Enhancing Machining performance in Stainless Steel Machining using MXene Coolant: A Detailed Examination

Metal cutting, a complex process in manufacturing, involves various factors that significantly affect the quality of the final product. Notably, the turning process is crucial, with outcomes that heavily depend on multiple machining parameters. These parameters encompass speed, depth of cut, feed rate, the type of coolant used (specifically, high heat transfer MXene coolant), and insert types, among others. The material of the workpiece is also a critical factor in the metal-cutting operation. This study focuses on achieving optimal surface quality and minimizing cutting forces in the turning process. It recognizes the substantial impact of numerous process parameters, directly or indirectly affecting the product's surface roughness and cutting forces. Understanding these optimal parameters can lower machining costs and improve product quality. Our research concentrates on turning a stainless-steel alloy workpiece using a carbide insert tool. We employ the Response Surface Method (RSM) to optimize cutting parameters within a set range of cutting speed (100, 125, 150 m/min), feed rate (0.1, 0.2, 0.3 mm/rev), and depth of cut (0.4, 0.8, 1.2 mm). Additionally, we use various tool geometries and the RSM design of experiments to enhance and analyze the multi-response parameters of surface roughness and tool life. Optimal machining parameters for MXene-NFC involve a cutting speed of 140 m/min, a feed rate of 0.05 mm/rev, and a depth of cut of 0.5 mm. These settings ensure minimal surface roughness, maximum tool life, and the greatest total length of cut, achieving a composite desirability of 0.695

Global prevalence and genotype distribution of hepatitis C virus infection in 2015 : A modelling study

Publisher Copyright: © 2017 Elsevier LtdBackground The 69th World Health Assembly approved the Global Health Sector Strategy to eliminate hepatitis C virus (HCV) infection by 2030, which can become a reality with the recent launch of direct acting antiviral therapies. Reliable disease burden estimates are required for national strategies. This analysis estimates the global prevalence of viraemic HCV at the end of 2015, an update of—and expansion on—the 2014 analysis, which reported 80 million (95% CI 64–103) viraemic infections in 2013. Methods We developed country-level disease burden models following a systematic review of HCV prevalence (number of studies, n=6754) and genotype (n=11 342) studies published after 2013. A Delphi process was used to gain country expert consensus and validate inputs. Published estimates alone were used for countries where expert panel meetings could not be scheduled. Global prevalence was estimated using regional averages for countries without data. Findings Models were built for 100 countries, 59 of which were approved by country experts, with the remaining 41 estimated using published data alone. The remaining countries had insufficient data to create a model. The global prevalence of viraemic HCV is estimated to be 1·0% (95% uncertainty interval 0·8–1·1) in 2015, corresponding to 71·1 million (62·5–79·4) viraemic infections. Genotypes 1 and 3 were the most common cause of infections (44% and 25%, respectively). Interpretation The global estimate of viraemic infections is lower than previous estimates, largely due to more recent (lower) prevalence estimates in Africa. Additionally, increased mortality due to liver-related causes and an ageing population may have contributed to a reduction in infections. Funding John C Martin Foundation.publishersversionPeer reviewe

Timing of surgery following SARS-CoV-2 infection: an international prospective cohort study.

Peri-operative SARS-CoV-2 infection increases postoperative mortality. The aim of this study was to determine the optimal duration of planned delay before surgery in patients who have had SARS-CoV-2 infection. This international, multicentre, prospective cohort study included patients undergoing elective or emergency surgery during October 2020. Surgical patients with pre-operative SARS-CoV-2 infection were compared with those without previous SARS-CoV-2 infection. The primary outcome measure was 30-day postoperative mortality. Logistic regression models were used to calculate adjusted 30-day mortality rates stratified by time from diagnosis of SARS-CoV-2 infection to surgery. Among 140,231 patients (116 countries), 3127 patients (2.2%) had a pre-operative SARS-CoV-2 diagnosis. Adjusted 30-day mortality in patients without SARS-CoV-2 infection was 1.5% (95%CI 1.4-1.5). In patients with a pre-operative SARS-CoV-2 diagnosis, mortality was increased in patients having surgery within 0-2 weeks, 3-4 weeks and 5-6 weeks of the diagnosis (odds ratio (95%CI) 4.1 (3.3-4.8), 3.9 (2.6-5.1) and 3.6 (2.0-5.2), respectively). Surgery performed ≥ 7 weeks after SARS-CoV-2 diagnosis was associated with a similar mortality risk to baseline (odds ratio (95%CI) 1.5 (0.9-2.1)). After a ≥ 7 week delay in undertaking surgery following SARS-CoV-2 infection, patients with ongoing symptoms had a higher mortality than patients whose symptoms had resolved or who had been asymptomatic (6.0% (95%CI 3.2-8.7) vs. 2.4% (95%CI 1.4-3.4) vs. 1.3% (95%CI 0.6-2.0), respectively). Where possible, surgery should be delayed for at least 7 weeks following SARS-CoV-2 infection. Patients with ongoing symptoms ≥ 7 weeks from diagnosis may benefit from further delay

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Error compensation of complex three-dimensional surfaces machined on computer-numeric-control grinding machine tools

This study discusses the development of a method for compensating profile errors, resulting from the deviation of the actual grinding wheel radius from the calculated one. The study also elaborates on a control strategy that may be followed to minimise the profile error and allow the use of a four-axis grinding machine instead of five-axis one to perform the same machining task. This approach can be completely justified when the reduction in the machining cost is achieved as a result of grinding the gauge profile on a four-axis CNC machine tool instead of the five-axis one. When a number of five segments are chosen, the first control program is established for the first mean radius (170 mm) of the first segment. When the grinding wheel radius reaches 150 mm as a result of wheel dressing, a new control program that will consider a new nominal radius of 160 mm will be activated. © 2009 Asian Network for Scientific Information

Fourth order torque prediction model in end milling

This study presents the development of mathematical models for torque in end-milling of AISI 618. Response Surface Method (RSM) was used to predict the effect of torque in the end-milling. The relationship between the manufacturing process factors including the cutting speed, feed rate, axial depth and radial depth with the torque can be developed. The effect of the factors can be investigated from the equation developed for first order to fourth order model. The acquired results show that the torque increases with decreases of the cutting speed and increases the feed rate, axial depth and radial depth. It found that the second order is more accurate based on the analysis of variance (ANOVA) and the predicted torque results is closely match with the experimental results. Third- and fourth-order model generated for the response to investigate the 3 and 4-way interaction between the factors. It’s found less significant for the variables

Cutting force prediction model by FEA and RSM when machining Hastelloy C-22HS with 90° holder

421-427Finite element (FEA) method and response surface method (RSM) are used to find the effect of milling parameters (cutting speed, feed rate and axial depth) on cutting force when milling Hastelloy C-22HS. Based on variance analyses of First- and Second-Order RSM models, most influential design variable is feed rate. Optimized cutting force values are subsequently obtained from model equations. FEA model shows distribution of cutting force

Tool wear analysis in end milling of advanced ceramics with TiAlN and TiN coated carbide inserts

Advanced ceramic materials are difficult to machine by conventional methods due to the brittle nature and high hardness. The appropriate selection of cutting tool and cutting conditions may help to improve machinability by endmilling. Performance of TiAlN and TiN coated carbide tool insert in end milling of machinable glass ceramic has been investigated. Several dry cutting tests were performed to select the optimum cutting parameters for the endmilling in order to obtain better tool life. In this work, a study was carried out on the influence of cutting speed, feed rate and axial depth of cut on tool wear. The technique of design of experiments (DOE) was used for the planning and analysis of the experiments. Tool wear prediction model was developed using Response surface methodology. The results indicate that tool wear increased with increasing the cutting speed and axial depth of cut. Effect of feed rate is not much significant on selected range of cutting condition

Surface roughness prediction model of 6061-T6 aluminium alloy machining using statistical method

This paper explores on the optimization of the surface roughness of milling mould 6061-T6 aluminium alloys with carbide coated inserts. Optimization of the milling is very important to reduce the cost and time for machining mould. The purposes of this study are to develop the predicting model of surface roughness, to investigate the most dominant variables among the cutting speed, feed rate, axial depth and radial depth and to optimize Surface Roughness Prediction Model of 6061-T6 Aluminium Alloy Machining Using Statistical Method the parameters. Response surface method based optimization approach was used in this study. It can be seen from the first order model that the feed rate is the most significantly influencing factor for the surface roughness. Second-order model reveals that there is no interaction between the variables and response