The growing size and complexity of energy system optimization models, driven by high-resolution spatial data, pose significant computational challenges. This study introduces methods to reduce model’s size and improve computational efficiency while preserving solution accuracy. First, a composite-curve-based approach is proposed to aggregate granular data into larger resolutions without averaging out specific properties. Second, a general clustering method groups geographically proximate fields, replacing multiple transportation arcs with a single arc to reduce transportation-related variables. Lastly, a two-step algorithm that decomposes the sup-ply chain design problems into two smaller, more manageable subproblems is introduced. These methods are applied to a case study of switchgrass-to-biofuels network design in eight U.S. Midwest states, demonstrating their effectiveness with realistic and detailed spatial data.

Most studies in process systems engineering are applying incomplete methods when incorporating sustainability. Including sustainability is a laudable goal, and practitioners are encouraged to develop systems that promote economic, environmental, and social aspects. Ten methods that are often overlooked in performing sustainable process systems engineering are listed in this effort and discussed in detail. Practitioners are encouraged to create designs that are inherently safer, to be more complete in their identification of process chemicals used and released, to be complete in their definitions of supply chains, and to apply additional environmental impact categories. Other methods point to items that are factors in process systems engineering such as disruptive recycling, robust superstructures for optimizations, and employing complete sets of objectives. Finally, users should be aware that sustainability tools are available, which might have been outside of their awareness.

In response to the global imperative to address climate change, this research focuses on enhancing the transparency and efficiency of the Carbon Capture Utilization and Storage (CCUS) supply chain under carbon tax. We propose a decision-making framework that integrates the CCUS supply chain's optimization model, emphasizing carbon tax policies, with a blockchain network. Smart contracts play a pivotal role in automating the exchange and utilization of carbon emissions, enhancing the digitalization of the CCUS supply chain from source to sink. This automation facilitates seamless matching of carbon sources with sinks, efficient transfer of emissions and funds besides record-keeping of transactions. Consequently, it improves the monitoring, reporting, and verification processes within the CCUS framework, thereby simplifying compliance with regulatory mandates for net emission reductions and carbon taxation policies. By eliminating reliance on third-party verifiers, our blockchain-based... [more]

Plastic packaging plays a fundamental role in the food industry, avoiding food waste and facilitating food access. The increasing plastic production and the lack of appropriate plastic waste management technologies represent a threat to the environmental and human welfare. Therefore, there is an urgent need to identify sustainable packaging solutions. Circular economy (CE) promotes reducing waste and increasing recycling practices to achieve sustainability. In this work, we propose a CE framework based on multi-objective optimization, considering both economic and environmental impacts, to identify optimal packaging designs and waste management technologies. Using mixed-integer linear programming (MILP), techno-economic analysis (TEA), and life cycle assessment (LCA), this work aims to build the first steps in packaging design, informing about the best packaging alternatives and the optimal technology or technologies to process packaging waste. For the economic analysis, we consider th... [more]

Achieving worldwide sustainable development is a practical challenge that demands an efficient management of resources across their entire value chains. This practical task requires the optimal selection of pathways for extracting, processing, and transporting resources to meet the demands in different geographic regions at minimal economic cost and environmental impact. This work addresses the challenge by proposing a systematic framework for designing resource-processing networks that can be applied to resource management problems. The framework considers the integration and resource exchange within and across multiple processing clusters. It allows for the life cycle assessment of the environmental and economic impacts of the defined value chains, and design accordingly the different processing and transport systems from extraction to final use. The proposed representation and optimization model are demonstrated in a case study to assess the impact of energy transition under decarbo... [more]

Modern mechanical recycling infrastructure for plastic is capable of processing only a small subset of waste plastics, reinforcing the need for parallel disposal methods such as landfilling and incineration. Emerging pyrolysis-based chemical technologies can “upcycle” plastic waste into high-value polymer and chemical products and process a broader range of waste plastics. In this work, we study the economic and environmental benefits of deploying an upcycling infrastructure in the continental United States for producing low-density polyethylene (LDPE) and polypropylene (PP) from post-consumer mixed plastic waste. Our analysis aims to determine the market size that the infrastructure can create, the degree of circularity that it can achieve, the prices for waste and derived products it can propagate, and the environmental benefits of diverting plastic waste from landfill and incineration facilities it can produce. We apply a computational framework that integrates techno-economic analy... [more]

Critical minerals are essential to the future of clean energy, especially energy storage, electric vehicles, and advanced electronics. In this paper, we argue that process systems engineering (PSE) paradigms provide essential frameworks for enhancing the sustainability and efficiency of critical mineral processing pathways. As a concrete example, we review challenges and opportunities across material-to-infrastructure scales for process intensification (PI) with membranes. Within critical mineral processing, there is a need to reduce environmental impact, especially concerning chemical reagent usage. Feed concentrations and product demand variability require flexible, intensified processes. Further, unique feedstocks require unique processes (i.e., no one-size-fits-all recycling or refining system exists). Membrane materials span a vast design space that allows significant optimization. Therefore, there is a need to rapidly identify the best opportunities for membrane implementation, t... [more]

To mitigate the effects of catastrophic failure while maintaining resource and production efficiencies, energy systems need to be designed for resilience and sustainability. Conventional approaches such as redundancies through backup processes or inventory stockpiles demand high capital investment and resource allocation. In addition, responding to unexpected “black swan” events requires that systems have the agility to transform and adapt rapidly. To develop targeted solutions that protect the system efficiently, the supply chain network needs to be considered as an integrated multi-scale system incorporating every component from individual process units all the way to the whole network. This approach can be readily integrated with analogous multiscale approaches for sustainability, safety, and intensification. In this work, we bring together classical supply chain resilience with process systems engineering to leverage the multi-scale nature of energy systems for developing resilienc... [more]

Plastics are widely used for their affordability and versatility across many consumer and industrial applications. However, the end-of-life (EoL) management stage can often lead to releasing hazardous chemical additives and degradation products into the environment. The increasing demand for plastics is expected to increase the frequency of material releases throughout the plastic EoL management activities, creating a challenge for policymakers, including ensuring proper material segregation and disposal management and increasing recycling efficiency and material reuse. This research designed a Python-based EoL plastic management tool to support decision-makers in analyzing the holistic impacts of potential plastic waste management policies. The constructed tool was developed to reduce the complexity of material flow analysis calculations, estimating material releases, and environmental impacts. The utility of the tool was tested through the hypothetical nationwide adoption of an exten... [more]

Sustainable and economically viable plastic recycling methodologies are vital for addressing the increasing environmental consequences of single-use plastics. In this study, we evaluate the plastic waste management value for the state of Georgia, US and investigate the potential of introducing novel depolymerization methods within the network. An equation-based formulation is developed to identify the optimum supply-chain design given the geographic location of existing facilities. Chemical recycling technologies that have received increasing attention are evaluated as candidate technologies to be integrated within the network. The optimum supply-chain design is selected based on environmental and economic objectives. The designed network of pathways uses a mix of different technologies (chemical and mechanical recycling) in a way that are both economically environmentally sound.

An important measure to achieve global reduction in CO2 emissions is CO2 capture, transport, and storage. The deployment of CO2 capture requires the development of a shared CO2 transport infrastructure, where CO2 can be transported with different transport modes. Furthermore, the cost of CO2 transport can be subject to significant economies of scale effects with respect to the amount of CO2 transported, also mentioned as clustering effects. Therefore, optimizing the shared infrastructure of multiple CO2 sources can lead to significant reductions in infrastructure costs. This paper presents a novel formulation of the clustered CO2 transport network. The Markov Decision Process formulation defined here allows for more detailed modeling of non-linear, discrete transport costs and increased geographical resolution. The clustering effects are modeled through cooperative multi-agent interactions. A multi-agent, reinforcement learning-based algorithm is proposed to optimize the shared transpo... [more]

This study presents a comprehensive approach to optimizing hydrogen supply chain network (HSCN), focusing initially on Texas, with potential scalability to national and global regions. Utilizing mixed-integer nonlinear programming (MINLP), the research decomposes into two distinct modeling stages: broad supply chain modeling and detailed hub-specific analysis. The first stage identifies optimal hydrogen hub locations, considering county-level hydrogen demand, renewable energy availability, and grid capacity. It determines the number and placement of hubs, county participation within these hubs, and the optimal sites for hydrogen production plants. The second stage delves into each selected hub, analyzing energy mixes under variable solar, wind, and grid profiles, sizing specific production and storage facilities, and scheduling to match energy availability. Iterative refinement incorporates detailed insights back into the broader model, updating costs and configurations to converge upo... [more]

The (bio-)pharmaceutical industry is facing crossroads in an effort to ramp up its global capacity, while working to meet net-zero targets and to ensure continuous drug supply. Beyond geopolitical challenges faced worldwide, (bio-)pharmaceutical processes have been historically very complex to design, optimise and integrate in a global distribution network that is resilient and adaptable to changes. In this paper we offer a perspective of how Process Systems Engineering (PSE) tools can support and advance (bio-)pharma practices with an outlook towards 3-fold sustainability. The latter is considering three main pillars, namely social (drug supply), economical and environmental sustainability. We discuss PSE contributions that have revolutionised process design in this space, as well as the optimisation of distributions networks in pharmaceuticals. We do this by means of example cases: one on model-based unit operation design and a second one on sustainable supply chain networks in the... [more]

Sustainability and circular economy enclose initiatives to achieve economic systems and industrial value chains by improving resource use, productivity, reuse, recycling, pollution prevention, and minimizing disposed material. However, shifting from the traditional linear economic production system to a circular economy is challenging. One of the most significant hurdles is the absence of sustainable end-of-life (EoL)/manufacturing loops for recycling and recovering material while minimizing negative impacts on human health and the environment. Overcoming these challenges is critical in returning materials to upstream life cycle stage facilities such as manufacturing. Chemical flow analysis (CFA), sustainability evaluation, and process systems engineering (PSE) can supply chemical products and processes performances from environmental, economic, material efficiency, energy footprint, and technology perspectives. These holistic evaluation techniques can improve productivity, source mate... [more]

A green supply chain economy considering environmental, social, and governance (ESG) factors improves the chances of functional growth through minimal risk factors. The implication of sophisticated technologies such as the Industrial Internet of Things (IIoT) and the blockchain improves the optimization and evaluation of ESG performance. An IIoT-Blockchain-based Supply Chain Economy Evaluation (IB-SCEE) model is introduced to identify and reduce functional growth risk factors. The proposed model uses green blockchain technology to identify distinct transactions’ economic demands and supply distribution. The flaws and demands in the circular economy process are validated using the IIoT forecast systems relying on ESG convenience. The minimal and maximum risks are identified based on economic and distribution outcomes. The present investigation highlights the significance of ongoing ESG-conceptualized research into blockchain-based supply chain economics. Companies who recognize the bloc... [more]

Unexpected instances have posed challenges to production lines over the last few years. The latest COVID-19 global epidemic is one notable example. In addition to its social impact, the virus has destroyed the traditional industrial production system. Industry 4.0 requires adapting to changing prerequisites with adaptability. However, the next movement, Industry 5.0, has emerged in recent years. Industry 5.0 takes a more coordinated approach than Industry 4.0, with increased collaboration among humans and machines. With a human-centered strategy, Industry 5.0 improves Industry 4.0 for greater sustainability and resilience. The concept of Industry 4.0 is the interconnection via cyber-physical systems. Industry 5.0, also associated with systems enabled by Industry 4.0, discusses the relationship between “man and machine,” called robots or cobots. This paper discusses the industry 5.0 possibilities, the restrictions, and future analysis potentials. Industry 5.0 is a new paradigm change th... [more]

Sustainable energy projects in Africa are particularly vulnerable in terms of sourcing vital alternative fuels due to the complexity of sourcing processes, contract agreements and relationships between society managers or directors and supplier chain entities. These challenges can affect any phase of a sustainable project, and the losses can be as high as 3.2 EURO/GJ. In addition, there is reduced competition and fair trade, low profits and poor quality of the fuel purchased. Technology (mobile application) is one powerful tool that can solve the above challenges by controlling or managing the supply and demand of biomass-based fuels, agriculture residue, industrial waste and many more. Thus, the main objective of this study is to evaluate the feasibility of a developed digital platform to remove barriers in the trade of alternative fuels. Data collection began with the identification of the key production areas (sources) and quantities of three selected AFs. Secondly, data on the seas... [more]

The management of the supply chain for enterprise-wide operations generally consists of strategic, tactical, and operational decision stages dependent on one another and affecting various time scales. Their integration usually leads to multiscale models that are computationally intractable. The design and operation of energy hubs faces similar challenges. Renewable energies are challenging to model due to the high level of intermittency and uncertainty. The multiscale (i.e., planning and scheduling) energy hub systems that incorporate renewable energy resources become more challenging to model due to an integration of the multiscale and high level of intermittency associated with renewable energy. In this work, a mixed-integer programming (MILP) superstructure is proposed for clustering shape-based time series data featuring multiple attributes using a multi-objective optimization approach. Additionally, a data-driven statistical method is used to represent the intermittent behavior of... [more]

To meet climate policy goals, it will be necessary to deploy a series of low-carbon energy technologies, including nuclear power. The small modular reactor (SMR) can potentially support climate change mitigation and energy security issues. Small modular reactors (SMRs) are gaining popularity; however, one crucial debate is whether SMRs can compete economically with conventional nuclear reactors or not. From a commercial point of view, SMRs will be able to provide process heat in various industrial applications, replace older nuclear, natural gas, and coal power facilities, and serve smaller energy markets with less established infrastructure. Realizing these advantages would rely heavily on the near-term quick up-scaling of SMRs; this paper, then, examines and identifies some of the most hindering constraints and barriers for the quick deployment of SMR such as the technology choice, licensing, economy of scale and financing, public acceptance, supply chain, and proliferation. A clear... [more]

Electric vehicles (EVs) have been garnering wide attention over conventional fossil fuel-based vehicles due to the serious concerns of environmental pollution and crude oil depletion. In this article, we have conducted a systematic literature survey to explore the battery raw material supply chain, material processing, and the economy behind the commodity price appreciation. We present significant areas of concern, including resource reserves, supply, demand, geographical distribution, battery reuse, and recycling industries. Furthermore, details of the battery supply chain and its associated steps are illustrated. The authors believe the presented study will be an information cornerstone in boosting manufacturing and understanding the key components and materials required to facilitate EV battery production. Further, this study discusses the major industries, and their policies and global market share in each material category.

Machine Learning (ML) is one of the major driving forces behind the fourth industrial revolution. This study reviews the ML applications in the life cycle stages of biofuels, i.e., soil, feedstock, production, consumption, and emissions. ML applications in the soil stage were mostly used for satellite images of land to estimate the yield of biofuels or a suitability analysis of agricultural land. The existing literature have reported on the assessment of rheological properties of the feedstocks and their effect on the quality of biofuels. The ML applications in the production stage include estimation and optimization of quality, quantity, and process conditions. The fuel consumption and emissions stage include analysis of engine performance and estimation of emissions temperature and composition. This study identifies the following trends: the most dominant ML method, the stage of life cycle getting the most usage of ML, the type of data used for the development of the ML-based models,... [more]

The aim of the study was to analyze emissions in the supply chain and to identify, based on a literature analysis, which supply chain strategies could contribute to reducing these emissions. A broad spectrum of new supply chain strategy solutions was identified and, based on simulations of selected products, conclusions were drawn and the advantages and disadvantages of theoretical solutions were presented for individual cases. A critical analysis of the literature and simulation methods were used to illustrate the problem presented in this paper, to identify the factors causing greenhouse gas emissions and to draw conclusions in the form of proposals to redesign existing strategies, considering the factors determining the increase in pollution caused by the performed logistics processes. The results of the simulations and the literature analysis indicate that solutions related to the redesign of strategies must consider the specificity of the product and the nature of the chain. Not a... [more]

Extensive studies are conducted to investigate the potential and techno-economic feasibility of bioenergy routes in different countries. However, limited researches have been focused on the whole national agricultural bioenergy resources in Egypt. This research provides an assessment of the potential agricultural biomass resources for electric energy production in Egypt. It provides a strategic perspective for the design of a national network of biomass power plants to utilize the spatially available agricultural residues throughout a country. A comprehensive approach is presented and is applied to Egypt. First, the approach estimates the amount, type, and characteristics of the agricultural residues in each Egyptian governorate. Then, a techno-economic appraisal for locating a set of collection stations, and installing a direct combustion biomass power plant in each governorate is conducted. SAM simulation software is used for the technical and economic appraisals, and preliminary pla... [more]

At present, electric vehicles (EVs) are attracting increasing attention and have great potential for replacing fossil-fueled vehicles, especially for logistics applications. However, energy management for EVs is essential for them to be advantageous owing to their limitations with regard to battery capacity and recharging times. Therefore, inefficiencies can be expected for EV-based logistical operations without an energy management plan, which is not necessarily considered in traditional routing exercises. In this study, for the logistics application of EVs to manage energy and schedule the vehicle route, a system is proposed. The system comprises two parts: (1) a case-based reasoning subsystem to forecast the energy consumption and travel time for each route section, and (2) a genetic algorithm to optimize vehicle routing with an energy consumption situation as a new constraint. A dynamic adjustment algorithm is also adopted to achieve a rapid response to accidents in which the vehic... [more]

Refrigerators play an important role in perishable goods supply chains and are expected to operate efficiently. Thermoelectric refrigerators need specific criteria for assessing their energy efficiency. The existing criteria do not take into account the insulation properties of a refrigerator cabinet, which results in a low credibility of the assessment of energy parameters of thermoelectric coolers. The aim of the research was to develop and approve a new universal criterion for assessing the energy efficiency of stationary thermoelectric refrigerators used in supply chains. It was proposed to replace the known criterion of specific power consumption with a new indicator Pk, that takes into account the overall thermal transfer coefficient of the refrigerator cabinet. Based on experimental studies, the approval of the proposed indicator was carried out on the example of a comparative analysis of four thermoelectric refrigerators from different manufacturers. The indicator application r... [more]