The effects of cutting fluids to health, environment, productivity and quality in machining operations have been discussed. MQL is green technology which is gradually applied in mechanical processing. The article has introduced about MQL cooling lubrication method in mechanical processing. Some previous research result have been made to clarify the meaning of this method. In addition, the comparison of the outputs of MQL, dry and wet methods has also been shown to show the effectiveness of the MQL method. Then, based on the MQL equipment being used at Tran Dai Nghia University, the authors designed the experiment to evaluate the impact of MQL parameters on the process outputs. Machining and optimization of that parameter. This paper presents of the MQL parameters optimization approach in which the multi-response outputs based on Taguchi's L9 orthogonal array method is used. During the turning AISI-1045 steel, the cutting temperature, the maximum of tool wear, and the surface roughness were measured. The MQL parameters which are ratio of soluble lubricant and water, pressure of spray head, flow volume of emulsion was simultaneously optimized by taking the multi-response outputs using Taguchi based grey relational analysis (GRA) into consideration. In turning experiments, three different flow volume of emulsion Q (40, 60, 80 ml/h), three different levels pressure of spray head P (3, 5, 7 bar) and three different levels ratio of soluble lubricant and water R (4, 6, 8%) were used. Here, three mathematical models were created using response surface regression methodology. The experiments had been done to investigate the effect of the MQL parameters to the turning process. As the results, the set of optimal MQL parameters had been pointed out to simultaneously minimize the cutting temperature, the tool wear and surface roughness. The Flow volume of emulsion 80 ml/h, Pressure of spray head 7 bar, Ratio of soluble lubricant and water 6% was observed to be the most effective. Lubrication (MQL) on cutting temperature, tool wear and surface roughness in turning AISI-1045 material. Sci. Tech. Dev. J. -Engineering and Technology; 2(SI):xxx-xxx. 1 U n c o r r e c t i o n P r o o f Science & Technology Development Journal -Engineering and Technology, 2(SI):xxx-xxx tionally, the machining of parts uses flood cooling in 36 which the jet of coolant is directed toward the cutting 37zone. Here, the coolant is deployed in large quantities. 38There are several disadvantages to using this method. 39The first one has to do with the cost of machining 40 and its disposal. Approximately fifteen percent of to-41 tal cost in machining is incurred by the coolant and 42 its disposal. The second one deals with a safety issue 43 for the operators. One problem that exists for opera-44 tors is that when they stay in contact with the coolant 45 for a long time, it may cause skin problems. The third 46 one is the effect on the environment. After machin-47

This study presents conducted heat simulations and experimental jointing flat-plate of aluminum alloy 6061 and SUS 304. Temperature is simulated by the COMSOL software in three states: (1) Preheat the Friction Stir Welding (FSW) by TIG welding, (2) Thermal contact resistance between Aluminium and steel, and (3) The welding process using stiring friction is simulated. The simulations intended to predicting the temperature which is used for preheat and welding process to ensuring the required solid-state welding. The temperature is also determined and checked by a thermal imager comparing with simulation results. Besides, the results of tensile strength is carried out. The Box - Behnken method is used to identify the relationship between the welding parameters (rotation, speed and offset), temperature and tensile strength. The maximum tensile strength is 77% compared to the strength of aluminum alloy. The optimal set of parameters for the process is n = 676 rpm, v = 46 mm / min and x = 0.6 mm. The optimizing welding parameters to achieving good quality of welding process are described. SEM images to determine some properties of welding materials. This is also the basis for initial research to identify some defects in welding of two different materials (IMC thickness and interconnected pores) and the cause of these defects.

Friction stir welding exploits its solid-state process behavior to join aluminum to steel, which differs in thermal and mechanical properties, and where a combination of these metallic alloys by fusion welding prompts a deleterious reaction as a result of the melting and resolidification phases. Recently, hybrid techniques have been employed in FSW for several materials and alloys, particularly for steel–steel joining. These methods are generally aimed to pre-heat the steel plate materials. This study presents conducted heat simulations and experimental jointing flat-plate of aluminum alloy 6061 and SUS 304. Temperature is simulated by the COMSOL software in three states: (1) Preheat the Friction Stir Welding (FSW) by TIG welding, (2) Thermal contact resistance between aluminum and steel, and (3) The welding process using stirring friction is simulated. The simulations intended to predict the temperature, which is used for the preheating and welding process to ensuring the required solid-state welding. The temperature is also determined and checked by a thermal imager comparing with simulation results. Besides, the results of tensile strength are carried out. The Box - Behnken method is used to identify the relationship between the welding parameters (rotation, speed, and offset), temperature, and tensile strength. The maximum tensile strength is 77% compared to the strength of the aluminum alloy. The optimal set of parameters for the process is n = 676 rpm, v = 46 mm / min and x = 0.6 mm. The optimizing welding parameters to achieving a good quality of the welding process are described. SEM images to determine some properties of welding materials. This is also the basis for initial research to identify some defects in the welding of two different materials (IMC thickness and interconnected pores) and the cause of these defects.

This paper presents a prediction of cutting temperature in turning process, using a continuous cutting model of Johnson-Cook (J-C). An method to predict the temperature distribution in orthogonal cutting is based on the constituent model of various material and the mechanics of their cutting process. In this method, the average temperature at the primary shear zone (PSZ) and the secondary shear zone (SSZ) were determined for various materials, based on a constitutive model and a chip-formation model using measurements of cutting force and chip thicknes. The J-C model constants were taken from Hopkinson pressure bar tests. Cutting conditions, cutting forces and chip thickness were used to predict shear stress. Experimental cutting heat results with the same cutting parameters using the minimum lubrication method (MQL) were recorded through the Testo-871 thermal camera. The thermal distribution results between the two methods has a difference in value, as well as distribution. From the difference, we have analyzed some of the causes, finding the effect of the minimum quantity lubrication parameters on the difference.