Monitoring of Cutting Process and Tool Condition of Metal and Metal Composite.

Machining is a manufacturing process that involves the use of machines to remove materials from a workpiece to create a desired shape and size [...].

Evaluation of the Relationship between Baseline Autonomic Tone and Haemodynamic Effects of Dexmedetomidine.

Dexmedetomidine, a central α-2 agonist, is used for procedural sedation and for conscious sedation influences on heart rate and blood pressure. Authors verified whether it is possible to predict bradycardia and hypotension with the use of heart rate variability (HRV) analysis for an autonomic nervous system (ANS) activity assessment. The study included adult patients of both sexes with an ASA score of I or II scheduled for ophthalmic surgery to be performed under sedation. The loading dose of dexmedetomidine was followed by a 15 min infusion of the maintenance dose. The frequency domain heart rate variability parameters from the 5-min Holter electrocardiogram recordings before dexmedetomidine administration were used for the analysis. The statistical analysis also included pre-drug heart rate and blood pressure as well as patient age and sex. The data from 62 patients were analysed. There was no relationship between the decrease in heart rate (42% of cases) and initial HRV parameters, haemodynamic parameters or sex and age of patients. In multivariate analysis, the only risk factor for a decrease in mean arterial pressure (MAP) > 15% from the pre-drug value (39% of cases) was the systolic blood pressure before dexmedetomidine administration as well as for a >15% decrease in MAP sustained at more than one consecutive time point (27% of cases). The initial condition of the ANS did not correlate with the incidence of bradycardia or hypotension; HRV analysis was not helpful in predicting the abovementioned side effects of dexmedetomidine.

Metrological Aspects of Assessing Surface Topography and Machining Accuracy in Diagnostics of Grinding Processes.

The paper presents probabilistic aspects of diagnostics of grinding processes with consideration of metrological aspects of evaluation of topography of machined surfaces and selected problems of assessment of machining accuracy. The processes of creating the geometric structure of the ground surface are described. It was pointed out that the distribution of features important for process diagnostics depends on the mechanism of cumulative effects of random disturbances. Usually, there is a multiplicative mechanism or an additive mechanism of the component vectors of relative displacements of the tool and workpiece. The paper describes a method for determining the classification ability of specific parameters used to evaluate stereometric features of ground surfaces. It is shown that the ability to differentiate the geometric structure of a certain set of surfaces using a selected parameter depends on the geometric mean of the differences in normalized and sorted, consecutive values of this parameter. A methodology is presented for evaluating the ability of various parameters to distinguish different geometric structures of surfaces. Further, on the basis of analyses of a number of grinding processes, a methodology was formulated for proceeding leading to a comprehensive evaluation of machining accuracy and forecasting its results. It was taken into account that in forecasting the accuracy of grinding, it is necessary to determine the deviations, arising under the conditions of multiplicative interaction of the effects of various causes of inaccuracy. Examples are given of processes in which, due to the deformation of the technological system, dependent on the position of the zone and machining force, varying temperature fields and tool wear, the distributions of dimensional deviations are not the realization of stationary processes. It was emphasized that on the basis of the characteristics of the dispersion of the deviation value in the sum set of elements, it is not possible to infer its causes. Only the determination of the "instantaneous" values of the deviation dispersion parameters allows a more complete diagnosis of the process.

Technological Aspects of Variation in Process Characteristics and Tool Condition in Grinding Process Diagnostics.

The article presents the technological aspects of the diagnostics of grinding processes. The main features of the grinding process and their importance in diagnostic issues are discussed. Selected issues of research and assessment of the condition of the active surface of grinding wheels are presented. The authors pointed out that the parameters used to assess the topography of the ground surfaces do not have sufficient possibilities to differentiate the surface condition of the grinding wheels. This publication draws attention to the possibility of using new dedicated parameters to assess the properties of the grinding wheel surface. These parameters have a high ability to differentiate changes occurring as a result of the abrasion of grain vertices, their chipping or loading of the grinding wheel surface. The methodology of assessing the processes of abrasive grain wear and changes in the shape and dimensions of the grinding wheel, taking into account the probabilistic features of the grinding process, was formulated. The directions for the development of abrasive tools are presented, pointing to hybrid tools with a multi-phase structure, modified by additions of abrasive aggregates. A new research direction has also been formulated on the use of additive technology to produce specialised abrasive tools, including those with built-in process sensors.

Prediction of the Occurrence of the Oculocardiac Reflex Based on the Assessment of Heart Rate Variability. An Observational Study.

INTRODUCTION: Ophthalmic surgery is assumed to be safe, but some operations require general anaesthesia which is associated with a number of potential complications. In addition, adverse cardiovascular symptoms, such as severe slowing of the heart rate and, in some cases, cardiac arrest may occur due to the surgical technique. The aim of this study was to determine whether it is possible to predict the occurrence of oculocardiac reflex (OCR) based on heart rate variability (HRV) analysis for autonomic nervous system (ANS) activity assessment measured prior to the induction of anaesthesia and immediately before eyeball traction. METHODS: Fifty-two adults of both sexes (age range 18-65 years) with American Society of Anesthesiologists (ASA) physical status class 1 and 2 were enrolled in this study. All patients had underwent episcleral buckling under general anaesthesia. High-frequency (HF) changes in HRV are thought to reflect parasympathetic impulse transmission, whereas low-frequency (LF) changes reflect both sympathetic and parasympathetic activity. However, in practice, LF changes can be considered to reflect sympathetic changes. Thus, the LF/HF ratio reflects the actual balance between sympathetic and parasympathetic activity. Based on that, frequency domain HRV parameters from 5-min Holter electrocardiogram recordings before anaesthesia induction and before eyeball traction were used for the analysis. The statistical analysis also included patient age, sex, ASA status and preanaesthesia and premanoeuvre heart rate and blood pressure. RESULTS: Data from 42 patients were analysed. Oculocardiac reflex was observed in 32 patients (76.2%). No difference was found in the analysed parameters between patients with and without oculocardiac reflex. There was no relationship between the incidence of the OCR and the analysed parameters. CONCLUSION: The prediction of OCR based on initial ANS tone was not possible, and the initial heart rate, blood pressure, age, sex, and ASA status were not helpful for the identification of patients at risk of this reflex. TRIAL REGISTRATION: ClinicalTrials.gov identifier no.: NCT01714362.

Machine Learning Approaches for Monitoring of Tool Wear during Grey Cast-Iron Turning.

The dynamic development of new technologies enables the optimal computer technique choice to improve the required quality in today's manufacturing industries. One of the methods of improving the determining process is machine learning. This paper compares different intelligent system methods to identify the tool wear during the turning of gray cast-iron EN-GJL-250 using carbide cutting inserts. During these studies, the experimental investigation was conducted with three various cutting speeds vc (216, 314, and 433 m/min) and the exact value of depth of cut ap and federate f. Furthermore, based on the vibration acceleration signals, appropriate measures were developed that were correlated with the tool condition. In this work, machine learning methods were used to predict tool condition; therefore, two tool classes were proposed, namely usable and unsuitable, and tool corner wear VBc = 0.3 mm was assumed as a wear criterium. The diagnostic measures based on acceleration vibration signals were selected as input to the models. Additionally, the assessment of significant features in the division into usable and unsuitable class was caried out. Finally, this study evaluated chosen methods (classification and regression tree, induced fuzzy rules, and artificial neural network) and selected the most effective model.

Intravenous Vitamin C in Adults with Sepsis in the Intensive Care Unit.

BACKGROUND: Studies that have evaluated the use of intravenous vitamin C in adults with sepsis who were receiving vasopressor therapy in the intensive care unit (ICU) have shown mixed results with respect to the risk of death and organ dysfunction. METHODS: In this randomized, placebo-controlled trial, we assigned adults who had been in the ICU for no longer than 24 hours, who had proven or suspected infection as the main diagnosis, and who were receiving a vasopressor to receive an infusion of either vitamin C (at a dose of 50 mg per kilogram of body weight) or matched placebo administered every 6 hours for up to 96 hours. The primary outcome was a composite of death or persistent organ dysfunction (defined by the use of vasopressors, invasive mechanical ventilation, or new renal-replacement therapy) on day 28. RESULTS: A total of 872 patients underwent randomization (435 to the vitamin C group and 437 to the control group). The primary outcome occurred in 191 of 429 patients (44.5%) in the vitamin C group and in 167 of 434 patients (38.5%) in the control group (risk ratio, 1.21; 95% confidence interval [CI], 1.04 to 1.40; P = 0.01). At 28 days, death had occurred in 152 of 429 patients (35.4%) in the vitamin C group and in 137 of 434 patients (31.6%) in the placebo group (risk ratio, 1.17; 95% CI, 0.98 to 1.40) and persistent organ dysfunction in 39 of 429 patients (9.1%) and 30 of 434 patients (6.9%), respectively (risk ratio, 1.30; 95% CI, 0.83 to 2.05). Findings were similar in the two groups regarding organ-dysfunction scores, biomarkers, 6-month survival, health-related quality of life, stage 3 acute kidney injury, and hypoglycemic episodes. In the vitamin C group, one patient had a severe hypoglycemic episode and another had a serious anaphylaxis event. CONCLUSIONS: In adults with sepsis receiving vasopressor therapy in the ICU, those who received intravenous vitamin C had a higher risk of death or persistent organ dysfunction at 28 days than those who received placebo. (Funded by the Lotte and John Hecht Memorial Foundation; LOVIT ClinicalTrials.gov number, NCT03680274.).

Lessening Organ Dysfunction With Vitamin C (LOVIT) Trial: Statistical Analysis Plan.

BACKGROUND: The LOVIT (Lessening Organ Dysfunction with Vitamin C) trial is a blinded multicenter randomized clinical trial comparing high-dose intravenous vitamin C to placebo in patients admitted to the intensive care unit with proven or suspected infection as the main diagnosis and receiving a vasopressor. OBJECTIVE: We aim to describe a prespecified statistical analysis plan (SAP) for the LOVIT trial prior to unblinding and locking of the trial database. METHODS: The SAP was designed by the LOVIT principal investigators and statisticians, and approved by the steering committee and coinvestigators. The SAP defines the primary and secondary outcomes, and describes the planned primary, secondary, and subgroup analyses. RESULTS: The SAP includes a draft participant flow diagram, tables, and planned figures. The primary outcome is a composite of mortality and persistent organ dysfunction (receipt of mechanical ventilation, vasopressors, or new renal replacement therapy) at 28 days, where day 1 is the day of randomization. All analyses will use a frequentist statistical framework. The analysis of the primary outcome will estimate the risk ratio and 95% CI in a generalized linear mixed model with binomial distribution and log link, with site as a random effect. We will perform a secondary analysis adjusting for prespecified baseline clinical variables. Subgroup analyses will include age, sex, frailty, severity of illness, Sepsis-3 definition of septic shock, baseline ascorbic acid level, and COVID-19 status. CONCLUSIONS: We have developed an SAP for the LOVIT trial and will adhere to it in the analysis phase. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/36261.

Experimental Investigation of Surface Roughness in Milling of DuralcanTM Composite.

In today's developing aircraft and automotive industry, extremely durable and wear-resistant materials, especially in high temperatures, are applied. Due to this practical approach, conventional materials have been superseded by composite materials. In recent years, the application of metal matrix composites has become evident in industry 4.0. A study has been performed to analyze the surface roughness of aluminum matrix composites named Duralcan® during end milling. Two roughness surface parameters have been selected: arithmetical mean roughness value Ra and mean roughness depth Rz regarding the variable cutting speed. Due to the classification of aluminum matrix composites as hard-to-cut materials concerning excessive tool wear, this paper describes the possibility of surface roughness prediction using machine learning algorithms. In order to find the best algorithm, Classification and Regression Tree (CART) and pattern recognition models based on artificial neural networks (ANN) have been compared. By following the obtained models, the experiment shows the effectiveness of roughness prediction based on verification models. Based on experimental research, the authors obtained the coefficient R2 for the CART model 0.91 and the mean square error for the model ANN 0.11.

Cutting Forces during Inconel 718 Orthogonal Turn-Milling.

Inconel 718 is a material often used in the aerospace and marine industries due to its properties and ability to work in harsh environments. However, its machining is difficult, and therefore methods are sought to facilitate this process. One of such methods is turn-milling. This paper presents the forces during orthogonal turn-milling of the Inconel 718 alloy. In this machining, both the side and the end edge are involved in the material removal, which causes the tool to be more loaded. The forces during turn-milling can be up to 50% higher than in the case of milling, which causes damage to the tool. Tool wear during machining has a significant impact on the values of the cutting force proportional coefficients. In the case of the tested material, it is important to take it into account when creating cutting force models.

Analysis of the Displacement of Thin-Walled Workpiece Using a High-Speed Camera during Peripheral Milling of Aluminum Alloys.

The paper presents the possibilities of a high-speed camera in recording displacements of thin-walled workpiece during milling made of aluminum alloys, which allowed for an analysis in which it was compared to other methods of testing the deflection of such elements. The tests were carried out during peripheral milling with constant cutting parameters. Deflection of thin-walled workpiece due to cutting forces was measured using a high-speed camera and a laser displacement sensor. Additionally, the experimental results were compared with the theoretical results obtained with the use of the finite element method. The research proved the effectiveness of the use of high-speed camera in diagnostics of thin-walled workpieces during milling with an accuracy of up to 11% compared to measurements made with a displacement laser sensor.

Tool Wear Prediction Based on Artificial Neural Network during Aluminum Matrix Composite Milling.

This article deals with the phenomenon of tool wear prediction in face milling of aluminum matrix composite materials (AMC), class as hard-to-cut materials. Artificial neural networks (ANN) are one of the tools used to predict tool wear or surface roughness in machining. Model development is applicable when regression models do not give satisfactory results. Because of their mechanical properties based on SiC or Al2O3 reinforcement, AMCs are applied in the automotive and aerospace industry. Due to these materials' abrasive nature, a three-edged end mill with diamond coating was selected to carry out milling tests. In this work, multilayer perceptron (MLP) models were used to predict the tool flank wear VBB and tool corner wear VBC during milling of AMC with 10% SiC content. The signals of vibration acceleration and cutting forces were selected as input to the network, and the tests were carried out with three cutting speeds. Based on the analysis of the developed models, the models with the best efficiency were selected, and the quality of wear prediction was assessed. The main criterion for evaluating the quality of the developed models was the mean square error (MSE) in order to compare measured and predicted value of tool wear.

Prediction of Tool Wear Using Artificial Neural Networks during Turning of Hardened Steel.

The ability to effectively predict tool wear during machining is an extremely important part of diagnostics that results in changing the tool at the relevant time. Effective assessment of the rate of tool wear increases the efficiency of the process and makes it possible to replace the tool before catastrophic wear occurs. In this context, the value of the effectiveness of predicting tool wear during turning of hardened steel using artificial neural networks, multilayer perceptron (MLP), was checked. Cutting forces and acceleration of mechanical vibrations were used to monitor the tool wear process. As a result of the analysis using artificial neural networks, the suitability of individual physical phenomena to the monitoring process was assessed.

Obesity Surgery and Anesthesiology Risks: a Review of Key Concepts and Related Physiology.

The obesity epidemic is swelling to epic proportions. Obese patients often suffer from a combination of hypertension, dyslipidemia, and type 2 diabetes mellitus (T2DM), also known as the "metabolic syndrome." The metabolic syndrome is an independent predictor of cardiac dysfunction and cardiovascular disease and a risk factor for perioperative morbidity and mortality. In this paper, we discuss the perioperative risk factors and the need for advanced care of obese patients needing general anesthesia for (bariatric) surgical procedures based on physiological principles.

The influence of epidural blockade on gut permeability in patients undergoing open surgical repair of abdominal aortic aneurysm.

BACKGROUND: Abdominal aortic clamping during aneurysm repair may cause a decrease in splanchnic blood flow and deterioration of gut barrier integrity. Epidural blocks have beneficial effects on vital organs during abdominal surgery, but sparse data are available on the influence on gut permeability during open aortic surgery. The aim of this study was to verify the hypothesis that epidural blocks may have beneficial effects on intestine permeability changes. METHODS: Seventy individuals undergoing elective open abdominal aortic aneurysm repair were randomly assigned to receive either balanced anaesthesia (continuous epidural and general anaesthesia, group E&G) or only general anaesthesia (group G). For group E&G, an epidural catheter was inserted into the epidural space before the induction of general anaesthesia. Ropivacaine was used for intraoperative and postoperative blocks. For both groups general anaesthesia was maintained with sevoflurane. For group G, analgesia was provided with remifentanil. The assessments of gut function were based on measurements of the absorption and percentages of urinary excretion of four sugars (m 3-O-methyl-D-glucose, D-xylose, L-rhamnose and lactulose) and the lactulose/rhamnose (L/R) ratio. RESULTS: No intergroup differences were observed for sugar recovery or L/R ratio. Significant decreases in 3-O-methyl-D-glucose, D-xylose, and L-rhamnose recoveries were revealed in both examined groups when comparing the results obtained at 12 and 24 hours following the administration of anaesthesia. The rate of blood pressure decrease was significantly higher in group E&G. CONCLUSIONS: Aortic clamping during open abdominal aortic repair led to unfavorable changes in intestinal permeability. Epidural block did not attenuate this deterioration.

Implementing enhanced recovery after bariatric surgery protocol: a retrospective study.

While the demand for bariatric surgery is increasing, hospital capacity remains limited. The ERABS (Enhanced Recovery After Bariatric Surgery) protocol has been implemented in a number of bariatric centers. We retrospectively compared the operating room logistics and postoperative complications between pre-ERABS and ERABS periods in an academic hospital. The primary endpoint was the length of stay in hospital. The secondary endpoints were turnover times-the time required for preparing the operating room for the next case, induction time (from induction of anesthesia until a patient is ready for surgery), surgical time (duration of surgery), procedure time (duration of stay in the operating room), and the incidence of re-admissions, re-operations and complications during admission and within 30 days after surgery. Of a total of 374 patients, 228 and 146 received surgery following the pre-ERABS and ERABS protocols, respectively. The length of hospital stay was significantly shortened from 3.7 (95 % confidence interval [CI] 3.1-4.7) days to 2.1 (95 % CI 1.6-2.6) days (P < 0.001). Procedure (surgical) times were shortened by 15 (7) min and 12 (5) min for gastric bypass and gastric sleeve surgery, respectively (P < 0.001 for both), by introducing the ERABS protocol. Induction times were reduced from 15.2 (95 % CI 14.3-16.1) min to 12.5 (95 % CI 11.7-13.3) min (P < 0.001).Turnover times were shortened significantly from 38 (95 % CI 44-32) min to 11 (95 % CI 8-14) min. The incidence of re-operations, re-admissions and complications did not change.

The influence of epidural anesthesia on the electrical activity of heart atria.

INTRODUCTION: High thoracic epidural anesthesia (TEA) causes blockade of sympathetic fibers involved in innervation of the heart (segments T1-T4), which results in changes of cardiac electrophysiology. The anti-arrhythmic effects of TEA on supraventricular arrhythmias, mainly atrial fibrillation, are controversial. THE AIM OF THE STUDY: The aim of the study was to assess the influence of epidural anesthesia on the electrical function of heart atria, including proven markers of increased risk of perioperative atrial fibrillation, such as P wave dispersion and P wave maximum duration. MATERIAL AND METHODS: The study involved 50 male patients, without a history of previous heart diseases, scheduled for elective surgical procedures. Patients received thoracic epidural anesthesia (group T, n = 25) or lumbar epidural anesthesia (group L, n = 25). The measurements were obtained from a continuous recording of ECG before epidural anesthesia and after the detection of blockade (T1 or T8 segment sensory block in groups T and L, respectively). RESULTS: The statistical analysis of electrocardiographic parameters, including the maximum, minimum and mean P wave duration; P wave dispersion; the maximum, minimum and mean PR interval duration; and PR interval dispersion, did not show any inter- or intragroup differences at selected time points. CONCLUSIONS: Regardless of its location, epidural anesthesia and sympathetic blockade associated with this procedure do not significantly affect the electrical functions of the cardiac atria reflected in superficial ECG, including the electrocardiographic parameters that are considered to be markers of increased risk of perioperative atrial fibrillation, such as P wave dispersion and its maximum duration.

The influence of low flow anaesthesia on renal function in cancer patients previously treated with nephrotoxic chemotherapeutic agents.

BACKGROUND: The aim of this study was to assess renal morbidity, associated with the use of low flow anaesthesia (LFA), in cancer patients previously treated with nephrotoxic chemotherapeutic agents. METHODS: Seventy-five patients, aged 30-70 years, scheduled for elective surgery, were randomly allocated to three groups: Group A included those patients who had received nephrotoxic chemotherapeutic agents (cisplatin, carboplatin, methotrexate or cyclophosphamide) within 90 days before surgery, and who were anaesthetised with low flow (0.8(-1) L min(-1)) air-oxygen-sevoflurane (1-3 MAC) anaesthesia; Group B included similar patients who received high flow (6 L min-1) anaesthesia. Non-cancer patients receiving low flow anaesthesia served as controls. Blood was sampled for serum creatinine, BUN, cistatin C, and electrolytes (Na(+), K(+), Cl(-), Ca(2+), P(3+), Mg(2+)) before anaesthesia, and one, three and five days after. RESULTS: There were no statistically significant differences between the groups. CONCLUSIONS: The use of low flow sevoflurane anaesthesia is not associated with an increased risk of nephrotoxicity in those previously exposed to nephrotoxic chemotherapeutic agents.

Surface roughness analysis of hardened steel after high-speed milling.

The work refers to analysis of various factors affecting surface roughness after end milling of hardened steel in high-speed milling (HSM) conditions. Investigations of milling parameters (cutting speed v(c) , axial depth of cut a(p) ) and the process dynamics that influence machined surface roughness were presented, and a surface roughness model, including cutter displacements, was elaborated. The work also involved analysis of surface profile charts from the point of view of vibrations and cutting force components. The research showed that theoretic surface roughness resulting from the kinematic-geometric projection of cutting edge in the workpiece is significantly different from the reality. The dominant factor in the research was not feed per tooth f(z) (according to the theoretical model) but dynamical phenomena and feed per revolution f.