Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/14403
Title: Development of ISO 23704 standardised cyber-physical production environment for on-line dimensional quality control
Authors: Kulkarni, Ajinkya Nandkishor
Supervisors: Pandhare, Vibhor
Keywords: Mechanical Engineering
Issue Date: 7-Jun-2024
Publisher: Department of Mechanical Engineering, IIT Indore
Series/Report no.: MT326;
Abstract: Industry 4.0 can be described as a transition towards a significant increase in making datadriven decisions across the global value-chain. Big Data, Industrial Internet of Things, Cyber- Physical Systems, Additive Manufacturing, Artificial Intelligence, etc. are some of the key enablers for Industry 4.0. The convergence of cyber-physical systems and product lifecycle management presents an unprecedented opportunity to revolutionize manufacturing practices within the framework of Industry 4.0. At the forefront of this technological wave is Additive Manufacturing (AM), rapidly establishing itself as a mainstream method in the manufacturing landscape. This attraction is fuelled by the potential to create novel designs, intricate features, lightweight structures, and the advantageous low material usage provided by AM. However, to fully harness the potential of AM, it is imperative to evolve monitoring methodologies commensurate with this paradigm shift. A machine is considered "smart" when it can perform the given tasks autonomously while make informed decisions and adapting to changing circumstances without constant human intervention. This work highlights the critical importance of combining Cyber-Physical Systems with Additive Manufacturing to optimize the process and improve product integrity. The proposed system employs a network of sophisticated sensors, particularly optical rotary encoders, and a comprehensive data collection system to continuously monitor key process parameters such as nozzle position, speed, and acceleration for a Fused-Deposition Modelling (FDM) process. By implementing real-time data analytics, the system can promptly detect and correct anomalies, which helps maintaining stringent quality control throughout the manufacturing process.
URI: https://dspace.iiti.ac.in/handle/123456789/14403
Type of Material: Thesis_M.Tech
Appears in Collections:Department of Mechanical Engineering_ETD

Files in This Item:
File Description SizeFormat 
MT_326_Ajinkya_Nandkishor_Kulkarni_2202103006.pdf5.77 MBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

Altmetric Badge: