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Pierre Carpentier Written by Pierre Carpentier, AVP - Technologies & Partnerships - Digital BU
on 24 May 2022

The opportunities are tremendous. The impact is tangible. What data has done to the manufacturing sector has a long-lasting effect on how businesses are transforming themselves to keep up with evolving customer demands. It has become a necessity rather than an opportunity. As we look closely into the evolution of Industry 4.0, Big Data is playing a critical role in shaping self-service systems, predictive maintenance, and automation of processes in production management.

While the Four Vs (volume, velocity, veracity, and variety) of data poses its own set of challenges, manufacturing organizations stand to gain significantly in boosting their profitability as well as overall productivity. Industry 4.0 has accelerated innovation within this industry, and significant milestones have been achieved thanks to the proliferation of data and analytics.

Rising demand, supply chain instability, and rapidly evolving customer needs have put manufacturers on edge. Key changes such as disruption, innovation, and global connectivity are all reshaping how manufacturers respond to the pressure of customer demands, unexpected events, and competition. Today, manufacturing innovation will impact every aspect of the enterprise, from production and supply chain to workers. However, with these challenges, opportunities also arise to reimagine work, transform operations, and emerge with more agility, resiliency, adaptability, and ingenuity.

The changes in the manufacturing industry are being significantly shaped by data and four trends, where data is the driving force behind the innovation process.

Data mesh: Concerns about the availability and accessibility of data are steadily being alleviated by the data mesh. Teams are successfully able to tie in their upstream design engineering systems as well as data and product configuration into the manufacturing process planning and supply chain. This allows a more integrated experience for those operating the manufacturing side. Observability, design changes, and even as the product is operated in the aftermarket, getting that data back in to be pushed into the same system, the need for a cohesive view of the product as opposed to having separate silos is driving ubiquitous adoption of the data mesh. Industries are consistently demanding that products in markets such as aerospace and acid intensive manufacturers go-to-market faster and remain cost-effective on the design cycle. Meandering towards trends such as the data mesh brings businesses closer to achieving these requirements.

Distributed systems or EDGE: The low costs and ready availability of computing power have led to the rapid adoption of technology that enables teams to manage an architecture end to end, without the hassles of caring where a server might be. EDGE computing is the driving force behind Industry 4.0, enabling automation across the factory floors and supply chain. EDGE is bringing communication closer to the source instead of having to send data to a remote server for analysis and response. By delivering the ability to be more flexible and cost-effective, data sharing across relevant manufacturing processes is as seamless as it has ever been.

Interoperability: There are several standards that exist, especially in smart manufacturing. Despite the presence of reference architectures on how smart manufacturing should be run, they are either being ignored or not being fully adopted as per how R&D teams suggest the benchmark of running a smart factory in terms of technology. Being successfully able to set a benchmark of how data can communicate between systems with highly technical protocols, standards and APIs brings manufacturers one step closer to true interoperability.

Talent: The constant need for the right talent to help drive digital transformation and move towards industry 4.0 is encouraging manufacturers to look for skillsets beyond core IT. Forward-thinking manufacturers are bringing together a diverse group of advanced skills that align with capabilities across technologies to accelerate smart manufacturing requirements.

Justifying ROI on digital projects has consistently proven challenging since several of these projects often fail, but successful projects bring manufacturers one step closer to Industry 4.0. Despite data, at its core, being intangible, the intrinsic value of data is tremendous as businesses look to keep up with continuous change. True ROI from the data comes from being able to identify the use cases and work backward to showcase value. At the same time, many consider data to be the new oil, oil by itself, unless extracted and refined, does not serve a greater purpose. Similarly, unless organizations can maneuver through the smorgasbord of data, transform it, and derive meaningful insights, justifying ROI can continue to pose a challenge.

Digital transformation projects need to be viewed as investments whose returns yield over time. By risk stratifying each project and evaluating how much it will cost to run it, and going deeper into the intrinsic value of existing data, organizations can realize ROI, not just on one project but on the overall transformation process.

To keep up with the trends and align with the changes in smart manufacturing, finding an ecosystem partner can help accelerate the digital transformation process. Organizations such as Cyient bring 30+ years of experience helping industries navigate the change to stay ahead of the competition.

You can learn more about INTELLICYIENT and our suite of Industry 4.0 solutions, purpose-built to help enterprises lay the foundation for a resilient future. If you’d like to have a conversation with Pierre to know more about his vision for Industry 4.0, you can connect with him here.

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