Abrasive fine-finishing technology is often applied as a final finishing process, and the selection of the right technology is crucial to obtaining the desired performance of functions such as fatigue life. This paper begins with classifications of the technology along with fundamentals and brief histories of the individual methods. The material removal mechanisms, specific energies, and finishing characteristics of the various technologies are summarized giving assessments of the surfaces created by them. Guidelines developed for selecting the appropriate methods, and case studies illustrate the effectiveness of various methods. This paper ends with a discussion of the future prospects of the technology. (C) 2016

Abrasive fine-finishing technology

Due to the advances in the digitalization process of the manufacturing industry and the resulting available data, there is tremendous progress and large interest in integrating machine learning and optimization methods on the shop floor in order to improve production processes. Additionally, a shortage of resources leads to increasing acceptance of new approaches, such as machine learning to save energy, time, and resources, and avoid waste. After describing possible occurring data types in the manufacturing world, this study covers the majority of relevant literature from 2008 to 2018 dealing with machine learning and optimization approaches for product quality or process improvement in the manufacturing industry. The review shows that there is hardly any correlation between the used data, the amount of data, the machine learning algorithms, the used optimizers, and the respective problem from the production. The detailed correlations between these criteria and the recent progress made in this area as well as the issues that are still unsolved are discussed in this paper.

A review of machine learning for the optimization of production processes

Ceramic Matrix Composites (CMCs) are currently an increasing material choice for several high value and safety-critical components, fact that has recently originated the need of understanding the effect of several machining processes. Due to the complex nature of CMCs - i.e. heterogeneous structure, anisotropic thermal and mechanical behaviour and generally the hard nature of at least one of the constituents (e.g. fibre or matrix) - machining become extremely challenging as the process can yield high mechanical and thermal loads. Furthermore, the orthotropic, brittle and heterogeneous nature of CMCs result in different material removal mechanisms which lead to unique surface defects. Hence, this review paper attempts to provide an informative literature survey of the research done in the field of conventional and non-conventional machining of CMCs with a main focus on critically evaluate how different machining techniques affect the machined surfaces. This is achieved by exploring and recollecting the different material characterisation techniques currently used to observe and quantify the mechanical and thermal surface and subsurface damages and highlight their governing removal mechanisms.

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The new challenges of machining Ceramic Matrix Composites (CMCs): Review of surface integrity

Abrasive Water Jet Machining process: A state of art of review

Thorough literature review of various modern machining processes is presented in this paper. The main focus is kept on the optimization aspects of various parameters of the modern machining processes and hence only such research works are included in this work in which the use of advanced optimization techniques were involved. The review period considered is from the year 2006 to 2012. Various modern machining processes considered in this work are electric discharge machining, abrasive jet machining, ultrasonic machining, electrochemical machining, laser beam machining, micro-machining, nano-finishing and various hybrid and modified versions of these processes. The review work on such a large scale was not attempted earlier by considering many processes at a time, and hence, this review work may become the ready information at one place and it may be very useful to the subsequent researchers to decide their direction of research.

Optimization of modern machining processes using advanced optimization techniques: a review

Mask-Less Pocket Milling of Composites by Abrasive Waterjets: An Experimental Investigation

Engineering parts usually deviate from their intended shapes during their manufacturing due to the inaccuracies of machine tools, deformation of various elements of machine tool, cutting tools and workpiece. Resulting geometric errors affect the functionality and assembly of the parts significantly. This demands a reliable strategy to accurately assess the errors during the final part quality inspection. Among all the geometric features, circular feature is very common on the majority of the engineering parts. Hence, the measurement and evaluation of circularity with a high degree of accuracy are of utmost importance. In the present work, a hybrid approach is proposed to accurately evaluate the circularity error. This approach comprises a least squares method (LSM) and a novel probabilistic global search Lausanne (PGSL) technique. The LSM is used to reduce the search space initially. Within the reduced search space, the PGSL performs efficient, fine and global search. In the process of establishing minimum zone circles to the measured data of the circular features, the proposed approach dynamically updates the probability distribution function of the circularity parameters continuously. The update procedure ensures that the probability of moving towards the potential optimal solutions is increased. The algorithm has been tested using several benchmark datasets for its generalization capability and robustness. The proposed strategy is found to be efficient in yielding accurate results. Therefore, the algorithm can be implemented in computer-aided circularity measuring instruments in order to minimize acceptance of bad parts and rejection of good parts.

Minimum zone evaluation of roundness using hybrid global search approach

Surface Integrity Analysis of Plain Waterjet Milled Advanced Engineering Composite Materials

In two-axis/five-axis macro/micro milling with abrasive waterjets (AWJs), the ‘top width of the jet footprint' is one of the critical measures that determine the dimensional accuracy of the part to be manufactured. In two-axis milling, the top width of the jet footprint is influenced by operating parameters such as the diameter of the focusing nozzle, the jet plume divergence in air, the standoff distance, and the jet feed rate, and in complex shape machining using five-axis milling, it is also influenced by the jet impingement angle, i.e. the angle between the jet axis and the horizontal workpiece plane. Hence, in this work, an analytical (i.e. geometrical) model for the top width of the jet footprint was proposed and tested on silicon carbide (SiC) workpeices by considering the diameter of the focusing nozzle, the jet plume divergence in air, the standoff distance, and jet impingement angle. The influence of jet feed rate was included in the model by the use of a parameter defined as the ‘effective jet ...

An analytical model for top width of jet footprint in abrasive waterjet milling: a case study on SiC ceramics

This paper presents an integrated approach for the monitoring and control of abrasive waterjet (AWJ) cutting process. A machine-vision-based monitoring approach was proposed to obtain the bore diameter of the focusing nozzle from time to time. A neuro-genetic approach, proposed by Srinivasu and Ramesh Babu (Appl Soft Comput 8(1):809–819, 2008) was employed as a control strategy to modify the process parameters, such as water pressure, abrasive flow rate, and jet traverse rate, so as to maintain the desired depth of cut, with changes in the diameter of the focusing nozzle monitored with a machine vision system. By combining the monitoring and control strategies, an integrated approach for adaptive control of AWJ cutting process is realized. The effectiveness of the proposed integrated approach for adaptive control of AWJ cutting process was shown by comparing the results obtained from the experiments with the process parameters suggested by the control strategy to achieve the desired depth of cut. From the results of the study, it is seen that the proposed monitoring system is capable of monitoring the focusing nozzle diameter with a mean absolute deviation of 0.05 mm and that the neuro-genetic strategy is capable of modifying the controllable process parameters to maintain the desired depth of cut with a mean absolute deviation of 0.87 mm.

An adaptive control strategy for the abrasive waterjet cutting process with the integration of vision-based monitoring and a neuro-genetic control strategy

D.S. Srinivasu

Papers

Mask-Less Pocket Milling of Composites by Abrasive Waterjets: An Experimental Investigation

Minimum zone evaluation of roundness using hybrid global search approach

Surface Integrity Analysis of Plain Waterjet Milled Advanced Engineering Composite Materials

An analytical model for top width of jet footprint in abrasive waterjet milling: a case study on SiC ceramics

An adaptive control strategy for the abrasive waterjet cutting process with the integration of vision-based monitoring and a neuro-genetic control strategy