Remanufacturing as an end-of-life disposal option poses challenges due to product and process complexities, customer requirements, and uncertainties associated with product take back and the ...remanufactured products’ market-base. To address these challenges, this study presents a decision support system based on a bi-level fuzzy computing approach that incorporates qualitative and quantitative product attributes in determining the remanufacturability of a product. The model uses fuzzy inference approach in assessing four key performance metrics herein referred to as sub models, namely; technological, economic, resource utilization and environmental metrics that influence product remanufacturability. The four sub-models are then aggregated to establish a unified fuzzy-based remanufacturability index. The model is applied to assess the remanufacturability of two control drive families manufactured by a multi-national company as case examples in this paper. The study shows that one of the control drives, which is larger in size, has been ten years in the market, has a higher percentage of billable returns and thus not relatively labor restrictive, has a higher remanufacturability index of 0.662. The second product, which is relatively small, has been in the market for less than five years, has a higher proportion of returns under warranty and thus labor restrictive, has a lower remanufacturability index of 0.448. The proposed model is versatile for comparing families of product and can therefore aid in making tactical decisions regarding product remanufacture.
Panic buying poses significant challenges for individuals and societies. This paper provides a literature review on the process by which a pandemic crisis evolves into panic buying behavior. The ...review offers a comprehensive perspective on studies related to panic buying and mitigation efforts, categorizing them based on their contributions in three stages: factors influencing panic buying, the process of transforming panic into increased demand and stockpiling, and applicable intervention strategies to mitigate panic situations. The paper introduces the Socio-Economic Framework of Panic (SEFP) to illustrate the interaction between demand and supply during a panic. The review identifies a lack of quantitative models explicitly correlating influencing factors with panic and estimating panic demand. Additionally, it reveals that suggested intervention strategies often lack practical implementation guidelines. Using the SEFP, the importance of considering interventions at various stages is highlighted, ranging from controlling influencing factors and panic demands to overseeing stockpiling and supply-related activities. The paper also identifies research gaps in both qualitative and quantitative modeling, policymaking, and governance.
The primary research on anode materials of lithium-ion batteries have been focused on increasing the specific capacity, while the working potential that is also closely related to the practical ...energy density of batteries has been paid much less attention. In this work, starting from micrometer-sized silicon and black phosphorus, we have reported a high-energy silicon-phosphorus/carbon anode (denoted as mSPC) via a high-energy ball milling process, which demonstrates an average discharge working potential of 0.3 V versus lithium, together with a high reversible capacity of > 2000 mAh/g, high initial coulombic efficiency of 84%, excellent cycle stability, and superior rate capability up to 15 A/g. Furthermore, in situ focused-ion-beam scanning electron microscopy reveals that the volume change of the mSPC anode during repeated (de) lithiation is effectively alleviated. In contrast, starting from nanometer-sized silicon, the resulted anode (denoted as nSPC) not only presents a lower reversible capacity (~ 1200 mAh/g), but also exhibits a higher charge/discharge working potential, leading to reduced energy density. Our results indicate the importance of composition/structure control in tailoring the working potential and specific capacity of alloying-type anodes towards high-energy lithium-ion batteries.
Graphical abstract
The interaction of silicon and phosphorus could tune the working potential and specific capacity of anode materials for lithium-ion batteries, leading to significantly improved energy density and power density.
A sensitivity based approach is presented to determine Nash solution(s) in multiobjective problems modeled as a non-cooperative game. The proposed approach provides an approximation to the rational ...reaction set (RRS) for each player. An intersection of these sets yields the Nash solution for the game. An alternate approach for generating the RRS based on design of experiments (DOE) combined with response surface methodology (RSM) is also explored. The two approaches for generating the RRS are compared on three example problems to find Nash and Stackelberg solutions. For the examples presented, it is seen that the proposed sensitivity based approach (i) requires less computational effort than a RSM-DOE approach, (ii) is less prone to numerical errors than the RSM-DOE approach, (iii) has the ability to find multiple Nash solutions when the Nash solution is not a singleton, (iv) is able to approximate nonlinear RRS, and (v) on one example problem, found a Nash solution better than the one reported in the literature.
Magnesium, Mg, has been widely investigated due to its promising potential as magnesium alloys for various applications, particularly as biomedical implantation devices among other medical ...applications. This work investigates the influence of different cooling rates on the strength of pure Mg. The cooling rates were set to cover a low cooling rate LCR (0.035 °C/s) in an insulated furnace, a moderate cooling rate MCR (0.074 °C/s) in uninsulated-ends furnace, and a high cooling rate HCR (13.5 °C/s) in liquid CO2. The casting process was accomplished using a closed system of melting and cooling due to the reactivity-flammability of magnesium in order to minimize processing defects and increase the safety factor. The as-cast samples were metallographically examined for their microstructure, and properties such as impact strength, hardness, and tension were determined. Increasing the solidification rate from 0.035 °C/s to 0.074 °C/s increased the hardness from 30 to 34 Rockwell Hardness and the UTS from 48 to 67 MPa. A higher solidification rate of 13.5 °C/s further enhanced the hardness to 48 Rockwell Hardness and the UTS to 87 MPa in comparison to the 0.074 °C/s cooling rate. Additionally, the fracture behavior and morphology were investigated. It was found that in general, the mechanical properties tended to improve by refining the grain structure.
The broad context of this literature review is the connected manufacturing enterprise, characterized by a data environment such that the size, structure and variety of information strain the ...capability of traditional software and database tools to effectively capture, store, manage and analyze it. This paper surveys and discusses representative examples of existing research into approaches for feature set reduction in the big data environment, focusing on three contexts: general industrial applications; specific industrial applications such as fault detection or fault prediction; and data reduction. The conclusion from this review is that there is room for research into frameworks or approaches to feature filtration and prioritization, specifically with respect to providing quantitative or qualitative information about the individual features in the dataset that can be used to rank features against each other. A byproduct of this gap is a tendency for analysts not to holistically generalize results beyond the specific problem of interest, and, related, for manufacturers to possess only limited knowledge of the relative value of smart manufacturing data collected.
In manufacturing, the technology to capture and store large volumes of data developed earlier and faster than corresponding capabilities to analyze, interpret, and apply it. The result for many ...manufacturers is a collection of unanalyzed data and uncertainty with respect to where to begin. This paper examines big data as both an enabler and a challenge for the connected manufacturing enterprise and presents a framework that sequentially tests and selects independent variables for training applied machine learning models. Unsuitable features are discarded, and each remaining feature receives a crisp numeric output and a linguistic label, both of which are measures of the feature’s suitability. The framework is tested using three datasets employing time series, binary, and continuous input data. Results of filtered models are compared to results obtained by base, unfiltered sets of features using a proposed metric of performance-size ratio. Framework results outperform base feature sets in all tested cases, and the proposed future research will be to implement it in a case study in the electronic assembly manufacture.
Increasing concerns about environmental sustainability strategies, take-back laws and natural resource limitation has highlighted the impact of disposing end-of-life (EOL) electrical and electronic ...products. To cope with this challenge, manufacturers have integrated reverse logistics into their supply chain or chosen to outsource product recovery activities to third parties. This research studies the remanufacturing processes of reusable products and parts, cost and demand of remanufactured products and parts to determine return quality thresholds during multiple production period. We present a general framework for a third party remanufacturer, where the remanufacturer has the alternative of supplying parts to external suppliers or bringing the disassembled parts to ‘as new’ conditions. The problem is formulated as a mixed integer non-linear programming (MINLP) problem, where with proposed discretization, the problem turns into a quadratic mixed integer programming (QMIP) problem. Finally, the impact of the quantity of returns, operational cost and upper bound disposal rate using a case numerical study of a personal computer (PC) remanufacturing facility has been studied.
•A model is presented to minimize the amount of water consumed by the energy sector.•The model dispatches the generation-cooling mix to quantify water consumption.•Electricity demand in California ...needs a minimum of 58,673 cubic meters of water.•16% reduction in the California electricity usage cuts the water consumption by 94%.•No hydro generation in California reduces water consumption by 61%.
Water is the greatest resource for life on earth. Various human activities affect the quality and quantity of this precious resource, and there are many initiatives to ensure water resources are protected from overuse, pollution, and industrial and agricultural waste. Since the energy sector is the second largest consumer of water after agriculture, water and energy systems are highly interlinked. Specifically, a significant amount of water is used in the energy generation process primarily for producing steam and for cooling processes, the water used for cooling processes will be returned back to the reservoir. Consequently, most fossil-based power plants in addition to consuming water, impact the water resources by raising the temperature of water withdrawn for cooling. Limited water resources can also affect the ability to generate electric power to meet the demand. Therefore, integrated planning for the interleaved energy and water sectors is essential for both water and energy savings. This paper describes a comprehensive study that analyzes and quantifies water withdrawals and consumption of various electricity generation sources such as coal, natural gas and renewable sources. The study has developed a general model to determine the water consumption and impact for various energy generation scenarios and to minimize the amount of water consumption while considering several limitations and restrictions. A case study performed for the state of California indicates that quantification of water consumption can be formulated and potential opportunities for water saving can be identified.
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