Application and performance of machine learning techniques in manufacturing sector from the past two decades: A review

UMR Paturi, S Cheruku - Materials Today: Proceedings, 2021 - Elsevier
Advancement in technology has created wide opportunities for the researchers to utilize
artificial intelligence in various fields. Numerous attempts have been made in the use of …

IoT in smart cities: A survey of technologies, practices and challenges

AS Syed, D Sierra-Sosa, A Kumar, A Elmaghraby - Smart Cities, 2021 - mdpi.com
Internet of Things (IoT) is a system that integrates different devices and technologies,
removing the necessity of human intervention. This enables the capacity of having smart (or …

Prediction for manufacturing factors in a steel plate rolling smart factory using data clustering-based machine learning

CY Park, JW Kim, B Kim, J Lee - IEEE Access, 2020 - ieeexplore.ieee.org
A Steel Plate Rolling Mill (SPM) is a milling machine that uses rollers to press hot slab inputs
to produce ferrous or non-ferrous metal plates. To produce high-quality steel plates, it is …

[PDF][PDF] Sustainability of the Steel Industry: A Systematic Review

DJ Horst, PP de Andrade Júnior - Proceedings Paper, 2022 - biointerfaceresearch.com
The concern for environmental sustainability focused on the decarbonization of industrial
processes is becoming increasingly important, especially in the steel and iron industries …

Progressive study and investigation of machine learning techniques to enhance the efficiency and effectiveness of industry 4.0

K Sharma, D Anand, KK Mishra… - International Journal of …, 2022 - igi-global.com
The goal of this article is to assess the most recent work on Industry 4.0 as well as the
present state of science on Industry 4.0 through papers produced between January 2017 …

Quality mining in a continuous production line based on an improved genetic algorithm fuzzy support vector machine (GAFSVM)

S Khademolqorani - Computers & Industrial Engineering, 2022 - Elsevier
Nowadays, instant decision making through applying available vast raw data has been
considered as one of the main challenges in various industries. Accurate and quick …

Explainable artificial intelligence based fault diagnosis and insight harvesting for steel plates manufacturing

A Kharal - arXiv preprint arXiv:2008.04448, 2020 - arxiv.org
With the advent of Industry 4.0, Data Science and Explainable Artificial Intelligence (XAI) has
received considerable intrest in recent literature. However, the entry threshold into XAI, in …

Artificial intelligence for sustainable smart cities

P Mishra, G Singh - … Smart Cities: Enabling Technologies, Energy Trends …, 2023 - Springer
In this chapter, an application of artificial intelligence (AI) in the sustainable smart city
operations is presented. The AI includes expert systems, natural language processing …

Logistic model tree forest for steel plates faults prediction

B Ghasemkhani, R Yilmaz, D Birant, RA Kut - Machines, 2023 - mdpi.com
Fault prediction is a vital task to decrease the costs of equipment maintenance and repair, as
well as to improve the quality level of products and production efficiency. Steel plates fault …

Dynamic multimode process monitoring using recursive GMM and KPCA in a hot rolling mill process

G Peng, K Huang, H Wang - Systems Science & Control …, 2021 - Taylor & Francis
The increasing competitive market has put forward higher demand for iron and steel
production process, which is characterized by high-dimensional, nonlinear and multi-scale …