Development of a methodology for monitoring continuous ore grinding processes using Artificial Intelligence with a focus on Industry 4.0.

• Grant number: 24/02750-1
• Support Opportunities: Scholarships in Brazil - Doctorate
• Start date: April 01, 2024
• End date: October 31, 2026
• Field of knowledge: Engineering - Mechanical Engineering - Manufacturing Processes
• Agreement: MCTI/MC
• Principal Investigator: Izabel Fernanda Machado
• Grantee: Modesto Valci Moreira Lopes
• Host Institution: Escola Politécnica (EP). Universidade de São Paulo (USP). São Paulo , SP, Brazil
• Company: Secretaria de Desenvolvimento Econômico (São Paulo - Estado). Instituto de Pesquisas Tecnológicas S/A (IPT)
• Associated research grant: 20/09850-0 - Applied Artificial Intelligence Research Center: accelerating the evolution of industries toward standard 5.0, AP.PCPE

Abstract

The advancement of technology throughout the Industrial Revolutions has transformed various manufacturing sectors, culminating in the current era of Industry 4.0. This scenario, characterized by the integration of advanced digital technologies such as cyber-physical systems and the Internet of Things, redefines production systems, making them smarter and more adaptable. At the core of this transformation is Artificial Intelligence (AI), a science that has been prominent in recent decades, offering algorithms capable of solving a variety of complex problems. In the context of mining, the application of these innovative methodologies aims to improve operational efficiency and enable projects that were previously considered unfeasible. Brazil, as a mineral powerhouse, presents a conducive environment for the application of these technologies, especially in the ore grinding process. The Institute of Technological Research (IPT) is leading efforts in this direction by implementing automated processes in the ore grinding pilot plant. This initiative, called Grinding 4.0, seeks to explore the concepts of Industry 4.0, using instrumentation and automation to collect data and develop studies related to process modeling, energy optimization, and performance control. In this context, the present work aims to develop a new methodology based on AI for process control and monitoring in the IPT's pilot plant. This methodology aims to enhance operational efficiency and detect anomalies, aligning with the requirements of Industry 4.0.