Deepak Keni is primarily responsible for Transformation and Change Management Initiatives, including Digital Transformation from conceptualization to implementation, to sustainability and benefits realization. Deepak leads development of specialist capabilities like Digital, IoT, Analytics and Technology systems and processes and scaling it up to a global level to deliver business results. He is a Chemical Engineer from UDCT with an M. Tech in Bio-Technology from USA and an MBA from University of Michigan (Ross Business School), Ann Arbor, USA.
Achieving sustainability by leveraging digital transformation makes more sense in today’s uncertain economic conditions. The subject has gained importance as part of every organization’s strategy and operations. So, what are the key digital interventions that we have tried and tested that provide the maximum business impact?
Digital transformation can act as a catalyst to reduce the manufacturing industry’s carbon footprint, especially in the chemical process manufacturing sector. It also acts as a key enabler, increasing productivity and efficiency in manufacturing operations, while acting as a catalyst for agility. Advanced technology like the Internet of Things, Industry 4.0 and Smart Manufacturing concepts provide several levers for sustainable technology. It helps adopt efficient ways to work and collaborate across operations, thus increasing agility and bringing in a sense of automated decision-making through data science and transparency. Additionally, digital infrastructure for brownfield and greenfield projects can act as a foundation for sustainable digital transformation in the long run. It also provides avenues for collaborating seamlessly with employees irrespective of their location.
Work from home can become effective if we leverage the right technology, collaboration and unified communication. Additionally, digital technology and IT mobility ensure that information is at your fingertips. For instance, our remote plant operations require robust Standard Operating Procedures and new ways of working. Also, digital transformation allows seamless convergence and reduces the gap between the shop floor and the top floor. The executive management can now view operations and dashboards at remote locations from their office.
The digital twin helps in reducing energy consumption at manufacturing operations and chemical plants, where consumption of energy goes in giga calories annually. At such a pass, even a 10%-20% efficiency helps reduce carbon footprint significantly. This can be achieved by implementing the digital twin concept, which simulates assets, operations and processes at the plant and analyses the data to predict and simulate the operations at a granular level. It provides the necessary alerts required for preventive corrections.
Big data analytics helps predict failure of equipment and machinery by capturing data on critical parameters, and continuously running smart algorithms with checks and balances to identify anomalies in process parameters. It helps in taking corrective actions like regular maintenance of critical equipment, so that instances of unplanned shutdowns are low. Unplanned shutdowns not only reduce the yield, but require significant energy when restarting. So, for any plant operation to reach peak performance as measured by Overall Plant Effectiveness through the maximum availability of the assets, it is important that the productivity remains at the desired quality. These measures can be improved using digital technology — increasing yield, reducing energy consumption, optimising consumption of raw materials, and improving the quality parameters.
Another key enabler, the Intelligent Transport Management system, reduces carbon footprint and fuel consumption in transporting raw material and finished goods. The technology helps improve turnaround time of trucks that transport finished goods from the plant to the warehouse or customer location. Leveraging IoT and big data analytics, we can optimize the warehouse locations and distribution lanes through network optimization and figure out the optimal route for servicing customers at a low distribution and fuel cost. This reduces the total cost of distribution by 10% and also eliminates unnecessary stock movement from warehouses because of misplaced inventory. Sales and operations planning, and intelligent fleet management systems coupled with optimization techniques and machine learning algorithms can assure one of inventory at the right place to service the customer at an optimum cost.
Smart technology like geofencing, asset tracking, and people movement tracking can ensure that the right people are accessing the right location. This prevents unnecessary visits to hazardous locations, and underutilization of equipment sitting at the wrong location. Video and image analytics from strategic locations at the plant can provide insights into plant operations with machine learning algorithms and advanced artificial intelligence platforms. Hazardous areas can be geofenced, and facial recognition can ensure proper access. If safety protocols are being violated, video image analytics can identify and alert security operations. Smart sensors coupled with video analytics can detect smoke or hazardous emissions early. Vibration sensors can provide the necessary alerts before a catastrophe takes place.
How to achieve sustainability via digital transformation? The key is to start identifying use cases for the most impact. Thereafter, one can formulate a solution that is scalable and integrated on a common digital platform and enabled over a period of time. This needs a robust data collection mechanism to bring data from sensors, DCS, plant operations data, ERP data, enterprise systems data on a common database or cloud. Here, data can be analysed to provide meaningful insights. The performance Indicators can be monitored, measured, and controlled seamlessly with minimal human intervention. This also provides a base for advanced technologies like artificial intelligence and machine learning, making us proactive. Technology needs to be adopted as part of the core operations to ensure that the benefits are realised. We need to find the sweet spot where machines and humans work seamlessly in the long run.