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Gas tungsten arc welding (GTAW) technology is widely used in industry and has advantages, including high precision, excellent welding quality, and low equipment cost. However, the inclusion of a large number of process parameters hinders its application on a wider scale. Therefore, there is a need to implement the prediction and optimization models that effectively enhance the process performance of the GTAW process in different applications. In this study, a five-factor five-level central composite design (CCD) matrix was used to conduct GTAW experiments. AISI 1020 steel blank was used as a substrate; UTP AF Ledurit 60 and UTP AF Ledurit 68 were used as the materials of two tubular wires. Further, an artificial neural network (ANN) was used to simulate the GTAW process and then combined with a genetic algorithm (GA) to determine welding parameters that can provide an optimal weld. In welding experiments, five different welding current levels, welding speed, distance to the nozzle, angle of movement, and frequency of the wire feed pulses were used. Using GA, optimal welding parameters were determined: welding current = 222 A, welding speed = 25 cm/min, nozzle deflection distance = 8 mm, travel angle = 25°, wire feed pulse frequency = 8 Hz. The determination coefficient (R2) and RMSE value of all response parameters are satisfactory, and the R2 of all the data remained higher than 0.65.

Products made of titanium and its alloys are widely used in modern areas like the mechanical engineering, instrument making, aerospace and medical sector. High strength and low thermal conductivity are the causes of difficulties with the machinability of these alloys. It is important to find ways to increase machinability by cutting titanium alloys. One way to implement this is to apply various methods of cooling on workpieces of titanium alloys and on cutting tools during machining. In this review article, an extensive analysis of the literature on such cooling techniques as dry, conventional cooling system, minimum quantity of lubricant (MQL), minimum quantity cooling lubrication (MQCL), cryogenic lubrication, and high-pressure cooling (HPC) is performed. The following groups of Ti alloys are considered: high-strength structural and high-temperature Ti alloys, intermetallic compounds, pure titanium, as well as composites CFRPs/Ti alloys. For the processes of turning, milling, drilling, and grinding, etc. it is shown how the type of cooling affects the surface integrity include surface roughness, tool wear, tool life, temperature, cutting forces, environmental aspects, etc. The main advantages, disadvantages and prospects of different cooling methods are also shown. The problems and future trends of these methods for the machining of Ti and its alloys are indicated.

A well-acknowledged role of cutting fluids in any cutting operation has made them inevitable to utilize regarding the provision of adequate cooling and lubrication. Mineral-based cutting fluids are common practice in the industry; however, they are not suitable for our ecology and health. Therefore, there is a need to implement sustainable cooling/lubrication system that helps the environment and improves the machinability of light weight alloys. This review is presenting the machining and sustainability characteristics of minimum quantity lubrication (MQL), nanofluids-MQL, Ranque-Hilsch vortex tube MQL (RHVT + MQL), cryogenic-MQL as alternative to flood cooling applications in the cutting of light-weight materials. It can be stated that MQL advancements can offer clear guidelines to implement hybrid cooling techniques to improve heat transfer, lubrication, and sustainable implementations.

Today, superalloys (also known as hard-to-cut materials) such as nickel, titanium and cobalt based cover a wide range of areas in engineering applications. At the same time, challenging material properties namely high strength and low thermal conductivity cause low quality in terms of cutting tool life and surface integrity of the machined part. It is important to improve the machinability of this type of materials by applying various methods in the perspective of sustainability. Therefore, current study presents surface integrity, tool wear characteristics and initiatives to improve them during the machining of superalloys. In this manner, it is outlined the surface integrity characteristics containing surface defects, surface roughness, microstructure alterations and mechanical properties. Also, tool wear mechanisms for example abrasive, adhesive, oxidation, diffusion and plastic deformation are investigated in the light of literature review. Finally, possible improvement options for tool wear and surface integrity depend on machining parameters, tool modifications, cooling methods and trade-off strategies are highlighted. The paper can be a guide for the researchers and manufacturers in the area of sustainable machining of hard-to-cut materials as explaining the latest trends and requirements. (C) 2021 CIRP.

Aluminum (Al) alloys are of particular importance to the aerospace industry owing to the combination of characteristics including strength, ductility, toughness, fatigue life and oxidation resistance as a light metal. This is the case of AA 2024 T3 Al alloy. In particular, machining of these alloys has similar importance for productivity and part quality. Recently, the use of nanofluids, which have various advantages in terms of both cooling ability and tribological aspects, has become popular for the efficient machining of such alloys. In this context, guiding data are needed that enable industry and researchers to machine these types of alloys with high efficiency. Taking these into account, in this study, AA 2024 T3 Al alloy was machined and various machinability indicators such as surface roughness, surface topography, maximum temperature and dominant tool wear mechanism under different cooling/lubrication strategies i.e., dry cutting, base fluid minimum quantity lubrication (MQL) and mineral oil based MoS2 nanofluid MQL (NFMQL) were investigated. As a results, significant improvements have been achieved in surface roughness, surface topography, and maximum temperature with help of NFMQL application. The intensive built-up edge (BUE) and built-up layer (BUL) formations are produced on the cutting tool when machining AA 2024 T3 Al alloy under dry cutting. On the other hand, BUE formation has been significantly eliminated thanks to NFMQL. Moreover, a less damaged cutting edge was obtained when machining Al alloy under NFMQL compared to both dry cutting and MQL environments. © 2021 The Author(s) FYL-2020-10160 The authors would like to thank the Erciyes University Research Fund for their financial support of present work (FYL-2020-10160). 2-s2.0-85114934698

The use of large amount of cutting fluid in machining process represents a great environmental and economic issue. Minimum quantity lubrication (MQL) seems to be a feasible alternative to flood application as it reduces drastically the volume cutting fluid used in machining process. This paper investigated the relationship between cutting parameters and machined surface quality in the end milling of maraging 300 steel when flood and MQL methods were used. A full factorial design setting feed per tooth, cutting speed cutting depth, and fluid application technique was performed. Then, the effects of these parameters on machining forces, surface roughness, and residual stresses were studied by analysis of variance (ANOVA). The analysis of variance showed that the most important milling parameter regarding results of both surface roughness and residual stresses was the feed per tooth. Minimum quantity lubrication system was able to reduce machining forces for most of tested conditions, and surface roughness (Ra) was reduce in approximately 10%. Residual stress results showed that MQL is able to produce better results than flood method when low feed rate is used. It was found that the use of MQL technique is advantageous in the milling of maraging steel.

Dies and molds steels are essential materials in the manufacturing industry of engineering products. These materials are usually machined in the hardened condition and therefore, can be problematic to transform them in chips. Calcium treatment can be a viable alternative to increase machinability without compromising the main properties of the steel. The present work investigates the machinability of the calcium treated mold steel, AISI P20 UF, and compares it to the non-treated version of the same material, AISI P20, in slot milling tests with triple coated (TiN, TiCN and Al2O3) cemented carbide tools. A consolidated method that minimizes the number of tests needed for the determination of the extended Taylor's equation coefficients was used and the power consumption was measured during the machining experiments. SEM was used for the exploration of the wear of the used tool and its mechanism. The results showed that the calcium treated steel presented a considerably higher tool life, and although the treatment did not affect the power consumption directly, indirectly it reduced it because of the positive reduction of the tool wear rate allowing the power to be kept at lower levels for more extended periods. Attrition (adhesion) and abrasion were the primary tool wear mechanisms observed when machining the non-treated steel and attrition for the calcium treated material. In this latter case, because of the longer tool lives, chippings of the cutting edge were also present.

Composite material is a material made by the combination of two or more constituent materials with considerably distinct properties resulting in a material that presents chemical and physical properties that are not seem in any traditional material part. The wide range of chemical and mechanical properties creates the possibility of their application in many different industries. However, the same characteristics that make these materials stand out as high quality material also increase the complexity of their manufacturing processes specially when it comes to subtractive manufacturing. Therefore, this presented review chapter intends to provide a literature survey of the state of the art and the main challenges to be overcome in the subtractive manufacturing of composite material. The characteristics of the main types of machining process and new emerging technologies and their application on the manufacturing processes of Polymer Matrix Composites (MMCs), Metal Matrix Composites (MMCs) and Ceramic Matrix Composites (CMCs) are discussed.

Titanium alloys are widely used in various applications including biomedicine, aerospace, marine, energy, and chemical industries because of their superior characteristics such as high hot strength and hardness, low density, and superior fracture toughness and corrosion resistance. However, there are different challenges when machining titanium alloys because of the high heat generated during cutting processes which adversely affects the product quality and process performance in general. Thus, optimization of the machining conditions while machining such alloys is necessary. In this work, an experimental investigation into the influence of different cutting parameters (i.e., depth of cut, cutting length, feed rate, and cutting speed) on surface roughness (Rz), flank wear (VB), power consumption as well as the material removal rate (MRR) during high-speed turning of Ti-6Al-4V alloy is presented and discussed. In addition, a backpropagation neural network (BPNN) along with the technique for order of preference by similarity to ideal solution (TOPSIS)-fuzzy integrated approach was employed to model and optimize the overall cutting performance. It should be stated that the predicted values for all machining outputs demonstrated excellent agreement with the experimental values at the selected optimal solution. In addition, the selected optimal solution did not provide the best performance for each measured output, but it achieved a balance among all studied responses.

Mechanical components and structures wear out as a result of friction between surfaces in relative motion. Residual stresses play an important role for the tribological performance of components since compressive residual stresses yield positive effects on wear resistance. However, the real effect of residual stresses on the tribological performance of surfaces is not entirely clear. The objective of this work is to evaluate the residual stress behavior during a pin-on-disk wear test of quenched and tempered AISI 4340 disk specimens against a counter-body of steel AISI E 52100. Tests were performed in shot peened and non-shot peened specimens in six steps and residual stresses were evaluated after each one by X-ray diffraction technique using sin2 method. The results shown that wear rate of the shot peened specimens was approximately fifty percent lower. Shot peening induced compressive residual stresses contributed to this effect even though they were modified during the pin-on-disk test. Keyword: Residual stress, X-ray diffraction, AISI 4340 steel, Wear, Pin-on-disk test, shot peening.

This paper presents the embedding of a temperature Surface Acoustic Wave (SAW) sensor in an additively manufactured 316L stainless steel part during the Laser Powder Bed Fusion (L-PBF) process. The embedding of sensors and integrated circuits in additively manufactured (AM) parts is an important step towards the development of smart components; however, there are still some barriers to overcome for this to become an established technology. The L-PBF process is paused to embed a SAW sensor in an AM part to produce a wireless and passive smart component. The effect of the pausing of the L-PBF process to embed sensors on the microstructure and hardness of the manufactured parts is investigated and the embedded sensor is also tested to verify its functionality. These results act as a proof-of-concept for the embedding of SAW sensors during the L-PBF process and will lead to the development of passive wireless smart components manufactured by additive manufacturing.

Titanium diboride (TiB 2 ) is a ceramic material with high mechanical resistance, chemical stability, and hardness at high temperatures. Sintering this material requires high temperatures and long sintering times. Non-conventional sintering techniques such as spark plasma sintering (SPS) can densify materials considered difficult to sinter. In this study, TiB 2 –AIN (aluminum nitride) composites were sintered by using the SPS technique at different sintering temperatures (1500 °C, 1600 °C, 1700 °C, 1800 °C, and 1900 °C). x-ray diffraction was used to identify the phases in the composites. mechanical properties such as hardness and indentation fracture toughness was obtained using a vickers indenter. Different toughening mechanisms were identified, and good densification results were obtained using shorter times and lower temperatures than those previously reported.

O diboreto de titânio (TiB 2 ) e um material cerâmico que se destaca por sua elevada resistencia mecânica, estabilidade quimica e dureza a altas temperaturas, entretanto, caracteristicas como baixa sinterabilidade e tenacidade a fratura limitam a atuacao deste material em aplicacoes termomecânicas. Tecnicas de sinterizacao nao convencionais como SPS e aditivo de sinterizacao como AlN e Si 3 N 4 podem reduzir a temperatura de sinterizacao e aumentar a tenacidade a fratura do TiB 2 . Neste sentido, o presente trabalho teve como objetivo avaliar a eficiencia da tecnica de sinterizacao por plasma pulsado (Spark Plasma Sintering - SPS) no processamento do diboreto de titânio. O nitreto de aluminio foi utilizado como aditivo para reduzir temperatura e tempo de sinterizacao e facilitar a densificacao do TiB 2 . Os resultados apontam a sinterizacao por plasma pulsado como uma tecnica eficiente na densificacao de composito cerâmico TiB 2 - AlN. Elevado grau de densificacao foi alcancado mesmo utilizando tempos de sinterizacao relativamente curto. Palavras-chave: Diboreto de titânio, sinterizacao, densificacao.

The necessity for decreasing the negative impact of the manufacturing industry has recently increased. This is getting recognized as a global challenge due to the rapid increase in life quality standards, demand, and the decrease in available resources. Thus, manufacturing, as a core of the product provision system and a fundamental pillar of civilized existence, is significantly influenced by sustainability issues. Furthermore, current manufacturing modeling and assessment criteria require intensive revisions and upgrades to keep up with these new challenges. Nearly all current manufacturing models are based on the old paradigm, which was proven to be inadequate. Therefore, manufacturing technology, along with culture and economy, are held responsible for providing new tools and opportunities for building novel resolutions towards a sustainable manufacturing concept. One of such tools is sustainability assessment measures. Revising and updating such tools is a core responsibility of the manufacturing sector to efficiently evaluate and enhance sustainable manufacturing performance. These measures should be adequate to respond to the growing sustainability concerns in pursuit of an integrated sustainability concept. The triple bottom line (TBL) that includes environment, economic, and social dimensions has usually been used to evaluate sustainability. However, there is a lack of standard sets of sustainable manufacturing performance measures. In addition to the sustainability concept, a new concept of smart manufacturing is emerging. The smart manufacturing concept takes advantage of the recent technological leap in Artificial Intelligent (AI), Cloud Computing (CC), and the Internet of Things (IoT). Although this concept offers an important step to boost the current production capabilities to meet the growing need, it is still not clear whether the two concepts of smart manufacturing and sustainability will constructively or destructively interact. Therefore, the current study aims to integrate the sustainable smart manufacturing performance by incorporating sustainable manufacturing measures and discussing current and future challenges that are faced by the manufacturing sector. In addition, the opportunities for future research incorporating sustainable smart manufacturing are also presented.