2nd ADVANCED ANALYTICS FOR INDUSTRY 4.0 APAC

The Fourth Industrial Revolution (or Industry 4.0) is the ongoing automation of traditional manufacturing and industrial practices using modern smart technology. Large-scale machine-to-machine communication (M2M) and the internet of things (IoT) are integrated for increased automation, improved communication, self-monitoring, and the production of smart machines that can analyze and diagnose issues without the need for human intervention. The 4th Industrial Revolution is the 21st-century convergence of digital, physical, and biotechnologies driving an unrelenting acceleration of human progress. Advances in computing power, artificial intelligence, IoT, and machines to speed and create amazing experiences in retail, healthcare, smart cities, and other vertical industries. The fourth industrial revolution technology is inseparably tied to the vast amounts of data needed to train artificial intelligence and other key forms of modern techno pace learning logy. The need for data has led to exponential growth in gathering it, and advanced analytics has gained massive momentum in the industrial sector. Its evolution and conquest of the markets are unstoppable, along with its presence and importance as an essential tool. The main objectives of this program are to present the scientific concepts and to provide industrial case studies for different applications of advanced analytics, which can be grouped into four main areas Descriptive Analytics: Its function is to describe, diagnose, and discover what trends and patterns occur in a given process, thanks to the real-time study of historical data. Predictive Analytics: Based on more advanced mathematical methods that include statistical analyses, data mining, predictive models, and machine learning, among others. Its function consists of predicting events that can occur in the future, thanks to developing a predictive model.  Prescriptive Analytics: Its function consists of defining the actions to take to obtain the best results in a process. It relies on predictive models, scenario simulations, localized rules, and technical optimization to transform data and recommends taking to obtain the desired result. This level of analytics is complete and more robust. It uses complex event processing, neural networks, heuristic learning, and “machine enable growth companies learning,” among others. Optimization: Optimization is one of the most important categories of advanced analytics.