Evaluation of industrial processes resilience to electrical disturbances in the context of industry 4.0

• Grant number: 18/20573-9
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: March 01, 2019
• End date: February 29, 2020
• Field of knowledge: Engineering - Electrical Engineering - Power Systems
• Principal Investigator: Juan Carlos Cebrian Amasifen
• Grantee: Erick Gaeski
• Host Institution: Universidade Estadual Paulista (UNESP). Campus Experimental de Itapeva. Itapeva , SP, Brazil

Abstract

This project aims to execute a survey in industrial companies to analyze productive process behaviors to different electrical disturbances and, consequently, to quantify resilience levels in terms of financial losses due to productive-processes involuntary interruptions (also called Cost of Interruption - CI). The research proposes to elaborate a questionnaire to collect data in relation to: I) technical information about equipment and processes during electrical disturbances, II) costs associated with productive-process interruptions and; III) technological and operational gaps of each industrial company so that it can be inserted in the context of Industry 4.0. Moreover, information as Process Immunity Time (PIT) and the interconnection (serial, parallel, etc.) between subprocesses will be collected. The PIT values obtained will be characterized according to the mean value, standard deviation and probability distribution. This project also aims to study PIT and CI as two performance indicators: PIT to quantify the resilience of each productive subprocess analyzed and CI as an economic indicator for the entire production process. Both indicators can be used to guide preventive and corrective measures that may increase the resilience of industrial companies. As part of this project, some solutions and technological alternatives within the context of Industry 4.0 will be proposed in order to increase the resilience of productive processes against electrical disturbances. The solutions will be grouped according to PIT and CI indicators to look for alternatives that can be applied within the facilities of the industrial companies and that take into account their respective particularities.