Industry 4.0

At the end of the second year of my undergraduate, my interest in digital manufacturing increased. Everyone in the industry talked about the fourth industrial revolution because of its potential to bring transparency to the business. Cyber-connected manufacturing systems – also known as Industry 4.0- improve efficiency and optimize operations and have the potential to bring revolutionary changes in the designing of manufacturing processes. We were extremely curious to investigate the challenges of implementing Industrial IoT.

First, we started by taking a closer look at the current status of the Industrial IoT in India. We had very detailed discussions with experts from tech companies such as Mahindra, Tata steels, Capgemini, etc. We found out that the factors that define Industry 4.0 readiness of the Indian industry were the availability of rapid connectivity, maturity of IT and security infrastructure, the trained workforce with Industry 4.0 expertise, level of willingness to invest in Industry 4.0 infrastructure. Nevertheless, Indian Industries have localized sensors for process control, quality inspection, and job monitoring & back-tracking. We interviewed various local industry owners and factory managers, and we realized that even though people were talking about terms like big data and analytics, cloud computing, etc., people were not so familiar with the core concepts of industry 4.0. Therefore, our professor suggested my team develop a tabletop model simulating the process and design of IoT based manufacturing systems for demonstration. 

The project was based on prioritization and decision-making communication between two stations: a CNC workstation and a transporting conveyor to demonstrate computing and decision making by machines. We prototyped the model using broken CD drives, plywood, broken rollers that we used in engineering graphics class.

Both models ran on the Arduino microcontroller. The communication was established through the Bluetooth modules. The designing of the priority decision algorithm, which was governed by factors like raw material availability, operation sequence, etc. was successfully simulated through our model.

Through this project, we gained more in-depth knowledge about communication algorithms, frameworks for different applications, part-rejection decision algorithms, prioritization in decisions, etc. At the end of the project, we were able to answer some of the questions about judiciously integrating robotics technology into the current scenario and avoid issues of unemployment.