...Jaqueline Alves do Nascimento; Rodrigo Goyannes Gusmão Caiado; Luiz Felipe Scavarda; Renan Silva Santos; Gilson Brito Alves Lima Purpose This research develops an integrated technological system combining multicriteria decision-making (MCDM) methods and machine learning (ML) techniques to support...

...), although established as a strategic resource for reducing variability and preventing defects, it shows limitations when dealing with non-normal data distributions or when faced with data with high dimensionality. In this context, machine learning (ML) techniques have emerged as complementary solutions...

... management in support of mission readiness, enabling improved resource allocation and aircraft availability, and reduced maintenance costs. Design/methodology/approach Textual data in aircraft repair records were processed using natural language processing (NLP), and six different machine learning...

...Berhanu Tolosa Garedew; Daniel Kitaw Azene; Kassu Jilcha; Sisay Sirgu Betizazu Purpose The study presented healthcare service quality, lean thinking and Six Sigma to enhance patient satisfaction. Moreover, the notion of machine learning is combined with lean service quality to bring about...

... Publishing Limited 2024 Emerald Publishing Limited Licensed re-use rights only Digital health platform Perceived quality Perceived usefulness Machine learning Classification Discriminant analysis Technology-enabled healthcare aims to develop smart, connected, and intelligent platforms...

... net Machine learning Cryptocurrency is a revolution again for the financial sector and traders, but it is the most exploited investor class that has raised considerably. Because of its unpredictability, some people think it’s the riskiest class of investors. Looking at the rise and fall...

... results and identifying corrective actions. Therefore, the approach proposed in this paper aims to provide a new rule-based Machine Learning (ML) framework for OEE enhancement and the selection of improvement actions. Design/methodology/approach Association Rules (ARs) are used as a rule-based ML...

... “similarity” of two processes mathematically and then use it to give a first estimate of the measurement uncertainty of the similar measurement process and develop different learning strategies. A trained machine-learning model is then migrated to a similar measurement process without having to perform...

... aims to develop, design and test a smart system that detects defects, categorizes them and uses this knowledge to enhance the quality of subsequent parts. Design/methodology/approach The proposed system integrates data collected from the deep learning module with the machine learning module...

... assurance and quality control. Our algorithm combines an auto-encoding neural network and an assessment of the risks when selecting KCs and omitting other quality characteristics. Machine learning methods and specifically auto-encoders are actively studied in quality control to extract characteristics...

...Joerg Leukel; Julian González; Martin Riekert Purpose Machine learning (ML) models are increasingly being used in industrial maintenance to predict system failures. However, less is known about how the time windows for reading data and making predictions affect performance. Therefore, the purpose...

...Simone Massulini Acosta; Angelo Marcio Oliveira Sant'Anna Purpose Process monitoring is a way to manage the quality characteristics of products in manufacturing processes. Several process monitoring based on machine learning algorithms have been proposed in the literature and have gained...

... Quality 4.0 Industry 4.0 Quality management Internet of things Big data Machine learning Quality control Predictive quality Decision making RQ2. What are the current challenges that hinder Q4.0 adoption? A limited number of reviews has been conducted by other researchers...

.... Section 5 concludes with the implications and limitation of the study. COVID 19 Probabilistic queueing theory Global study Machine learning The world has become volatile, and all walks of life is uncertain due to the COVID-19 pandemic. The pandemic has disrupted the very thread of all...

...Shashidhar Kaparthi; Daniel Bumblauskas Purpose The after-sale service industry is estimated to contribute over 8 percent to the US GDP. For use in this considerably large service management industry, this article provides verification in the application of decision tree-based machine learning...

... only Modelling Machine learning Neural networks Measurement uncertainty All measurements are subject to uncertainty. This includes measurements of dimensional characteristics, such as the measurement of a diameter with a micrometre or a coordinate measuring machine, as well...