An overview on 3D printing technology: Technological, materials, and applications

This paper presents a comprehensive review of the industrial applications of artificial neural networks (ANNs), in the last 12 years. Common questions that arise to practitioners and control engineers while deciding how to use NNs for specific industrial tasks are answered. Workable issues regarding implementation details, training and performance evaluation of such algorithms are also discussed, based on a judiciously chronological organization of topologies and training methods effectively used in the past years. The most popular ANN topologies and training methods are listed and briefly discussed, as a reference to the application engineer. Finally, ANN industrial applications are grouped and tabulated by their main functions and what they actually performed on the referenced papers. The authors prepared this paper bearing in mind that an organized and normalized review would be suitable to help industrial managing and operational personnel decide which kind of ANN topology and training method would be adequate for their specific problems.

A comprehensive review for industrial applicability of artificial neural networks

https://spiral.imperial.ac.uk/bitstream/10044/1/73026/9/1-s2.0-S0264127519306021-main.pdf

Review on design and structural optimisation in additive manufacturing: Towards next-generation lightweight structures

Connecting circular economy and industry 4.0

Line synchronization of grid connected power converters is a well recognized problem when the grid is weak, or derives from a remote area power supply with poor frequency regulation. Such systems can suffer significant line voltage distortion due to notches caused by power device switching and/or low frequency harmonic content, which can easily corrupt the output of a conventional zero crossing detector. This paper presents a method of filtering the incoming grid voltage using a recursive discrete Fourier transform (DFT). The filter provides a high degree of noise immunity but does produce a phase shift between the incoming grid voltage and the filtered output voltage when the DFT time window does not match the grid period. Two methods of compensating this phase shift are presented, based on tracking the drift in the phase predicted by the recursive DFT. The first method makes a deadbeat adjustment to the time window (thereby changing the sampling rate) while the second approach calculates the phase error based on the linear phase response of the DFT. These compensation algorithms can correct for discrepancies of at least 25% between the DFT time window and the system period, and can track grid frequencies with slew rates as high as 40 Hz/s with negligible phase shift (<2/spl deg/) between the grid voltage input and the filtered output waveforms.

Power converter line synchronization using a discrete Fourier transform (DFT) based on a variable sample rate

The Role of Additive Manufacturing in the Era of Industry 4.0

This paper presents efficient methods to estimate the spectral content of (noisy) periodic waveforms that are common in industrial processes The techniques presented, which are based on the recursive discrete Fourier transform, are especially useful in computing high-order derivatives of such waveforms Unlike conventional differentiating techniques, the methods presented differentiate in the frequency domain and thus are quite immune to uncorrelated measurement noise This paper also shows the theoretical relationship between the proposed methods and those of well-known resonant filters

http://www.initkms.ru/umk/etf/d/An_industrially_useful_means_for_decomposition_and_differentiation_of_harmonic_components..._(Dolen_M.,_Lorenz_R.D.).pdf

An industrially useful means for decomposition and differentiation of harmonic components of periodic waveforms

Despite the rapid growth in the past decade, the industrial adoption of additive manufacturing has not still been achieved due to certain limitations. A recent trend to alleviate its inherent drawbacks is to integrate additive manufacturing with secondary production techniques. Indeed, hybrid additive manufacturing solutions may help overcome the current barriers to today’s production systems by making use of the combined merits of merging technologies. This paper presents a comprehensive review of the current state-of-the-art in the field, covering the following three key aspects of the subject: (i) advances in the hybridization of additive manufacturing processes, (ii) developments in process planning for integrated technologies, and (iii) insights into the hybrid additive manufacturing industry. The main objective of the paper is to classify the latest knowledge for the researchers, along with highlighting challenges and future research directions in this field.

Current trends and research opportunities in hybrid additive manufacturing

This article introduces a new method entitled multi-objective feasibility enhanced partical swarm optimization (MOFEPSO), to handle highly-constrained multi-objective optimization problems. MOFEPSO...

Melik Dolen

Papers

The Role of Additive Manufacturing in the Era of Industry 4.0

An industrially useful means for decomposition and differentiation of harmonic components of periodic waveforms

Current trends and research opportunities in hybrid additive manufacturing

Multi-objective feasibility enhanced particle swarm optimization

Accurate pressure prediction of a servo-valve controlled hydraulic system