Optimization of Cutting Performance Using Vegetable Oil in Drilling of AA 6082 T6 by Minimum Quantity Lubrication

Industries were facing crucial problems on disposal of used lubricants who caused environmental pollution directly as well as indirectly. Also, surface quality was seen at lower rate using flood lubrication. The drilling process generates large energy and most of the energy is converted to heat. The intense heat affects the mechanical properties of the work material and the drill. Conventional coolants are used to control the heat and carry away the chips formed. The major aim of this study is to optimize the machining parameters using mustard oil as a MQL coolant (10ml/h mixing of oil with compressed air) and experiments were carried out with aluminium alloy 6082 T6 which possess high thermal conductivity. Later, Taguchi method was used in small number of experiments to study the parameters, using orthogonal arrays derived from the design of experiments theory. Process parameters were used for this study such as cutting tool (T), feed rate (F) and Speed (N). The performance characteristics were measured, which are surface roughness (S) and kerf angle (Ka). ANOVA is used to find the most influencing factor in drilling. In this study, results include the most contribution factor i.e., cutting tool which contributes 89.3% followed by feed rate of 6.73% and spindle speed 2.10 %. Conformation test has been carried out for improving grey relational analysis by 10.15%. In addition to that surface of chips were examined at machining region under scanning electron microscope (SEM)

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability