Search Results (12)

In this study, Zn-reinforced Mg matrix composite materials were produced via powder metallurgy by exposing them to ball milling at varying mechanical milling times. Following ball milling, the powders were cold-pressed under 600 MPa to obtain green compacts. The sintering process was carried out in a tube furnace under an argon atmosphere at 500 °C for 120 min. The effects of different milling times (2 h, 4 h, and 8 h) on particle and grain size, as well as the influence of sintering temperature and time on the microstructure, were investigated through SEM analysis. Phase evolution and changes in crystal planes occurring after ball milling were revealed by XRD analysis. SEM images show that Zn particles were homogeneously distributed within the matrix after 8 h of milling. Furthermore, it can be clearly stated that the highest hardness values were obtained from the samples produced after 8 h of milling. The sample group with the highest density, least mass loss, and lowest degradation rate was obtained from materials produced from 4 h ball milled powders. The intermetallic phase formed in the powder structure after 8 h of milling tends to reduce density and corrosion properties. The findings reveal that the addition of these alloys to pure Mg clearly enhances its hardness and density, while also imparting superior corrosion resistance. These combined improvements suggest that the developed materials hold strong potential for application in biomedical and clinical environments, where both mechanical strength and corrosion resistance are critical. Full article

The surface quality of machine elements may deteriorate over time while operating under different conditions. This deterioration adversely affects the wear behavior in the contact areas, and these materials become unusable over time. In machine elements especially, the heat transfer, wear amount and surface roughness parameters in the contact area are very important in order for the system to work efficiently. In order to understand this change, composite materials were produced by adding spheroidal graphite cast iron (GGG40) with high lubricating properties at different rates to bronze (CuSn10), which is widely used as a self-lubricating bearing material. In this study, four different mixing ratios (B60D40, B70D30, B80D20 and B90D10) and B100, which is completely produced from bronze chips, were used for comparison purposes. In addition, these produced composite materials were compared with pure CuSn10 and pure GGG40 via double-acting isostatic hot pressing, and then the results were examined. The composite materials were made at two different temperatures (400 °C and 450 °C) and three different pressures (480 MPa, 640 MPa and 820 MPa) using recycled waste chips. Composites produced by recycling waste chips both reduce costs and make a positive contribution to the natural environment. Thus, more advantageous self-lubricating bearing materials will be produced, and the efficiency will be increased in these materials. The time-dependent variation in the friction coefficient observed after the wear tests performed under constant load is explained, and the resulting surface structures are presented with SEM images and EDS analyses. After the wear tests, it was observed that the process parameters used in production effectively influenced the wear behavior. In particular, when the production pressure was low (480 MPa), the wear behavior was adversely affected because sufficient bonding between the chips could not be achieved. In addition, as the amount of GGG40 used as a reinforcement material increased, the spheroidal graphite contained in it positively affected the wear behavior. The lubricating effect provided by this spheroidal graphite reduced wear in the contact area and the friction coefficient. Full article

Condition monitoring provides insights into the type of damage occurring in the cutting tool during machining to facilitate its timely maintenance or replacement. By detecting and analyzing machining consequences (vibrations, chatter, noise, power consumption, spindle load, etc.), correlating them with different tool conditions enables real-time monitoring and the automated detection of tool failures. Machine learning (ML) plays a vital role in making tool condition monitoring (TCM) frameworks intelligent, and most research is geared toward classifying various types of tool wear. However, monitoring built-up edges, chipping, thermal cracking, and plastic deformation of milling cutter inserts are challenging and need careful consideration. To effectively monitor these phenomena, spindle vibrations can narrate the corresponding dynamic behavior of tool conditions and therefore have been investigated in this research. The acquired vibration data are then analyzed using histogram features and trained through the Partial C4.5 (PART) classifier to extract meaningful recommendations related to the milling cutter inserts condition. Full article

Machining of AISI 304 austenitic stainless steel is considered to be difficult due to its structural aspects and low thermal conductivity, which leads to increased temperatures during machining. To overcome the challenges of machining AISI 304 stainless steel, several cooling and lubricating techniques have been developed. The main objective of this experimental study is to evaluate the different turning conditions of AISI304 stainless steel under dry and minimum quantity lubrication (MQL) environment conditions. The machining experiments were conducted using a two-level full factorial design method and utilized a TiC-coated cutting tool. The tool-tip temperature, cutting force and surface roughness were analyzed regarding three cutting parameters namely, cutting speed, feed rate and cutting depth. Also, chip macro-morphology was investigated to define the interaction at the tool-chip-workpiece region. The cutting medium affects the surface roughness significantly (more than 100%) for all cutting parameter values. In some environmental cutting conditions, high cutting speed provides 10% lesser surface roughness than low cutting speed parameters. Also, the cutting force decreases by 20% in low feed rate machining conditions. However, the effect of this parameter disappeared for cutting forces in high feed rates and low cutting depth conditions in both MQL and dry environments. Cutting speed was observed as the most influential factor on surface roughness, followed by feed rate. The depth of cut was the main parameter that caused the temperature to increase in the dry machining environment. Full article

Industrial materials are materials used in the manufacture of products such as durable machines and equipment. For this reason, industrial materials have importance in many aspects of human life, including social, environmental, and technological elements, and require further attention during the production process. Optimization and modeling play an important role in achieving better results in machining operations, according to common knowledge. As a widely preferred material in the automotive sector, hardened AISI 4140 is a significant base material for shaft, gear, and bearing parts, thanks to its remarkable features such as hardness and toughness. However, such properties adversely affect the machining performance of this material system, due to vibrations inducing quick tool wear and poor surface quality during cutting operations. The main focus of this study is to determine the effect of parameter levels (three levels of cutting speed, feed, and cutting depth) on vibrations, surface roughness, and acoustic emissions during dry turning operation. A fuzzy inference system-based machine learning approach was utilized to predict the responses. According to the obtained findings, fuzzy logic predicts surface roughness (88%), vibration (86%), and acoustic emission (87%) values with high accuracy. The outcome of this study is expected to make a contribution to the literature showing the impact of turning conditions on the machining characteristics of industrially important materials. Full article

Sustainable technologies draw attention in the machining industry thanks to their contributions in many aspects such as ecological, economic, and technological. Minimum quantity lubrication (MQL) is one of these techniques that enable to convey of the high pressurized cutting fluid toward the cutting zone as small oil particulates. This study examines the potency of MQL technology versus dry conditions on the machining quality during the milling of structural Strenx 900 steel within the sustainability index. High strength and toughness properties make this steel a hard-to-cut material providing an important opportunity to test the performances of dry and MQL environments. The outcomes of the experimental data demonstrated that MQL is superior in enhancing the quality of significant machining characteristics namely surface roughness (up to 35%), flank wear (up to 94%), wear mechanisms, cutting energy (up to 28%), and cutting temperatures (up to 14%). Furthermore, after analyzing the main headings of the sustainable indicators, MQL provided the same (+5) desirability value with a dry (+5) medium. This experimental work presents a comparative approach for improved machinability of industrially important materials by questioning the impact of sustainable methods. Full article

The resources of the earth are being consumed day by day with the increasing population and necessities of humankind in many areas, such as industrial applications and basic needs in houses, workplaces and transportation. As a consequence, careful usage of the energy sources and the conversed energy is of great importance in order to obtain sustainable development. Machining operations have a large percentage of all manufacturing methods in terms of depleted energy which gives them a high potential for reducing the total energy consumption. The approaches handled in the literature for the minimization of the consumed energy in the machining industry were considered in this study. While several machinability characteristics under different machining processes were investigated broadly in the context of composites and superalloys, the comparison of these systems has been given cursory attention in the current literature, specifically for cutting energy saving. The overall performance of these group material systems utilizing widely in numerous significant industrial areas supplies important signs about manufacturing costs, service conditions and environmental impacts. It is highly crucial to monitor the indicators of energy-saving phenomena of the machined parts since the mechanisms behind the energy consumption of these systems is very complex and dynamic owing to different process-induced variables. This well-organized review paper distinguishes itself from previous studies in this field since the comprehensive literature survey paves the way for diverse approaches that regard energy saving, especially for composites and superalloys under different machining operations. This overview paper aims to contribute to the current literature by highlighting the effects of the state-of-the-art approaches in reducing energy consumption in the machining of industrially important materials. This study can also establish a framework in the context of the process-property interactions to comprehend the influence of energy-saving mechanisms through machining in a system of interest. Full article

Engineering materials are expected to contain physical and mechanical properties to meet the requirements and to improve the functionality according to their application area. In this direction, hybrid composites stand as an excellent option to fulfill these requests thanks to their production procedure. Despite the powder metallurgy method that allows for manufacturing products with high accuracy, machining operations are still required to obtain a final product. On the other hand, such materials are characterized with uncertainties in the structure and extremely hard reinforcement particles that aggravate the machinability. One of the prominent solutions for better machinability of composites is to use evolutionary cooling and lubricating strategies. This study focuses on the determination of tribological behavior of Cu-based, B-Ti-SiC_P reinforced, about 5% wt. hybrid composites under milling of several environments, such as dry, minimum quantity lubrication (MQL)-assisted and cryogenic LN₂-assisted. Comprehensive evaluation was carried out by considering tool wear, temperature, energy, surface roughness, surface texture and chips morphology as the machinability characteristics. The findings of this experimental research showed that cryogenic cooling improves the tribological conditions by reducing the cutting temperatures, flank wear tendency and required cutting energy. On the other hand, MQL based lubricating strategy provided the best tool wear index and surface characteristics, i.e., surface roughness and surface topography, which is related to spectacular ability in developing the friction conditions in the deformation zones. Therefore, this paper offers a novel milling strategy for Cu-based hybrid composites with the help of environmentally-friendly techniques. Full article

Minimum quantity lubrication (MQL) is a sustainable method that has been efficiently applied to achieve machinability improvements with various materials in recent years, such as hardened steels, superalloys, soft metals, and composites. This study is the first to focus on the performance evaluation of MQL and dry milling environments with AISI 1040 steel. The tool wear, cutting temperature, and power consumption were considered as the quality responses while cutting speed, feed rate and machining environment are taken as input parameters. The effects of the influential factors are analyzed using analysis of variance (ANOVA) and bar charts. Additionally, Taguchi signal-to-noise (S/N) ratios are utilized in order to determine the optimum parameters for the best quality responses. The results show that the MQL system provides better performance compared to dry milling by reducing the tool wear, cutting temperature, and power consumption. According to the ANOVA results, the cutting environment affects the cutting temperature (37%) and power consumption (94%), while cutting speed has importance effects on the tool wear (74%). A lower cutting speed (100 m/min) and feed rate (0.10 mm/rev) should be selected under MQL conditions to ensure minimum tool wear and power consumption; however, a higher feed rate (0.15 mm/rev) needs to be selected along with a low cutting speed and MQL conditions to ensure better temperatures. A comparative evaluation is carried out on the tool wear, cutting temperature, and power consumption under MQL and dry environments. This investigation is expected to contribute to the current literature, highlighting the superiority of sustainable methods in the milling of industrially important materials. Full article

Tribological properties are important to evaluate the in-service conditions of machine elements, especially those which work as tandem parts. Considering their wide range of application areas, metal matrix composites (MMCs) serve as one of the most significant materials equipped with desired mechanical properties such as strength, density, and lightness according to the place of use. Therefore, it is crucial to determine the wear performance of these materials to obtain a longer life and to overcome the possible structural problems which emerge during the production process. In this paper, extensive discussion and evaluation of the tribological performance of newly produced spheroidal graphite cast iron-reinforced (GGG-40) tin bronze (CuSn10) MMCs, including optimization, statistical, graphical, and microstructural analysis for contact zone temperature and specific wear rate, are presented. For this purpose, two levels of production temperature (400 and 450 °C), three levels of pressure (480, 640, and 820 MPa), and seven different samples reinforced by several ingredients (from 0 to 40 wt% GGG-40, pure CuSn10, and GGG-40) were investigated. According to the obtained statistical results, the reinforcement ratio is remarkably more effective on contact zone temperature and specific wear rate than temperature and pressure. A pure CuSn10 sample is the most suitable option for contact zone temperature, while pure GGG-40 seems the most suitable material for specific wear rates according to the optimization results. These results reveal the importance of reinforcement for better mechanical properties and tribological performance in measuring the capability of MMCs. Full article

Surface roughness reflects the quality of many operational parameters, namely service life, wear characteristics, working performance and tribological behavior of the produced part. Therefore, tribological performance is critical for the components used as tandem parts, especially for the MMCs (Metal Matrix Composites) which are a unique class of materials having extensive application areas such as aerospace, aeronautics, marine engineering and the defense industry. Current work covers the optimization study of production parameters for surface roughness and tribological indicators of newly produced cast iron reinforced bronze MMCs. In this context, two levels of temperature (400 and 450 °C), three levels of pressure (480, 640 and 820 MPa) and seven levels of reinforcement ratios (60/40, 70/30, 80/20, 90/10, 100/0 of GGG40/CuSn10, pure bronze-as received and pure cast iron-as received) are considered. According to the findings obtained by Taguchi’s signal-to-noise ratios, the reinforcement ratio has a dominant effect on surface roughness parameters (Ra and Rz), the coefficient of friction and the weight loss in different levels. In addition, 100/0 reinforced GGG40/CuSn10 gives minimum surface roughness, pure cast iron provides the best weight loss and pure bronze offers the desired coefficient of friction. The results showed the importance of material ingredients on mechanical properties by comparing a wide range of samples from starting the production phase, which provides a perspective for manufacturers to meet the market supply as per human requirements. Full article

The complex structure of turning aggravates obtaining the desired results in terms of tool wear and surface roughness. The existence of high temperature and pressure make difficult to reach and observe the cutting area. In-direct tool condition, monitoring systems provide tracking the condition of cutting tool via several released or converted energy types, namely, heat, acoustic emission, vibration, cutting forces and motor current. Tool wear inevitably progresses during metal cutting and has a relationship with these energy types. Indirect tool condition monitoring systems use sensors situated around the cutting area to state the wear condition of the cutting tool without intervention to cutting zone. In this study, sensors mostly used in indirect tool condition monitoring systems and their correlations between tool wear are reviewed to summarize the literature survey in this field for the last two decades. The reviews about tool condition monitoring systems in turning are very limited, and relationship between measured variables such as tool wear and vibration require a detailed analysis. In this work, the main aim is to discuss the effect of sensorial data on tool wear by considering previous published papers. As a computer aided electronic and mechanical support system, tool condition monitoring paves the way for machining industry and the future and development of Industry 4.0. Full article