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Shubham Sharma
Department of Mechanical Engineering, I.K. Gujral Punjab Technical University, Main Campus-Kapurthala, Punjab 144603, India

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Journal article
Published: 19 June 2021 in Metals
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The Activated Tungsten Inert Gas welding (A-TIG) technique is characterized by its capability to impart enhanced penetration in single pass welding. Weld bead shape achieved by A-TIG welding has a major part in deciding the final quality of the weld. Various machining variables influence the weld bead shape and hence an optimum combination of machining variables is of utmost importance. The current study has reported the optimization of machining variables of A-TIG welding technique by integrating Response Surface Methodology (RSM) with an innovative Heat Transfer Search (HTS) optimization algorithm, particularly for attaining full penetration in 6 mm thick carbon steels. Welding current, length of the arc and torch travel speed were selected as input process parameters, whereas penetration depth, depth-to-width ratio, heat input and width of the heat-affected zone were considered as output variables for the investigations. Using the experimental data, statistical models were generated for the response characteristics. Four different case studies, simulating the real-time fabrication problem, were considered and the optimization was carried out using HTS. Validation tests were also carried out for these case studies and 3D surface plots were generated to confirm the effectiveness of the HTS algorithm. It was found that the HTS algorithm effectively optimized the process parameters and negligible errors were observed when predicted and experimental values compared. HTS algorithm is a parameter-less optimization technique and hence it is easy to implement with higher effectiveness.

ACS Style

Jay Vora; Vivek Patel; Seshasai Srinivasan; Rakesh Chaudhari; Danil Pimenov; Khaled Giasin; Shubham Sharma. Optimization of Activated Tungsten Inert Gas Welding Process Parameters Using Heat Transfer Search Algorithm: With Experimental Validation Using Case Studies. Metals 2021, 11, 981 .

AMA Style

Jay Vora, Vivek Patel, Seshasai Srinivasan, Rakesh Chaudhari, Danil Pimenov, Khaled Giasin, Shubham Sharma. Optimization of Activated Tungsten Inert Gas Welding Process Parameters Using Heat Transfer Search Algorithm: With Experimental Validation Using Case Studies. Metals. 2021; 11 (6):981.

Chicago/Turabian Style

Jay Vora; Vivek Patel; Seshasai Srinivasan; Rakesh Chaudhari; Danil Pimenov; Khaled Giasin; Shubham Sharma. 2021. "Optimization of Activated Tungsten Inert Gas Welding Process Parameters Using Heat Transfer Search Algorithm: With Experimental Validation Using Case Studies." Metals 11, no. 6: 981.

Journal article
Published: 10 June 2021 in Applied Sciences
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Dumpers or dump trucks are used all over the world to move overburden from many opencast mines. Diesel engines are the main driving force behind the trucks. The frequency of damage due to the failure of diesel engines is enormous. Therefore, efforts are necessary to analyze failure to reduce the downtime periods. A detailed analysis of engine failure at the subsystem level needs to be done. Reliability analysis and maintenance planning remain the norm in this regard. The obstacle faced while analysing the reliability of dumpers was the availability of a large number of data failures. In this paper, this issue is addressed by using Common Beta Hypothesis test and Meta-analysis test. The engine is divided into five subsystems. The result shows that all five subsystems pass the CBH test and Meta-analysis test. Accordingly, the failure data is grouped. The trend test of grouped failure data shows that the Failure data of two subsystems follows the independent and identically distributed characteristics while the remaining three do not follow it. The reliability is estimated for all five subsystems. Finally, fuel supply subsystems show the highest reliability while the lowest value is seen for self-starting subsystems.

ACS Style

BrajeshKumar Dinkar; Alok Mukhopadhyay; Somnath Chattopadhyaya; Shubham Sharma; Firoz Alam; José Machado. Statistical Reliability Assessment for Small Sample of Failure Data of Dumper Diesel Engines Based on Power Law Process and Maximum Likelihood Estimation. Applied Sciences 2021, 11, 5387 .

AMA Style

BrajeshKumar Dinkar, Alok Mukhopadhyay, Somnath Chattopadhyaya, Shubham Sharma, Firoz Alam, José Machado. Statistical Reliability Assessment for Small Sample of Failure Data of Dumper Diesel Engines Based on Power Law Process and Maximum Likelihood Estimation. Applied Sciences. 2021; 11 (12):5387.

Chicago/Turabian Style

BrajeshKumar Dinkar; Alok Mukhopadhyay; Somnath Chattopadhyaya; Shubham Sharma; Firoz Alam; José Machado. 2021. "Statistical Reliability Assessment for Small Sample of Failure Data of Dumper Diesel Engines Based on Power Law Process and Maximum Likelihood Estimation." Applied Sciences 11, no. 12: 5387.

Journal article
Published: 07 December 2020 in Metals
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The hardened tool steel AISI O1 has increased strength, hardness, and wear resistance, which affects the complexity of the machining process. AISI O1 has also been classified as difficult to cut material hence optimum cutting parameters are required for the sustainable machining of the alloy. In this work, the effect of feed peer tooth (fz), cutting speed (vc), cutting of depth (ap) on surface roughness (Ra, Rt), cutting force (Fx, Fy), cutting power (Pc), machining cost (Ci), and carbon dioxide (Ene) were investigated during the slot milling process of AISI O1 hardened steel. A regression analysis was carried out on the obtained experimental results and the induction of nonlinear mathematical equations of surface roughness, cutting force, cutting power, and machining cost with a high coefficient of determination (R2 = 90.62–98.74%) were deduced. A sustainability assessment model is obtained for optimal and stable levels of design variables when slot milling AISI O1 tool steel. Stable indicators to ensure personal health and safety of operation, P1 values were set to “1” at a cutting speed of 20 m/min or 43.3 m/min and “2” at a cutting speed of 66.7 m/min or 90 m/min. It is revealed that for eco-benign machining of AISI O1, the optimum parameters of 0.01 mm/tooth, 20 m/min, and 0.1 mm should be adopted for feed rate, cutting speed, and depth of cut respectively.

ACS Style

Angelos P. Markopoulos; Nikolaos E. Karkalos; Mozammel Mia; Danil Yurievich Pimenov; Munish Kumar Gupta; Hussein Hegab; Navneet Khanna; Vincent Aizebeoje Balogun; Shubham Sharma. Sustainability Assessment, Investigations, and Modelling of Slot Milling Characteristics in Eco-Benign Machining of Hardened Steel. Metals 2020, 10, 1650 .

AMA Style

Angelos P. Markopoulos, Nikolaos E. Karkalos, Mozammel Mia, Danil Yurievich Pimenov, Munish Kumar Gupta, Hussein Hegab, Navneet Khanna, Vincent Aizebeoje Balogun, Shubham Sharma. Sustainability Assessment, Investigations, and Modelling of Slot Milling Characteristics in Eco-Benign Machining of Hardened Steel. Metals. 2020; 10 (12):1650.

Chicago/Turabian Style

Angelos P. Markopoulos; Nikolaos E. Karkalos; Mozammel Mia; Danil Yurievich Pimenov; Munish Kumar Gupta; Hussein Hegab; Navneet Khanna; Vincent Aizebeoje Balogun; Shubham Sharma. 2020. "Sustainability Assessment, Investigations, and Modelling of Slot Milling Characteristics in Eco-Benign Machining of Hardened Steel." Metals 10, no. 12: 1650.