Search Results (78)

Energy-intensive foundries require methods to explore trade-offs among delivery performance, production horizon, electricity use, and cost when industrial data are incomplete. This paper presents an offline, process-level digital twin case study for the melting and casting area of a Danish cast-iron foundry. A multi-agent simulation represents production orders, enterprise resource planning and manufacturing execution system functions, induction furnaces, holding furnaces, crane-based transfer of molten metal, vertical moulding lines, the operating calendar, and electricity cost accounting for the induction furnaces. The model is assessed through boundary definition, assumption registration, implementation checks, material flow plausibility, a diagnostic comparison of furnace temperature, controlled scenario experiments, and local sensitivity analysis. These activities support internal consistency and bounded interpretation but do not constitute independent operational validation of the full production system. In the simulated 200-order monthly case, First-Come-First-Served and Earliest Deadline First complete the same 288,620 pieces and 5482.00 t. Earliest Deadline First increases the simulated on-time completion rate from 87.5% to 100%, while makespan, model-estimated electricity use by induction furnaces, and model-estimated electricity cost increase by 7.52%, 0.58%, and 3.42%, respectively. The case indicates that deadline-oriented sequencing may improve delivery performance but lead to a longer production horizon and higher energy use and cost within the defined model boundary. The contribution is an auditable foundry-specific modelling workflow that links heterogeneous data conditions to modelling choices, supporting evidence, and interpretation limits. The model is therefore intended for preliminary offline scenario exploration rather than validated operational decision support. Full article

Durable medical devices (DMD) are essential healthcare assets, yet their management in public hospitals is constrained by fragmentation, limited traceability, reactive maintenance, and weak lifecycle integration. This study proposes a framework for digitally enabled, sustainable, and circular DMD management. A mixed-methods design integrated a literature review, expert consultation using the Best–Worst Method, weighted technology nominations, and case-based process mapping in Brazilian hospitals. Eleven experts assessed the criteria guiding Industry 4.0 technology selection for DMD management and the technologies best responding to these priorities; nine consistent judgments were aggregated. Patient-Centered Care, Operational Efficiency, and Resource Efficiency and Cost Reduction emerged as the leading influences on technology selection. Big Data and Analytics, Artificial Intelligence, the Internet of Things, Cloud Computing, Cyber-Physical Systems, Smart Sensors, and Machine Learning formed the priority portfolio, accounting for 84% of the weighted score. The cases contextualized these priorities by revealing discontinuous information flows, limited asset visibility, corrective maintenance, fragmented governance, and weak end-of-life practices. By connecting decision priorities and technological capabilities with observed gaps, the TO-BE framework organizes sustainable procurement, traceable use, predictive maintenance, redeployment, refurbishment, and responsible disposal through material and information flows, providing a pathway for digital and circular transformation in resource-constrained healthcare systems. Full article

The accelerating transition toward renewable electricity generation has elevated grid-scale electrochemical energy storage from an ancillary grid service to a foundational infrastructure requirement. This review provides a comprehensive account of rechargeable battery technologies for stationary grid applications, spanning advanced lithium-ion systems, sodium-ion and post-lithium multivalent chemistries, vanadium and organic flow batteries, solid-state architectures, and high-energy-density future systems such as lithium-sulfur and metal-air cells. The techno-economic context of grid-scale storage is systematically examined, including performance metrics, market drivers, and regulatory frameworks. Each battery chemistry is analyzed with respect to electrochemical mechanism, cycle life, energy density, safety profile, material availability, and commercial readiness. Non-electrochemical storage technologies are discussed as system-level alternatives. Battery safety engineering, thermal management system design, thermal runaway mechanisms and prevention, and failure containment strategies are examined in depth, followed by analysis of critical material supply-chain vulnerabilities, life-cycle assessment, and recycling pathways. The expanding role of artificial intelligence, machine learning, and digital twin frameworks in optimizing performance and enabling predictive maintenance is reviewed. Key challenges, including material bottlenecks, manufacturing scalability, long-duration storage gaps, and the absence of harmonized performance standards, are identified, and the review concludes with a techno-economic roadmap toward cost-competitive, resilient, and low-carbon grid storage. Full article

Perovskite solar cells (PSCs) have emerged as a disruptive photovoltaic technology for aerospace and extreme environment applications, driven by their substantial power-to-weight ratio and mechanical flexibility. However, continuous operation under harsh conditions, characterized by the AM0 spectrum, deep vacuum, extreme thermal cycling, and ionizing radiation, exposes the fundamental thermodynamic instability of traditional organic–inorganic hybrid perovskites. This comprehensive review systematically synthesizes 131 recent studies to provide a holistic framework for designing ultrastable, radiation-hardened PSCs. We critically examine the underlying degradation mechanisms, including vacuum-induced volatile desorption, UV-triggered halide segregation, and thermomechanical fracture at buried interfaces. To overcome these critical barriers, we highlight advanced engineering strategies: the transition to all-inorganic CsPbX₃ and lead-free double/chalcogenide perovskites (e.g., Cs₂SnI₆, CaHfS₃), the implementation of dopant-free inorganic transport layers coupled with self-assembled monolayers (SAMs) for cascade band alignment, and the integration of polymeric scaffolds for fracture energy toughening. Furthermore, we emphasize the imperative shift toward solvent-free vacuum deposition techniques (ALD, PLD). A distinctive focus of this review is the integration of Artificial Intelligence; specifically, we evaluate Deep Learning architectures, such as Long Short-Term Memory (LSTM) networks, for predictive State of Health (SOH) monitoring, underscoring the vital transition from simulated to empirical datasets. Finally, coupled with Material Flow Cost Accounting (MFCA), this review outlines a strategic roadmap for the commercialization and deployment of autonomous, self-diagnosing photovoltaic platforms in next-generation satellite and deep-space missions. Full article

Order picking is one of the most time-consuming and cost-intensive operations in distribution centers, particularly when material flow is constrained by fixed transport infrastructure. This paper addresses an order-picking problem in a distribution center equipped with a one-directional transfer conveyor and stop buffers that serve groups of storage racks. Containers move along the conveyor, visit the required buffers, and may reach upstream buffers only by completing a round trip through the depot. The objective is to minimize the makespan of all picking operations while accounting for picker availability, processing times, and conveyor travel times between buffers. Four heuristic algorithms are proposed. They differ in the primary sorting rule used within a two-level ordering procedure and are supported by a permutation-reduction mechanism for medium and large instances. The algorithms were evaluated on 60 generated test instances with 120 storage locations, six buffers, and six pickers. For the 20 small instances, the results were compared with solutions obtained using CP Optimizer in IBM ILOG CPLEX under a fixed computational time limit. Within this prescribed time limit, the proposed heuristics achieved lower makespans than the feasible solutions generated by the CP Optimizer in 18 out of 20 instances, while requiring an average of only 0.22 s. Medium and large instances were solved using the proposed heuristics, with average computational times of 2.10 min and 9.00 min, respectively. The results indicate that the proposed approach provides scalable and computationally efficient decision-support procedures for order-picking systems with one-directional material flow and buffer-based service constraints. Full article

Acquisition costs account for a significant share of total construction project costs, underscoring the importance of purchasing and supply management for organizational success. Supplier selection and evaluation are particularly critical because they involve multiple criteria, qualitative and quantitative attributes, and several decision-makers. In the construction industry, these activities become even more complex due to sector-specific characteristics such as convergent material flows, temporary facilities, buyer–supplier conflicts, price-oriented decisions, and the volatility of project-based markets. This paper investigates the supplier evaluation process in a construction company and identifies the company’s requirements and decision-makers’ expectations. Based on the collected data, this research proposes a model aligned with the company’s characteristics and the decision-makers’ expectations. The model combines two methods: the Intuitionistic Fuzzy approach to aggregate decision-makers’ opinions and ELECTRE TRI to classify suppliers based on predefined criteria and thresholds. The proposed model handles different weights assigned to each decision-maker for each criterion without allowing compensation among criteria. This model also explores the role of symmetry in multicriteria decision-making by combining Intuitionistic Fuzzy Sets with the ELECTRE TRI method. Decision-makers validated the proposal and emphasized its simplicity and flexibility, which allow future adjustments to both the criteria weights and the decision-makers’ assigned weights. Full article

Addressing the persistent challenges of low resource utilization efficiency and the difficulty in quantifying hidden costs within the beef cattle sector, this study proposes an integrated diagnostic methodology that couples Material Flow Cost Accounting (MFCA) with Value Stream Mapping (VSM). Using a cohort of 1623 beef cattle finished in 2024 at the case study farm in Heilongjiang Province, China, the full life-cycle accounting reveals that hidden costs constitute 6.43% of total inputs. Attribution analysis further pinpoints two critical nodes: feed loss and bedding consumption, which account for 33.14% and 35.77% of negative product costs, respectively. Based on these diagnostics, two optimization strategies were devised: refined feed supply chain management and a recycled bedding system centered on the aerobic fermentation of cattle manure. Empirical estimates indicate that upgrading hardware facilities could reduce the feed loss rate to under 2%, yielding annual savings of ¥485,200. Furthermore, the bedding recycling system not only achieves zero waste discharge but also generates an average annual displacement income of ¥3.504 million, with an investment payback period of just 0.54 years. These findings demonstrate the efficacy of the coupled MFCA-VSM model in identifying environmental costs and unlocking economic potential, thereby providing an actionable pathway for the livestock industry’s transition toward more intensive and circular practices. Full article

Assessing the investment attractiveness of companies is essential for effective capital allocation under conditions of uncertainty and heterogeneous risk–return profiles. Investors typically face multiple financing alternatives, making comparative evaluation impossible without robust and specialized assessment methodologies. This study proposes a refined conceptual model for assessing the investment attractiveness of production companies, with a specific focus on the manufacturing sector of Kazakhstan. The research is based on a modeling-oriented methodological framework that integrates a modified discounted cash flow (DCF) approach with elements of environmental controlling. The proposed model incorporates sector-specific characteristics, including resource utilization patterns, regulatory requirements and the potential “green” premium observed in capital markets. To capture investment-related uncertainty and risk, the study employs material flow cost accounting, scenario-based modeling and probabilistic decision tree analysis. Particular attention is given to improving the determination of the discount rate, recognizing its critical influence on present value-based investment assessments. The model accounts for macroeconomic and sectoral factors specific to Kazakhstan’s production industry and offers alternative discount rate estimation scenarios under different initial conditions. The study contributes to the literature on investment attractiveness assessment by integrating financial, environmental and risk dimensions into a unified framework. The proposed model enhances transparency in investment decision-making and provides new insights into investment evaluation practices in emerging industrial economies. Full article

Articulated Tug-Barge systems connect a tugboat and a barge via an articulated link, improving manoeuvrability and flow, and offering opportunities for greater efficiency. Due to their size, these systems are vital to waterborne cargo distribution, managing the transport of several types of oil, chemicals, and bulk goods, as well as container barges. The interest in these systems is driven by the rising demand for energy efficiency and environmentally friendly maritime transport. Analysing reliability, costs, environmental and operational conditions, and crew experience helps manage each design option more effectively. The dual-mode Articulated Tug-Barge (ATB) system can disconnect the tug from the barge when seaway loads reach design limits. Effective load management and real-time monitoring are essential in these situations. This research introduces a method for evaluating barge efficiency using a structural reliability index and associated costs, accounting for environmental conditions, operational scenarios, and crew experience. The reliability index assesses the barge’s hull integrity, accounting for environmental pollution from oil spills and air emissions from construction and operation, as well as crew proficiency. The chosen design, operational status, crew experience, hull failure progression, and their effects on structural integrity, along with impacts on the ship, cargo, and environment from construction, voyages, and cleaning, are all incorporated into the cost analysis. Mitigating risk measures focus on improving the crew experience, directly reducing costs and enhancing reliability without requiring additional structural materials to increase strength. Full article

The rapid growth of electric vehicles has increased the demand for lithium-ion batteries, highlighting the need for sustainable recycling of spent cathode materials. This study combines laboratory-scale leaching experiments and Material Flow Cost Accounting (MFCA) to compare citric, tartaric, and succinic acids for recovering Ni, Co, Mn, and Li. Under optimized conditions, citric acid achieved leaching efficiencies of 81.66% (Li), 76.05% (Co), 91.46% (Ni), and 98.94% (Mn) at a cost of USD 6.50 per 10 g battery; tartaric acid reached 87.29% (Li), 80.52% (Co), 95.79% (Ni), and 99.65% (Mn) at USD 17.23 per 10 g battery; succinic acid yielded 87.05% (Li), 73.82% (Co), 86.27% (Ni), and 99.12% (Mn) at USD 4.11 per 10 g battery. MFCA shows acid consumption dominates costs, suggesting reagent optimization and recycling could reduce expenses. These results provide a cost-oriented laboratory-scale perspective for selecting organic acids, while industrial feasibility requires further evaluation of scale-up, reagent regeneration, and process optimization. Full article

This study focuses on the optimization of valve assemblies in downhole rod pumping units (DRPUs), which remain the predominant artificial lift technology in oil production worldwide. The research addresses the critical issue of premature failures in DRPUs caused by leakage in valve pairs, i.e., a problem that accounts for approximately 15% of all failures, as identified in a statistical analysis of the 2022 operational data from the Uzen oilfield in Kazakhstan. The leakage is primarily attributed to the accumulation of mechanical impurities and paraffin deposits between the valve ball and seat, leading to concentrated surface wear and compromised sealing. To mitigate this issue, a novel valve assembly design was developed featuring a flow turbulizer positioned beneath the valve seat. The turbulizer generates controlled vortex motion in the fluid flow, which increases the rotational frequency of the valve ball during operation. This motion promotes more uniform wear across the contact surfaces and reduces the risk of localized degradation. The turbulizers were manufactured using additive FDM technology, and several design variants were tested in a full-scale laboratory setup simulating downhole conditions. Experimental results revealed that the most effective configuration was a spiral plate turbulizer with a 7.5 mm width, installed without axis deviation from the vertical, which achieved the highest ball rotation frequency and enhanced lapping effect between the ball and the seat. Subsequent field trials using valves with duralumin-based turbulizers demonstrated increased operational lifespans compared to standard valves, confirming the viability of the proposed solution. However, cases of abrasive wear were observed under conditions of high mechanical impurity concentration, indicating the need for more durable materials. To address this, the study recommends transitioning to 316 L stainless steel for turbulizer fabrication due to its superior tensile strength, corrosion resistance, and wear resistance. Implementing this design improvement can significantly reduce maintenance intervals, improve pump reliability, and lower operating costs in mature oilfields with high water cut and solid content. The findings of this research contribute to the broader efforts in petroleum engineering to enhance the longevity and performance of artificial lift systems through targeted mechanical design improvements and material innovation. Full article

There is a global demand for alternative energy sources away from unsustainable fossil fuels. The Conference of Parties (COP) 26 agreed that fossil fuels should be phased down; at COP27, anxiety about the cost and availability of energy was raised, and COP28 reiterated the phasedown of coal power. Solar technology in the form of perovskite solar cells is one such alternative energy source. This article considers the fabrication of the perovskite layer in a solar cell and postulates the extent to which material flow cost accounting (MFCA) could be used as a feasible costing method, among other things, to address material flows and waste reduction. Through MFCA, the monetary and physical flows of materials are identified and can be applied throughout the supply chain to facilitate affordability, from the extraction of the ore to the transportation and fabrication of the chemicals, manufacturing and distribution of the solar cell and panels, and, finally, the recycling of the panel. Informed by these observations, a conceptual framework for applying MFCA in fabricating the perovskite layer in the supply chain is developed based on sets of qualitative propositions. Future work will involve researching the processes involved in manufacturing solar cells, costing raw materials, energy flows, and solar cell manufacturing emissions. Full article

Industrial symbiosis (IS) involves transferring waste materials and/or energy flows between stakeholders to enhance resource efficiency and reduce environmental impacts. The success of these transactions depends on supply–demand matching, technical feasibility of waste integration into industrial processes, economic savings, and compliance with legal and environmental regulations. This paper presents a methodology for the technoeconomic assessment of IS projects, integrating material flow cost accounting (MFCA) and cost–benefit analysis (CBA) incorporating CAPEX and OPEX considerations. MFCA, traditionally used to identify hidden costs from inefficiencies, is adapted here to assess resource utilisation across industry networks. The methodology is applied to two real-world demo cases: a novel fertiliser production process in Escombreras (Spain), where IS focuses on process optimisation and by-product valorisation, and an IS process design in Frövi (Sweden), where CO₂ and residual energy flows are exchanged between industrial sectors. The results demonstrate the potential of MFCA-CBA integration to enhance decision making in IS implementation. In Spain, process optimisation led to a 50% reduction in operating costs, whereas, in Sweden, CO₂ reutilisation resulted in a 30% increase in resource efficiency. These findings highlight the economic and environmental benefits of IS and provide insights into cost allocation and pricing strategies. Full article

Background: This study applied levelized cost of hydrogen (LCOH) and environmental cost accounting techniques to evaluate the feasibility of producing green hydrogen (GH₂) via alkaline electrolysis for use in a bus fleet in Fortaleza, Brazil. Methods: A GH₂ plant with a 3 MW wind tower was considered in this financial project. A sensitivity analysis was conducted to assess the economic viability of the project, considering the influence of production volume, the number of electrolysis kits, financing time, and other kay economic indices. Revenue was derived from the sale of by-products, including green hospital oxygen (GHO₂) and excess wind energy. A life cycle assessment (LCA) was performed to quantify material and emission flows throughout the H₂ production chain. A zero-net hydrogen price scenario was tested to evaluate the feasibility of its use in urban transportation. Results: The production of GH₂ in Brazil using alkaline electrolysis powered by wind energy proved to be economically viable for fueling a hydrogen-powered bus fleet. For production volumes ranging from 8.89 to 88.9 kg H₂/h, the sensitivity analysis revealed high economic performance, achieving a net present value (NPV) between USD 19.4 million and USD 21.8 million, a payback period of 1–4 years, an internal rate of return (IRR) of 24–90%, and a return on investment (ROI) of 300–1400%. The LCOH decreased with increased production, ranging from 56 to 25 USD/MWh. Over the project timeline, GH₂ production and use in the bus fleet reduced CO₂ emissions by 53,000–287,000 t CO₂ eq. The fuel cell bus fleet project demonstrated viability through fuel cost savings and revenue from carbon credit sales, highlighting the economic, social, and environmental sustainability of GH₂ use in urban transportation in Brazil. Full article

The design of industrial installations using digital design techniques (digital twin), aligned with the concept of Industry 4.0, provides a tool to optimize maintenance costs, process gas emissions, energy consumption and to reduce the risks associated with production testing. Modern manufacturing plants conduct chemical processes by combining production experience with model-based research. Analyzing processes using advanced digital techniques can replace traditional methods of technological process balancing. The methodology based on the digital twin already serves as a holistic system of process connections, supporting production, research and development, production planning, and quality control. This paper presents the digital design, optimization, and comparison of process data obtained through simulations for two different types of ammonia recovery units in soda ash production using the ammonia–soda process. Using specialized modeling software and relying on historical data, engineering assumptions, and new concepts, virtual models were created in which the material and thermal balances of the process were simulated. This research is divided into two stages. In the first stage, a model-based approach and model optimization techniques are presented, while in the second stage, the preparation of models of the distillation installation is presented, and the influence of various structural parameters of the equipment on the temperature profile and gas flow rate in the ammonia recovery section is discussed. The process of the research method, based on simulations in a virtual environment, allows for evaluating the implementation potential of the proposed concepts, optimizing process parameters, and redefining the approach to conducting chemical processes. A series of simulations conducted in studies on ammonia recovery indicated a potential increase in gaseous ammonia recovery by up to 14.09%, taking into account the type of distillation apparatus or the height of the packing section. Full article