Multi-objective optimization of energy consumption and surface quality in nanofluid SQCL assisted face milling

Considering the significance of improving the energy efficiency, surface quality and material removal quantity of machining processes, the present study is conducted in the form of an experimental investigation and a multi-objective optimization. The experiments were conducted by face milling AISI 1045 steel on a Computer Numerical Controlled (CNC) milling machine using a carbide cutting tool. The Cu-nano-fluid, dispersed in distilled water, was impinged in small quantity cooling lubrication (SQCL) spray applied to the cutting zone. The data of surface roughness and active cutting energy were measured while the material removal rate was calculated. A multi-objective optimization was performed by the integration of the Taguchi method, Grey Relational Analysis (GRA), and the Non-Dominated Sorting Genetic Algorithm (NSGA-II). The optimum results calculated were a cutting speed of 1200 rev/min, a feed rate of 320 mm/min, a depth of cut of 0.5 mm, and a width of cut of 15 mm. It was also endowed with a 20.7% reduction in energy consumption. Furthermore, the use of SQCL promoted sustainable manufacturing. The novelty of the work is in reducing energy consumption under nano fluid assisted machining while paying adequate attention to material removal quantity and the product’s surface quality

Multi-response optimisation of machining aluminium-6061 under eco-friendly electrostatic minimum quantity lubrication environment

The emerging grave consequences of conventional coolants on health, ecology and product quality, have pushed the scientific research to explore eco-friendly lubrication technique. Electrostatic minimum quantity lubrication (EMQL) has been underscored as a burgeoning technology to cut-down bete noire impacts in machining. This research confers the adoption of a negatively charged cold mist of air-castor oil employed in turning of aluminium-6061T6 material by varying the cutting conditions, as per experimental designed through response surface methodology (RSM). For comprehensive sagacity, a range of cutting speed, feed, depth of cut and EMQL-flow rate were considered. Material removal rate, tool life, surface roughness and power consumption of machine tool were adopted as performance measures. To satisfy multi-criterion simultaneously, RSM-based grey relational analysis (GRA) was employed for multi-objective optimisation. Highest proportion of grey relational grade (GRG) as a single desideratum response function, provided a trade-off between performance measures with 15.56% improvement in GRG

Taguchi-based GRA for parametric optimization in turning of AISI L6 tool steel under cryogenic cooling

Cutting fluids have frequent use in industrial sector to improve the machinability. Due to the negative impact on our ecology, recent focus has shifted to explore some environment-friendly cooling techniques such as cryogenic cooling. Cryogenic cooling involving liquid nitrogen is one of the alternative techniques which improves the efficiency of the machining process and is environmentally friendly as well. In current work, cutting parameters in turning such as cutting speed and feed rate were optimized under cryogenic cooling for machining of AISI L6 tool steel which is difficult to cut material. The output parameters under consideration are surface roughness, cutting energy, tool wear and Material Removal Rate (MRR). The optimization for multi-responses was carried out through Taguchi based Grey Relational Analysis (GRA). For experimental design, tests were based on L9 orthogonal array. According to the GRA optimization results, optimum cutting speed level was 160 m/min and the feed rate was 0.16 mm/rev. The percentage improvement in Grey Relational Grade (GRG) was calculated as 19.07%, thus showing the advantage of using the GRA

Sustainable manufacturing and parametric analysis of mild steel grade 60 by deploying CNC milling machine and Taguchi method

Design and manufacturing are the key steps in the sustainable manufacturing of any product to be produced. Within the perspective of injection molds production, increased competitiveness and repeated changes in the design require a complete optimized manufacturing process. Local and minor improvements in the milling process do not generally lead to an optimized manufacturing process. The goal of the new geometry and parametric analysis of the mould is to reduce the quality issues in mild steel grade 60. In this explicit research, the surface roughness (smoothness) of indigenously produced injection moulds in the local market in Pakistan is investigated. The CNC milling machine (five-axis) is used for the manufacturing of an injection mould, and the Taguchi method of the design of the experiment is applied for parameters optimization. Hence, the overall process is assisted in balancing the milling machine parameters to trim down the surface roughness issue in mild steel moulds and increase their sustainability. The spindle speed (rpm), the depth of cut (mm), and the feed rate (mm/rev) are considered as input variables for process optimization, and the experiments are performed on mild steel grade 60. It is deduced that the combination of a spindle speed of 800 rpm, feed rate of 10 mm/rev and depth of cut of 0.5 mm is the best case in case of minimum surface roughness, which leads to sustainable products. It is also deduced from ANOVA, that the spindle speed is a factor that affects the surface roughness of mild steel products, while the feed rate turns out to be insignificant

Internal cracks and non-metallic inclusions as root causes of casting failure in sugar mill roller shafts

The sugar mill roller shaft is one of the critical parts of the sugar industry. It requires careful manufacturing and testing in order to meet the stringent specification when it is used for applications under continuous fatigue and wear environments. For heavy industry, the manufacturing of such heavy parts (>600 mm diameter) is a challenge, owing to ease of occurrence of surface/subsurface cracks and inclusions that lead to the rejection of the final product. Therefore, the identification and continuous reduction of defects are inevitable tasks. If the defect activity is controlled, this offers the possibility to extend the component (sugar mill roller) life cycle and resistance to failure. The current study aims to explore the benefits of using ultrasonic testing (UT) to avoid the rejection of the shaft in heavy industry. This study performed a rigorous evaluation of defects through destructive and nondestructive quality checks in order to detect the causes and effects of rejection. The results gathered in this study depict macro-surface cracks and sub-surface microcracks. The results also found alumina and oxide type non-metallic inclusions, which led to surface/subsurface cracks and ultimately the rejection of the mill roller shaft. A root cause analysis (RCA) approach highlighted the refractory lining, the hot-top of the furnace and the ladle as significant causes of inclusions. The low-quality flux and refractory lining material of the furnace and the hot-top, which were possible causes of rejection, were replaced by standard materials with better quality, applied by their standardized procedure, to prevent this problem in future production. The feedback statistics, evaluated over more than one year, indicated that the rejection rate was reduced for defective production by up to 7.6%

Energy-Based Novel Quantifiable Sustainability Value Assessment Method for Machining Processes

Sustainability assessments of cooling/lubrication-assisted advanced machining processes has been demanded by environment control agencies because it is an effective management tool for improving process sustainability. To achieve an effective and efficient sustainability evolution of machining processes, there is a need to develop a new method that can incorporate qualitative indicators to create a quantifiable value. In the present research work, a novel quantifiable sustainability value assessment method was proposed to provide performance quantification of the existing sustainability assessment methods. The proposed method consists of three steps: establishing sustainable guidelines and identifying new indicators, data acquisition, and developing an algorithm, which creates the Overall Performance Assessment Indicator (OPAI) from the sustainability assessment method. In the proposed algorithm, initially, both quantitative and qualitative sustainability indicators are normalized. After weight assignment and aggregation, the OPAI is obtained. The developed algorithm was validated from three literature case studies, and optimal cutting parameters were obtained. The present methodology provides effective guidelines for a machinist to enhance process performance and achieve process optimization. The study also offers a relationship between sustainable and machining metrics for the support of industrial sustainability

Investigation on Machinability Characteristics of Inconel 718 Alloy in Cryogenic Machining Processes

In this innovative work, Inconel 718 alloy turning simulation models under dry and cryogenic machining (Cryo) conditions are developed. The machinability characteristics of the aforementioned alloy were assessed with relation to cutting temperature (Tct) and cutting force (Fcf). The comparison of the Tct and Fcf results from simulation with those obtained under the identical experimental conditions served as additional evidence of the effectiveness of the suggested simulation model. By varying the cutting speed, the reduction in Tct under Cryo conditions was 9.36% to 11.98% compared to dry cutting. Regarding the force comparison under experiment and simulation, the average difference between the simulation and experimental values for the main cutting force (Fc) was 13.73%, whereas the average deviation for the feed force (Ff) was 14.63%. Response surface methodology (RSM) was employed to build the forecasting models for Tct and Fcf in cryogenic settings. These mathematical models showed excellent predictive performance and were able to estimate the Tct and Fcf under machining operations settings, according to the present research. When compared to dry cutting, Cryo reduced the cutting temperature, which had a positive impact on the alloy’s machinability

An experimental investigation on Cryo-LN2 turning of hardened steel: a sustainability assessment

To achieve an excellent workpiece surface quality and long tool life in machining of hardened steel is an inordinate challenge. Recently, conventional flood cooling assisted machining processes are used to address this problem. However, such proposed processes have adverse effects on the environment as well as on the machine shop worker’s health. Hence, in this study, the effects of traditionally used flood cooling and sustainable Cryo-LN2 techniques on the six machining indices, such as surface roughness, cutting power, energy consumption, tool life, tool wear, and productivity in the external turning of AISI-52100 have been investigated. Comparative results showed that Cryo-LN2 technique outperformed flood cooling for all measured indices. The Cryo-LN2 assisted turning process yielded 18% less energy consumption and 66% more productivity. The findings of the current study encourage metal processing industries to use such type of sustainable techniques in the machine shop

A Comparative Study of Face Milling of D2 Steel Using Al2O3 Based Nanofluid Minimum Quantity Lubrication and Minimum Quantity Lubrication

This study aims to investigate the effects of process parameters feed, depth of cut and flow rate, on the temperature during face milling of the D2 tool steel under two different lubricant conditions, Minimum Quantity Lubrication (MQL) and Nanofluid Minimum Quantity Lubrication (NFMQL). Distilled water with the flow rate range 200-400 ml/hr was used in MQL. 2% by weight concentration of Al2O3 nanoparticles with distilled water as the base fluid used as NFMQL with same flow rate. Response surface methodology RSM central composite design CCD was used to design experiment run, modeling, and analysis. ANOVA was used for the adequacy and validation of the system. The comparison shows that NFMQL condition reduced more temperature during machining

An Ultrasonic-Based Detection of Air-Leakage for the Unclosed Components of Aircraft

Air-leakage detection is among the most important processes at the assembly stage of unclosed components, especially for large aircraft. A series of air-leakage detecting methods are generally applied during the final assembly, nevertheless, many of them are less effective to detect the leakage at the assembly stage. The present study aims to discuss the principles of ultrasonic generation in negative pressure conditions to detect the air-leakage. An ultrasonic-based detection method is proposed and designed to detect the air-leakage of unclosed components for aircraft. A relationship between the acoustic power, sound pressure, and the leak aperture detection distance was identified and discussed. A leakage rate model related to leakage rate, leak aperture, and system pressure was implemented and confirmed through experiments. Findings have indicated that the air-leakage can be detected effectively within a detection distance of 0.8 m and a leak aperture greater or equal to 0.4 mm with this method. Besides, the leak location, leak aperture, and leakage rate was acquired in an accurate and fast way. It is an effective method of detecting the air-leakage of unclosed components at the aircraft assembly stage reducing the testing time, energy consumption, and cost for the air-leakage detection in the final assembly stage of large aircraft