From smartphones to smart cars to smarter IoT devices, industries have witnessed smart technologies penetrating various sectors, bringing in evolutionary transformation. With Industry4.0 it is smart factories driven by digital transformation and intelligent automation. The manufacturing sector’s digital facelift came along with a massive transformation of processes, delivery, and customer experience. And, artificial intelligence (AI) is among the key drivers of this change alongside automation, blockchain, and large language models.
In the backdrop of the recently concluded 2nd edition of Technology Senate North, Atul Govil, Chief Technology Officer and Head for SAP and IT at India Glycols, shared his vantage points on the emergence of smart manufacturing with the onset of new-gen technologies. The forum also witnessed numerous interesting discussion sessions and presentations depicting the evolution of technology implementation and beyond.
Now, before we delve into the details of the fourth leg of the industrial revolution and the widespread adoption of AI-driven solutions, let us uncover what lies behind the scenes of a smart factory. As per the SAP definition, a smart factory is a cyber-physical system that houses interconnected machines, communication network, and robust computing power. The facility utilises advanced technology deployments like AI and machine learning (ML) to intelligently automate processes, analyse data, and feed on the same to train itself to flag alerts in case of anomalies and provide business-relevant actionable insights for better decision-making by the leaders.
Considering the evolution of industries, cutting-edge technologies have driven the change – the steam engine marked the first industrial revolution, while the assembly line led the second one. The onset of computers completely changed humanity, making the third leg of the Industrial Revolution the most important one. With Industry 4.0, it is about digital transformation and intelligent automation. Smart manufacturing will result in the enhancement of operational efficiencies across industries. According to research by the Boston Consulting Group (BCG), the manufacturing sector will witness a major increase of about 25 percent in the share of tasks performed by robots, by 2025. The current global average of the same marks 10 percent of the task share. Further, the study reveals that the wider adoption of robotics will pushup productivity by up to 30 percent improving performance by five percent year-on-year while reducing the average labour costs.
Sharing the story of India Glycols at the forum, Atul Govil said, “We created a smart factory by digitalising processes and using data analytics. These are connected through data acquisition architecture which gathers and analyses the much-needed data from IoT devices.”
Legacy infrastructure’s scalability issue, a roadblock
The internet, books, and even the common citizens can speak volumes about the benefit of adopting cutting-edge technologies, especially AI. However, enterprises must not hurry, but rather analyse and weigh the technologies and their business requirements before racing to be the first mover in tech adoption. Unfortunately, many organisations begin modernising their backend infrastructure without a clear roadmap and fail to fetch desired results. According to report by McKinsey, around 70 percent of digital transformation initiatives unable to fulfil their goals due to poor end-user adoption and inadequate planning.
Opening up on the journey of India Glycols, Govil highlighted the challenges he faced. Flagging scalability and flexibility as major concerns he brought to light how India Glycols faced unscheduled stoppages, visibility gaps, in the initial days. However, with upgrades to backend architecture and effective IoT deployments, he was able to successfully establish smart factory solutions.
Key to smart manufacturing
A clear vision of one’s goals help enterprises pave a path to attain successful deployment and get desired results. “With our IoT deployment, the key focus was to enhance asset monitoring, anomaly detection, predictive maintenance, overall equipment effectiveness (OEE), and forecasting,” said Govil, clearly underlining the focus areas why India Glycols needed a smart factory.
Today, enterprises must understand that at the core of any tech stack transformation lies strategic decision-making. The IT leaders need to weave the technology deployment in the fabric of business operations over a course of time. Elaborating on the process, he stated, “We did detailed mapping of stages and SLAs and introduced auto timestamping of plant stages as a part of smart logistics for in-plant and en-route tracking. This also helped us in sharing proactive alerts to the stakeholders in case of delays.”
However, with digital transformation journey enterprises must understand that advanced data analysis and effective data management are the key drivers or the ‘smart’ in a smart factory. Hence, a well-organised database with a robust ERP system in place runs the engine of a smart factory. To effectively run a smart factory, CIOs need to ensure the capability of the backend infrastructure to manage Big Data and to integrate AI, ML, and advanced analytics.
The pace at which a technology gets obsolete is high today. It becomes imperative for the CIOs today to get back to the drawing board time and again to come up with innovative ways to adopt new technologies to improve the the overall business outcome. However, to be effective, it need not have to happen all at once, concluded Govil.
