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Industry 4.0-based smart monitoring system for tool condition monitoring in drilling using IoT and cloud manufacturing

Grant number: 20/05576-1
Support type:Scholarships in Brazil - Post-Doctorate
Effective date (Start): March 01, 2022
Effective date (End): February 29, 2024
Field of knowledge:Engineering - Mechanical Engineering - Manufacturing Processes
Principal researcher:Alessandro Roger Rodrigues
Grantee:Pedro de Oliveira Conceição Junior
Home Institution: Escola de Engenharia de São Carlos (EESC). Universidade de São Paulo (USP). São Carlos , SP, Brazil

Abstract

Industry 4.0 concept is on a growth curve and is one of the key drivers for success in today's globalized economy. As a result, manufacturing technologies are upgraded by the Internet of Things (IoT) and cloud computing to a smart level. It thus enables full use of advanced information, smart decisions through real-time communication and cooperation with humans, machines, and sensors. This paradigm shift is fundamentally transforming industry value chains and business models. On this basis, an Industry 4.0-based smart monitoring system is proposed in this Research Project for tool condition monitoring in the drilling operation. Key-enabling technologies, such as IoT and cloud manufacturing will be used with this aim. The effectiveness of the proposed approach will be validated through an experimental investigation of CFRP composite drilling for aeronautical assembly. A wireless and innovative sensor system will be employed to acquire real-time signals during the drilling operation. The pre-processed signals will be transferred via IoT protocols to an assigned cloud manufacturing server. A local software connected to the machine tool will receive the data from the cloud server, will perform the tool condition diagnosis on the basis of computational algorithms, and will decide on the proper actions to be taken, e.g.: the tool replacement. It is expected that the proposed approach will provide a more reliable in-process condition-based tool replacement strategy optimizing tool life diagnosis and contribute to advancing the manufacturing industry forward with focus to the Brazilian scenario. (AU)

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