Manufacturing Business Today, U.S.: Cognizant’s ManLog Leaders Say Manufacturers can Derive Greater Value by Using IoT to Drive Business Strategy and Innovation

Rajaram Radhakrishnan, Vice President and Head of Manufacturing and Logistics, Cognizant, and Prasad Satyavolu, Head of Innovation, Manufacturing and Logistics, Cognizant

“Manufacturers face an exciting yet challenging future,” write Cognizant’s Rajaram Radhakrishnan, Vice President and Head of Manufacturing and Logistics, and Prasad Satyavolu, Head of Innovation, Manufacturing and Logistics. “Meeting consumer demands for personalization, increasing productivity despite the skills shortage and generating new revenue opportunities are all major strategic issues.” Excerpts:

“Deep, real-time visibility into plant operations and supply chains, the ability to predict plant floor events and anticipate broader trends using existing resources to their fullest capacity are all required capabilities. The Internet of Things (IoT), with its potential to assimilate real-time information through sensory enablement and a growing network of interconnected devices, can equip manufacturers with these capabilities, giving them higher flexibility to respond to changing market dynamics.

Each manufacturer’s IoT strategy will be unique to their specific operating system, place in the value chain and the customers they serve. Manufacturers should use the following as benchmarks to ensure IoT implementations provide the data and business intelligence required to succeed in today’s business environment.

Broad Scope of Instrumentation: IoT allows the manufacturers to take their automation to the next level, leveraging information available inside, around and beyond the walls of the plant floors.

Advanced Predictive Analytics: Predictive analytics, an essential element of IoT, enable manufacturers to have real-time visibility and insights, as well as to develop data-driven foresight. By analyzing real-time data, analytics can predict problems before they occur, which can create supply chain transparency.

Expanded Data Storage Capacity: Getting maximum benefit from predictive analytics will require most manufacturers to store more data and for longer periods than before. The reason: more data means smarter algorithms.

Integration of Semantic Data: Semantic data must be integrated with manufacturing system and machine-created data to create a truly comprehensive view of plant operations. Analytics tools can correlate semantic data with machine data to create a richer context for identifying patterns and root causes accurately.

Closed Loop Between Operations and IT: Foresight is wasted if not acted on. Manufacturers must close the loop between IoT insights and predictions and plant control functions. Achieving these seamless interactions requires careful orchestration between IT and IoT.

High Performance Computing Powers Real-Time Intelligence: Applying business rules, identifying exceptions and taking corrective measures in near real-time requires powerful high performance computing of vast volumes of data. Keeping all systems and data synchronized while delivering insights makes this computing paradigm a necessity.

Open Yet Secure: Sharing predictive knowledge gleaned from the IoT can create additional value, whether integrated with a plant manager’s mobile device or supplier and customer systems. Today’s public cloud solutions enable manufacturers to share data in controlled, secure fashion with robust security measures, from encryption to identity management.

While IoT can drive automated responses, manufacturers will derive greater value by using IoT to drive business strategy and innovation. Manufacturers not only need to benchmark against the practices above but also must be creative in augmenting and accelerating their IoT programs. These programs will help organizations build capabilities to meet the challenges in markets and fulfill consumer preferences that are driving different imperatives for manufacturers.”

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