Publikační činnost Katedry obrábění, montáže a strojírenské metrologie / Publications of Department of Working and Assembly (346)

Permanent URI for this collectionhttp://hdl.handle.net/10084/71298

Kolekce obsahuje bibliografické záznamy publikační činnosti (článků) akademických pracovníků Katedry obrábění, montáže a strojírenské metrologie (346) v časopisech registrovaných ve Web of Science od roku 2003 po současnost.
Do kolekce jsou zařazeny:
a) publikace, u nichž je v originálních dokumentech jako působiště autora (adresa) uvedena Vysoká škola báňská-Technická univerzita Ostrava (VŠB-TUO),
b) publikace, u nichž v originálních dokumentech není v adrese VŠB-TUO uvedena, ale autoři prokazatelně v době jejich zpracování a uveřejnění působili na VŠB-TUO.

Bibliografické záznamy byly původně vytvořeny v kolekci Publikační činnost akademických pracovníků VŠB-TUO, která sleduje publikování akademických pracovníků od roku 1990.

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Now showing 1 - 20 out of 306 results

Determination of the brittleness of glass fibers on selected mechanical and rheological properties of the polymer composite
(Budapest University of Technology and Economics, Faculty of Mechanical Engineering, Department of Polymer Engineering, 2024) Miščík, Stanislav; Dobránsky, Jozef; Gombár, Miroslav; Čep, Robert
The paper deals with the influence of the brittleness of glass fibers on the selected performance properties of the fibrous polymer composite. Understanding the fatigue behavior of fiber-reinforced plastics is desirable for exploiting their features in safe, durable, and reliable industrial components. Based on the proposed methodology, it is possible to assess the impact of material reuse on selected mechanical and rheological properties. To verify the methodology by experimental analysis, homopolymer PP reinforced with chemically grafted glass fiber (30 wt%) was selected. The proposed methodology was subsequently verified by experimental analysis and evaluated statistically. The morphology of the fracture surfaces was evaluated, and the fiber-polymer matrix adhesion was monitored at the interface of the fracture surfaces. Based on the measured and evaluated values and fracture surfaces, we can say that the brittleness of the fibers significantly affects the performance properties of the tested polymer composite.
Proposes geometric accuracy and surface roughness estimation of anatomical models of the pelvic area manufactured using a material extrusion additive technique
(MDPI, 2025) Turek, Pawel; Snela, Slawomir; Budzik, Grzegorz; Bazan, Anna; Jablonski, Jaroslaw; Przeszlowski, Lukasz; Wojnarowski, Robert; Dziubek, Tomasz; Petrů, Jana
One of the main benefits of using 3D printing in orthopedics is the ability to create custom solutions tailored to a patient’s specific anatomical and functional needs. Conducting a reliable evaluation of the accuracy of the manufacture of anatomical structure models is essential. However, particular standards or procedures still need to be implemented to control the surface quality of anatomical models manufactured using additive manufacturing techniques. Models of pelvic parts made of polylactic acid (PLA) material were manufactured using the Material Extrusion (MEX) additive technique. Subsequently, guidelines were developed to reliably verify the geometric and surface roughness of the 3D printed models using Computer-Aided Inspection (CAI) systems. For this purpose, a measuring arm system (MCA-II) with a mounted laser head and Atos II Triple Scan was used. To inspect surface roughness parameters, procedures were developed for an Alicona InfiniteFocusG4 optical microscope. The results of the geometrical verification of the models are within the tolerance limits of ±0.22 mm to ±0.6 mm. In the case of surface roughness measurement, the highest values for the arithmetical mean height Sa were obtained on the side of the support material, while the smallest values were found along the applied layers. After the metrological control process, the models were used in the planning process for hip surgery.
Maximization of wear rates through effective configuration of standoff distance and hydraulic parameters in ultrasonic pulsating waterjet
(University of Niš, 2024) Nag, Akash; Dixit, Amit Rai; Petrů, Jana; Váňová, Petra; Konečná, Kateřina; Hloch, Sergej
A pulsating waterjet is a technological modification of a conventional waterjet that utilizes ultrasonic vibrations to generate a modulated jet, resulting in repetitive fatigue loading of the material. The erosion efficiency of the ultrasonic pulsating waterjet is majorly determined by the hydraulic factors and its interaction with standoff distance. However, the dependency of the wear rates on different hydraulic factors and formulation of an implicit prediction model for determining effective standoff distance is still not present to date. Therefore, in this study, the combined dependency of the supply pressure (20-40 MPa), nozzle diameter (0.3-1.0 mm), and standoff distance (1-121 mm) on wear rates of AW-6060 aluminum alloy are studied. Statistical analysis is used to determine the statistically significant factors and formulate regression equations to determine output responses within the experimental domain. The surface topography and sub-surface microhardness of the eroded grooves were studied. The results show that both the disintegration depth and the material removal increase with an increase in the nozzle diameter and supply pressure. However, the dependency of the output responses on nozzle diameter is statistically more evident than supply pressure and two-way interactions. Cross-sectional images of the grooves showed typical hydrodynamic erosion characteristics in erosion cavities, subsurface voids, and material upheaving. The results of microhardness analysis showed an approximately 15-20% increase in hardness values compared to the untreated samples.
Submerged surface texturing of AISI 304L using the pulsating water jet method
(Springer Nature, 2024) Stolárik, Gabriel; Klichová, Dagmar; Poloprudský, Jakub; Chlupová, Alice; Nag, Akash; Hloch, Sergej
Submerged jets have a variety of practical applications due to their versatility in providing efficient and environmentally friendly options for treatment in various industries. The physical background is based on the continuous water jet (CWJ) application powered via stagnation pressure. However, it is known that impact pressure is much more effective than static pressure. When the impact pressure is repeated with a high frequency per time unit, the erosive effects of water can be used even at pressures below 100 MPa, which is attractive from the point of view of the low demands of the hydraulic system. Surface modification utilising impact pressure can be achieved by employing the pulsed water jet (PWJ) method. The combination of parameters such as the traverse speed and trajectory pattern can control the number of water clusters impacting the material surface. So far, the field of application of PWJ for surface treatment has mostly been investigated water atmospheric conditions. This article focuses on the possibility of the surface modification of AISI 304L stainless steel using the PWJ method under submerged conditions. The results are compared to those obtained under atmospheric conditions. The reference samples were treated by the same technological conditions using a continuous water jet (CWJ). The affected surfaces were characterised using areal surface roughness parameters Sa, Sz, Sp, and Sv, and the surface topography and mechanism of erosion wear were evaluated by scanning electron microscopy. A significant increase in all roughness parameters was confirmed using the PWJ compared to the CWJ method (both in atmospheric and submerged conditions), which confirms the importance of using impact pressure. The surface treatment by PWJ under submerged conditions resulted in a decrease of the surface roughness parameter Sa by approximately 97% compared to atmospheric conditions at a traverse speed of 2 mm/s for perpendicular interleaved trajectory, nevertheless, the homogeneity of treatment over a larger area was improved.
Study of eddy current testing ability on SLM aluminium alloy
(MDPI, 2024) Gel’atko, Matúš; Hatala, Michal; Botko, František; Vandžura, Radoslav; Hajnyš, Jiří
The detection of defects in aluminium alloys using eddy current testing (ECT) can be restricted by higher electrical conductivity. Considering the occurrence of discontinuities during the selective laser melting (SLM) process, checking the ability of the ECT method for the mentioned purpose could bring simple and fast material identification. The research described here is focused on the application of three ECT probes with different frequency ranges (0.3-100 kHz overall) for the identification of artificial defects in SLM aluminium alloy AlSi10Mg. Standard penetration depth for the mentioned frequency range and identification abilities of used probes expressed through lift-off diagrams precede the main part of the research. Experimental specimens were designed in four groups to check the signal sensitivity to variations in the size and depth of cavities. The signal behavior was evaluated according to notch-type and hole-type artificial defects' presence on the surface of the material and spherical cavities in subsurface layers, filled and unfilled by unmolten powder. The maximal penetration depth of the identified defect, the smallest detectable notch-type and hole-type artificial defect, the main characteristics of signal curves based on defect properties and circumstances for distinguishing between the application of measurement regime were stated. These conclusions represent baselines for the creation of ECT methodology for the defectoscopy of evaluated material.
A bibliometric review on application of machine learning in additive manufacturing and practical justification
(Elsevier, 2024) Ma, Quoc-Phu; Nguyen, Hoang-Sy; Hajnyš, Jiří; Měsíček, Jakub; Pagáč, Marek; Petrů, Jana
This paper delves into the cutting-edge applications of Machine Learning (ML) within modern Additive Manufacturing (AM), employing bibliometric analysis as its methodology. Formulated around three pivotal research questions, the study navigates through the current landscape of the research field. Utilizing data sourced from Web of Science, the paper conducts a comprehensive statistical and visual analysis to unveil underlying patterns within the existing literature. Each category of ML techniques is elucidated alongside its specific applications, providing researchers with a holistic overview of the research terrain and serving as a practical checklist for those seeking to address particular challenges. Culminating in a vision for the Smart Additive Manufacturing Factory (SAMF), the paper envisions seamless integration of reviewed ML techniques. Furthermore, it offers critical insights from a practical standpoint, thereby facilitating shaping future research directions in the field.
Frame design of inline skates made by additive technology
(MM Science, 2024) Posmyková, Eliška; Hruban, Jiří; Měsíček, Jakub; Bláha, Roman; Ma, Q.-P.; Hajnyš, Jiří; Petrů, Jana
The aim of the article was to investigate the possibility of topological optimization (TO) of the inline skate frame manufactured through the Powder Bed Fusion (PBF) method of AISi10Mg-0403, an Additive Manufacturing (AM) technique. The study's core objective was to leverage The Altair Inspire software to re-envision the initial CAD model, culminating in an organic and bionic frame design. Incorporating comprehensive load analysis, the research considered various load scenarios, including static mass, dynamic forces, and acceleration during cornering, to ascertain the frame's strength and stability. Topological optimization was excluded within a defined design space, preserving critical functional elements while enhancing performance. The first part of the article is devoted to defining the concepts and nature of AM metallic materials. The practical part follows, in which the design of the skate frame is specified with specific requirements and the procedure of individual steps needed to create its final CAD Model. The work concludes by describing the preparation of the designed optimized frame construction.
Many-objective whale optimization algorithm for engineering design and large-scale many-objective optimization problems
(Springer Nature, 2024) Kalita, Kanak; Ramesh, Janjhyam Venkata Naga; Čep, Robert; Jangir, Pradeep; Pandya, Sundaram B.; Ghadai, Ranjan Kumar; Abualigah, Laith
In this paper, a novel Many-Objective Whale Optimization Algorithm (MaOWOA) is proposed to overcome the challenges of large-scale many-objective optimization problems (LSMOPs) encountered in diverse fields such as engineering. Existing algorithms suffer from curse of dimensionality i.e., they are unable to balance convergence with diversity in extensive decision-making scenarios. MaOWOA introduces strategies to accelerate convergence, balance convergence and diversity in solutions and enhance diversity in high-dimensional spaces. The prime contributions of this paper are-development of MaOWOA, incorporation an Information Feedback Mechanism (IFM) for rapid convergence, a Reference Point-based Selection (RPS) to balance convergence and diversity and a Niche Preservation Strategy (NPS) to improve diversity and prevent overcrowding. A comprehensive evaluation demonstrates MaOWOA superior performance over existing algorithms (MaOPSO, MOEA/DD, MaOABC, NSGA-III) across LSMOP1-LSMOP9 benchmarks and RWMaOP1-RWMaOP5 problems. Results validated using Wilcoxon rank sum tests, highlight MaOWOA excellence in key metrics such as generational distance, spread, spacing, runtime, inverse generational distance and hypervolume, outperforming in 71.8% of tested scenarios. Thus, MaOWOA represents a significant advancement in many-objective optimization, offering new avenues for addressing LSMOPs and RWMaOPs' inherent challenges. This paper details MaOWOA development, theoretical basis and effectiveness, marking a promising direction for future research in optimization strategies amidst growing problem complexity.
Many-objective artificial hummingbird algorithm: an effective many-objective algorithm for engineering design problems
(Oxford University Press, 2024) Kalita, Kanak; Jangir, Pradeep; Pandya, Sundaram B.; Čep, Robert; Abualigah, Laith; Migdady, Hazem; Daoud, Mohammad Sh
Many-objective optimization presents unique challenges in balancing diversity and convergence of solutions. Traditional approaches struggle with this balance, leading to suboptimal solution distributions in the objective space especially at higher number of objectives. This necessitates the need for innovative strategies to adeptly manage these complexities. This study introduces a Many-Objective Artificial Hummingbird Algorithm (MaOAHA), an advanced evolutionary algorithm designed to overcome the limitations of existing many-objective optimization methods. The objectives are to improve convergence rates, maintain solution diversity, and achieve a uniform distribution in the objective space. MaOAHA implements information feedback mechanism (IFM), reference point-based selection and association, non-dominated sorting, and niche preservation. The IFM utilizes historical data from previous generations to inform the update process, thereby improving the algorithm's the exploration and exploitation capabilities. Reference point-based selection, along with non-dominated sorting, ensures solutions are both close to the Pareto front and evenly spread in the objective space. Niche preservation and density estimation strategies are employed to maintain diversity and prevent overcrowding. The comprehensive experimental analysis benchmarks MaOAHA against four leading algorithms viz. Many-Objective Gradient-Based Optimizer, Many-Objective Particle Swarm Optimizer, Reference Vector Guided Evolutionary Algorithm, and Nondominated Sorting Genetic Algorithm III. The DTLZ1-DTLZ7 benchmark sets with four, six, and eight objectives and five real-world problems (RWMaOP1-RWMaOP5) are considered for performance assessment of the selected algorithms. The results demonstrate that internal parameter-free MaOAHA significantly outperforms its counterparts, achieving better generational distance by up to 52.38%, inverse generational distance by up to 38.09%, spacing by up to 56%, spread by up to 71.42%, hypervolume by up to 44%, and runtime by up to 52%. These metrics affirm the MaOAHA's capability to enhance the decision-making processes through its adept balance of convergence, diversity, and uniformity.
Simulation of orbital fractures using experimental and mathematical approaches: A pilot study
(MDPI, 2024) Eiba, Patrik; Frydrýšek, Karel; Zanganeh, Behrad; Čepica, Daniel; Maršálek, Pavel; Handlos, Petr; Timkovič, Juraj; Štembírek, Jan; Cienciala, Jakub; Onderka, Arnošt; Březík, Michal; Mizera, Ondřej
This contribution gives basic information about the mechanical behavior of the facial part of the human skull cranium, i.e., the splanchnocranium, associated with external loads and injuries caused mainly by brachial violence. The main areas suffering from such violence include the orbit, frontal, and zygomatic bones. In this paper, as a first approach, brachial violence was simulated via quasi-static compression laboratory tests, in which cadaveric skulls were subjected to a load in a testing machine, increasing till fractures occurred. The test skulls were also used for research into the dynamic behavior, in which experimental and numerical analyses were performed. A relatively high variability in forces inducing the fractures has been observed (143-1403 N). The results lay the basis for applications mainly in forensic science, surgery, and ophthalmology.
A novel equal area-equal width-equal bin numbers technique using salp swarm optimization algorithm for maximizing the success rate of ball bearing assembly
(Springer Nature, 2024) Nagarajan, Lenin; Mahalingam, Siva Kumar; Čep, Robert; Ramesh, Janjhyam Venkata Naga; Elangovan, Muniyandy; Mohammad, Faruq
In this work, an algorithmic technique is used to minimize the excess parts and maximize the success rate of selective assembly. In this study, a unique method known as Equal Area-Equal Width-Equal Bin Numbers is introduced to group the parts of a ball bearing assembly by taking into account their range of tolerance. A full factorial design is used to conduct the experiments, and the salp swarm optimization (SSO) algorithm is employed to evaluate the best bin combinations and identify the possibility of making the maximum number of assemblies. Computational results showed a 13.16 percent increase in success rate when compared to prior research when employing the proposed method. Comparing the computational outcomes versus those obtained by the Antlion optimization and Genetic algorithms validates the adoption of the SSO algorithm. A paired T-test is performed to assess the statistical significance of the findings. The convergence plot further supports the superiority of the SSO algorithm.
Electrodeposition of Zn/TiO2 coatings on Ti6Al4V produced by selective laser melting, the characterization and corrosion resistance
(IOP Publishing, 2024) Gündüz, Demet Özaydın; Küçüktürk, Gökhan; Pul, Muharrem; Salunkhe, Sachin; Kaya, Duran; Kabalci, Mehmet; Čep, Robert; Nasr, Emad Abouel
Recently, additive manufacturing techniques have begun to be implemented extensively in the production of implants. Ti6Al4V alloy is a material of choice for implants due to its low density and high biocompatibility. Recent research, however, has demonstrated that Ti6Al4V alloy emits long-term ions (such as Al and V) that are hazardous to health. Surface modifications, including coating, are therefore required for implants. The electrodeposition method was utilized to deposit Zn-doped TiO2 onto the surfaces of Ti6Al4V samples, which were manufactured via the selective laser melting method. The effects of processing time, amount of TiO2 addition, microstructure of anode materials, and resistance to wear and corrosion were investigated. The coating hardness and thickness increased with increasing processing time and TiO2 concentration. It has been observed that the addition of TiO2 to zinc anode coatings results in an increase in wear and a decrease in corrosion rate. It was noted that the specimens exhibiting the most significant wear also possessed the highest hardness value. The specimens were generated utilizing a graphite anode, underwent a 30-min processing time, and comprised 10 g l(-1) of TiO2.
Wearable assistive rehabilitation robotic devices - A comprehensive review
(MDPI, 2024) Lingampally, Pavan Kalyan; Ramanathan, Kuppan Chetty; Shanmugam, Ragavanantham; Čepová, Lenka; Salunkhe, Sachin
This article details the existing wearable assistive devices that could mimic a human's active range of motion and aid individuals in recovering from stroke. The survey has identified several risk factors associated with musculoskeletal pain, including physical factors such as engaging in high-intensity exercises, experiencing trauma, aging, dizziness, accidents, and damage from the regular wear and tear of daily activities. These physical risk factors impact vital body parts such as the cervical spine, spinal cord, ankle, elbow, and others, leading to dysfunction, a decrease in the range of motion, and diminished coordination ability, and also influencing the ability to perform the activities of daily living (ADL), such as speaking, breathing and other neurological responses. An individual with these musculoskeletal disorders requires therapies to regain and restore the natural movement. These therapies require an experienced physician to treat the patient, which makes the process expensive and unreliable because the physician might not repeat the same procedure accurately due to fatigue. These reasons motivated researchers to develop and control robotics-based wearable assistive devices for various musculoskeletal disorders, with economical and accessible solutions to aid, mimic, and reinstate the natural active range of motion. Recently, advancements in wearable sensor technologies have been explored in healthcare by integrating machine-learning (ML) and artificial intelligence (AI) techniques to analyze the data and predict the required setting for the user. This review provides a comprehensive discussion on the importance of personalized wearable devices in pre- and post-clinical settings and aids in the recovery process.
Treatment of crude oil-polluted water using CoFe2O4-doped mango (Mangifera indica) seed shell composite
(Springer Nature, 2024) Asadu, Christian O.; Ujah, Chika Oliver; Ekwueme, Benjamin Nnamdi; Ezema, Chinonso Anthony; Onah, Thomas O.; Makhkamov, Trobjon; Aka, Christian Chikezie; Ugwele, Franklin O.; Onu, Chijioke Elijah
This study investigates the potential of cobalt ferrite-doped mango seed shell (CoFe2O4-MSS) as an innovative and eco-friendly approach for the treatment of crude oil-polluted water. CoFe2O4-MSS was synthesized by impregnating carbonized mango seed shell with cobalt ferrite nanoparticles through thermal precipitation. The study systematically evaluated the adsorption capacity, kinetics, and isotherm behavior of the developed material using standard equations. Experimental results demonstrate the effectiveness of the cobalt ferrite-doped mango seed shell in adsorbing crude oil components, with high removal efficiency of 98.3% at 80 degrees C after 50 min. The crystallite sizes of raw mango seed shell and CoFe2O4-MSS are 31.8 nm and 21.3 nm, respectively. The calculated adsorption capacity stood at 55.50 mg/g, the Brunauer-Emmett-Teller surface area of CoFe2O4-MSS was 1007.4m(2)/g with a porosity distribution of 1.685 eta while the volume and pore diameter are 3.104m(3)/g and 7.212 nm, respectively. FTIR analysis revealed the presence of aliphatic, aromatic, and silicon compounds. The isotherm data matched well with Langmuir isotherm model while kinetic data fitted well with Bhattacharya-Venkobachar model. The unique properties of cobalt ferrite, a magnetic and iron-based material, combined with the abundant and biodegradable nature of mango seed shells, make this composite an attractive adsorbent for removing crude oil contaminants. This research contributes to the development of sustainable and cost-effective solutions for addressing environmental challenges posed by crude oil pollution. Also, this research has contributed immensely to the sustainable development goals of the united nation (UN-SDG) regarding environmental protection.
Analysis of Caputo fractional-order co-infection COVID-19 and influenza SEIR epidemiology by Laplace Adomian decomposition method
(MDPI, 2024) Meenakshi, Annamalai; Renuga, Elango; Čep, Robert; Karthik, Krishnasamy
Around the world, the people are simultaneously susceptible to or infected with several infections. This work aims at the analysis of the dynamics of transmission of two deadly viruses, COVID-19 and Influenza, using a co-infection epidemiological model by applying the Caputo fractional derivative. Fractional differential equations are currently used worldwide to model physical and biological phenomena. Our comprehension of complicated phenomena is improved when fractional-order derivatives are used to model systems with memory effects and long-range interactions. Mathematical depictions of infectious disease dynamics and dissemination across communities are provided by epidemiological models, which are essential resources for understanding and controlling infectious diseases. These models support informed decision making to prevent outbreaks, evaluate intervention measures, and help researchers and policymakers understand how diseases spread. A subclass of epidemiological models called co-infection models focuses on studying the dynamics of several infectious illnesses that occur in the same population at the same time. They are especially useful in situations where people are simultaneously susceptible to or infected with several infections. Co-infection models provide information on the development of effective control techniques, the progression of disease, and the interactions between several pathogens. The qualitative study via stability analysis is discussed at equilibrium, the reproduction number R0 is computed, and the results are simulated using the Laplace Adomian Decomposition Method (LADM) for Fractional Differential Equations. We employ MATLAB R2023a for graphical presentations and numerical simulations.
DSC of biodegradable plastic composites material
(Springer Nature, 2024) Nowak, Agnieszka J.; Waśkiewicz, Sylwia; Baszczeńska, Oliwia; Niesporek, Kamil; Król, Mariusz; Hajnyš, Jiří
The article presents the thermal analysis of new, fully biodegradable thermoplastic composites filled with natural additives. The samples were made of thermoplastic material with the trade name BIOPLAST (R) GS 1289, and the natural filler was powder from walnut shells and chicken egg shells in various mass proportions. Differential scanning calorimetry (DSC) analysis was used to assess the quality of the new materials obtained. Moreover, it allowed to determine and select technological parameters of processing and explain the occurrence of undesirable phenomena related to the processing of these materials. The thermal properties of the obtained samples were determined using a Mettler-Toledo DSC 3 scanning calorimeter by the ISO 11357 standard. The analysis was carried out using the following method: conditioning the sample for 10 min at - 20 degrees C and heating from - 20 to 180 degrees C at a 10 K min-1 speed. Each sample was subjected to three measurements according to the given method, the first and second cycle in a row, and the third cycle was performed after 24 h. The mass melt flow rate (MFR) was also determined. The critical share of filler in the matrix (BIOPLAST (R) GS 1289) and the influence of natural fillers on signals on the curve were determined, and it was related to the processing properties of the developed materials.
Achieving sustainable machining of titanium grade 3 alloy through optimization using grey relational analysis (GRA)
(Elsevier, 2024) Ahmad, Adnan; Khan, Muhammad Ali; Akram, Sohail; Faraz, Muhammad Iftikhar; Jaffery, Syed Husain Imran; Iqbal, Tahir; Petrů, Jana
In the contemporary landscape of advanced manufacturing, there is an increasing demand for machining processes that excel in both quality and energy efficiency. One of the prime objectives is to excel in an era of machining practices that are environmentally conscious and economically sustainable. This research addresses this challenge by undertaking a comprehensive exploration of multi-objective optimization, specifically tailored to address the machining challenges presented by Titanium Grade 3 alloy. A robust Taguchi-Grey integrated approach was adopted with research aim to strike an optimum balance among specific cutting energy, tool wear, surface finish, and material removal rate. The impact of machining inputs i.e., feed rate, cutting speed, and depth of cut were analyzed. Best machining setting was identified using grey relational analysis. Feed rate was identified as the most influential member affecting grey relational grade having contribution ratio of 73.95%. Furthermore, surface plots and contour plots were developed for aid of machinists on job floor in selection of best cutting conditions. Harnessing the usefulness of response surface optimization, the machinability was further enhanced by 9% reduction in specific cutting energy and 7% improvement in tool wear. However, it is imperative to acknowledge the trade-offs as a result of MOO; surface roughness increases by 12%, potentially necessitating additional post-processing steps.
Sustainability assessment of machining Al 6061-T6 using Taguchi-grey relation integrated approach
(Elsevier, 2024) Zaidi, Sajid Raza; Butt, Shahid Ikramullah; Khan, Muhammad Ali; Faraz, Muhammad Iftikhar; Jaffery, Syed Husain Imran; Petrů, Jana
Modern machining requires reduction in energy usage, surface roughness, and burr width to produce finished or near-finished parts. To ensure high surface quality in machining processes, it is crucial to minimize surface finish and minimize burr width, which are considered as significant parameters as specific cutting energy. The objective of this study was to identify the optimal machining parameters for milling in order to minimize surface roughness, burr width, and specific cutting energy. To achieve this, the research investigated the impact of feed per tooth, cutting speed, depth of cut, and number of inserts on the responses across three intervals using Taguchi L9 array. Observing the responses by varying these parameters, underlined the need for multi objective optimisation. Machining conditions of 0.14 mm/tooth fz, 350 m/min Vc and 2 mm ap using 1 cutting insert (exp no 9) was identified as the best machining run using grey relational analysis owing to its highest grey relational grade of 0.936. ANOVA examination identified cutting speed as the leading factor impacting the grey relational grade with 31.07 % contribution ratio, with the number of inserts, depth of cut, and feed per tooth also making notable contributions. Conclusively, machining parameters identified through response surface optimisation resulted in 21.69 % improvement in surface finish, 11.39 % reduction in specific energy consumption, and 6.2 % decrease in burr width on the down milling side albeit with an increase of 9 % in burr width on the up-milling side.
Vibration analysis of piping connected with shipboard equipment
(Frontiers Media S.A., 2024) Tripathi, Radharaman; Jadhav, Tushar A.; Gaikwad, Mahesh K.; Naidu, Mithul J.; Gawand, Aishwarya B.; Kaya, Duran; Salunkhe, Sachin; Čep, Robert; Nasr, Emad Abouel
The piping system connected with the shipboard equipment may be subjected to excessive vibration due to harmonic base excitation produced by hydrodynamic force imposed on the propeller blades interacting with the hull and by other sources. Vibration design aspects for shipboard pipework are often ignored, which may cause catastrophic fatigue failures and, consequently, leakage and spillage in the sea environment. Without dedicated design codes, the integrity of shipboard equipment against this environment loading can be ensured by testing as per test standard MIL-STD-167-1A (2005). However, in many cases, testing is not feasible and economically viable. Hence, this study develops an FE-based vibration analysis methodology based on MIL-STD-167-1A, which can be a valuable tool to optimize the testing requirement without compromising the integrity of these piping systems. The simulated model dynamic properties are validated with experimental modal testing and Harmonic response analysis result confirm that a mitigating solution option can be verified by a FE based vibration analysis to mitigate the vibration problem.
Exploring tribological properties in the design and manufacturing of metal matrix composites: an investigation into the AL6061-SiC-fly ASH alloy fabricated via stir casting process
(Frontiers Media S.A., 2024) Murmu, Sagar Kumar; Chattopadhayaya, Somnath; Čep, Robert; Kumar, Ajay; Kumar, Ashwini; Mahato, Shambhu Kumar; Kumar, Amit; Sethy, Priya Ranjan; Logesh, K.
This study investigates a novel methodology to intricately craft a HAMMC and thoroughly examine its multifaceted mechanical and tribological characteristics. By combining silicon carbide (SiC) and fly ash as reinforcements, a unique identity is bestowed upon this hybrid composite, enhancing its structural integrity and functional attributes. Stir casting is the chosen methodology for fabricating this composite, favored for its economic viability and suitability for large-scale manufacturing. In this research, the emphasis is on developing a cost-effective composite that not only meets stringent economic considerations but also exhibits improved material properties. Within the realm of hybrid metal matrix composites, the well-regarded Al6061 takes on the role of the matrix material, while the synergistic inclusion of fly ash and SiC serves as reinforcing constituents. Three specimens with compostion 90% Al6061 + 5% SiC +5% Fly ash, 90% Al6061 + 10% SiC +6% Fly ash and 90% Al6061 + 15% SiC +7% Fly ash were fabricated. To unravel the intricacies of the fabricated Al6061 metal matrix composite, comprehensive tests are employed. These tests, including the Pin-on Disc test, Scratch test, Rockwell Hardness test, and Charpy Impact test, collectively work to unveil the nuanced tribological and mechanical behaviors encapsulated within this innovative alloy. The results indicated significant improvement in wear resistance in specimen comprising 78% Al6061 + 15% SiC +7% Fly Ash and volumetric loss found to have 0.96 g. Superior hardness characteristics and enhanced abrasion resistance found in 78% Al6061 + 15% SiC +7% Fly Ash than other two specimens. The highest impact strength exhibited in 90% Al 6,061 + 5% SiC +5% Fly ash specimen.

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