Industry 4.0 project at DHI CoE in Advanced Manufacturing Technology, IIT Khragpur Project 1
REMOTE MONITORING AND REAL TIME CONTROL OF DEFECTS IN FRICTION STIR WELDING PROCESS AND PREVENTIVE HEALTH MONITORING OF FRICTION STIR WELDING MACHINE TO BE BUILT AND DRIVEN BY TCS CONNECTED UNIVERSE PLATFORM
Industry partner: TATA CONSULTANCY SERVICES
Digital Technologies have significantly marked their presence in the context of advanced manufacturing. It is proclaimed
that Industrial Internet of Things (IIoT) and data analytics will serve a critical role in enabling the vision of smart machines and
intelligent cooperation between multiple machines promoting sustainable operations. The digital interventions will transform the way that machines will be deployed, operated, monitored, and serviced in the future. The global IIoT market for discrete manufacturing is projected to reach $40 billion by 2020 (Ref: https://www.newgenapps.com/blog/8-uses-applications-and-benefits-ofindustrial-iot-in-manufacturing). It is expected to augment the various subsectors of Indian Capital Goods (CG) sector including metallurgical equipment and mining machinery such as earth movers,
remote operating machinery, underground mining equipment & attachments etc. Thus, it is the right instant to start investing on IIoT in India.
Objective of this project
It is the development of an integrated, unobtrusive, multimodal sensing unit that can coherently acquire sensors’ data and analyze it in a composite engine for descriptive, diagnostic and predictive analyses of machinery condition to optimize and take informed decisions.
Technical work modules
|Deliverables of the project
- Experimental model of Friction Stir Welding process with respect to machine tool attributes –critical for manufacturing quality.
- Build an optimal model for welding quality for similar materials vis-à-vis machine tool attributes.
- Creation of a knowledge base for welding different materials through FSW
- Ontology models and workflow information as integrated with TCS PREMAP.
- Online collection of sensor data using TCS IOT platform –TCUP towards quantifying FSW machine’s key performance measures.
- Development of a 3D simulation model for understanding the material flow behaviour.
- Integration of experimental and simulation knowledge base for real time correction of FSW process.
- Model development for online prediction of weld quality and correction in FSW on TCUP
- Digital Twin for health prediction of a FSW machine.
Major infrastructure in this project
Micro/ Macro FSW machine (robot assisted)
Industry 4.0 enabled FSW machine assisted by a 500 Kg payload robot with a reach of 2830 mm. Suitable for micro-size jobs & dissimilar materials
CNC turning centre for tool fabrication
High precise, positioning and repeatability.
Electric spindle with high torque and rotational speed.
A hand held array of 30 microphones with integrated data acquisition system and software for real-time noise source
identification for both stationary and non-stationary measurements.
A touch screen with a 160° viewing angle with high temperature ranges up to 1500 °C.
Measures the input of effective electrical power of spindle and axle drives.
Benefits to CG sector
- The implementation of IoT will increase the capacity utilization and productivity, and optimize the workforce.
- It will result in energy savings and reduction of wastage.
- It will prevent costly unplanned downtime.
More details about this project can be found at: www.coeamt.com