The demands of global competition have rapidly increased in the last five years. SmartFactory provides an easily installed automated data acquisition system that can be operational within hours and can be easily retro fitted. Our Smart Digital Display technology using our analysis tools and visualisation tools can help identify hidden loses in any production process and reduce planned and unplanned downtime minimising changeover and maintenance time and greatly reducing the need for costly line validations. SmartFactory highlights losses in real time. By wirelessly gathering data you can dispense with critical data errors that are frequently overlooked by legacy information collection systems, changing behaviour, improving throughput and increasing overall productivity by five to ten percent. With SmartFactory, you can: Eliminate the wasteful effort of preparing and printing paper reports and digitise the daily management process.
Intel’s Smart Factories Benefits
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Journal of Big Data volume 6 , Article number: 93 Cite this article. Metrics details. Manual exploratory literature reviews should be a thing of the past, as technology and development of machine learning methods have matured. The learning curve for using machine learning methods is rapidly declining, enabling new possibilities for all researchers. A framework is presented on how to use topic modelling on a large collection of papers for an exploratory literature review and how that can be used for a full literature review. The aim of the paper is to enable the use of topic modelling for researchers by presenting a step-by-step framework on a case and sharing a code template.
Skip to search form Skip to main content You are currently offline. Some features of the site may not work correctly. DOI: The future is Internet of Things, which will transform the real world objects into intelligent virtual objects.
Background: The percentage of smartphone users-especially among minors-is growing, and so is the body of literature hinting at increasing rates of problematic smartphone use in children and adolescents. However, comprehensive reviews regarding this issue are still scarce. Objective: The main aim of this review was to provide an overview of studies focusing on specific risk factors predicting problematic smartphone use in children and adolescents. Results: The search yielded 38 articles that met the criteria for inclusion in this review. Research regarding influencing factors such as gender, age, and social, family, and personality factors, as well as duration of use and use patterns, could be found.