insideBIGDATA Guide to Computer Aided Engineering – Part 3

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The Manufacturing industry is in the middle of a transition to what’s being called the fourth
industrial revolution: Industry 4.0. Industry 4.0, or Industrial Internet of Things (IIoT), is enabled by smart or connected manufacturing and brings together physical production and operations with digital technologies, machine learning, and big data analytics. It creates a more connected and holistic ecosystem of machines, assets, and processes capable of autonomously exchanging information, identifying anomalies, and triggering actions.

The essential first step for manufacturers is to consider how much data the enterprise has at its disposal. Most manufacturers collect vast troves of process data but typically use it only for tracking purposes, not as a basis for improving operations. The challenge is for these players to invest in the systems and skillsets that will allow them to enhance their use of existing process statistics. This Guide, “insideBIGDATA Guide to Computer Aided Engineering,” sponsored by Dell Technologies, will walk through some of the ways to expand the scope of analytics to further increase business value.

With the high rate of adoption of sensors and connected devices, there has been a massive increase in the data points generated in the digital Manufacturing industry. These data points can be of various types. In manufacturing, operations managers can use analytics to drill down into historical process data, discover previously unidentified knowledge among discrete process steps and inputs, and then optimize the factors that are shown to have the greatest effect on yield. Many manufacturers across a broad range of industries now have an abundance of real-time shop floor data and the capability to conduct sophisticated statistical learning assessments.

They are taking previously siloed data sets, aggregating and joining the data before analyzing them to reveal key insights. Even when considering manufacturing operations that are thought to be best in class, the use of analytics may reveal further opportunities to increase yield above industry benchmarks. In addition, companies can reduce their waste of raw materials, reduce energy costs and increase profitability by rigorously assessing production data, all without having to make additional capital investments or implementing major change initiatives.

How Dell Technologies Helps

In manufacturing, the fourth industrial revolution is based on how technology is intimately connecting products, smart factories and supply chains, with analytics and artificial intelligence (AI) technologies providing a key driving force. Due to this, predicting storage needs can be difficult. The Dell EMC PowerScale portfolio of storage solutions enables manufacturers to use the massive amounts of data being collected for predictive analytics from industrial sensors and devices (Industrial IOT), and delivers new ways of automating production, designing and even ‘printing’ products using AI and deep learning (DL) technologies.

PowerScale lets you start small with the storage you need today and scale easily to petabyte levels. Storage nodes can be added to a cluster as required in seconds, without downtime. Offering a choice of all-flash, hybrid or archive systems, Dell EMC PowerScale storage and analytics solutions combine a powerful, simple, massively scalable platform with integrated support for Hadoop analytics, allowing you to quickly implement data analytics capabilities, without increased operating costs and time- consuming replication of data on a separate infrastructure.

GENERATING PRODUCT AND PROCESS INSIGHTS

Manufacturers collect an enormous amount of data pertaining to the production of product components, the post-production performance of products, and manufacturing and supply chain processes. Today, in the era of the Internet of Things, manufacturers’ data management challenges are growing in scope as products continually generate data related to their performance, functionality and quality. The challenge is not only to capture all this data, but to manage and analyze it to generate product and process insights. Hadoop provides an ideal solution to these challenges.

Conclusion

Technology has long been a major driver of competitiveness in manufacturing. For decades, manufacturers have been using technologies such as high performance computing (HPC) to power the computer aided engineering that helps them create innovative products and grow revenue while cutting costs. Now the Manufacturing industry is undergoing a “fourth industrial revolution,” powered by the rapid advancement of technologies that promise to reshape the industry. Sensors and devices that make up the Industrial Internet of Things (IIoT) can provide manufacturers with important new data points that, when combined with other unstructured business data, create a clearer picture of the entire product lifecycle. Data analytics and artificial intelligence (AI), underpinned by powerful HPC systems, are key to unlocking the value of that data.

And when harnessed, this intelligence can inform and drive decisions that impact success. The manufacturing sector is already leading the way in the application of advanced computing. In particular, HPC powered analytics and AI will revolutionize engineering to help manufacturers speed time to market with more innovative and higher quality products.

Dell Technologies Solutions for Digital Manufacturing, powered by the latest AMD EPYC™ processors and AMD Instinct™ GPUs, are engineered with the right balance of performance and low TCO for AI, Analytics and HPC workloads. Built for processing massive amounts of data, the platform features a high performance architecture, generous memory and storage options, and industry-leading security.

What’s more, Dell Technologies’ worldwide Customer Solution Centers, HPC & AI Innovation Lab and HPC & AI Centers of Excellence make it easier to collaborate with some of the brightest minds in AI, HPC, and data analytics. The expert network of resources can help you fine-tune your solutions test new technologies, and share best practices for optimized results.

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Download the complete insideBIGDATA Guide to Computer Aided Engineering technology guide courtesy of Dell Technologies and AMD. 

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