Chandra Gour of Machnika shared with the audience that adoption of Industry 4.0 includes cyber and physical systems which consist of several technologies. For example; digital supply chain. He highlighted aspects of smart factories that provide a competitive advantage in terms of automated data, quality, lower production cost, and predictive maintenance.

He said, “With the adoption of digitisation in factories, they get agile, connected, transparent, optimised and proactive. Through adoption of data analytics and AI, the overall efficiency is boosted by 18%.” Gour classified the packaging industry as “omnipresent” and is a part of the bigger supply chain.

“The journey of digitisation and automation in packaging shows us how the machine capabilities have improved with the help of data, right from manual shrink wrapping to the machines communicating to each other,” explained Gour.

“But how do we use data?”

Tushar Bhotica of Shree Arun Packaging Company (SAPCO) talked about how building a “smart factory” is all about a holistic approach. It involves passing on information and reforming one’s business model.

A point made during the discussion was, “In order to start with being smart, there should be a digital twin of the factory and the entire workflow of how you envision it to be.” Gour gave an example of having a centralised machine or a system which collects data from all other centres on the shop floor, and uses it to communicate.

Sanjay Patel of Param Packaging put a query forward, “What is the entry point for the packaging industry into smart factories? How do we shake hands with digital?” To which Gour responded, “We can start with creating a digital replica or a digital twin of the business plan and goals. Later it can be a model to measure certain aspects such as shop floor, machines and more.”

Patel, simplifying this defined smart factories, “So a digitised platform created through historical data which also gives real-time information to improve overall efficiency.”

Pankaj Gupta of Parksons Packaging brought to the panellists’ notice about demographics and cultural significance in adopting digitisation for the print and packaging industry. According to Chandra Gour, there are four steps in order to create a digital twin or a mock-up of a factory. “Activity mapping; allocating relevance factor; visualising process; and correlating everything with time.”

Gupta said with the help of creating a digital twin, there is a value replica we are able to draw out, and this helps us with many solutions.

Sanjay Patel talked about predictive maintenance which helps predict the machine breakdown due to data collection from sensors in the machine. Chandra Gour explains the table, “Having data of the machine and complete history helps us predict certain parameters of the machine. Hence, this data, if fed to machine learning (ML), will help us with predictive maintenance and more resolutions.”

He said that through ML, we can resolve many issues related to maintenance with 96% accuracy. Gour emphasised that data is interrelated. He said with right data and modelling, all answers can be drawn and solutions can be obtained by using tools such as Generative AI.