In the present work, the approach used for the optimization of the process capabilities for Oil&Gas components machining will be described. These components are machined by turning of stainless steel castings workpieces. For this purpose, a proper Design Of Experiments (DOE) plan has been designed and executed: as output of the experimentation, data about tool wear have been collected. The DOE has been designed starting from the cutting speed and feed values recommended by the tools manufacturer; the depth of cut parameter has been maintained as a constant. Wear data has been obtained by means the observation of the tool flank wear under an optical microscope: the data acquisition has been carried out at regular intervals of working times. Through a statistical data and regression analysis, analytical models of the flank wear and the tool life have been obtained. The optimization approach used is a multi-objective optimization, which minimizes the production time and the number of cutting tools used, under the constraint on a defined flank wear level. The technique used to solve the optimization problem is a Multi Objective Particle Swarm Optimization (MOPS). The optimization results, validated by the execution of a further experimental campaign, highlighted the reliability of the work and confirmed the usability of the optimized process parameters and the potential benefit for the company.

Residual stresses appear in a component as a consequence of thermo-mechanical processes (e.g. ring rolling process) casting and heat treatments. When machining these kinds of components, distortions arise due to the redistribution of residual stresses due to the foregoing process history inside the material. If distortions are excessive, they can lead to a large number of scrap parts. Since dimensional accuracy can affect directly the engines efficiency, the dimensional control for aerospace components is a non-trivial issue. In this paper, the problem related to the distortions of large thin walled aeroengines components in nickel superalloys has been addressed. In order to estimate distortions on inner diameters after internal turning operations, a 3D Finite Element Method (FEM) analysis has been developed on a real industrial test case. All the process history, has been taken into account by developing FEM models of ring rolling process and heat treatments. Three different strategies of ring rolling process have been studied and the combination of related parameters which allows to obtain the best dimensional accuracy has been found. Furthermore, grain size evolution and recrystallization phenomena during manufacturing process has been numerically investigated using a semi empirical Johnson-Mehl-Avrami-Kohnogorov (JMAK) model. The volume subtractions have been simulated by boolean trimming: a one step and a multi step analysis have been performed. The multi-step procedure has allowed to choose the best material removal sequence in order to reduce machining distortions.

Taking into account the main importance of nickel-based superalloy in aerospace, marine and chemical industries concerning the production of high performance artifacts, in this paper experimental results of cutting forces, chip morphology, tool wear and temperatures were investigated during orthogonal machining of Waspaloy (45 HRC). All the experiments were performed in dry and lubricated cutting conditions, analyzing and comparing the collected results for a range of different cutting parameters: cutting speed and feed rate. The results show a good trends coherence, highlighting the influence of lubrication during machining.

Wear mechanisms taking place during machining strongly affect the overall process reliability, product quality, and production costs. It is necessary to have useful monitoring techniques for monitoring the wear trend during the process and to identify wearing phenomena occurring during the evolution of the process. In order to get a reliable tool, it is necessary to identify and distinguish the contributing factors and wear mechanisms happening during machining. In this paper, an acoustic emission sensor has been used to identify characteristic features pertaining different wear mechanism displayed during turning of waspaloy. The methodology used to distinguish the contributing elements was developed coupling turning tests with corresponding tribological experiments so that clear evidences on different contributions were identified showing a useful tool for industrial and research applications.