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This paper focuses on robustly stabilizing stable and unstable fractional-order plants with one uncertain fractional-order term and interval uncertainties using fractional order $ PI^{\mu }D^{\lambda } $ PIμDλ controllers. Two necessary and sufficient conditions are provided to check the robust stability of the closed-loop control system. Moreover, the D-decomposition technique is utilized to determine the robust stability region of the system. Subsequently, evolutionary algorithms, such as the Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Differential Evolution (DE), can be utilized to discover a fractional-order controller within the region of robust stability. This work introduces three primary contributions, outlined as follows: (1) Utilizing a graphical approach, a set of stabilizing controller is obtained. (2) Rather than employing just a single stabilizing fractional-order controller, a collection of controllers is provided for the control system. (3) Employing evolutionary algorithms to find an optimal fractional-order controller. Finally, four numerical examples are presented to validate the results. [ABSTRACT FROM AUTHOR]

In today's customer-centric economy, the demand for personalized products has compelled corporations to develop manufacturing processes that are more flexible, efficient, and cost-effective. Flexible job shops offer organizations the agility and cost-efficiency that traditional manufacturing processes lack. However, the dynamics of modern manufacturing, including machine breakdown and new order arrivals, introduce unpredictability and complexity. This study investigates the multiplicity dynamic flexible job shop scheduling problem (MDFJSP) with new order arrivals. To address this problem, we incorporate the fluid model to propose a fluid randomized adaptive search (FRAS) algorithm, comprising a construction phase and a local search phase. Firstly, in the construction phase, a fluid construction heuristic with an online fluid dynamic tracking policy generates high-quality initial solutions. Secondly, in the local search phase, we employ an improved tabu search procedure to enhance search efficiency in the solution space, incorporating symmetry considerations. The results of the numerical experiments demonstrate the superior effectiveness of the FRAS algorithm in solving the MDFJSP when compared to other algorithms. Specifically, the proposed algorithm demonstrates a superior quality of solution relative to existing algorithms, with an average improvement of 29.90%; and exhibits an acceleration in solution speed, with an average increase of 1.95%. [ABSTRACT FROM AUTHOR]

We consider a finite-horizon discrete-time dynamic model of oligopolistic competition, with uncertain supply. The firms (retailers) make their decisions on quantities (sales) and orders of goods from a nonstrategic manufacturer taking into account uncertainty in demand parameters and available supply capacity. The retailers need to satisfy the joint available supply capacity constraint. The model is described as a game played over an event tree with given transition probabilities. We find a normalized equilibrium for the game with coupling constraints. The two-step procedure to find this equilibrium is described. We provide the necessary conditions of the equilibrium and examine different scenarios of uncertainties in the model by numerical simulations. [ABSTRACT FROM AUTHOR]

The robust stability assessment of the second order plus interval time delay (SOPITD) plant controlled by Fractional-Order Proportional Integral Derivative (FOPID) controllers is the focus of this research. A simple graphical procedure for analyzing the robust stability of the interval system is presented based on the zero exclusion condition and the value set concept. The incorporation of an auxiliary function, derived through a judicious application of fundamental geometric principles intrinsic to convex polygons, serves to significantly alleviate the complexity and facilitate the application of the robust stability analysis approach, thereby affording a more streamlined and efficient means of designing robust control systems. Moreover, the computational burden for the robust stability analysis is also reduced by novel bounds. Moreover, a novel robust performance checking function is provided to improve the performance system. Three illustrative examples are then given to support the findings and show their applicability. [ABSTRACT FROM AUTHOR]

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This paper develops an outsourcing collaboration model from a firm's perspective operating in a developing economy. The model considers that producers of the final goods residing in a developed country, and operators of manufacturing plants in a developing country collaborate with each other. The final goods producer supplies headquarter services for the production of intermediate goods in the developing country. The operators of manufacturing plants also supply their services in the domestic economy. This arrangement leads to foreign outsourcing collaborations (FOC) between firms of developed country and developing country. The operators of manufacturing plant maximize revenue subject to the cost constraint. The first order conditions suggests that an increase in wages of skilled labor, price of domestic inputs, and cost of production deter FOC. On the other hand, an increase in demand for and price of foreign headquarter services increases the FOC. Empirical analysis based on data collected from 217 clothing (textile and apparel) firms in the city of Faisalabad (Pakistan) reveals that an increase in wage to labor-productivity ratio reduces FOC. An improvement in skilled of the labor and foreign headquarter services give rise to FOC, whereas an increase in economies-of-scope enhances FOC. Additionally, an inverted U-shaped relationship is found between the cost of production and FOC, which shows that at the initial stage, the firm's cost of production increases with an increase in the level of FOC, but soon after the tipping point, the firm's cost starts decreasing with a further increase in FOC. [ABSTRACT FROM AUTHOR]

Xiang FZ001 was used as a test variety in this experiment, which was conducted in a plant factory with a cycle of 16 hours of light and 8 hours of darkness to study the effects of varying light intensities on the growth and development of cotton (Gossypium hirsutum L.), three light intensity treatments with parameters of L1: 450 µmol⋅m-2⋅s-1, L2: 600 µmol⋅m-2⋅s-1, and L3: 750 µmol⋅m-2⋅s-1, were established to determine the dry weight of each cotton organ. The height of the cotton plant was measured using a straightedge, the chlorophyll content of cotton leaves was measured using a SPAD-502 chlorophyll meter. Additionally, six chlorophyll fluorescence parameters were measured, including initial fluorescence (F0) and maximum fluorescence (Fm), using a Flour Pen 110. The relative chlorophyll content and plant height of cotton were greatest under the L1 light intensity treatment, the root dry weight of cotton was greatest under the L2 light intensity treatment, and the total weight of cotton stems, leaves, and individual plants under the three light intensity treatments were L3>L2>L1 in descending order, and the F0 and Fm were L1>L2>L3 in descending order. The maximum photochemical quantum yield (Fv/Fm) was L2>L3>L1 in descending order. The photochemical bursting coefficient (qp) and effective quantum yield (φPSII) of cotton under the same light intensity treatment showed the same curves of change. During the pre-growth era, there was no significant difference in the qp, φPSII, and nonphotochemical burst (NPQ) of cotton under the three light intensity treatments. However, in the late period, there was a greater difference. For the late growth stage, cotton's qp and φPSII under the three light intensity treatments were high to low in the order of L3>L2>L1, and high to low in the order of L2>L3>L1. High light intensities increase the dry weight, stem dry weight, and leaf dry weight of cotton plants; low light intensities enhance the height of the cotton plant, but too high or too low a light intensity prevents the growth of cotton roots. Compared with cotton under L1 and L3 light intensity treatments, L2 light intensity was suitable for cotton growth, avoiding both inter-plant competition for light and the phenomenon of photoinhibition, with moderate chlorophyll content, resulting in the highest photochemical efficiency of cotton. This study can provide a guidance for cotton factory production and cotton breeding accelerator development and application. [ABSTRACT FROM AUTHOR]

In the era of the competitive environment, the improvement in current products is ensured through activities aimed at increasing a product's quality level and, consequently, reducing the amount of waste. The dynamically changing production environment and sudden changes in customer expectations force us to take precise and well-thought-out development steps. Furthermore, it is important to anticipate favourable product changes to prepare for market changes over time. This is still an open problem. The aim of this study was to develop a method to predict the quality of potential product prototypes resulting from the proposed modifications of the product features. This methodology takes into account current customer expectations. The method was created based on the principles of creating Quality Function Deployment (QFD) in the context of taking into account current and future customer expectations regarding product features. This is a new approach to analysing product quality within the principles of the traditional QFD method. The originality of the study is the technique used in the method to estimate the expected values of product features and their importance (weights), taking into account current customer expectations. Its originality is also manifested in drawing conclusions supporting the decision-making process of product improvement, because it involves ensuring the pro-quality modification of selected features of current products in the order that is most advantageous from the customer's point of view. The use of the proposed method allows for the analysis of the impact of modifying the current value of a product feature. The method is illustrated with an example of a vacuum cleaner for home use. However, the proposed method can be applied to the design of any product to predict products that will meet customer expectations. [ABSTRACT FROM AUTHOR]

This paper concentrates on presenting a reliable procedure to compute the stabilizing region of fractional‐order proportional integral derivative (FOPID) controllers for interval fractional‐order plants having an interval time delay. An interval fractional‐order plant is defined as a fractional‐order transfer function whose denominator and numerator coefficients are all uncertain and lie in specified intervals. Also, an interval time delay points to a delay term whose value varies in a specific interval. The D‐decomposition technique and the value set concept are employed to determine the stabilizing region of FOPID controllers. In this study, first, a theorem is presented to compute the boundary of the value sets of systems having interval time day. Then, a lemma is provided for robust stability analysis of the given closed‐loop control system. For a convenient use of the paper results, an algorithm is proposed to solve the problem of robustly stabilizing interval fractional‐order plants with an interval time delay using FOPID controllers. Finally, four examples are provided to illustrate the proposed procedure. [ABSTRACT FROM AUTHOR]

Several major companies operate large online order fulfillment systems to ship goods from fulfillment centers through a distribution network to customer destinations in response to purchase orders. These networks make several types of decisions in real-time to serve customers. First, when a customer places an order, when and where (which fulfillment center) is it fulfilled from? Second, once an order has been packaged, how is it moved through the network to get to the customer? Making optimal decisions can yield significant cost savings or improvements in customer service. Unfortunately, these are large optimization problems, and are furthermore subject to uncertainty in the products and destinations of customer orders and the inventory replenishment of the fulfillment centers. This uncertainty makes the problem difficult to solve to optimality. Although the problem can be modeled as a Markov decision process, solving it exactly using standard computational methods is not possible due to the curse of dimensionality. We propose an alternative approach to this problem. We define a relatively simple real-time control policy and prove that it serves all customer demand if at all possible. This proof is achieved using Lyapunov drift techniques to relate the real-time control performance to the average performance necessary to serve all customers on average. Correspondingly, we characterize the average network performance, which may be used for network topology design while the control policy adapts to real-time stochasticity. We demonstrate the performance and stability properties on a numerical example based on hundreds of Amazon facility locations in the United States. The max-pressure control and greedy policies perform similarly at low demands, but at higher demand the throughput properties of the max-pressure control manifest as improvements in throughput and customer service metrics. Funding: Financial support from the National Science Foundation [Grant 1935514] is gratefully acknowledged. Supplemental Material: The e-companion is available at https://doi.org/10.1287/trsc.2023.0096. [ABSTRACT FROM AUTHOR]

The superficial quality of the strip is a very important issue in steel production. Considering the dimensions, the thickness is one of the most important variables in the production of a strip. In the present study, the elastic curve of Back Up Rolls (BURs) is analyzed, considering them as simply supported beams as well as the effect of rolls on the profile of the strip, specifically in the strip edge producing edge drop. The analysis included theoretical and numerical measurements in the mill. The results showed that there is an instability zone of 76 mm in the strip edge, and this geometry is symmetrical in both ends of the strip. This study not only provides a theoretical basis for the edge drop, but also provides a basis for the understanding of deformation on rolls used in rolling mill processes and their effect on the thickness, profile, shape, and dimensional quality of strips. To reduce the edge drop and significantly improve the surface quality of the strip, it is suggested to complement the simulation by compensating for the elastic curve of BUR, in the process applying bending on Work Roll (WR) combined with the use of positive crowns on it. [ABSTRACT FROM AUTHOR]

In this sustainability-oriented research, the properties of plant-based inks were evaluated denoting the viscosity range of 8.5 to 10 cP, the relative density of 1.06, conductivity value of 2.51 mS/cm, and the surface tension of 60 mN/m and pH of 4.9 to be most effective for inkjet printing. The changes in these properties to the one-month storage phase are detailed as determined with attenuated total reflectance – Fourier transform infrared spectroscopy, viscometer, and tensiometer. The varied colours of plant-based inks were stable to storage time except for the blue colour ink made from bio indigo herb that displayed agal-like sediments. After the storage phase, the plant-based inks exhibited anti-thixotropic viscosity except for yellow colour plant-based ink demonstrating thixotropic behaviour. High conductivity values of 18.5 and 15.6 mS/Cm were noted for blue and black colour plant-based inks, indicating their potential for constituting conducting inks; however, the conductivity values dropped to 7.5 and 9.5, respectively, after 1 month. The pH and surface tension were found steady during the storage period. The study of the life cycle analysis of plant-based inks is suggested for future work. The significance of this work in developing plant-based inks for inkjet printing of textiles lies in the convergence of sustainability and innovation. Plant-based inks can offer an eco-friendly alternative to traditional synthetic inks that are used currently, which provides a knowledge base for good practises meeting the environmentally conscious in the digital printing of the textile industry. These developed inks from this study can not only reduce the environmental impact but also promote a healthier ecosystem. [ABSTRACT FROM AUTHOR]

With the growing severity of global environmental issues, the international community has reached a consensus on the importance of reducing and controlling carbon emissions. As a result, an increasing number of consumers are opting to purchase green products in order to reduce the emission of greenhouse gases. This trend has prompted supply-chain enterprises to invest in green innovation. Simultaneously, carbon tax policies have gained significant attention from governments worldwide due to their dual role as environmental laws and fiscal-policy tools. Considering consumers' preference for green products and the risk of R&D failure associated with them, this study focuses on the effects on emissions reductions and profits associated with different carbon tax policies for a green supply chain consisting of a manufacturer and a retailer. The results reveal that (1) increases in the carbon tax per unit of product motivate the manufacturer to increase R&D efforts; (2) wholesale and retail prices follow a pattern of initial increase and subsequent decrease as the carbon tax per unit of product rises; (3) higher carbon taxes per unit of product generally lead to lower manufacturer profits, while both carbon emissions and retailer profits can increase with a per-unit carbon tax under certain circumstances; and (4) the increase in the proportion of the population with green preferences can yield long-term benefits for both the retailer and the manufacturer, yielding an inverted U-shaped relationship with carbon emissions. [ABSTRACT FROM AUTHOR]

Ascorbate recycling is required for high ascorbate accumulation. Hence, when the ascorbate pool size is small, does the demand for ascorbate recycling decrease? We herein investigate the impact of ascorbate recycling capacity on ascorbate pool size in an ascorbate-deficient background. Our findings demonstrate that a smaller ascorbate pool size lowers the need for ascorbate recycling capacity even under light stress. [ABSTRACT FROM AUTHOR]

In a smart factory, setting a production plan, relocating production equipment, and producing small batches of various products in real-time at a low cost is essential. This study discusses clustering customer orders with the same or similar process routes using a sequential pattern-mining technique, simplifying the overall production process and reducing the relocation and restructuring of equipment and machines in smart factories. We present a similarity measure to evaluate the similarity between two process routes and mathematically formulate integer programming to solve the problem of clustering similar routes. Considering process routes with alternatives, we use sequential pattern-mining techniques to cluster customer orders and determine alternative routes related to customer orders. We propose two sequential pattern-mining algorithms to expedite customer orders in smart factories. Algorithm 1 cluster customer orders and finds frequent process route patterns based on the similarity of the process routes. Algorithm 2 determines frequent sequential patterns based on the frequency of customer orders. We compared the results of 0–1 integer programming and Algorithm 1 and evaluated the algorithms' running time and memory space. This study demonstrates how data-mining techniques can be integrated into manufacturing systems to simplify process routes and reduce the complexity of the manufacturing process in the customer order phase. [ABSTRACT FROM AUTHOR]

Filters are electrical circuits or networks that filter out unwanted signals. In these circuits, signals are permeable in a certain frequency range. Attenuation occurs in signals outside this frequency range. There are two types of filters: passive and active. Active filters consist of passive and active components, including transistors and operational amplifiers, but also require a power supply. In contrast, passive filters only consist of resistors and capacitors. Therefore, active filters are capable of generating signal gain and possess the benefit of high-input and low-output impedance. In order for active filters to be more functional, the parameters of the resistors and capacitors in the circuit must be at optimum values. Therefore, the active filter is discussed in this study. In this study, the tree seed algorithm (TSA), a plant-based optimization algorithm, is used to optimize the parameters of filters with tenth-order Butterworth and Bessel topology. In order to improve the performance of the TSA for filter parameter optimization, opposition-based learning (OBL) is added to TSA to form an improved TSA (I-TSA). The results obtained are compared with both basic TSA and some algorithms. The experimental results show that the I-TSA method is applicable to this problem by performing a successful prediction process. [ABSTRACT FROM AUTHOR]

Managing industrial processes in real-time is challenging due to the nonlinearity and sensitivity of these processes. This unpredictability can cause delays in the regulation of these processes. The PID controller family is commonly used in these situations, but their performance is inadequate in systems and surroundings with varying set-points, longer dead times, external noises, and disturbances. Therefore, this research has developed a novel controller structure for PIDD α that incorporates the second derivative term from PIDD 2 while exclusively using fractional order parameters for the second derivative term. The controllers' robust performance has been evaluated on four simulation plants: first order, second order with time delay, third-order magnetic levitation systems, and fourth-order automatic voltage regulation systems. The controllers' performance has also been evaluated on experimental models of pressure and flow processes. The proposed controller exhibits the least overshoot among all the systems tested. The overshoot for the first-order systems is 9.63%, for the third-order magnetic levitation system, it is 12.82%, and for the fourth-order automatic voltage regulation system, it is only 0.19%. In the pressure process plant, the overshoot is only 4.83%. All controllers for the second-order systems have a time delay, while the flow process plant has no overshoot. The proposed controller demonstrates superior settling times in various systems. For first-order systems, the settling time is 14.26 s, while in the pressure process plant, the settling time is 8.9543 s. Similarly, the proposed controllers for the second-order system with a time delay and the flow process plant have the same settling time of 46.0495 s. In addition, the proposed controller results in the lowest rise time for three different systems. The rise time is only 0.0075 s for the third-order magnetic levitation system, while the fourth-order automatic voltage regulation system has a rise time of 0.0232 s. Finally, for the flow process plant, the proposed controller has the least rise time of 25.7819 s. Thus, in all the cases, the proposed controller results in a more robust controller structure that provides the desired performance of a regular PIDD 2 controller, offering better dynamic responses, shorter settling times, faster rise times, and reduced overshoot. Based on the analysis, it is evident that PIDD α outperforms both PID and FOPID control techniques due to its ability to produce a more robust control signal. [ABSTRACT FROM AUTHOR]

Reseller contract and online marketplace contract are two typical supply chain contracts provided by Online retail platforms (ORPs) in online retailing. Manufacturers can either wholesale their products to an ORP using the traditional reseller contract or choose an agency selling contract to sell their products directly to consumers through an online marketplace provided by the ORP. Based on a game model, this paper studies the contract choice strategy for a monopoly manufacturer facing two competing downstream ORPs. The results show that the competition intensity between the ORPs and the order-fulfilment costs critically moderates the choice decision. Specifically, for a given competition intensity (level of order-fulfilment costs), with rising order-fulfilment costs (the downstream competition intensity), the preferred mode for the manufacturer switches from the pure online marketplace mode to the hybrid mode and then to the pure reseller mode. The intuition of this lies in the interaction of the transfer of the pricing rights and the responsibility for order fulfilment. Meanwhile, the conditions to ensure the dominant equilibrium in the competition of ORPs are analysed. Finally, we extend the basic model by relaxing the assumptions about the same proportion fee rate and the fixed order-fulfilment cost. [ABSTRACT FROM AUTHOR]

Rooted from the Industry 4.0 principles, Cloud Manufacturing (CMfg) is a novel customer-oriented manufacturing norm, which can assist enterprises to withstand in the nowadays highly volatile and competitive market. CMfg systems comprise two separate parties, namely, customers and factories, with independent individuals. In this regard, considering the utilities of both customers and factories and establishing the equity amongst their individuals are of particular importance for the survival and flourishment of CMfg systems. Furthermore, due to the limited capacity of resources, tightness of due dates, and customers' cost expectations, all orders may not be accepted in CMfg systems. Accordingly, this paper aims to explore a scheduling problem in a CMfg system. A multi-objective mathematical model is presented for the problem, which can determine the acceptance or rejection of orders, set prices, and schedule them in an integrated manner to maximise the customers and factories' utilities, and enhance the equity among their members. Due to the high complexity of the problem, two matheuristic methods based on the Multi-Objective Grey Wolf Optimizer (MOGWO) and Non-dominated Sorting Genetic Algorithm II (NSGA-II) are developed. An extensive computational experiment is carried out to validate the proposed matheuristic methods and evaluate their performance. Moreover, some guidance is presented for managers by conducting a sensitivity analysis. [ABSTRACT FROM AUTHOR]

Multi-factory production planning and scheduling problems have been increasingly studied by scholars recently due to market uncertainty, technological trends like Industry 4.0 and increasing collaboration. Geographically dispersed factories may provide cost-saving potential and increase efficiency while also being subjected to varying capabilities and restrictions such as capacity constraints and labour costs. Traditional approaches in production planning and scheduling focus on the allocation of demand to a single factory and obtain sequences of operations on machines in this factory. In the multi-factory or distributed setting, an additional task includes assigning orders to potential factories beforehand. Starting with the first case studies in the late 1990s, research has increasingly been devoted to this research field and has considered numerous variations of the problem. We review 128 articles on multi-factory production planning and scheduling problems in this contribution and classify the literature according to shop configuration, network structure, objectives, and solution methods. Bibliometric analysis and network analysis are utilised to generate new findings. Research opportunities identified include integration with other planning stages, an investigation of key real-life objectives such as due date compliance and examining dynamic characteristics in the context of Industry 4.0. Besides, empirical studies are necessary to gain new practical insights. [ABSTRACT FROM AUTHOR]

Purpose: The paper aims to clarify the effects of brand differentiation on the platform's formulation of channel strategy and help the online platform formulate the optimal channel strategy, which involves selecting a proper selling mode for each brand. Design/methodology/approach: The paper develops a multistage game model consisting of one online platform and two competing manufacturers with differentiated brands and examines the effects of brand differentiation on these three channel members' profits under each candidate channel strategy. Findings: The results show that the platform prefers to offer the reselling mode for both brands when the brand differentiation is low, and this preference will be enhanced by the decrease in order fulfilment cost. By contrast, when the brand differentiation is high, it will offer the reselling mode for the premium brand but the marketplace service for the economy brand if the order fulfilment cost is not high; or the marketplace mode will be offered to both brands if this cost is high. Research limitations/implications: This study assumes that the order fulfilment costs of platform and manufacturer are fixed and symmetric. Therefore, researchers are encouraged to consider asymmetric costs of order fulfilment. Practical implications: The paper guides the online platform to formulate the optimal channel strategy for differentiated brands and provides managerial insights for differentiated brands entering online markets. Originality/value: This paper explores platforms' optimal channel strategy by jointly considering the effects of brand differentiation and investigates the impacts of brand differentiation on the optimal decision making under four candidate options. Moreover, this paper has been extended to examine the case when the manufacturers' production costs cannot be neglected. [ABSTRACT FROM AUTHOR]

Summary: This paper investigates a new implementation of a passive fractional‐order capacitor (FOC) based on a single‐component fractional‐order inductor (FOI). The significance of this approach lies in providing the fractional‐order passive circuit to synthesize an FOC, which avoids the approximation that only depends on the integer‐order transfer function and reflects truly the infinite‐dimensional nature of fractional‐order impedance characteristic. For this purpose, the realizable conditions of this passive FOC are obtained and the main ideas of the proposed method are described by examples. The sensitivity of the impedance magnitude and phase angle on required components parameters is also analyzed in order to facilitate the design of the FOC emulator. Furthermore, the bandwidth is extended by modular structures connected in series, and the proposed approach shows an improvement over some previous methods in terms of accuracy. Also, based on the fractional calculus Grünwald–Letnikov definition, a single‐component FOI circuit element is packaged to build simulation circuit in Matlab/Simulink, and the effectiveness of the proposed method are validated by simulated and experimental results. In the application of an FOC, the results from in the series–parallel fractional‐order RLCβ bandreject filter circuit indicate that the fractional‐order counterpart can reduce the ripple and improve the suppression level at a certain frequency, and the peak amplitude and the overshoot decrease initially with decreasing order. Moreover, under the fixed inductance, capacitance, and resistance, the rise time varies almost inversely with order, whereas the setting time is on the decrease as the order is decreasing. [ABSTRACT FROM AUTHOR]

To investigate the edge drop control characteristics of the roll contour on the taper segment of a taper-work roll, a three-dimensional roll stack-strip-tension coupling model was established with the finite element method, and the simulation model was verified using experimental data. The effects of the taper-work roll shifting (T-WRS) for different contours on the edge drop, center crown, flatness, and nonuniformity of the rolling pressure field unevenness were studied. The results indicated that the thickness difference caused by the combination of the roll contour and the work roll shifting (WRS) effectively compensated for the edge drop caused by the elastic deformation of the roll was the main way for T-WRS to reduce edge drop. Increasing the height of the roll contour inserted into the strip could significantly improve the edge drop control ability. However, it would also lead to increasing the trend of M-mode waviness defects and increase the peak of rolling pressure and the unevenness of the contact pressure between the rolls. Therefore, a novel approach for the roll contour evaluation was proposed by constructing the multi-objective function of the taper-work roll shifting. With edge drop control as the primary goal, the optimal range and suitable range of the WRS for different roll contours were calculated for the first stand of the tandem cold mill. [ABSTRACT FROM AUTHOR]

Purpose: The successive waves of the Covid-19 SARS-II pandemic and the attendant lockdown imposed by the governments worldwide drove the economic activities to a halt. Offices and factories closed, production of goods and services declined and supply chains got severely disrupted. Many companies were embattled with the grim reality of shrinkage of aggregate demand, first due to supply shock and later due to loss of jobs and wages. Amidst all this, the handling and shipping of commodities became extremely complex. As the pandemic shifted consumer preference in favour of digital platforms, more and more fast-moving consumer goods (FMCG) companies were confronted with multiple strategies and choices of an appropriate distribution channel to ensure smooth delivery of raw materials and products. The present study aims to study this shift and its implications in the Indian context. Design/methodology/approach: A mix-method approach, integrating quantitative and qualitative analysis, is employed to investigate the factors influencing the selection of distribution channels amongst general trade, modern trade, e-commerce and hyperlocal for FMCG companies in India. The first phase of the study uses exploratory factor analysis (EFA), followed by the application of analytical hierarchy process (AHP) approach in a fuzzy environment to realise the priority weights and ranking of the identified factors. Finally, sensitivity analysis is performed to confirm the robustness of the fuzzy analytical hierarchy process (FAHP) outcomes. Findings: The study revealed that modern trade has emerged as the most favoured channel in the post-pandemic Indian economy. It has the potential to disrupt general trade. The study also revealed that the hyperlocal delivery model is not economically viable, and the partnership of FMCG companies with these applications is at best a short-term solution. However, it must be submitted that due to its sheer capability to ensure quick deliveries within a confined geographic area, hyperlocal delivery will gain momentum with the advancement of technology. Originality/value: This study can be seen as the first attempt to investigate the issues related to the selection of the distribution channels in the FMCG sector of India using multi-criteria decision-making technique (MCDM). [ABSTRACT FROM AUTHOR]

As a result of limited resources and economic development acting as dual bottleneck constraints, optimizing industrial layout structures has been a general trend in heavy industry. The visual supervision of heat source factories based on integrated multidimensional information is important for optimizing an industrial layout. Based on Visible Infrared Imaging Radiometer Suite (VIIRS) I‐band 375‐m active fire product (VNP14IMG) data, point of interest data, enterprise attribute information and other data, combined with clustering regression, knowledge graphs (KGs), 3D geographic information systems, and other technical methods, the temporal and spatial variations in China's heat source industries are macroscopically analyzed, and a visual supervision platform for heat source industries with functions such as visualization, time‐series analysis, and knowledge discovery is established. The results show that: (1) overall, heat source factories exhibit a spatial pattern of dense in the east and sparse in the west, and the number of industrial heat source objects and the number of industrial fire hotspots decreased from 2013 to 2021, with rates of decline of 22.0 and 27.3%, respectively; (2) the enterprise KG, which contains basic enterprise information, dynamic enterprise risk information and enterprise equity structure information, can provide users with accurate and reliable enterprise knowledge; and (3) the remote sensing monitoring information platform for heat source factories performs well in terms of the discovery and management of heat source factories at large scale. In general, the platform constructed in this study can support the rapid monitoring and positioning of industrial heat sources over large areas to improve supervision in terms of finding problems and preventing risks and to provide a necessary reference for optimizing industrial spatial patterns and environmental governance. [ABSTRACT FROM AUTHOR]

This paper concentrates on computing the stabilizing region of fractional‐order proportional integral derivative (FOPID) controllers for interval delayed fractional‐order plants. An interval delayed fractional‐order plant is defined as a fractional‐order transfer function with a time delay whose denominator and numerator coefficients are all uncertain and lie in specified intervals. In the present study, first, a theorem is proven to analyze the robust stability of the given closed‐loop. Then, a method is proposed to solve the problem of robustly stabilizing interval delayed fractional‐order plants by using FOPID controllers. Moreover, two auxiliary functions are presented to fulfill the additional specifications of design, ensuring better performance of the controlled system with respect to the disturbance and noise. Finally, two examples are provided to illustrate the design procedure. [ABSTRACT FROM AUTHOR]

Purpose: Due to uncertainty in supply chains caused by the coronavirus disease 2019 (COVID-19), organizations are adjusting their supply chain design to address challenges faced during the pandemic. To safeguard their operations against disruption in order quantities, supply chain members have been looking for alternate suppliers. This paper considers a two-level supply chain consisting of a manufacturer and two suppliers of a certain type of components required for the production of a finished product. The primary supplier (supplier A) is unreliable, in the sense that the quantity delivered is usually less than the ordered quantity. The proportion of the ordered quantity delivered by supplier A is a random variable with a known probability distribution. The secondary supplier (supplier B) always delivers the order in its entirety at a higher cost and can respond instantaneously. In order for supplier B to respond instantaneously, the manufacturer is required to reserve a certain quantity at an additional cost. Once the quantity received from the main supplier is observed, the manufacturer may place an order not exceeding the reserved quantity. Design/methodology/approach: A mathematical model describing the production/inventory situation of the supply chain is formulated. The model allows the determination of the manufacturer's optimal ordering policy. Findings: An expression for the expected total cost per unit time function is derived. The optimal solution is determined by solving a system of nonlinear equations obtained by minimizing the expected total cost function. Practical implications: The proposed model can be used by supply chain managers aiming at identifying various ways of handling the uncertainty in the flow of supplies across the chain. Originality/value: This proposed model addresses a gap in the production/inventory literature. [ABSTRACT FROM AUTHOR]

A paint manufacturing firm's customers typically place orders for two or more products simultaneously. Each product belongs to a family that denotes batching compatibility during manufacturing. Further, products can be split into several sublots to allow overlapping production in a two-stage hybrid flow shop wherein various identical, capacitated machines operate in parallel at each stage. We present a mixed-integer linear program (MILP) for this integrated batching and lot streaming problem with variable sublots, incompatible job families, and sequence-dependent setup times. The model determines the number and size of sublots for each product and the production sequencing for each sublot such that the total weighted completion time is minimised. To promote practical implementation, we develop and evaluate heuristics to efficiently solve this problem. [ABSTRACT FROM AUTHOR]

Trade credit is a popular payment method in the supply chain. However, it may transfer the market risk facing by the retailer to the manufacturer in the form of default risk. To reduce the default loss, we set up a modified newsvendor model incorporating random default probability. Under the goal of loss minimisation, the manufacturer's optimal production quantity is derived with the criterion of conditional value at risk, and compared with the retailer's optimal order quantity. It is found that, compared with traditional newsvendor setting, the setting of default possibility in trade credit can increase the order quantity but decrease the production quantity. If the risk aversion level and gross profit of product are low, the manufacturer may deliver below the quantity ordered. Although the default loss can be reduced by cutting order, the profits of both agents decrease, thereby leading to a deviation from the supply chain coordination. Trade credit coordinating the supply chain requires an extremely long credit period, which is not feasible. Moreover, quantity discount contract is able to improve the retailer's order quantity, but insufficient to achieve coordination, which also depends on the manufacturer's risk aversion level. [ABSTRACT FROM AUTHOR]

Working in the self-dual sector for Yang-Mills and gravity, we show how to construct an extended phase space at null infinity, to all orders in the radial expansion. This formalises the symmetry origin of the infrared behaviour of these theories to all subleading orders. As a corollary, we also derive a double copy mapping from a subset of YM gauge transformations to a subset of diffeomorphisms to all orders in the transformation parameters, which to our knowledge has not been presented before in the literature. [ABSTRACT FROM AUTHOR]

This paper focuses on computing the stabilizing region of fractional-order proportional integral derivative (FOPID) controllers for interval fractional-order plants. In this study, first, a theorem is presented to investigate the robust stability of the given closed-loop system. Then, an algorithm is proposed to solve the problem of robustly stabilizing the interval fractional-order plant using FOPID controllers. Also, two auxiliary functions are proposed to achieve the control requirements on the disturbance rejection and the noise reduction. Finally, four numerical examples are presented to confirm the obtained results. [ABSTRACT FROM AUTHOR]

The aeronautic manufacturing industry has been seeking to enhance competitiveness and product quality by applying the Industry 4.0's technologies. Particularly, on the roadmap of the digital twin era, a way to achieve a reduction in manufacturing time and thus production cost is to obtain prediction models of the main elementary assembly operations and functions within aircraft manufacturing process, such as the clamping force applied by the temporary fasteners on the aircraft's structural parts. Besides being a mandatory operation, it affects multiple tasks along the product's assembly lifecycle. This work focuses on the role of the clamping force in the assembly process, establishing its functional model by means of an experimental approach based upon resources used on a real shop floor of a major aircraft manufacturer. To evince the main requirements that the clamping force tools can achieve, this work employs the Taguchi Design method, design of experiments, and process capability analysis. The model resulted from the aforementioned methods and tools allows the assembly behavior prediction and thus the control of the manufacturing process, ultimately yielding a better geometry quality. [ABSTRACT FROM AUTHOR]

Counterfeit drugs are without a doubt becoming a greater hazard to consumers and the pharmaceutical sector. As a result, real-time visibility of drug manufacturing and management is required. The proposed system uses Ethereum blockchain as the main technology. The primary advantage of blockchain technology is that the transactions are maintained in immutable digital ledger format and it may be read easily without jeopardizing the users' security and privacy. In our proposed system, the admin validates and adds the manufacturers. The manufacturer after registering and logging in can perform tasks like adding the drug and seller list. The seller can place order to the manufacturer which the manufacturer can accept or reject. The seller can update status of order of accepted orders to delivered. The customer can view the order details by entering the serial number on the drug package. Any transaction or exchange that occurs in the network is recorded in the chain. It functions similarly to other networks, but blockchain technology is distinguished by the fact that no data can be removed or altered by anyone in the network. No changes to the network can be made unless it has been validated by all of the network's authorized users. All the information stored can be read by anybody so to incorporate more security, AES has been used to store data in the blockchain. The use of AES encryption technique distinguishes this system from all the existing implementations. Thus, this makes it easy to trace to the exact point in the supply chain and detect any counterfeit drugs in movement. As an extension to the drug counterfeit prevention system a Drug Recommendation System is also performed using the ensemble model with a combination of Random Forest and Logistic Regression for sentiment analysis training. Furthermore, when compared to the existing Linear SVM model, which has an accuracy of 90.39%, the suggested model has the best accuracy of 93.31%. Using the obtained sentiment for each drug, the drug is predicted accurately for the specified medical condition. [ABSTRACT FROM AUTHOR]

Despite the progress that has been in the field of producing and marketing of medicinal and aromatic plants in general and the chamomile and fennel crops in particular from the successes at the local and global levels as it is considered as a raw material for manufacturing a large number of products and commodity export which contributed in increasing the outcome of national income. It was a motivation to development of agriculture and trade of these crops and increases their competitiveness against the competing countries., and despite this, the percentage that the value of medicinal and aromatic plants contributes about 2 billion pounds, or 0.7% of the value of vegetarian production, in Egypt is not absent from the markets of global medicinal and aromatic plants, as the value of its trading trade reached towards 156.3 million dollars, or 2.8 % of the total value of agricultural exports for 2020, which is a small percentage. The results of the research showed that the nominal protection laboratories for the Chamomile and Fennel crops are the average period (2016-2020) has reached about 1.01, 1.01 in order, which means that the state supports and protects the agricultural product and increases the tax burdens of the consumer, meaning that the local (agricultural) price is It exceeds the global price, and that producers of these crops in Egypt receive implicit support. It also turned out that the effective protection laboratories for the chamomile and fennel Shiites in Egypt during the previous period are estimated at 0.73, 0.82 in order, which means that the producer receives implicit support and that the consumer bears an implicit tax, as it became clear that the relative feature factories or resource cost Local for the Chamomile and Fennel has reached about 0.91, 0.89 in the order, which is less than the correct one, which means the crop has a comparative advantage in its production, and that the costs needed to add one pound of one pound representing about 0.91, 0.89 pounds per acre On the arrangement during the search period. This feature can be used to increase exports to the chamomile and fennel crops to the external markets It also became clear from the research that the economic surplus for the cobes of the chamomile and fennel Shiites in Egypt during the average period (2016-2020) estimated at 376.6, 415 pounds per acre in the order, which means increasing the economic profit of the state from the financial profit of the farmer by about 36.7%, 21, 5% in the arrangement, and this is confirmed by the percentage of the net acres of the farmer on the net of the state's academic return, which was estimated at 0.73, 0.82, respectively for the two crops during the research period In light of the previous results, the study recommends the following: 1- Facing obstacles that prevent exporting oil crops to foreign markets and over coming these obstacles, such as high production requirements and product quality and prices, and studying the most important foreign markets importing. 2 -Activating the cooperation between the government and private sector to improve the ability of oil crops producers to export in order to increase their incomes provided that quality standards and improve the marketing structure oil crops by availability of storage, transportation and information marketing ways. `3- Creating economic and production structure to encourage producers to cultivate new land in the reclaimed areas to increase the cultivated area of oil crops. 4-Holding educational training courses for farmers and providing them with all new studies and research for medical and aromatic plants 5-Establishing a marketing information device within the cooperative structure at the state level and within all the production areas. [ABSTRACT FROM AUTHOR]

A simulation model of the process of transportation of spare parts from the manufacturer to airports was developed using the method of agent modeling in the AnyLogic environment. During the construction of the model, a GIS map of the OpenStreetMap resource was used, which allows you to add coordinates of objects and build routes as close as possible to real ones. The imitation model was built for the Antonov Serial Plant and seven Ukrainian airports, which need spare parts for aircraft maintenance and repair twice a week. The order comes from the airport to the factory via notification. After that, the truck is loaded, the maximum number of cars for transportation is seven. The time for loading and unloading is two to three hours. After receiving the spare parts, the airport notifies this enterprise by the message «Delivered!». Then the truck is sent back to the enterprise. During the development of the simulation model, the single agent for the factory «Manufacturing», the population of the agent «Airport», which contains a collection of airports with their coordinates, the population of agents «Truck» and the agent type «Order» are created. The process of placing an order for new spare parts is described, given that each airport sends a request of the same form. The logic of order processing by the plant is described, which takes into account: receiving an application, time for loading the truck, sending it to the customer, unloading the truck, notification of delivery and returning the truck to the company. An optimization experiment was created and conducted to minimize the number of cargo vehicles for the supply of spare parts to Ukrainian airports, the loading of which is no more than 85%. The results of the experiment showed that the best allowable value for the use of resources is about 64% when using 2 trucks. According to the results of the conducted research the average value of the resource utilization rate at the enterprise will range from 60–85 %. [ABSTRACT FROM AUTHOR]

Green manufacturing (especially the right production scale) and optimization of logistics transportation (especially logistics transportation to ensure economic benefits) have become challenging issues. This paper focuses on production planning and scheduling of dynamic supply chain via H ∞ control scheme. This paper considers the production scale control and resource scheduling optimization of complex dynamic supply chain under the impact of the COVID-19 pandemic.Firstly, the information of green manufacturing production is collected, and a new mathematical model of complex dynamic supply chain including multi-level distributor/retailer, multi-delay inventory and multi-lead time is established. Secondly, the optimal resource scheduling scheme is designed based on the principle of H ∞ cybernetics, which is called the hierarchical scheduling of complex dynamic supply chain in this paper. Finally, a numerical example shows the effectiveness and feasibility of the proposed scheme. Through this model, the production of manufacturers, the inventory of manufacturers and distributors, and the order quantity of distributors can be arranged in advance, which improves the robustness of the closed-loop dynamic supply chain. [ABSTRACT FROM AUTHOR]

The responses of photosynthesis to change of temperature and CO2 concentration are divergent among various alpine plant species at high altitude regions; however, very few direct in situ measurements have been conducted to compare photosynthetic capacity among different functional plants along altitude gradients in the Qinghai‐Tibet Plateau (QTP). This study measured the net photosynthetic assimilation rate (An), maximum carboxylation rate (Vcmax), maximum electron transport rate (Jmax), stomatal conductance (gs) and mesophyll conductance (gm) for CO2 of three plant functional types (PFTs, sedge, grass and shrub) and functional traits at different altitudes in the Qinghai Lake watershed during growing season. Meanwhile we simulated An of the PFTs under potential future scenario. Results indicate that grass maintain a relatively stable An by decreasing Vcmax, Jmax, ratio of Jmax to Vcmax (J/V) and gs, while slightly increasing gm with increasing altitudes. In contrast, the An of sedge and shrubs increased with rising Vcmax, Jmax, gs and gm values, resulting in a large increment in the An at low altitudes. Grass was less sensitive to temperature by reducing the supply of CO2, while sedge and shrub increased. Ca was a more dominant factor than Ta in affecting the An of grass. The order of rising An in PFTs was shrub > sedge > grass, and the An of alpine meadow was found to increase more under the Representative Concentration Pathways (RCP) 4.5 and 8.5 scenarios. Our results indicate that grass may be more resistant to future warming and suggested that considering PFTs is of great significance for improving the simulating of the response of vegetation physiological and ecological processes to future climate change in alpine regions. [ABSTRACT FROM AUTHOR]