entire manufacturing footprint, while a firm with a high product turnover rate may not need to adapt its supply chain portfolio at all. Furthermore, the need for supply chain adaptation is not only determined by the business context in which a firm operates, but can also be manipulated by the firm's product portfolio decisions. Finally, a firm should carefully align its supply chain portfolio with the employed supply chain adaptation strategy to exhaust attainable benefits. In Chapter 4, we widen our scope and develop a step-by-step process to guide sustained alignment between a firm's business context and its supply chain portfolio in practice. Drawing on academic literature, insights from our quantitative models, and extensive interviews with executives from leading firms, we propose and detail four process steps. In the first step we suggest challenging the performance of a firm's current supply chain setup and identifying pressure points to evaluate how acute supply chain realignment is. As a second step we propose and detail a business context analysis to identify what a supply chain lacks and potential areas for realignment. To complement the previous analysis, in a third step, we frame and discuss generic options for long-term supply chain strategy. As a fourth step, we lay out opportunities and pitfalls during the project implementation. We conclude with recommendations on how to stay aligned in the long term. We end the dissertation with a conclusion in Chapter 5.

Forest resource information and real-time order-supply service are significant in wood fuel procurement. Section 1 defines the data sources of solid wood fuel procurement for regional power plants and their material supply chain. Section 2 presents an architecture for the order-supply process of wood fuel, and Section 3 creates an application for managing the supply chain and reporting. The system creates and uses data from different sources: a forest resource information system, wood material webstores, and enterprise resource planning (ERP). The data model, which follows the entity-attribute-value approach, is based on the annual processes of wood fuel procurement. These include wood fuel procurement planning in plants, processing of wood materials, ordering of wood fuel, and reporting. There is the view of the characteristics of PC and mobile services used by the enterprises of solid wood fuels. Reporting includes real-time information for suppliers, effectiveness of transportation and megawatt production, and spatial marking of forest nature reserves and carbon sinks.

In order to meet the Paris Agreement and EU Green Deal, the demand for critical minerals (e.g., cobalt, nickel, lithium, and rare earth elements) is growing exponentially. With their demand arise urgent concerns about the injustices of their supply chain, including concerns about labour exploitation, environmental degradation, and child labour. This literature review examines news media, blogs, governmental and NGO reports, and academic sources to assess the risk of child labour in the extraction of 34 EU-designated critical minerals, 17 of which are considered ‘strategic.’ Using a combined risk reduction and assessment framework, the study identifies high-risk minerals (cobalt, graphite, nickel, aluminium, copper, and rare earth elements) and high-risk countries (the Democratic Republic of the Congo, Mozambique, India, the Philippines, Indonesia, and Myanmar). The findings reveal the broader negative impact on communities of mining, including increased vulnerability to child trafficking and sexual exploitation. Thus, the risk of child labour does not imply its actual occurrence due to the biased undercount of child labour numbers. Recommendations include further research, raising awareness of children’s rights, supporting household livelihoods, and improving traceability in artisanal and small-scale mining to ensure a just transition.

In the rapidly evolving landscape of supply chain (SC) management, the importance of tracking services in overseeing the lifecycle from production to sale cannot be overstated. These services rely on sophisticated systems that monitor vital condition information such as temperature and humidity. However, beyond the technical and mechanical aspects, human factors play a critical role in the operational integrity of these systems. This paper introduces a novel risk assessment methodology for SC tracking, emphasizing human error alongside technological and security risks, and integrates motivation and contribution aspects into the SC risk assessment framework.Our methodology is comprehensive, exploring the strategic business and technical requirements of SC tracking systems. It uniquely extends to assess the frequency, nature, and impact of human errors, alongside considering technological aspects. We investigate how human factors interact with elements such as IoT, cloud services, and standard IT systems, potentially leading to security vulnerabilities and operational inefficiencies. By mapping these human-centric risks to key operational components, we provide a comprehensive view of potential threats in SC tracking.In an environment where standardization efforts in SC risk assessment methodologies are ongoing, our work identifies the necessity for more specialized techniques, particularly those addressing security risks related to tracking and monitoring systems. Given the distributed nature and internet connectivity of these systems, they are inherently susceptible to numerous security challenges, predominantly involving their technological equipment. This underscores the imperative for a targeted risk assessment methodology focusing on the security risks of SC tracking systems, particularly in the context of traceability services and the monitoring of the state of assets in transit.Employing well-known risk assessment standards and threat modeling guides, our methodology scrutinizes targeted IT components used in SC tracking systems, their technical characteristics, and realistic threat agents in the SC ecosystem. We aim to evaluate whether security attacks originating from SC-specific threat agents result in tangible security risks against targeted hardware and software components within SC networks.To validate our methodology, we present a proof of concept application based on a real-case scenario. This demonstration highlights the versatility of our methodology to accommodate various SC scenarios, such as food, pharmaceuticals, and cold supply chains. The primary advantage of our proposed methodology lies in its ability to integrate risk estimation with the technological attributes of typical SC tracking systems and their operational requirements, which may vary based on the type of goods and services involved.In conclusion, this paper addresses the broader challenges in developing and implementing smart SC tracking systems, with a special emphasis on the integration of human error in these technologically advanced environments. We underscore the significant influence of human factors on the reliability and security of SC tracking systems and the cost implications and potential operational disruptions caused by human factors, thereby highlighting their pivotal role in the overall effectiveness and security of SC ecosystems.

Increasing industrialization and globalization has spawned the unprecedented generation of environmental toxic and hazardous wastes. The existence of publicly known hazardous waste problems such as toxic spills, and river pollution that pose serious and very real threats to human health puts extensive pressure on the government to take an aggressive role in hazardous waste control and transportation. The main objective of hazardous waste transportation is public safety. Each government has the responsibility to ensure that hazardous materials should be transported safely for the social and economic good of the country. Hazardous waste management is now a major and urgent global concern. Various techniques, models, and guidelines for the perception of risks associated with the transport of the hazardous materials are developed. Database of the accident data are developed by transportation agencies to be used for the development of models to improve safety of hazardous waste transportation. Based on the available risk perception models, accident models, the type of hazardous material, origin/destination, and the availability of emergency response routes for their transport are properly designed. Advanced technologies, automated vehicle location system (AVL) and geographical information system (GIS) are also used for the analysis and modeling for the safe transport of hazardous materials. The purpose of this project is to present a literature review of hazardous waste materials and their impact on human health, regulations to control the movement of hazardous materials, Basel Convention and its effectiveness, treatment and disposal of hazardous materials, model developments for risk perception and management and the use of advanced technologies for safe transportation of hazardous wastes. Based on the literature review, the conclusions and future recommendations for possible improvement of the models and techniques used for safe transportation of hazardous wastes are presented.

The transportation accident of hazardous materials possibly causes heavy personnel casualties, long-term environmental pollution and huge economic losses, the public and the media are very sensitive to the accident. Selecting the reasonable transport route is of great significance for the prevention of accidents. Aiming at hazardous materials highway transportation network, this paper proposed the definition of integrated transport costs and integrated danger coefficient firstly, then the N-shortest path algorithm was used to determine the alternative transportation route parameter of hazardous materials, thirdly, the algorithm steps of finding the best transportation route were constructed through using entropy model, finally an example demonstrated the feasibility of the decision-making method. This decision-making method can help the government relevant authority and the transport enterprises choose the reasonable transportation route.KeywordsHazardous materialTransportation routeDecision-makingN-shortest path algorithmEntropy model

Maritime container supply chains (MCSCs) is exposed to various risks arising from both internal operations and the external environment, and the increasing complexity of the modern global logistics system makes the situation even worse, thus causing a significant challenge to the effective risk management of MCSCs. However, systematic studies on this topic are relatively few. In view of this, this study aims to explore and analyse various MCSC risks, develop suitable risk assessment methods, and evaluate the overall performance of MCSCs from a systematic perspective, so as to ensure the safety, reliability, and resilience of MCSCs. This research starts with the identification and classification of all possible risk factors that may be involved in an MCSC based on a comprehensive literature review, and the research results are further validated through a Delphi expert survey. The identified risk factors are then analysed, screened, and assessed in detail. The novelty of this study lies not only on the risk assessment of MCSCs under an uncertain environment from a supply chain level but also on the consideration of the impact of risk condition of each individual MCSC on the overall performance of the entire container supply network. The research results will provide useful insights and valuable information for both researchers and practitioners on the risk analysis and assessment of MCSCs, which is beneficial to different types of stakeholders involved in the maritime shipping industry. The work is also able to provide a theoretical foundation for risk-based decision making and shipping route optimisation in further work. Although the risk assessment methods are presented on the basis of the specific context in MCSCs, it is believed that, with domain-specific knowledge and data, they can also be tailored for a wide range of applications to evaluate the reliability and performance of other supply chain systems, especially where a high level of uncertainty is involved.

This chapter examines the relationship between supply chain management and quantum computing, with a particular emphasis on real-time decision-making in supply chain operations. Quantum computing offers a solution to traditional supply chain decision-making by enabling faster computations at unprecedented speeds. This technology can improve inventory management, transportation routing, and demand forecasting. However, it faces challenges in real-time decision-making due to compatibility with current technologies and hardware limitations. The chapter explores the fundamentals of quantum computing and its potential applications in supply chain management, highlighting real-time decision-making-friendly quantum algorithms and quantum-inspired optimization strategies. Despite these challenges, quantum computing offers revolutionary possibilities for enhancing supply chain flexibility and effectiveness.