Partner POV | Streamline Manufacturing Cycles with HPE Private Cloud AI

Enable the factory of the future

The manufacturing industry is highly competitive, with companies racing to deliver diverse new products and services at competitive prices to global consumers. Artificial intelligence (AI) is setting companies apart in today's dynamic marketplace. As companies face challenges such as identifying new revenue streams, operating more efficiently and scaling resources with demand, AI can make the difference between meeting these requirements and losing out to competitors.

Many manufacturers are pursuing AI innovation to uncover real-time insights from their data that enable them to make better business decisions and boost overall performance. The following key use cases for AI can accelerate and improve operations at each stage of manufacturing:

• AI-augmented quality management investigation: AI techniques that automate quality control processes can help us get closer to making zero defects a reality. Using data collected during the manufacturing process, AI algorithms apply analytics and predictive analytics to identify issues and anticipate potential defects in real time, which can streamline inspections, reduce human error, reduce waste and improve overall product quality.
• Automated preventative maintenance: Hone maintenance cycles with condition monitoring and preventative maintenance to boost productivity and increase uptime. Manufacturers can use data from videos, sensors and equipment on the factory floor to monitor and predict maintenance needs before they occur, alerting workers to early warning signs of malfunctions which can reduce failures, costly emergency repairs and workplace injuries.
• AI-augmented supply and logistics: Uncover greater efficiencies across the supply chain by analyzing production schedules, lead times, sales data and costs in real time. AI analysis enables manufacturers to stream insights from multiple cloud and edge environments to increase visibility and control across their operations.
• Chatbots for sales process recommendation: Enhance customer satisfaction with chatbots able to offer personalized product recommendations, automate sales processes and streamline customer support. Chatbots can create a seamless experience for customers while also saving companies time and productivity by handling floor queries on behalf of employees, providing inventory updates through messaging apps, and tracking numerous orders and deliveries.

The key to success for manufacturers is implementing technologies that enable these critical applications — technologies that offer the flexibility and performance to meet the escalating demands of AI, the capacity to utilize vast amounts of available data, and robust data security controls.

Unleash AI precision

Despite AI's promise, manufacturers can be slow to launch such projects into production. These companies often lack the expertise to develop an end-to-end technology strategy to succeed with AI, which can lead to IT complexity and fragmented environments that are costly and difficult to manage, secure and update as requirements change. Manufacturers need a comprehensive solution that makes AI innovation fast and simple to achieve, whether their goal is to accelerate productivity on the plant floor or to expand their operations with visibility across multiple locations and endpoints.

An end-to-end approach to AI includes several factors: technology and industry requirements, the objectives of critical use cases, and ethical considerations for using AI. Your specific approach can power a broad range of workloads, from inference with large language models (LLMs) to fine-tuning and retrieval augmented generation (RAG). These techniques are opening the door to advanced capabilities like generative AI (GenAI).

Public cloud solutions, while feature-rich, can potentially expose sensitive data to threats at different points in the manufacturing cycle. A private cloud approach can offer better security and control while also reducing IT complexity. As a result, more manufacturers are adopting hybrid cloud strategies as the foundation for their AI-powered operations. A full-stack private cloud, known as HPE Private Cloud AI (PCAI), supports the entire AI development lifecycle and provides seamless experiences for users everywhere.

With a private cloud solution for AI, manufacturers won't have to choose between productivity, profits and keeping their data safe. Rather, they'll benefit from a turnkey environment that continues to deliver consistent experiences as AI infrastructure changes over time.

Why HPE Private Cloud AI?

HPE and NVIDIA see an unfulfilled opportunity for manufacturers to streamline AI adoption and make these game-changing strategies more accessible, regardless of your operation's size or level of experience, our answer is HPE PCAI.

HPE PCAI is the first co-engineered solution to come from NVIDIA AI Computing by HPE — a new joint initiative to help manufacturers supercharge their performance and prepare for the future. NVIDIA AI Computing (or HPE PCAI with NVIDIA) includes AI-optimized infrastructure, networking, software and foundation models that accelerate the entire AI workflow, so projects reach production faster with higher accuracy, efficiency and infrastructure performance at a lower overall cost. This flagship offering is tailored to AI models and designed to scale quickly with the growth and utilization of AI use cases. We give you a complete solution to overcome common roadblocks to AI and quickly recoup your investment by delivering a flexible, pre-tested, AI-optimized private cloud.

HPE GreenLake is the component that makes all this possible. HPE GreenLake provides a self-service cloud experience with a portfolio of services to automate, orchestrate and manage users and data across hybrid environments. Unlike full-stack AI solutions based on reference architectures that can take months to plan, build and deploy, HPE PCAI is ready to use out of the box. Start as small as a single AI pilot and evolve quickly for multiple use cases in one solution. Plus, you can manage workloads either on-premises, using colocation or in the public cloud while controlling financial risks. Consumption-based options deliver 45 percent reduced cost of infrastructure as well as 43 percent lower cost of operations over three years.

With the value of HPE GreenLake, HPE PCAI has the potential to increase AI development productivity by 2x and accelerate inference workloads by 4x. (1), (2)

Get the NVIDIA AI Computing by HPE advantage

Unlike our competitors, HPE and NVIDIA offer a rich ecosystem of proprietary and open-source tools to rapidly deploy AI workloads, simplify infrastructure configuration and management, and take on new use cases while keeping manufacturing data private and secure.

HPE PCAI brings a fully curated environment that incorporates purpose-built hardware and software tools to support each stage of AI development, along with a library of models most applicable to your use cases. The solution combines NVIDIA AI computing, networking and software with robust HPE ProLiant Gen12 inferencing servers, HPE AI storage, and HPE GreenLake cloud to provide manufacturers with a flexible path to select and deploy AI.

AI-optimized hardware is available as a single rack in small or medium configurations. Small configurations are ideal for basic LLM inferencing (e.g., AI-augmented supply and logistics and sales process recommendation). Medium configurations can support RAG for LLMs (e.g., automated preventative maintenance). Large multi-rack configurations are also available, which are capable of fine-tuning the most complex models (e.g., AI-augmented quality management investigation).

The software layer has a specialized set of AI tools leveraging NVIDIA AI Enterprise software to address your long-term AI needs. Integration with NVIDIA NIM inference microservices helps you create data pipelines, develop and fine-tune your models, and deploy AI applications faster than before. Enterprise-grade tools support collaboration with role-based access control, data versioning and lineage, and development capabilities for model fine-tuning.

Disrupt the future of manufacturing

The widespread use of AI and the emergence of generative AI (GenAI) are transforming how we approach product design, development and delivery. With new insights come new possibilities that can help manufacturers evolve faster and smarter than before to meet today's requirements and tomorrow's demands.

HPE and NVIDIA are ready to unleash those possibilities with HPE PCAI. Whether you are an established AI user or just starting your journey, we can help you discover the benefits of a private cloud solution for AI.

HPE AI Services are available globally to support your AI journey. HPE and NVIDIA experts collaborate with you to create, launch and manage your AI environment. We take the guesswork out of critical AI decisions and implementation strategies by helping you:

• Define your AI initiative plans
• Assess required data for your use case
• Consider Al security and data privacy
• Define the technology stack
• Deliver proof of value for your key stakeholders

Bring your business into the future with the power of AI for manufacturing.

References

(1) 90 percent developer productivity increase is based on 2023 UA data: Reduction in total time to build, train, evaluate and operationalize ML model using bespoke tools in comparison with fully integrated workflows and self-service access to data and ML frameworks.

(2) The 4x faster time to inference is in comparison with the typical DIY manual steps to operationalize LLM versus automation in AI essentials (for example, virtual assistant chatbot solution accelerator with RAG).