HPE GreenLake for Manufacturing is a dynamic, scalable edge-to-cloud platform that helps manufacturers unlock value from all of their data to achieve faster time to insight and gain greater manufacturing efficiency. Learn all about it at Hannover Messe!
By Carolyn Cairns, HPE Global Marketing Lead, Manufacturing Industry
The future of manufacturing is connected, data-driven, autonomous, and secure. It is characterized by digitized factory operations and AI-enabled processes for predictability, virtual product development, and real-time decision-making—all while striving to improve the industry’s environmental and social footprint.
For manufacturers, digital transformation with an edge-to-cloud approach has become an imperative to help ensure continuity of operations and to maintain or re-gain a competitive advantage amidst a changing global landscape.
The pandemic has illustrated how critical it is for manufacturers to be able to respond quickly to changing conditions – whether it’s lockdowns, supply chain disruptions, or sudden fluctuations in demand. To keep pace with these challenges, manufacturers need a flexible, cloud-like IT environment that is available on demand – from the factory floor (the manufacturing edge) to the data center, and to the public cloud where appropriate.
The edge-to-cloud approach
At Hannover Messe 2022, HPE is showcasing HPE GreenLake for Manufacturing, a dynamic, scalable edge-to-cloud environment for manufacturing companies with a pure pay-per-use licensing model. The benefits of an edge-to-cloud approach with HPE GreenLake cloud services are three-fold:
1. Faster time to insights: Leveraging data to optimize production has never been more important. Manufacturers need real-time visibility to adapt to changing production priorities, predict failures, and reduce unexpected downtime.
2. Agile infrastructure: The flexibility for IT to operate both on-premises and on the public cloud is imperative to supporting new production lines and plants based on market needs. An agile hybrid cloud infrastructure ensures flexibility to augment shifting demands.
3. Scalability to meet demand: A data-centric architecture means manufacturers can start their digital transformation for a single location or product line on a pay-per-use model, wherever they may be in their digital journey, then scale up across multiple factories and add additional services as needed.
Smart manufacturing: the catalyst for autonomous operations
Manufacturing companies are under exreme pressure. In addition to the relentless focus on innovation and delivering high quality products, they face enormous time and cost pressures from rising raw material prices and just-in-time production chains. The effects of the pandemic has created a new hybrid workforce with large numbers of manufacturing and industrial employees working remotely As a result, manufacturers are being forced to introduce more autonomous workflows and continually improve production processes to support remote work and gain greater manufacturing efficiency.
This is where smart manufacturing, intelligent factories and Industry 4.0 come into play. Deloitte defines a smart factory as “a leap forward from more traditional automation to a fully connected and flexible system—one that can use a constant stream of data from connected operations and production systems to learn and adapt to new demands.”1 It’s why the industry is placing more focus on digitization and the convergence of OT and IT systems.
End-to-end industrial IoT-ready networking, along with sensor data, high performance computing (HPC) and powerful analytics using artificial intelligence (AI) and machine learning (ML), offer an enormous potential to increase efficiency even further. Examples range from digital twins of machinery and equipment for higher overall equipment effectiveness (OEE) to robots for automated optical quality control.
At the same time, the smart factory clears the path for data-driven services that enable entirely new business models based on product lifecycle and usage data. For example, an automotive manufacturer could selectively recycle used vehicle parts such as batteries or transmissions based on knowledge of their previous use, so as to support the company’s sustainability goals.
Addressing key manufacturing priorities with a data-centric architecture
The foundation for the smart factory is the near-real-time analysis of data accross the manufacturing cycle – from simulation data in product development to order data in the ERP system, GPS data in the supply chain, and sensor data on the factory floor. That’s why three things are at the top of the agenda for manufacturing today:
- Optimizing productivity on the factory floor
- Achieving faster insights into rapidly growing data sets
- Maintaining data sovereignty, which enables manufacturers to keep control of their data and determine who has access to it and how to monetize it.
HPE can help manufacturers address these concerns with a data-centric architecture – a scalable solution to connect all relevant systems while implementing data governance, metadata management, and access control.
AI/ML-driven optimization and innovation, however, have traditionally required significant IT investments – in HPC clusters, for example. Hyperscalers have long offered AI capabilities “as a service”, but not everything can be moved to the public cloud – some calculations have to be performed directly on the factory floor to avoid latency. For example, insights from video analytics-based quality inspections must be delivered in near-real-time to ensure a rapid response to quality shortcomings. At the same time, many companies are reluctant to become dependent on a hyperscaler – where regulations often make it difficult to transfer data off-site, especially across national borders.
The good news is that today, manufacturing companies can bring the cloud right to the factory floor – without becoming dependent on a hyperscaler. With HPE GreenLake for Manufacturing, a broad portfolio of hardware solutions is available that a manufacturer can order on demand at short notice and pay for purely on a per-use basis – just as it is done with cloud services. In line with HPE’s edge-to-cloud approach, workloads can be flexibly processed directly on the factory floor, in the public cloud, or in a private cloud, either in the company’s own data center or in a co-lo environment.
This means that companies can always decide for themselves where their data is processed. And thanks to high security and clearly defined access rights, data sovereignty is maintained, while multi-cloud approaches can be optimally implemented. At the same time, HPE GreenLake platform’s usage-based licensing guarantees line-of-sight into costs, so they always remain within reasonable, predictable limits.
How Zenseact leveraged the HPE GreenLake platform
An example from the European automotive industry illustrates the advantages: Zenseact is a Swedish startup focused on autonomous driving; it belongs to parent company Volvo Cars. It has developed a platform that supports tens of thousands of simulations per second to make cars safer. To do so, it has partnered with HPE to ensure the technology is always available, provided as a service and paid for over time. Zenseact’s test vehicles capture many gigabytes of data per second, which is transferred to an HPE-provided data center so the development team can analyze the data – by now in excess of 100 petabytes.
“One of the key components was to have a flexible platform that we could scale with, both up and down,” says Robert Tapper, CIO of Zenseact, “and HPE GreenLake came out as the winner because it gave us the flexibility that we needed.” (Read more: Making Autonomous Driving a Reality)
A broad path to your digital future
The smart factory promises streamlined production operations, new data-driven business models, and the operational agility to respond to market fluctuations such as supply shortages. With a data-centric architecture delivered via HPE GreenLake platform, the infrastructure required for this can be scaled flexibly and operated at reasonable cost, wherever you want: in the cloud, in your own data center, or directly on the factory floor. This applies not only to individual companies, but also to groups of businesses, supply chains, and ultimately even to industry-wide swarm learning by means of shared data spaces. This enables manufacturers to not only better withstand day-to-day pressures, but also to powerfully press on toward a digital future.
Read more about HPE GreenLake for Manufacturing.
Learn more about IT solutions for manufacturing from HPE.
Learn about HPE innovations at Hannover Messe 2022 here.
If you will be attending Hannover Messe 2022, please visit us in Hall 5, Booth 33, and schedule an appointment with experienced HPE consultants here.
To learn more about HPE GreenLake for Manufacturing and how data can improve product quality and the manufacturing lifecycle, listen to the podcast below.
1. Deloitte University Press: The Smart Factory: Responsive, Adaptive, Connected Manufacturing
Carolyn Cairns is responsible for developing marketing strategy, content, and priority solutions for the Manufacturing and Industrial sectors at HPE. Her diverse business experience includes business development, product management and marketing roles in the telecommunications, public sector, and IT technology and services industries. She has supported numerous pursuits and accounts within the food & beverage, oil & gas, and industrial sectors. She holds an Honours BA from the University of Toronto.
Contact Carolyn on LinkedIn: Carolyn Cairns
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