https://escholarship.org/content/qt4h56k1ch/qt4h56k1ch.pdf

Advanced monitoring of machining operations

Titanium and nickel alloys represent a significant metal portion of the aircraft structural and engine components. When these critical structural components in aerospace industry are manufactured with the objective to reach high reliability levels, surface integrity is one of the most relevant parameters used for evaluating the quality of finish machined surfaces. The residual stresses and surface alteration (white etch layer and depth of work hardening) induced by machining of titanium alloys and nickel-based alloys are very critical due to safety and sustainability concerns. This review paper provides an overview of machining induced surface integrity in titanium and nickel alloys. There are many different types of surface integrity problems reported in literature, and among these, residual stresses, white layer and work hardening layers, as well as microstructural alterations can be studied in order to improve surface qualities of end products. Many parameters affect the surface quality of workpieces, and cutting speed, feed rate, depth of cut, tool geometry and preparation, tool wear, and workpiece properties are among the most important ones worth to investigate. Experimental and empirical studies as well as analytical and Finite Element modeling based approaches are offered in order to better understand machining induced surface integrity. In the current state-of-the-art however, a comprehensive and systematic modeling approach based on the process physics and applicable to the industrial processes is still missing. It is concluded that further modeling studies are needed to create predictive physics-based models that is in good agreement with reliable experiments, while explaining the effects of many parameters, for machining of titanium alloys and nickel-based alloys.

Machining induced surface integrity in titanium and nickel alloys: A review

An overview of the machinability of aeroengine alloys

Achieving sustainability in manufacturing requires a holistic view spanning not just the product, and the manufacturing processes involved in its fabrication, but also the entire supply chain, including the manufacturing systems across multiple product life-cycles. This requires improved models, metrics for sustainability evaluation, and optimization techniques at the product, process, and system levels. This paper presents an overview of recent trends and new concepts in the development of sustainable products, processes and systems. In particular, recent trends in developing improved sustainability scoring methods for products and processes, and predictive models and optimization techniques for sustainable manufacturing processes, focusing on dry, near-dry and cryogenic machining as examples, are presented.

Sustainable manufacturing: Modeling and optimization challenges at the product, process and system levels

Surface integrity in material removal processes: Recent advances

Influence of scanning strategies on L-PBF processing of titanium aluminides

A method of adaptive tracking for pure-feedback nonlinear systems is presented for the case where linear parameterization conditions are met. The resulting adaptive controllers can be viewed as a state-space model reference adaptive controller with updating of both the state diffeomorphism and the control variables. The tracking problem is considered with respect to parametric and dynamic uncertainties, while prior results have been limited to the parametric uncertainty. Restrictive assumptions on the unknown parameters are removed, overparameterization is avoided, computation time is considerably reduced, and an error model is derived for formulation of the adaptive tracking problem. The robustness of the adaptive controller with respect to unmodeled dynamics is analyzed, and simulation results are presented. >

Adaptive tracking in pure-feedback nonlinear systems

Laser powder bed fusion of hydroxyapatite functionalized Ti-6Al-4V bi-material with potential biomedical applications

A stochastic self-tuning controller is implemented to regulate the cutting forces in end milling under varying cutting conditions. A microprocessor controlled NC milling machine is used in this study. The force controller is implemented using another microcomputer system interfaced with the CNC milling machine. Both the linear and nonlinear characteristics of the cutting forces are examined. A deadbeat controller is then used for force regulation. The proposed controller is shown using simulation and experimental resul ts to be stable with good performance characteristics over a wide range of operating conditions.

Stochastic Self-Tuning Control of Cutting Forces in a CNC Machine Tool

A Fracture Mechanics Approach to the Prediction of Tool Wear in Dry High Speed Machining of Aluminum Cast Alloys: Part 2 — Model Calibration and Verification

Mohamed Elbestawi

Papers

Influence of scanning strategies on L-PBF processing of titanium aluminides

Adaptive tracking in pure-feedback nonlinear systems

Laser powder bed fusion of hydroxyapatite functionalized Ti-6Al-4V bi-material with potential biomedical applications

Stochastic Self-Tuning Control of Cutting Forces in a CNC Machine Tool

A Fracture Mechanics Approach to the Prediction of Tool Wear in Dry High Speed Machining of Aluminum Cast Alloys: Part 2 — Model Calibration and Verification