Serial Lines Research Articles

Theoretical and Experimental Analysis of Practical Porous Electrodes for Lithium-Sulfur Batteries By Electrochemical Impedance Spectroscopy

We present in this talk a simplified model for a porous sulfur/carbon electrode based on a uniform cylindrical pores and a transmission line model (TLM) to explain the observations of Electrochemical Impedance Spectroscopy (EIS) measurements. We provide an understanding of the origin of the internal resistances of the porous sulfur electrode/electrolyte interface in Li-S batteries. The proposed model can serve as a diagnostic tool for determining the state of health of the cell and for quantifying the ionic resistances limiting the design of high-power systems. Nevertheless, the separation of impedance elements for a Li-S cell is not a straightforward task due to the multiple reaction steps and volume changes during the discharge and charge process involving the dissolution of the sulfur into polysulfides and their precipitation into the insulating low order polysulfides. EIS studies in combination with TLM have been presented for lithium-ion cells by several authors.1-3 Other researchers have characterized the resistances involved in the cell by fitting EIS data.4-8 In addition, there have been efforts using TLMs for estimating the impedance response of a Li-S cell, to provide an understanding about the internal resistances in the electrode and a description of its possible electrical circuit.7, 8 Nevertheless, there is still no agreement on the parameters affecting the results nor neither their contribution, and thus, only trends have been postulated. Therefore, this work goes beyond the general scope of previous studies and attempts to rationalize the effect of the electrode architecture (geometry, thickness, surface area) and active material loading for the sulfur/carbon composite electrode in the initial performance of Li-S batteries. The use of a practical and simple electrode description captures the significant variables that have an effect on the initial discharge process of the Li-S cell. The geometrical simplification stands as an attractive and straightforward strategy for engineering new electrodes and predicting initial cell performance. Abarbanel, D. W.; Nelson, K. J.; Dahn, J. R., Exploring Impedance Growth in High Voltage NMC/Graphite Li-Ion Cells Using a Transmission Line Model. Journal of The Electrochemical Society 2015, 163 (3), A522-A529.Nara, H.; Mukoyama, D.; Yokoshima, T.; Momma, T.; Osaka, T., Impedance Analysis with Transmission Line Model for Reaction Distribution in a Pouch Type Lithium-Ion Battery by Using Micro Reference Electrode. Journal of The Electrochemical Society 2015, 163 (3), A434-A441.Illig, J.; Ender, M.; Weber, A.; Ivers-Tiffée, E., Modeling graphite anodes with serial and transmission line models. Journal of Power Sources 2015, 282, 335-347.Ogihara, N.; Kawauchi, S.; Okuda, C.; Itou, Y.; Takeuchi, Y.; Ukyo, Y., Theoretical and Experimental Analysis of Porous Electrodes for Lithium-Ion Batteries by Electrochemical Impedance Spectroscopy Using a Symmetric Cell.Barchasz, C.; Leprêtre, J.-C.; Alloin, F.; Patoux, S., New insights into the limiting parameters of the Li/S rechargeable cell. Journal of Power Sources 2012, 199, 322-330.Kolosnitsyn, V. S.; Kuz’mina, E. V.; Karaseva, E. V.; Mochalov, S. E., Impedance spectroscopy studies of changes in the properties of lithium-sulfur cells in the course of cycling. Russian Journal of Electrochemistry 2011, 47 (7), 793-798.Qiu, X.; Hua, Q.; Zheng, L.; Dai, Z., Study of the discharge/charge process of lithium–sulfur batteries by electrochemical impedance spectroscopy. RSC Advances 2020, 10 (9), 5283-5293.Deng, Z.; Zhang, Z.; Lai, Y.; Liu, J.; Li, J.; Liu, Y., Electrochemical Impedance Spectroscopy Study of a Lithium/Sulfur Battery: Modeling and Analysis of Capacity Fading. Journal of The Electrochemical Society 2013, 160 (4), A553-A558. Figure 1

An effective and efficient divide-and-conquer algorithm for energy consumption optimisation problem in long Bernoulli serial lines

Reducing energy consumption in the energy-intensive production systems is of great significance and attracts more and more attention. Although a lot of efforts have been devoted to formulate and solve the energy consumption optimisation problem in the Bernoulli serial lines, existing methods for solving the problem in long Bernoulli lines either cannot obtain the optimal solution or are time-consuming. For this purpose, this paper divides the problem in the long line into a set of problems in two-machine lines and proposes a computationally efficient and globally convergent algorithm to solve it. Extensive numerical experiments show that the proposed algorithm not only can optimally (in the numerical way) solve the energy consumption optimisation problem in long Bernoulli serial lines, but also is orders of magnitude more efficient than existing algorithms.

Eco-efficient management of a feeding system in an automobile assembly-line

Purpose This study aims to reduce carbon emissions and costs in an automobile production plant by improving the operational management efficiency of a serial assembly line assisted by a feeding electric tow vehicle (ETV). Design/methodology/approach A multi-objective function is formulated to minimize the energy consumption of the ETV from which emissions and costs are measured. First, a mixed-integer linear programming model is used to solve the feeding problem for different sizes of the assembly line. Second, a bi-objective optimization (HBOO) model is used to simultaneously minimize the most eco-efficient objectives: the number of completed runs (tours) by the ETV along the assembly line, and the number of visits (stops) made by the ETV to deliver kits of components to workstations. Findings The most eco-efficient strategy is always the bi-objective optimal solution regardless of the size of the assembly line, whereas, for single objectives, the optimization strategy differs depending on the size of the assembly line. Research limitations/implications Instances of the problem are randomly generated to reproduce real conditions of a particular automotive factory according to a previous case study. The optimization procedure allows managers to assess real scenarios improving the assembly line eco-efficiency. These results promote the implementation of automated control of feeding processes in green manufacturing. Originality/value The HBOO-model assesses the assembly line performance with a view to reducing the environmental impact effectively and contributes to reducing the existent gap in the literature. The optimization results define key strategies for manufacturing industries eager to integrate battery-operated motors or to address inefficient traffic of automated transport to curb the carbon footprint.

Order-Reduced Dynamic Decoupling Approach for Performance Evaluation of Multitype and Small-Batch-Based Serial Lines With Adjustments and Resets

In the existing literature, extensive investigations focus on evaluating the performance of production systems that typically assumed to be operating under rigid production mode. Mass production as well as single type of products is the representative characteristics of this production mode. However, by applying prompt equipment adjustments and resets, modern production lines are capable of making different products in small batches with varying processing requirements. This is referred to as flexible manufacturing mode. With the flexible manufacturing mode, which has been widely used in recent years, real-time performance evaluation and prediction, small-batch-based real-time scheduling, and management of such systems, etc., are having important research significance. In this article, by considering adjustments and resets on serial production lines with multitype and small-batch-based production, the transient performance evaluation problem is studied. Specifically, for the system with machines having the Bernoulli reliability model and buffers having finite capacities, the mathematical model is formulated first. Then, we develop a Markovian model and a computational procedure for evaluating various system real-time performance indicators, such as production rates and completion times of different batch-based production tasks, etc. In addition, an order-reduced dynamic decoupling approach is proposed to approximate system real-time performance with high accuracy and computational efficiency. Finally, theoretic properties of the system under the flexible manufacturing mode are discussed.

Proteomic analyses reveal divergent ubiquitylation patterns in hepatocellula carcinoma cell lines with different metastasis potential

Hepatocellular carcinoma (HCC) is one of the most common malignant tumours, metastasis and recurrence remain the primary reasons for poor prognosis. Ubiquitination serves as a degradation mechanism of proteins, but it is involved in additional cellular processes including metastasis. Here, by using label-free quantification, double-glycine (di-Gly) antibody affinity purification and high-resolution liquid chromatography tandem mass spectrometry (LC-MS/MS), we investigated quantitative proteome, ubiquitylome, and the crosstalk between the two datasets in HCC cell lines with different metastasis potential to identify biomarkers associated with HCC metastasis. In total, 83 ubiquitinated proteins significantly and steadily changed their abundance according to their metastatic potential, and the participated biological processes of these ubiquitinated proteins were tightly associated with tumour metastasis. Further signaling pathway analysis revealed that the ribosome and proteasome were significantly over-activated in the highly metastatic cells. Furthermore, we analyzed the crosstalk between the whole proteome and the ubiquitylome, and further discussed the mechanism that how ubiquitination events affect HCC metastasis. Eventually, the ubiquitination of Ku80 was validated to be significantly down-regulated in the high-metastatic cells comparing with the low-metastatic cells. We believe that these findings will help us better understand the underlying molecular mechanisms of the metastasis of HCC. SignificanceIn this manuscript, we used label free based proteomics combined with diglycine antibody (di-Gly) affinity purification approach to identify biomarkers associated with HCC recurrence/metastasis in in a serial HCC cell lines with increasing invasion and metastasis potential. And then, we analyzed the crosstalk between the whole proteome and the ubiquitylome. Eventually, the ubiquitination of Ku80 was confirm to be closely associated with invasion and migration of HCC cells. As far as we know, this is the first time to use quantitative proteomic approach to study the ubiquitylomics in HCC cell lines with increasing metastasis ability.

A new aggregation algorithm for performance metric calculation in serial production lines with exponential machines: design, accuracy and robustness

Performance metric calculation is one of the most important problems in production system research. In this paper, we consider serial production lines with finite buffers and machines following the exponential reliability model. Analytical formulas are first given for performance analysis of two-machine lines. Based on these formulas, a throughput-equivalent aggregation procedure is derived to represent a two-machine exponential line by a single exponential machine. Following this approach, we propose a new aggregation-based iterative algorithm to calculate the performance metrics of a multi-machine serial line by representing it using a group of virtual two-machine lines. Numerical experiments are used to justify the convergence of the algorithm and to evaluate the accuracy of the calculated performance metrics. The results show that the proposed algorithm significantly improves the performance metric approximation accuracy, compared with two commonly used aggregation-based methods in the literature, without incurring additional computational burden. The improvement is even more prominent for systems with relatively small buffers. We believe that this work makes an important contribution to the field of Production Systems Engineering and has the potential to generate great impact as the new algorithm replaces the existing ones in future research and applications by scholars and practitioners.

Problem Formulation and Solution Methodology for Energy Consumption Optimization in Bernoulli Serial Lines

As the main force of energy consumption, machines consume a huge amount of energy in some production systems. To operate the systems in an energy-efficient way, the efficiencies of the machines should be elaborately optimized so that the total energy consumption in the production lines is minimized while maintaining the required production rate. For this purpose, this article investigates the energy consumption optimization problem in Bernoulli serial lines having more than two machines. Specifically, this problem is first formulated as a nonlinear programming with a production rate constraint; due to difficulties in solving this constrained nonlinear programming, structural characteristics of the problem and properties of the objective function, which are inspired by the results and insights obtained in two-machine lines, are analyzed. Finally, based on the structural characteristics and properties explored, a solution methodology is developed to recursively solve the unique optimal solution of the energy consumption optimization problem. Extensive numerical experiments show that the solution provided by this method, which has the reversibility property and is better than the one provided by an existing method in the literature, is numerically optimal (note that the theoretically optimal solution is extremely hard to obtain if not totally impossible). Note to Practitioners-Machines consume a huge amount of energy in energy-intensive (i.e., high energy-consuming) production systems in, e.g., automobile, semiconductor, and steel companies. Due to economic, social, and environmental concerns, it is a high priority to consider ways to reduce the energy consumption in these production systems. In this article, the problem of minimizing the total energy consumption in Bernoulli serial lines while maintaining the required production rate is investigated. Based on the aggregation method developed for performance analysis of long lines and the optimization results obtained for two-machine lines, the energy consumption optimization problem for long Bernoulli serial lines is elaborately analyzed and a method is proposed to recursively solve its unique optimal solution (i.e., the optimal machine efficiencies). From the point of view of system operation, this research, which makes the system operate in the most energy-efficient manner, offers a new managerial paradigm for the production systems.

Assessment of the JMA Serial Observation Lines in the Northwestern Pacific in OSSE Studies with the GFDL Ensemble Coupled Data Assimilation System

AbstractTwo major serial observational positions (137°E and 165°E, operated by the Japan Meteorological Agency [JMA] in the Northwestern Pacific) were assessed using observation system simulation experiments (OSSEs) with the Geophysical Fluid Dynamics Laboratory (GFDL) ensemble coupled data assimilation system. In the OSSEs, the “True Ocean” is a simulation time series of the fully coupled GFDL climate model (CM2.1), and the “control ocean” is defined as the same CM2.1 simulation result using different initial conditions and ensemble members. The sea surface temperature, subsurface temperature, and salinity data that were drawn from the “truth” were assimilated into the “control.” The degree by which the assimilation recovers the “truth” is an assessment of the representation of the serial observation lines for regional circulations and their variability in the Northwestern Pacific. Results show that the assimilation effect of sea surface temperature is maintained to the deeper ocean by adjusting the interannual variability of the ocean temperature in the Northwestern Pacific. The root mean square error in the western area of each observational system was much lower than that in the eastern area. This is closely related to the anomalous geostrophic clockwise flow pattern strengthened throughout the assimilation process of the JMA data. We confirmed this result using a reverse bias experiment. Therefore, the assimilation effect of 165°E appearing larger western areas is also stronger than 137°E. However, the assimilation performances of the two observation systems were not significantly different in the long‐term simulations of more than 25 years in the Northwestern Pacific.

Decomposition and Aggregation-Based Real-Time Analysis of Assembly Systems With Geometric Machines and Small Batch-Based Production Tasks

Steady-state analysis on production systems, especially serial lines with rigid production mode, have been carried out in a large amount of research literature. With the development of the advanced manufacturing technologies, as well as the national strategies, for example, Made in China 2025, real-time performance evaluation, prediction, production management, and efficient control of systems with flexible production mode are gradually becoming important issues. Under the assumption of assembly systems with small batch-based production tasks, we develop a mathematical model for the real-time performance analysis of such systems with the geometric machine reliability model, which is applicable in many manufacturing environments. The formulas for real-time performance analysis are derived first using the Markovian approach for three-machine assembly systems. Then, based on the idea of decomposition and aggregation, an algorithm with high accuracy and efficiency for system real-time performance approximation is proposed. Finally, the decomposition and aggregation-based real-time analysis approach is extended to the generalized assembly systems. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —As the concept of manufacturing intelligence being proposed and promoted, system flexibility appears frequently in production in recent years. A flexible production refers to the implementation of small batch-based production with multitype of products on the same production line, by quick setup or machine adjustments. The steady-state analysis method that is traditionally used might be not applicable in this case since most of the production process is in transient state. An approximation-based analytical method, for real-time performance evaluation of assembly systems with small batch-based production tasks and with machines having the geometric reliability model, is proposed. The algorithm developed in this article can be utilized by production managers and engineers, with which the real-time performance of the systems can be predicted with high accuracy. It can also provide assistance for decision-making on activities of production control.

A new split-based hybrid metaheuristic for the reconfigurable transfer line balancing problem

We consider the Reconfigurable Transfer Line Balancing Problem. This problem consists of allocating a set of operations (necessary to machine a single part) to different workstations placed into a serial line. Each workstation can contain multiple machines operating in parallel. The machines considered are mono-spindle head CNC machines which may imply sequence-dependent setup times between operations in order to perform tool changes. Therefore, the operations allocated to a workstation should be sequenced. Besides, accessibility, inclusion, exclusion and precedence constraints between operations are considered. In this article, we propose a polynomial exact algorithm that balances the transfer line provided the overall sequence of the operations (called ‘giant sequence’) is given. We use this algorithm to solve the balancing problem when the overall sequence of operations is not fixed by embedding it in a metaheuristic framework. We perform experimentation on literature instances. The results obtained show the effectiveness of the proposed approach compared to literature.

Transient Analysis of Multiproduct Bernoulli Serial Lines With Setups

Performance analysis of flexible manufacturing systems has received substantial research attention. Most of the studies focus on steady-state behavior. The transient performance, which is critical for system operation, control, and improvement, is less investigated. No analytical method is available to evaluate the transients in flexible lines with unreliable machines, finite buffers, and setup times. In this article, an analytical model is introduced to study the transient performance of multiproduct serial lines with Bernoulli reliability machines and nonnegligible setups during changeovers. To reduce the state-space dimension, an approximation method is introduced to evaluate the performance in two-machine lines, where the sequence of multiple part types in the inventory is approximated by the ratio of product mix. Such an approximation method leads to high precision of production rate estimation. Then, for longer lines, the analysis approach in two-machine lines is used as a building block in an iterative aggregation procedure. Numerical experiments show that the iteration procedure is convergent and results in an acceptable accuracy in performance evaluation. In addition, system properties, such as monotonicity and reversibility, are investigated.

Tetrapod Automaton in the Shamble’s Management with the Fish Eye Lens Pi Cam

Automation Is The Future Technology, Without This Most Of The Technologies Are Implausible. This Paper Is All About The Tetrapod Robot Which Is The Four Legged Robot That Could Be Used In The Shamble’s Management Application. This Robot Has Four Legs For Kinesis. The Motion Of The Legs Is Achieved By The Concept Of Inverse Kinematics. The Servo Motors Are Making The Bot To Drive. The Arduino UNO Is Used To Send Signals. It Has I2C (Inter Integrated Circuits) Interface. It Has Two Signals. They Are Serial Clock Line Signal And Serial Data Line For Master Slave Communication. The Main Motive Of This Bot Is To Make It Walk Under The Disaster Areas Where Human Intervention Is Challenging. It Takes Live Images And Streams Video In The Disaster Areas. The Image Capturing And Video Streaming Is Achieved Using Raspberry Pi Fisheye Lens Camera Module. It Provides A Slight Image Difference In The Field Of View Compared To The Usage Of Normal Lens. The Resolution Of This Camera Is 5megapixels.The Advantage Of Using This Bot Is For Implementing It Under Impossible Human Intervention. It Moves In Any Bleak Surfaces Which The Maneuvered Robot Cannot Get The Stability. The Legged Robot Gets Its Stability Due To The Arrangement Of Legs With The Chassis Taking The Center Of Gravity Into Consideration.

Models and algorithms for throughput improvement problem of serial production lines via downtime reduction

Throughput is one of the key performance indicators for manufacturing systems, and its improvement remains an interesting topic in both industrial and academic fields. One way to achieve improvement is to reduce the downtime of unreliable machines. Along this direction, it is natural to pose questions about the optimal allocation of improvement effort to a set of machines and failure modes. This article develops mixed-integer linear programming models to improve system throughput by reducing downtime in the case of multi-stage serial lines. The models take samples of processing time, uptime and downtime as input, generated from random distributions or collected from real system. To improve computational efficiency while guaranteeing the exact optimality of the solution, algorithms based on Benders Decomposition and discrete-event relationships of serial lines are proposed. Numerical cases show that the solution approach can significantly improve efficiency. The proposed modeling and algorithm is applied to throughput improvement of various systems, including a long line and a multi-failure system, and also to the downtime bottleneck detection problem. Comparison with state-of-the-art approaches shows the effectiveness of the approach. Supplementary materials are available for this article. Go to the publisher’s online edition of IISE Transactions.

КАТАЛОГИЗАЦИЯ СОЦИАЛЬНЫХ ТИПОВ В СМИ (на материале серийных перифраз)

The periphrases of humans in the language of the media from the position of secondary (repeated) nomination were studied. The purpose of the study was to identify serial periphrastic lines in media texts sharing the same structural and semantic model. The study is highly relevant due to the fact that personal names serve as a background of the news message by encoding the most important roles of humans in the society. A total of 11 serial peripheral lines were identified. A detailed description of the most frequent serial peripheral lines for naming humans in the language of the media was performed. A new model was introduced for analysis of serial periphrastic lines. It was proved that the formation of serial periphrastic lines in the media is conditioned by both linguistic and extralinguistic factors. The obtained results demonstrate that serial periphrastic lines help to a decrease the number of nominative options and favor the formation of social frames, which saves cognitive efforts of the addressee. The theoretical importance of the research is that the algorithm introduced for investigation of peripheral lines can be extrapolated to other typical descriptive lines. The results of the study can be also helpful in lexicography and teaching special courses on the language of the media and the theory of nomination.

Highly-Accurate Fractional-Order Microwave Differentiators for Band-Specific UWB Applications

Highly accurate designs of band-specific fractional-order microwave differentiators are proposed to operate in lower and upper frequency bands of UWB range. Firstly, fractional-order digital differentiators are obtained by minimizing the magnitude error function of a single-zero multi-pole transfer function. Absolute relative error (ARE) analysis clearly demonstrates that the proposed lower and upper band fractional-order digital differentiator designs are having highly accurate magnitude response and outperform the existing fractional-order differentiators with maximum ARE values of − 44.14 dB and − 48.79 dB respectively. To operate in microwave range, these designs are realized using Z-domain chain scattering parameters of equal-electrical length line elements. Microstrip configurations obtained for lower and upper band fractional-order microwave differentiators consist of a short-circuited shunt stub and three serial transmission line sections. Implementation of designs is done on Rogers RO3003 substrate having thickness 0.75 mm. Measured results for transmission coefficient of lower and upper frequency band designs are found to be in good agreement with simulated ones over the frequency range 1.2 to 6.2 GHz and 6 to 10.9 GHz respectively.

Closed Bernoulli lines with finite buffers: real-time performance analysis, completion time bottleneck and carrier control

Based on the deployment of the new manufacturing strategies (e.g. smart manufacturing), real-time performance analysis, continuous improvement and efficient production management of flexible production systems are with great importance to be investigated. Relevant studies on the serial lines and assembly systems are obtained in recent years. We study real-time performances of closed production lines in this paper. Specifically, the system is assumed to have Bernoulli machines, finite buffers and finite carriers. By using Markovian approach, exact mathematical model for the system under consideration as well as the formulas to calculate the system's transient-based real-time performances are derived. For estimating the performances of a closed line under finite production run-based operation, we propose an approximation method with high accuracy and computational efficiency. Then, completion time bottleneck of the closed line is discussed. Finally, to illustrate the effectiveness of the method, a closed Bernoulli line with carrier control during production is studied.

Acquisition and Data Logging Inertial Navigation System (INS) on Combat Submarine Using Arduino-SD Card

In a combat submarine operating system, navigation device acts as a location information provider on inside or at sea level. Such information is position data provided by GPS (Global Positioning System) and data transmitted by IMU (Inertial Measurement Unit) sensor. Combining these two device is called INS (Inertial Navigation System). This inertial sensor interacts using serial communication data, however records are needed to collect, store and store incoming data in order to be processed easily. Data logging process is feasible as a recorder and data storage using SD Card. Enhancements, such as SD cards are needed because in general system is equipped with a small memory capacity. Arduino is a microcontroller that can assist in process because data obtained from sensor is processed using serial communication lines (RX and TX). Results obtained from calculation and logging data are calculation Roll, Pitch, Heading, Latitude, Longitude, Microseconds, Gyroscope on X axis, Y, Z, Accelerometer on X axis, Y, Z, Magnetometer on X, Y, Z, Velocity North, East, Down. This proves that system acceleration and data logging using Arduino and SD Card can assist in obtaining information and KTBA situations

Intelligent self-designing production control strategy: Dynamic allocation hybrid pull-type mechanism applicable to closed-loop supply chains

The objective of this research is to establish an approach to select the best performing production control strategy for a Closed-Loop Supply Chain (CLSC) system with stochastic supply and demand. To test the operational performance of several pull-type production control strategies, a simulation-based methodology is applied to serial lines with variable processing times. The strategies experimented are: Hybrid Extended Kanban CONWIP (HEKC-II) with modifications, Hybrid Kanban CONWIP (HKC), Dynamic Allocation Hybrid Extended Kanban CONWIP (DNC HEKC-II) special case, Dynamic Allocation Hybrid Kanban CONWIP (DNC HKC) and the newly postulated Intelligent Self-Designing Production Control Strategy (ISD). The successful implementation and the highly positive experimental results for the new strategy provided a major shift of the Pareto performance frontier, simultaneously minimising the conflicting objectives of reducing customer demand backlog (by over 80%) and reducing the WIP (by over 22%) relative to an optimised HKC strategy, the control group.

A simulation analysis of a serial line pull system producing orders with various part types and volumes

ABSTRACT In practice, orders composed of different part/job types with varying quantities randomly arrive at a production area and they have a due date which designates the latest time before which all jobs in the order should be completed. Therefore, an order can only be fulfilled until all the jobs in that order are finished. This paper studies a pull production environment where there are five serial stations capable of processing different part types and part movement is controlled by a dual-card kanban system in order to reduce work-in-process inventory. Following the definition of a base model with given parameters, we discuss simulation-related experimental design features, performance criteria involving due-date-related ones, statistical analyses and design clusters. Statistical findings for each design cluster with predetermined input factors are interpreted.

Bernoulli serial lines with batching machines: Performance analysis and system-theoretic properties

Aiming at Bernoulli serial lines with batching machines and finite buffers, this study develops analytical methods for performance analysis and system-theoretic properties. Batching machines can process several jobs simultaneously as a batch, as long as the number of jobs in a batch does not exceed the machine’s batch capacity. The batch capacities of all machines are not necessarily equal. Batching machines bring about a new characteristic of state transitions depending on batch capacities and machine states. For two-machine lines, the joint impacts of batching machines on state transitions are analyzed. Theoretically, the state transition rules are revealed. Based on the state transition rules, this study proposes a hierarchical state transition diagram, proves the ergodicity condition, and derives analytical formulas to evaluate the performance measures. Then, for multi-machine lines, this study develops a computationally efficient aggregation method with high accuracy. Furthermore, the impacts of system parameters, including machine efficiency pattern, batch capacity pattern, batch capacity mismatch, and system size, on the accuracy are qualitatively analyzed. Finally, this study investigates the reversibility and monotonicity properties. These analytical methods and results help production managers to scientifically evaluate, accurately predict, and continuously improve Bernoulli serial lines with batching machines.