Serial System Research Articles

Compensating for part arrival uncertainties in two-processing-machine, one-buffer flow lines: Inventory flexibility design based on the system transient performances

• A structured Markov process model for the proposed flow lines;. • Transition equation derivation for the flow lines;. • The algorithms for factoring a class of states to derive closed-form expressions;. • System transient performance analysis of the flow lines system;. • Discrete event dynamic system simulation and verification. In one-of-a-kind production (OKP), a flow line with two distinct deterministic processing time machines and one “flexible” storage buffer is studied from the perspective of manufacturing system design and transient behaviour analysis. This manufacturing process is disrupted by part arrival uncertainties and is considered a discrete dynamic stochastic system. The dynamic behaviour of the flow line is structured as a transfer line with multi-state machines and finite-storage buffers by a discrete-time, discrete-state Markov chain for the transient performance analysis, optimal design and efficient production operation. To assess the dynamic disruptions and further limit the cascading effects on the flow line, in the presented analytical model, the studies quantify the evolution of a basic serial production process over time; and meanwhile, we evaluate and optimize the manufacturing system transient performance to determine the optimal design of inventory flexibility as a function of the time and states. By factoring out a class of appropriate transient states associated with an initial state at a certain time slot and deriving closed-form expressions using the transition equations, we sought to determine the transient probabilities of the manufacturing system states to establish relationships between the variable system parameters and the performance measures. By embedding these practical results with quantitative precision in an optimal design process of inventory flexibility, we consider setting the storage buffer level between two processing machines for refined production optimization and control when the part arrival uncertainties and lack of synchronization constantly occur in this serial manufacturing system.

Numerical simulation of dyeing wastewater treated by a multi-stage reverse electrodialysis reactor series system

By developing the mathematical model of a serial multi-stage reverse electrodialysis reactor (REDR) system for wastewater treatment, this paper numerically simulates the degradation process of azo dye (methyl orange) dyeing wastewater. The operation performances of the serial system with an anode and cathode synergetic degradative circulation mode are explored by numerical simulation. The influences of operation parameter variations on key performance indicators are investigated and discussed. Results indicate that the serial system can achieve excellent electricity conversion efficiency and degradative performance under an appropriate output current condition. A high initial MO concentration and electrode rinse solution (ERS) flowrate are helpful to improve the treatment performance of the system. A low concentrated solution (CS) concentration is beneficial for raising the electricity conversion efficiency and reducing the total energy consumption (TEC).

Evaluation of the Toxicity of Cafeteria Wastewater Treated by a Coupled System (ARFB-SD)

In developing countries, achieving greater coverage in the treatment and safe reuse of graywater is a pending task. Therefore, this article presents the results obtained from cafeteria wastewater treatability tests and effluent toxicity tests. For the treatment, a serial system was applied: an aged refuse filled bioreactor (ARFB) and a solar distiller (SD). In the first stage (ARFB), two hydraulic loads (HLs) were tested (200 and 400 L/m3·day), the latter being the best of them, with an average decrease of 95.7% in chemical oxygen demand (COD). In the second stage (SD), the decrease was 62.8%, resulting in a final effluent with 67.7 mg/L COD, which corresponded to a global COD decrease of 97.4%. For the toxicity tests, radish seeds were used in the serial system effluent, obtaining a relative seed germination (RSG) rate of 93.3% compared to 80% obtained in the ARFB effluent. For the percentage germination index (PGI), it was determined that both effluents (ARFB and ARFB-SD) presented a toxicity considered low, especially the ARFB-SD effluent whose PGI value was close to zero (−0.0667). The results obtained showed not only that the ARFB-SD system is efficient in removing the high organic load that can go along with cafeteria wastewater, but also that it can provide an effluent with a very low toxicity level based on the PGI close to zero.

Economic assessment of a serial production system with random imperfection and shortages: A step towards sustainability

Recent paradigm shifts in production modeling have evolved away from only economic considerations and toward the three pillars of sustainability: economic, environmental, and social, in order to accomplish sustainable development goals. While production modeling research has undergone a radical shift, quite a few studies in the production management literature have addressed sustainability challenges. These classic sustainable production models are only applicable to single-stage production systems and overlook a variety of real-world situations associated with random defective output and resulting shortages during demand fulfillment. To address this concern about developing sustainable strategies for multi-stage production, this paper analyzes a cleaner multi-stage production management system for carbon emissions reduction and active participation in corporate social responsibility activities, while also advancing the system economically. Three scenarios of random imperfect proportion are constructed, and a reworking opportunity is implied to clean the multi-stage production system. A planned backorder policy is advised to address anticipated shortages and improve the system’s service level. Analytical optimization techniques are used in the developed situations to determine the appropriate batch size and backorder quantity, hence minimizing the system’s overall cost and achieving global optimum solutions. Numerical evaluation and sensitivity analysis are used to conduct a comparative examination of the model scenarios. Significant managerial insights are developed to demonstrate the suggested cleaner multi-stage production model’s actual relevance. According to the model results, a lower batch size is the optimal strategy in response to increasing holding and CSR activity costs, but otherwise for the setup cost in a serial production system.

Optimum consultation for serial distributed detection systems

<p>This paper considers a distributed detection system which consists of sensors that are connected in series. The observations of each sensor in this system design are considered to be statistically independent of all other sensors. In contrast to the popular serial decision fusion systems, we assume that consultations are allowed in a serial manner between successive sensors that make up the system. In addition, the paper demonstrates the similarity between the proposed consulting serial system and the optimal serial one in terms of detection probabilities for a give probability of false alarm. However, it should be emphasized that the proposed system has the benefit of conditional nonrandom consultation among the sensors. Consequently, its survivability is higher than that of serial systems. Numerical evaluations for the cases of two and three sensors are provided and compared with those of the serial as well as the centralized schemes.</p>

Serial anaerobic digestion improves protein degradation and biogas production from mixed food waste

Optimization of the biogas generation process is important to achieve efficient degradation and high methane yield, and to reduce methane emissions from the digestate. In this study, serial digester systems with two or three biogas reactors were compared with a single reactor, with the aim of improving degree of degradation and methane yield from food waste and assessing adaptation of microbial communities to different reactor steps. All systems had the same total organic load (2.4 g VS/(L d)) and hydraulic retention time (55 days). Serial systems increased methane yield by >5% compared with the single reactor, with the majority of the methane being obtained from the first-step reactors. Improved protein degradation was also obtained in serial systems, with >20% lower outgoing protein concentration compared with the single reactor and increasing NH4+-N concentration with every reactor step. This resulted in separation of high ammonia (>384 mg NH3-N/L) levels from the main methane production, reducing the risk of methanogen inhibition. Methanosarcina dominated the methanogenic community in all reactors, but increases in the hydrogenotrophic genera Methanoculleus and Methanobacterium were observed at higher ammonia levels. Potential syntrophic acetate-oxidizing bacteria, such as MBA03 and Dethiobacteraceae, followed the same trend as the hydrogenotrophic methanogens. Phylum Bacteroidota family Paludibacteraceae was highly abundant in the first steps and then decreased abruptly, potentially linked to an observed decrease in degradation in the last-step reactors. Nevertheless, the results indicated a trend of increasing relative abundance of the potentially proteolytic genera Proteiniphilum and Fastidiosipila with successive reactor steps.

Numerical Simulation and Comparative Analysis of Three Boil-Off Gas Reliquefaction Systems

Abstract In view of the problem that the boil-off gas (BOG) generated by small liquefied natural gas (LNG) ships affects the transportation safety, three BOG reliquefaction systems are improved, which are as follows: case 1: serial nitrogen expansion reliquefaction system (N2-BOG); case 2: single mixed refrigerant reliquefaction system (SMR-BOG); and case 3: propane precooled mixed refrigerant reliquefaction system (C3MR-BOG). The basic process is simulated in aspen plus and combined with the mathematical model built up in matlab where the three cycles are optimized with the specific power consumption (SPC) as the objective function. The results show that the SPC of three cases are 0.8021 kWh/kg (LNG), 0.4150 kWh/kg (LNG), and 0.5063 kWh/kg (LNG); the coefficient of performance (COP) of cases 1, 2, and 3 are 0.20, 0.39, and 0.30; the exergy efficiency of 36.56%, 70.66%, and 57.93% along with the total product cost of 89.00 $/h, 55.73 $/h, and 77.54 $/h are achieved in Cases 1–3, respectively. In addition, the overall exergy destruction of the cycles and each equipment are discussed, and the matching of the cold and heat sources of the multistream heat exchanger in the three systems is analyzed. In conclusion, under the condition that the BOG mass flowrate is 350 kg/h, the improved SMR-BOG has advantages on thermodynamic performance and economic analysis, which makes it a better choice.

Design of serial alarm systems based on deadbands and delay timers for removing false alarms

Alarm deadbands and delay timers are widely used in practice to remove false alarms. This paper proposes a method to design serial alarm systems that are composed of alarm deadbands serially followed by delay timers. Serial alarm systems are effective for removing false alarms with different types of alarm deviations and alarm durations, while alarm deadbands or delay timers alone are suitable only for one type of false alarms. A minimization problem is formulated to simultaneously design optimal values of the alarm deadband width and delay timer factor, for achieving a desired ratio of false alarms to be remove. Bayesian estimation approach is exploited to resolve a main technical challenge in achieving reliable estimates of joint probabilities of alarm deviations and alarm durations. Existing methods are confined to the isolated design of alarm deadbands or delay timers based on probability density functions of process variables, and are subject to a restrictive assumption that process variables are independent and identically distributed. By contrast, the proposed method is for the joint design of serially-connected alarm deadbands and delay timers; it is based on joint probabilities of alarm deviations and alarm durations, and does not require the restrictive assumption. Numerical and industrial examples are provided to illustrate the proposed method and compare with existing ones.

Multihop radio and optical wireless relaying systems over EGK, DGG, and CU fading channels

Optical wireless communications (OWC) systems provide higher data rates in the unlicensed spectrum bands compared to traditional radio frequency (RF) wireless communications systems. OWC systems are categorized as free space optical (FSO) communications and visible light communications (VLC) for outdoor and indoor environments, respectively. In this paper, we propose a multihop serial RF, FSO, and VLC system and investigate the link performance for five different scenarios with amplify-and-forward and decode-and-forward relaying protocols under different channel conditions. Based on the SNR statistics, we show closed-form expressions for the outage probability for all scenarios and derive their diversity orders. In addition, we examine the accuracy and correctness of the derived expressions by means of Monte Carlo simulations. We further prove that the diversity order is a function of the severity of the RF links and the shaping parameters, the atmospheric turbulence, the pointing error in FSO links, the detection method, and number of links. Finally, the presented results complement and extend several results previously reported in the literature.

Developing and Organizing an Easy Work Environment For Users of Computers Using Information Technology

The study aims to implement a serial security technology system to organize a comfortable work environment for users of computers in the General Directorate of Education in Baghdad Karkh3. The most important findings of the study are the application of a serial technology system. It is connected with scientific goals that show the scientific structure of computer learning and its applications. It considers global learning systems and take into account the ease and scientific flow of the class of elderly employees. In addition, employees of other categories, are the outputs of the sequential technological system. The aim is to create a purposeful technological system and keep pace with global developments, to gain experience, skills and knowledge. The system is executed at the lowest time and cost at all different scientific levels, in the field of computer science, information technology, and communication.

FPGA Implementation of Data Flow Graphs for Digital Signal Processing Applications

A rapid growth in digital signal processing applications has increased the requirement for high-speed digital systems. Multiprocessor systems are the best choice for these applications. A prior sequence of operations should be applied to the operations that described the nature of these applications before hardware implementation is produced. These operations should be scheduled and hardware allocated. This paper proposes a new scheduling technique for digital signal processing (DSP) applications has been represented by data flow graphs (DFGs). In addition, hardware allocation is implemented in the form of embedded system. A proposed scheduling technique also achieves the optimal scheduling of a DFG at design time. The optimality criteria considered in this algorithm are the maximum throughput within the available hardware resources. The maximum throughput is achieved by arranging the DFG nodes according to their inter-related data dependencies. Then, two nodes can be clustered into one compound task to reduce the overall execution time by minimizing the number of tasks to be executed that minimizing the number of cycles to execute them. Then each task is presented in form of instruction to be executed in the hardware system. A hardware system is composed of one or multiple homogenous pipelined processing elements and it is designed to meet the maximum-rate schedule. Two implementations are proposed of the system architecture according to the number of the processing elements, namely: the serial system and the parallel system. The serial system comprises one processing element where all tasks are processed sequentially, whilst the parallel system has four processing elements to execute tasks concurrently. These systems consist mainly of seven units: central shared memory, state table, multiway function unit buffer, execution array, processing element/s, instruction buffer and the address generation unit. The hardware components were built on an FPGA chip using Verilog HDL. In synthesis results, the parallel system has better system performance by 25.5% than the serial system. While the serial system requires smaller area size, which described by the number of slice registers and the number of the slice lookup tables (LUTs) than the parallel one. The relationship between the number of instructions that are executed in both systems, and the system area and the system performance that presented by system frequency, are studied. By increasing memories size in both systems, the system performance isn’t affected as in a serial system, and it is slightly decreased as the parallel system by 1.5% to 4.5%. In terms of the systems area, both serial system area and parallel system area are increased and in some cases are doubled. The proposed scheduling technique is shown to outperform the retaining technique, which we have chosen to compare with. The serial system has better performance by 19.3% higher system frequency than a retiming technique. And the parallel system also outperforms the retaining technique by 51.2% higher system frequency in synthesis results.

Automatic Surgery and Anesthesia Emergence Duration Prediction Using Artificial Neural Networks.

Cost control is becoming increasingly important in hospital management. Hospital operating rooms have high resource consumption because they are a major part of a hospital. Thus, the optimal use of operating rooms can lead to high resource savings. However, because of the uncertainty of the operation procedures, it is difficult to arrange for the use of operating rooms in advance. In general, the durations of both surgery and anesthesia emergence determine the time requirements of operating rooms, and these durations are difficult to predict. In this study, we used an artificial neural network to construct a surgery and anesthesia emergence duration-prediction system. We propose an intelligent data preprocessing algorithm to balance and enhance the training dataset automatically. The experimental results indicate that the prediction accuracies of the proposed serial prediction systems are acceptable in comparison to separate systems.

General Approach to the Description of Computer Number Systems

General relationships, algorithms, and differences for three numerical systems used in the field of computing technology are analyzed: positional, polyadic and modular. Their power-law modifications are obtained. A single basic algorithm for the formation of components of vectors representing numerical values in these systems, which are residues in relatively simple modules from the set of bases of a numerical system, is analyzed with an estimate of complexity. Vector representation of numerical values is a mathematical and algorithmic basis for generating arithmetic computer formats focused on high-performance parallel processing. Generalization of the representation of numerical values in three computer number systems in the form of vectors with an indication of the limits of change of representation components is intended for the analysis and parallelization of complex computational processes. Analysis from a unified position of computer number systems makes it possible to find computational problems for which the use of individual of them is effective. For tasks in which it is necessary to simultaneously process data in various formats associated with number systems, a correct description from a general point of view of the corresponding data formats is used. The analysis of number systems is intended for the development of mathematical structures as a base of software and algorithmic tools and the generation of machine data formats associated with these systems, designed to increase the efficiency of complex computational processes and assess their convergence for calculations in large computer ranges, focused on serial computers and scalable multiprocessor systems SIMD — architectures.

Perspectives on the Structure and Function of the Avian Respiratory System: Functional Efficiency Built on Structural Complexity

Among the air-breathing vertebrates, regarding respiratory efficiency, the avian respiratory system rests at the evolutionary zenith. Structurally, it is separated into a lung that serves as a gas exchanger and air sacs that mechanically ventilate the lung continuously and unidirectionally in a caudocranial direction. Largely avascular, the air sacs are delicate, transparent, compliant and capacious air-filled spaces that are not meaningfully involved in gas exchange. The avian lungs are deeply and firmly attached to the vertebrae and the ribs on the dorsolateral aspects, rendering them practically rigid and inflexible. The attachment of the lung to the body wall allowed extreme subdivision of the exchange tissue into minuscule and stable terminal respiratory units, the air capillaries. The process generated a large respiratory surface area in small lungs with low volume density of gas exchange tissue. For the respiratory structures, invariably, thin blood-gas barrier, large respiratory surface area and large pulmonary capillary blood volume are the foremost adaptive structural features that confer large total pulmonary morphometric diffusing capacities of O2. At parabronchial level, the construction and the arrangement of the airway- and the vascular components of the avian lung determine the delivery, the presentation and the exposure of inspired air to capillary blood across the blood-gas barrier. In the avian lung, crosscurrent-, countercurrent- and multicapillary serial arterialization systems that stem from the organization of the structural parts of the lung promote gas exchange. The exceptional respiratory efficiency of the avian respiratory system stems from synergy of morphological properties and physiological processes, means by which O2uptake is optimized and high metabolic states and capacities supported. Given that among the extant animal taxa insects, birds and bats (which accomplished volancy chronologically in that order) possess structurally much different respiratory systems, the avian respiratory system was by no means a prerequisite for evolution of powered flight but was but one of the adaptive solutions to realization of an exceptionally efficient mode of locomotion.

A serial inventory system with lead-time-dependent backordering: A reduced-state approximation

We study a serial inventory system where the external customers may have a maximum time that they would be willing to wait for delivery in cases of stock-out and the demand would be lost if the remaining delivery lead time of the next available item is longer. This lead-time-dependent backordering behavior subsumes the models of partial backordering regardless of the wait that a customer would experience. In the inventory literature, this behavior has only been analyzed in single-location settings. We study this behavior in a multi-stage setting. We consider continuous review policies at all stages facing external Poisson demands. Using the method of supplementary variables, we define the stochastic process representing the inventory system and obtain the expressions for the operating characteristics of the inventory system. Based on the solution structures for the special cases, we propose an approximate solution which rests on replacing the state-dependent purchasing decision of the customer with an averaged-out purchase probability computed using only the age of the oldest item. An extensive numerical study indicates that the proposed approximation performs very well. Our numerical study provides additional insights about the sensitivity and allocation of stock levels across stages.

Machine-learning-based water quality management of river with serial impoundments in the Republic of Korea

Euiam Lake in the Republic of Korea This study establishes a framework to prioritize total phosphorus (TP) management strategies based on machine learning (ML). A comparative analysis is conducted to evaluate the performance of four ML methods: random forest (RF), extreme gradient boosting (XGBoost), deep neural network (DNN), and long short-term memory (LSTM). The LSTM-based model is selected as the optimal predictive model of TP concentration in Euiam Lake (E_TP) on seasons (May to October) with high rainfall and inflow from two upstream dams (Chuncheon Dam and Soyanggang Dam). We also perform a gradient-based analysis to figure out the most influential factors on E_TP using the LSTM model. The top four priority factors are TP concentrations and suspended solids concentrations in the upstream dams. This application of the gradient-based analysis enables the predictive model to discuss quantitative reductions in the priorities. Based on these numerical results, we anticipate that the proposed framework can enhance the feasibility of management practices for achieving the water quality management goal of the study region. This study demonstrates that a robust predictive model can be developed for a serial impoundment system with distinct seasonal characteristics of rainfall, temperature, and water quality, thereby facilitating the selection of management priorities. Based on the predictive model results, we conclude that it is the key for managing the target TP concentration to prioritize the incoming TP concentrations and determine the quantitative • Water quality management strategy is established using RF, XGBoost, DNN, and LSTM. • The LSTM model outperforms the other ML methods when predicting the TP concentration in Euiam Lake. • The LSTM gradient-based analysis determines TP management priorities and their quantitative reduction.

Microcontroller Controlled Inverter Application

The limited use of fossil fuels has increased the interest in renewable energy sources. Renewable energy sources are generally direct current (DC) production. The popularity of inverters converting from DC to AC is increasing due to the generation of the generated DC signal and the current grid being alternating current (AC). In this study, a computer-controlled inverter was designed with the 16F877 microcontroller chosen as the model, and frequency and amplitude controls were realized with the serial communication system of this structure. A digital-analog converter (DAC) circuit is formed by connecting the R-2R ladder type resistor to the relevant ports of the microprocessor. With the codes written to the microprocessor, the signal response was taken from the DAC circuit, and the signal response at the ports was combined with the inverter and collector operational amplifier (op-amp) circuits, and the inverter design was completed.

A Novel Analytical Modeling Approach for Quality Propagation of Transient Analysis of Serial Production Systems.

Production system modeling (PSM) for quality propagation involves mapping the principles between components and systems. While most existing studies focus on the steady-state analysis, the transient quality analysis remains largely unexplored. It is of significance to fully understand quality propagation, especially during transients, to shorten product changeover time, decrease quality loss, and improve quality. In this paper, a novel analytical PSM approach is established based on the Markov model, to explore product quality propagation for transient analysis of serial multi-stage production systems. The cascade property for quality propagation among correlated sequential stages was investigated, taking into account both the status of the current stage and the quality of the outputs from upstream stages. Closed-form formulae to evaluate transient quality performances of multi-stage systems were formulated, including the dynamics of system quality, settling time, and quality loss. An iterative procedure utilizing the aggregation technique is presented to approximate transient quality performance with computational efficiency and high accuracy. Moreover, system theoretic properties of quality measures were analyzed and the quality bottleneck identification method was investigated. In the case study, the modeling error was 0.36% and the calculation could clearly track system dynamics; quality bottleneck was identified to decrease the quality loss and facilitate continuous improvement. The experimental results illustrate the applicability of the proposed PSM approach.

Optimal Policies for a Multi-Echelon Inventory Problem with Service Time Target and Expediting

Problem definition: We study the optimal inventory ordering, expediting, and allocation decisions in a multiechelon supply chain over a finite horizon, in which customer orders are quoted with a fixed fulfillment time window, termed the service time target (STT). Academic/practical relevance: Service time target is commonly used as a marketing strategy to increase customer satisfaction and strengthen firms’ competitive edge. However, how to efficiently manage a multistage supply chain to meet the target has received relatively scant attention in the literature. Our study fills this gap. Methodology: We use dynamic programming to characterize the optimal policy. Results: We show that an echelon base stock policy and a rationing policy are optimal for inventory ordering and inventory allocation/expediting, respectively. We also develop a polynomial-time algorithm to compute the optimal policy. To derive these results, we uncover a new functional property named the decomposable of degree 2 property, which is a nontrivial generalization of the celebrated Clark-Scarf decomposition. This property further allows us to derive induced penalty and compensation to coordinate a decentralized serial system with STT and expediting. Managerial implications: Our result provides an efficient decision tool for managing centralized and decentralized serial supply chains with STT and expediting. Our model can be used to quantify the tradeoff between marketing and operational decisions, such as the impact of a marginal reduction in STT on system cost and expedition frequency, as explored in our numerical studies.

Identification of key microorganisms in facultative stabilization ponds from dairy industries, using metagenomics.

Wastewater stabilization ponds are a natural form of wastewater treatment. Their low operation and maintenance costs have made them popular, especially in developing countries. In these systems, effluents are retained for long periods of time, allowing the microbial communities present in the ponds to degrade the organic matter present, using both aerobic and anaerobic processes. Even though these systems are widespread in low income countries, there are no studies about the microorganisms present in them and how they operate. In this study, we analised the microbial communities of two serial full-scale stabilization ponds systems using whole genome shotgun sequencing. First, a taxonomic profiling of the reads was performed, to estimate the microbial diversity. Then, the reads of each system were assembled and binned, allowing the reconstruction of 110 microbial genomes. A functional analysis of the genomes allowed us to find how the main metabolic pathways are carried out, and we propose several organisms that would be key to this kind of environment, since they play an important role in these metabolic pathways. This study represents the first genome-centred approach to understand the metabolic processes in facultative ponds. A better understanding of these microbial communities and how they stabilize the effluents of dairy industries is necessary to improve them and to minimize the environmental impact of dairy industries wastewater.