| | December 20218Industry 4.0 has encompassed new technologies like Internet of Things, Artificial Intelligence, Cloud Computing, Cognitive Computing and Augmented Realities. What are the major challenges that companies face in the adoption of these new technologies?Industry 4.0 is not a product, but journey where adoption/rollout takes time due to various challenges encountered during adoption cycle like resource availability which will have passion to work on this and ready to work on invisible paradigm with required skill. We have to balance internal/statutory requirement like data sharing policy for information/cybersecurity control, interoperability between two systems for integration of tow or multiple different system to bring input to main controller, security threats due to various location access & different integrator following different policy. Data storage location & policy add another dimension from PII perspective.Industry 4.0 solutions give businesses greater insight, control and data visibility across their entire supply chain. How can companies deliver services and products to market, faster, cheaper and better quality to gain an advantage over less-efficient competitors by leveraging supply chain management capabilities?Integrated SCM platform which is enabling us to be more customer centric though real-time integration of factory to customer (market) including customer sentiment, behaviour, demand & supply pattern & adjust SCM response as per consumer behaviour/requirement right from manufacturing speed till deliverable in the market. This gives greater insight, control, and data visibility across their entire supply chain for planner for monitoring the product flow, demand, supply position, customer consumption pattern vs .manufacturing capacity and forecast & fine tune the demand/supply in the market and release the product in the market on time to increase profitability.Predictive analytics allows companies to not just ask reactive questions like, 'what has happened?' or 'why did it happen?', but also proactive questions like, 'what is going to happen?' and 'what can we do to prevent it from happening?'. How do these analytics enable manufacturers to pivot from preventive maintenance to predictive maintenance?Data analytics & data reading through AI capabilities & enabling service provider to give future problems & probable solution, enabling service provider to be proactively ready to face the problem with all required inputs or change the plan to overcome the onward issue. This increases manufacturing efficiency and throughput. Predictive analytics is giving edge to domains like Preventive Maintenance, Reliably center maintenance to predict machine behaviour in future and proactive action to line-up. This is going to increase availability & uptime IN MY OPINIONINDUSTRY 4.0: AN OVERVIEWBy Prashant Pandharinath Ahire,Vice President & Head - PMO & Service Delivery, Technology Solution Group, IIFL FinancePrashant Pandharinath Ahire,
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