Industry 4.0 bets on digital transformation to accelerate automation, flexibility and interoperability

By Viswanath Ramaswamy Vice President, Technology, IBM Technology Sales, IBM India South Asia and Jaidev Rawat, IBM Power Sales Leader, IBM Technology Sales, IBM India South Asia

What happens when a cement company upgrades its’ IT infrastructure to enhance its’ core business applications? It helps the organisation to seamlessly enhance its productivity while bringing in supply chain efficiencies across its manufacturing units. In another instance, pandemic-led working from anywhere meant that an engineering company had to upgrade its hardware to support the organisation’s digital initiatives, particularly, cyber security. All of this points to the fact that India’s manufacturing sector is embracing Industry 4.0 while rapidly growing and adapting to new-age digital technologies.

Today, successful manufacturers are on an ongoing journey from a standard to automated factory set-up, with some organisations even ramping up to intelligent factories and herein RISC processor-based servers continue to provide the building blocks of a next-generation IT architecture. Building an efficient and intelligent hybrid multi-cloud IT infrastructure is now a key component for manufacturers seeking to up their digital transformation in the ‘Industry 4.0’ scenario.  

Hybrid Cloud and AI– the way forward in the Next Normal

The pandemic has demanded businesses to change their IT strategies and priorities overnight. Their accelerated transformation has meant that they are looking for a secure and agile digital experience and the cloud seems like the next big thing, the key to moving forward. Furthermore, the new generation workload has meant that manufacturers are leveraging AI for their systems to self-learn and become more efficient in the process. 

Currently, cloud fragmentation is making it impossible to achieve efficiency, scale, or standardisation. This also holds true for AI, an imperative catalyst for innovation. For organisations that are looking to scale AI are looking at its scalability, latency especially while managing the high volume of data along with its ability to access data from anywhere across the world. 

Hybrid cloud is a combination with automation and AI that can deliver multiple important benefits, from increased speed, agility and scalability to a shift in the cost model from capital expenditures to operating expenses. Simply put, the hybrid cloud architecture combines a mix of public and private clouds along with on-premise infrastructure with integration across these elements. While AI-based intelligence will help with critical business processes and outcomes, fuelling faster planning, scheduling, optimising supply chain costs etc, Hybrid Cloud migration can boost business productivity to meet an organisation’s evolving needs of its growing ecosystem of external stakeholders. Today AI adoption needs substantial resources, storage space and most importantly a resilient and robust IT infrastructure 

What is it that organisations need to do to push for a Hybrid Cloud Strategy without compromising or adding to the complexity of their IT infrastructure? 

A Robust IT Infrastructure for Hybrid Cloud Approach 

Businesses or the manufacturing sector, in this case, needs to embrace an open, hybrid cloud strategy – one that unifies existing cloud environments to create a bridge for a strong infrastructure for the future.

When it comes to AI, organisations continue to face several challenges such as complexity of data extraction, data transfer overhead to AI platform and most importantly, latency incurred in receiving predictions from AI platform on the operational platform. Furthermore, maintaining multiple environments for AI execution and reserving capacity adds to IT complexity and cost. Besides these, the key concerns for AI are operationalising it, data security, infrastructure costs, and managing the AI software stack. Like the hybrid cloud, AI platforms for organisations need to meet real-time anomaly detection, risk analytics and efficiency standards.

While adopting AI, it is important to verify if the system is designed to democratise AI across all applications and operating environments. It should be designed to infuse AI directly into core business applications and enterprise databases while running close to where data resides. 

For a Hybrid Cloud transition, it is critical to remember the 4S Rule to creating a robust IT infrastructure: 

  1. SCALABILITY: Is the infrastructure strong enough to expand, monitor, predict aspects such as maintenance, extending the equipment life, high performance on a large scale while maintaining efficiency?
  2. SUSTAINABLE: In doing so, are the infrastructure designed to minimise energy consumption and space requirements to tick all the right boxes for sustainability? It should be able to reuse existing components from the previous systems thereby reducing the stress on the environment of producing new components and discarding old ones. 
  3. SECURE: Does the infrastructure focus on cyber-resilience, end-to-end security to reduce exposure to threats? Look for a hybrid cloud that concentrates on dimensions such as advanced data protection, platform security, innovations to identify modern threats and an integrated security management system.
  4. STEADFAST: Today’s environments cannot afford downtime. Is the infrastructure reliable in terms of unplanned outages, memory with an ability to run 24×7, 365 days? The infrastructure needs to be designed in a way that is high on precision, self-heal faults that cause recoverable errors, recover from soft errors automatically without taking an outage and mitigate impacts of other unrecoverable errors. 

Building a hybrid cloud infrastructure for the manufacturing sector will be critical in its digital transformation and thereby in their adoption of Industry 4.0

automationdigital transformationflexibilityIBMIndustry 4.0interoperability
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