scholarly journals Freight Fleet Management Problem: Evaluation of a Truck Utilization Rate Based on Agent Modeling

2022 ◽  
Vol 24 (2) ◽  
pp. D46-D58
Author(s):  
Ganna Samchuk ◽  
Denis Kopytkov ◽  
Alexander Rossolov
Keyword(s):  
Regression Analysis ◽  
Process Parameters ◽  
State Of The Art ◽  
Fleet Management ◽  
Utilization Rate ◽  
Management Problem ◽  
Fleet Size ◽  
Software Product ◽  
Transportation Process ◽  
Probabilistic Nature

The article deals with the problem of estimating the rational number and utilization rate of the vehicles' fleet. According to the analysis results of the state-of-the-art literature it has been revealed that the issue of substantiating the rational fleet size and the rate of its utilization were not fully solved. The purpose of the study was to increase the efficiency of servicing transportation orders by determining the required number of vehicles. The goal of the research was the influence of the transportation process parameters on the truck utilization rate. Originating from the probabilistic nature of the transportation process, it has been proposed to use the AnyLogic software product to develop a simulation model for vehicle orders' servicing. From the processing of the experimental results by the regression analysis methods, it has been found that the dependence of changes in the vehicle utilization rate is of a linear form.

scholarly journals INFORMATION TECHNOLOGY OF DECISION SUPPORT TO DESIGN THE TRANSPORTATION ORDERS' SERVICING

2021 ◽  
Vol 1 (161) ◽  
pp. 176-186
Author(s):  
Yu. Davidich ◽  
G. Samchuk ◽  
D. Kopytkov ◽  
N. Davidich ◽  
O. Plygun
Keyword(s):  
Operating Conditions ◽  
Working Time ◽  
Utilization Rate ◽  
Proper Solution ◽  
Fleet Size ◽  
Variation Range ◽  
Transportation Distance ◽  
Time Determination ◽  
Probabilistic Nature

The main purpose of most transport companies is to provide the quality services to customers with minimal costs. At the same time, determination of the number of vehicles and their utilization rate when satisfying transportation orders is the important task, the proper solution of which leads to the full and timely servicing and contributes to an increase of a transport company's competitiveness in the present-day market. Due to the analysis results of the state-of-the-art literature and Internet sources, it has been revealed that the problem of finding the rational fleet size and the rate of its utilization to complete the transportation orders were not fully solved. From the criteria analysis it has been proposed to substantiate the vehicle fleet size according to the car utilization rate to be assigned as the "vehicle working time-to-total working time" ratio. Considering the probabilistic nature of the transportation process, a simulation model to complete the orders by a truck fleet has been developed in the AnyLogic environment. An experimental plan has been developed to reproduce the real transportation order conditions and consisted of 27 series, each of which was of 100 experiments. The variation range of input factors, which was the transportation distance, vehicles' number and orders' hourly intensity were [10;30], [1;3] and [0.6;1], respectively. From the experimental results processing by the regression analysis methods, it has been found that the dependence of changes in the car utilization rate, transportation distance, vehicle' number and orders' intensity was of linear form. The obtained dependence has been estimated via the determination coefficient, which was 0.95, and indicated the high quality of the model proposed. The resulting model allows calculating the required number of vehicles from their operating conditions. In the case study the 2 vehicles were recommended to service the transportation orders. Further research efforts can be taking into account a larger number of influencing factors, increasing their variation range and obtaining dependencies to describe the presented criterion change to acceptable accuracy.

Investigation of interactions between fabric performance, sewing process parameters and seam pucker of shirt fabric

2021 ◽  
Vol 16 ◽  
pp. 155892502110203
Author(s):  
Daoling Chen ◽  
Pengpeng Cheng ◽  
Yonggui Li
Keyword(s):  
Regression Analysis ◽  
Process Parameters ◽  
Linear Regression Analysis ◽  
Objective Evaluation ◽  
Multiple Linear Regression Analysis ◽  
Complex Dynamic ◽  
Dynamic Interactions ◽  
Sewing Thread ◽  
Sewing Threads ◽  
Seam Pucker

Seam pucker is a common problem in sewing. It not only affects the appearance of product, but also affects product performance. The purpose of this study is to quantify the complex dynamic interactions between fabric performance, sewing process parameters and seam pucker. In order to solve the problem of shirt seam pucker, this study selected four kinds of shirt fabrics, three kinds of polyester sewing threads, three kinds of stitch density and four kinds of seam types for experiments. Through unitary regression analysis, the subjective and objective evaluation results are consistent. Further analysis the results of objective experiment revealed that fabric performances, seams type, sewing thread and stitch densities all have impact on seam pucker. Meanwhile also find out the sewing process parameters for the four fabrics when the seam shrinkage’s were smallest, so it’s helpful for the apparel enterprises to improve seam quality. Multiple linear regression analysis of experimental results show that fabric performances has the greatest influence on seam pucker, thickness, weight and warp density of fabric properties significantly affect seam pucker. And as the breaking elongation of sewing thread increases, seam pucker also increases. Stitch densities and seam type has the least affected on seam pucker, they affect the seam pucker by changing the extension of stitch and thickness of fabric at the seam, respectively. Seam type has greater impact on fabrics that are prone to seam pucker, seam type T1 get larger seam shrinkage than T4. Finally, the complex dynamic interactions was quantified and expressed through mathematical models.

scholarly journals A Multi-Branch U-Net for Steel Surface Defect Type and Severity Segmentation

Metals ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 870
Author(s):  
Robby Neven ◽  
Toon Goedemé
Keyword(s):  
Process Parameters ◽  
Visual Inspection ◽  
Steel Surface ◽  
Surface Defect ◽  
State Of The Art ◽  
Sheet Steel ◽  
Real Life ◽  
Single Task ◽  
Severity Estimation ◽  
Task Model

Automating sheet steel visual inspection can improve quality and reduce costs during its production. While many manufacturers still rely on manual or traditional inspection methods, deep learning-based approaches have proven their efficiency. In this paper, we go beyond the state-of-the-art in this domain by proposing a multi-task model that performs both pixel-based defect segmentation and severity estimation of the defects in one two-branch network. Additionally, we show how incorporation of the production process parameters improves the model’s performance. After manually constructing a real-life industrial dataset, we first implemented and trained two single-task models performing the defect segmentation and severity estimation tasks separately. Next, we compared this to a multi-task model that simultaneously performs the two tasks at hand. By combining the tasks into one model, both segmentation tasks improved by 2.5% and 3% mIoU, respectively. In the next step, we extended the multi-task model using sensor fusion with process parameters. We demonstrate that the incorporation of the process parameters resulted in a further mIoU increase of 6.8% and 2.9% for the defect segmentation and severity estimation tasks, respectively.

Evaluation of Process Parameters in Machining of AA6063 Alloy

2018 ◽  
Vol 1148 ◽  
pp. 109-114
Author(s):  
M. Balaji ◽  
C.H. Nagaraju ◽  
V.U.S. Vara Prasad ◽  
R. Kalyani ◽  
B. Avinash
Keyword(s):  
Surface Roughness ◽  
Regression Analysis ◽  
Process Parameters ◽  
Single Channel ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Roughness Parameters ◽  
Surface Roughness Parameters ◽  
Aa6063 Alloy

The main aim of this work is to analyse the significance of cutting parameters on surface roughness and spindle vibrations while machining the AA6063 alloy. The turning experiments were carried out on a CNC lathe with a constant spindle speed of 1000rpm using carbide tool inserts coated with Tic. The cutting speed, feed rate and depth of cut are chosen as process parameters whose values are varied in between 73.51m/min to 94.24m/min, 0.02 to 0.04 mm/rev and 0.25 to 0.45 mm respectively. For each experiment, the surface roughness parameters and the amplitude plots have been noted for analysis. The output data include surface roughness parameters (Ra,Rq,Rz) measured using Talysurf and vibration parameter as vibration amplitude (mm/sec) at the front end of the spindle in transverse direction using single channel spectrum analyzer (FFT).With the collected data Regression analysis is also performed for finding the optimum parameters. The results show that significant variation of surface irregularities and vibration amplitudes were observed with cutting speed and feed. The optimum cutting speed and feed from the regression analysis were 77.0697m/min and 0.0253mm/rev. for the minimum output parameters. No significant effect of depth of cut on output parameters is identified.

DEVELOPMENT OF A SUBSYSTEM FOR DIAGNOSTICS OF GYNECOLOGICAL DISEASES BASED ON STATISTICAL AND SIMULATION MODELING

2021 ◽  
pp. 94-98
Author(s):  
Екатерина Ивановна Новикова ◽  
Анастасия Юрьевна Корниенко
Keyword(s):  
Differential Diagnosis ◽  
Mathematical Models ◽  
Simulation Modeling ◽  
Clinical Laboratory ◽  
Software Product ◽  
Gynecological Diseases ◽  
Medical Structure ◽  
Diagnostic Signs ◽  
Attending Physician ◽  
Probabilistic Nature

В статье рассматриваются методы кластерного и дискриминантного анализа для построения математических моделей диагностики гинекологических заболеваний. Гинекологические патологии занимают значительное место в структуре заболеваемости у женщин. Между тем, точная дифференциальная диагностика патологий зачастую бывает, невозможна, так как гинекологические заболевания носят вероятностный характер, большинство диагностических признаков выражаются качественными показателями, которые индивидуальны для каждой пациентки. Лечащему врачу приходится решать сложную задачу по анализу клинических, лабораторных и инструментальных признаков для постановки точного диагноза. С применением аппарата сетей Петри произведено построения модели дифференциальной диагностики гинекологических заболеваний. На основе полученных математических моделей, сформирована структура и информационно-программное обеспечение для системы диагностики гинекологических заболеваний в медицинских организациях. Внедрение разработанного программного продукта в медицинскую структуру позволит уменьшить вероятность врачебной ошибки, а также повысить эффективность и точность постановки диагноза пациенткам The article discusses the methods of cluster and discriminant analysis for constructing mathematical models for the diagnosis of gynecological diseases. Gynecological pathologies occupy a significant place in the structure of morbidity in women. Meanwhile, accurate differential diagnosis of pathologies is often impossible, since gynecological diseases are of a probabilistic nature, most of the diagnostic signs are expressed in qualitative indicators that are individual for each patient. The attending physician has to solve a complex task of analyzing clinical, laboratory and instrumental signs to make an accurate diagnosis. Using the apparatus of Petri nets, a model for the differential diagnosis of gynecological diseases was constructed. On the basis of the obtained mathematical models, the structure and information software for the system of diagnostics of gynecological diseases in medical organizations was formed. The introduction of the developed software product into the medical structure will reduce the likelihood of medical error, as well as increase the efficiency and accuracy of diagnosing patients

scholarly journals On Residual Stress Development, Prevention, and Compensation in Metal Additive Manufacturing

Materials ◽  
2020 ◽  
Vol 13 (2) ◽  
pp. 255 ◽  
Author(s):  
Kevin Carpenter ◽  
Ali Tabei
Keyword(s):  
Additive Manufacturing ◽  
Process Parameters ◽  
Mechanical Performance ◽  
State Of The Art ◽  
Measurement Techniques ◽  
Complex Geometries ◽  
Quality Inspection ◽  
Metal Additive Manufacturing ◽  
Computational Costs ◽  
Metal Additive

One of the most appealing qualities of additive manufacturing (AM) is the ability to produce complex geometries faster than most traditional methods. The trade-off for this advantage is that AM parts are extremely vulnerable to residual stresses (RSs), which may lead to geometrical distortions and quality inspection failures. Additionally, tensile RSs negatively impact the fatigue life and other mechanical performance characteristics of the parts in service. Therefore, in order for AM to cross the borders of prototyping toward a viable manufacturing process, the major challenge of RS development must be addressed. Different AM technologies contain many unique features and parameters, which influence the temperature gradients in the part and lead to development of RSs. The stresses formed in AM parts are typically observed to be compressive in the center of the part and tensile on the top layers. To mitigate these stresses, process parameters must be optimized, which requires exhaustive and costly experimentations. Alternative to experiments, holistic computational frameworks which can capture much of the physics while balancing computational costs are introduced for rapid and inexpensive investigation into development and prevention of RSs in AM. In this review, the focus is on metal additive manufacturing, referred to simply as “AM”, and, after a brief introduction to various AM technologies and thermoelastic mechanics, prior works on sources of RSs in AM are discussed. Furthermore, the state-of-the-art knowledge on RS measurement techniques, the influence of AM process parameters, current modeling approaches, and distortion prevention approaches are reported.

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