Wyniki wyszukiwania - BazTech

1

Incidences of variables in labor absenteeism: an analysis of neural networks

Pérez-Campdesuñer Reyner, De Miguel-Guzmán Margarita, García-Vidal Gelmar, Sánchez-Rodríguez Alexander, Martínez-Vivar Rodobaldo

Management and Production Engineering Review

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2020

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Vol. 11, No. 1

3–-12

EN

Labor absenteeism is a factor that affects the good performance of organizations in any part of the world, from the instability that is generated in the functioning of the system. This is evident in the effects on quality, productivity, reaction time, among other aspects. The direct causes by which it occurs are generally known and with greater reinforcement the diseases are located, without distinguishing possible classifications. However, behind these or other causes can be found other possible factors of incidence, such as age or sex. This research seeks to explore, through the application of neural networks, the possible relationship between different variables and their incidence in the levels of absenteeism. To this end, a neural networks model is constructed from the use of a population of more than 12,000 employees, representative of various classification categories. The study allowed the characterization of the influence of the different variables studied, supported in addition to the performance of an ANOVA analysis that allowed to corroborate and clarify the results of the neural network analysis.

2

Towards the optimization of process parameters for impact strength of natural fiber reinforced composites: Taguchi method

Yusuf S. S., Islam M. N., Ali M. H., Akram M. W., Siddique M. A.

Advances in Materials Science

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2020

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Vol. 20, nr 2(64)

54--70

EN

This paper presents an investigation of impact strength of sponge gourd, coir, and jute fibers reinforced epoxy resin-based composites. Impact strength of specimens, made of composites with various proportions of wt% ratio of resin and hardener, wt% of resin and hardener, wt% ratio of sponge gourd and jute, wt% ratio of sponge gourd and coir, was measured. Design of experiment was done by Taguchi method using four control factors with three levels. Effect of the above control factors on impact strength was examined and the best combinations of control factors are advised. Confirmation test was performed by using this combination and the percentage of contribution of the above factors on impact strength was investigated by Analysis of Variance (ANOVA). Contour and interaction plots provide helpfully examines to explore the combined influences of different control factors on output characteristics. The regression equation represents a mathematical model that relates control factors with impact strength.

3

Optimization of process parameters on friction stir welding of AA 6082-T6 butt joints using Taguchi method

Arab M., Zemri M.

Mechanics and Mechanical Engineering

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2018

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Vol. 22, nr 4

1371--1380

EN

Friction Stir Welding (FSW) was carried out on Aluminum Alloy 6082-T6 plates with dimensions of 200 x 70 x 2 mm. Design of Experiment (DOE) was applied to determine the most important factors which influence the Ultimate Tensile Strength (UTS) and Hardness (HV) of AA 6082-T6 joints produced by Friction Stir Welding (FSW). Effect of two factors which include tool rotational speed and welding speed on (UTS, HV) were investigated by Taguchi method using L9 orthogonal array to find the optimum process parameters. An analysis of variance (ANOVA) was carried out to determine which of the selected factors are more significant on both of responses, the optimum parameters for the higher UTS it found by using a rotational speed of 1400 rpm and 125 mm/min for the welding speed, also 1400 rpm and 160 mm/min to maximize Hardness (HV).

4

Supply chain management in SMEs: evidence from Poland and Kazakhstan

Kot S., Onyusheva I., Grondys K.

Engineering Management in Production and Services

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2018

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Vol. 10, no. 3

23--36

EN

The research aimed to assess Supply Chain Management (SCM) in small and medium enterprises in Kazakhstan and Poland, and, more specifically, identify similarities and differences in the approach to the SCM concept in selected countries. The research methodology was based on ANOVA analysis comparing samples of contemporary SMEs operating in Poland and Kazakhstan. Primary data was collected using the CAWI quantitative method and then studied using the ANOVA statistical data analysis method. The research results demonstrated similar involvement in the implementation of the concept with significant differences in some areas, such as cost reduction and focus on end customers. The concept of Supply Chain Management is a very common subject of theoretical and practical analysis. Even though research efforts in this area indicate the positive effects of the implemented concept, most of them concern large organisations. The research results showed similar involvement in the implementation of the concept, although significant differences were found in selected areas, such as cost reduction and focus on end customers.

5

AFM surface investigation of Inconel 825 with multi wall carbon nano tube in electrical discharge machining process using Taguchi analysis

Prabhu S., Vinayagam B. K.

Archives of Civil and Mechanical Engineering

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2011

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Vol. 11, no 1

149-170

EN

Demand for better surface finish has been increasing recently for super alloys. Carbon nano tube (CNT) is mixed with dielectric fluid in EDM process because of high thermal conductivity. The analysis of surface characteristics like surface roughness, micro cracks of Inconel-825 is carried out and an excellent machined nano finish can be obtained by setting the machining parameters at optimum level. The Taguchi design of experimental technique is used to optimize the machining parameters and an L9 orthogonal array is selected. The predicted surface roughness was estimated using S/N ratio and compared with actual values. ANOVA analysis is used for finding the significant factors affecting the machining process in order to improve the surface characteristics of Inconel-825 material. Taguchi design of experiments were used to identify the best experiment which optimize the surface roughness to nano level and meet the demand of high surface finish and accuracy to great extent. AFM analysis using CNT improves the surface characteristics like surface morphology, surface roughness and micro cracks from micro level to nano level. The regression analysis are used to predict the error between actual and regression values of surface roughness using carbon nano tube as dielectric fluid in EDM process.

PL

Wymagania dotyczące końcowej jakości powierzchni stopów typu Inconel 825 są bardzo wysokie. Zastosowanie nanorurek węglowych w dielektryku w procesie obróbki elektroerozyjnej pozwalają znacznie poprawić jakość powierzchni obrabianych materiałów. W pracy zastosowano metodę Taguchi w celu określenia optymalnych parametrów procesu.

6

Interaction model for predicting bead geometry for Lab Joint in GMA welding process

Thao D.T., Kim I.S.

Archives of Computational Materials Science and Surface Engineering

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2009

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Vol. 1, nr 4

237-244

EN

Purpose: The prediction of the optimal bead geometry is an important aspect in robotic welding process. Therefore, the mathematical models that predict and control the bead geometry require to be developed. This paper focuses on investigation of the development of the simple and accuracy interaction model for prediction of bead geometry for lab joint in robotic Gas Metal Arc (GMA) welding process. Design/methodology/approach: The sequent experiment based on full factorial design has been conducted with two levels of five process parameters to obtain bead geometry using a GMA welding process. The analysis of variance (ANOVA) has efficiently been used for identifying the significance of main and interaction effects of process parameters. General linear model and regression analysis has been employed as a guide to achieve the linear, curvilinear and interaction models. The fitting and the prediction of bead geometry given by these models were also carried out. Graphic results display the effects of process parameter and interaction effects on bead geometry. Findings: The fitting and the prediction capabilities of interaction models are reliable than the linear and curlinear models and it was found that welding voltage, arc current, welding speed and 2-way interaction CTWD welding angle have the large significant effects on bead geometry. Research limitations/implications: The these models developed are extended to shielding gas composition, weld joint position, polarity and many other parameters which are not included in this research in order to establish a closed loop feedback control system to minimize possible errors from uncontrolled variations. Practical implications: The developed models apply real-time control for bead geometry in GMA welding process and perform the Design of Experiments (DOE) analysis steps in order to solve optimisation problems in GMA welding process. Originality/value: The interaction factors, welding voltage arc current, CTWD welding angle, also imposes a significant effect on bead geometry. With the experimental data of this study, the interaction models have a more reliable fitting and better predicting than that of linear and curvilinear models.

7

Predicting Lap-Joint bead geometry in GMA welding process

Thao D., Jeong J., Kim I., Kim J.

Archives of Materials Science and Engineering

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2008

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Vol. 32, nr 2

121-124

EN

Purpose: The prediction of the optimal bead geometry is an important aspect in robotic welding process. Therefore, the mathematical models that predict and control the bead geometry require to be developed. This paper focuses on investigation of the development of the simple and accuracy interaction model for prediction of bead geometry for lap joint in robotic Gas Metal Arc (GMA) welding process. Design/methodology/approach: The sequent experiment based on full factorial design has been conducted with two levels of five process parameters to obtain bead geometry using a GMA welding process. The analysis of variance (ANOVA) has efficiently been used for identifying the significance of main and interaction effects of process parameters. General linear model and regression analysis in SPSS has been employed as a guide to achieve the linear, curvilinear and interaction models. The fitting and the prediction of bead geometry given by these models were also carried out. Graphic results display the effects of process parameter and interaction effects on bead geometry. Findings: The fitting and the prediction capabilities of interaction models are reliable than the linear and curvilinear models. It was found that welding voltage, arc current, welding speed and 2-way interaction CTWD×welding angle have the large significant effects on bead geometry. Practical implications: The model should also cover a wide range of material thicknesses and be applicable for all welding position. For the automatic welding system, the data must be available in the form of mathematical equations. Originality/value: It has been realized that with the use of the developed algorithm, the prediction of optimal bead dimensions becomes much simpler to even a novice user who has no prior knowledge of the robotic GMA welding process and optimization techniques.