Sunday, June 16, 2024

Google Distributed Cloud, AI & edge in Modern manufacturing

Emerging technologies are giving manufacturers new opportunities to redefine norms for product quality, safety, and operational efficiency. Examples of these include artificial intelligence (AI), edge computing, and software infrastructure. The intricacy of putting these state-of-the-art technologies into practice and scaling them across various industrial settings and locales is still a hurdle.

Google Distributed Cloud, a tool that lets manufacturers use the newest AI, cutting-edge infrastructure, and security from Google Cloud right on site, is at the vanguard of this technological revolution. Google Distributed Cloud is an agile platform for running modern applications on the shop floor that can be deployed in a variety of configurations to suit OT security, latency, and availability needs. These configurations vary from self-managed software-only to fully managed hardware and cloud services.

Use cases for manufacturing

A wide range of manufacturing operations are being powerfully transformed by Google Distributed Cloud.

Visual examination

Quality control was formerly dependent on human inspection, which was expensive, time-consuming, and prone to errors. AI models deployed on the edge have the ability to visually inspect, analyse real-time high-resolution picture and video streams, and discover faults with never-before-seen speed and precision. Improved customer satisfaction, less waste, and reputation protection are all benefits of this real-time quality assurance.

For AI-driven visual inspection, feeds from tens to hundreds of cameras must be analysed quickly in less than a second while the effectiveness of the AI models doing the analysis must be continuously monitored. Customers need to be able to update AI models to support new configurations as business needs dictate modifications to production lines. Visual inspection infrastructure is an essential part of the production process and needs to function consistently.

Process control that is automated

Automated process control, like use cases for visual inspection, generates enormous amounts of data from sensors or cameras integrated in industrial equipment via the Internet of Things (IoT). AI can be used by modern process control infrastructure to minimise energy usage and downtime, optimise processes to produce higher quality with greater throughput, and make tiny modifications to machinery.

New use cases for workforce safety, like proactive hazard identification, make use of wearables and cameras to provide automatic corrective actions or real-time notifications to safeguard employees. Augmented reality (AR) based on the edge improves maintenance and training protocols by decreasing human error and increasing task efficiency. A safer workplace is produced by preventing accidents and injuries, which also lessens worker bodily harm, mechanical damage, and eventually expensive disruptions.

Safety and productivity of the workforce

By adding AI capabilities to current production processes, ageing infrastructure can gain new capabilities and potentially avoid expensive overhauls. By utilising machine learning models at the edge, important information from current equipment can be extracted, facilitating predictive maintenance that can avert malfunctions, prolong equipment lifespans, and save expensive downtime.

AI-powered modernization of outdated systems

For the most demanding visual inspection workloads, Google Distributed Cloud running on-premises offers easy scalability, operational resilience, and real-time responsiveness. Furthermore, Google Distributed Cloud makes it possible to efficiently filter, aggregate, and analyse data locally, eliminating the need to transfer large datasets to the cloud and maximising bandwidth utilisation while cutting expenses. For modern OT and IT demands, Google Distributed Cloud offers the flexibility and seamless interaction.

These are only a handful of the fascinating ways that Google Distributed Cloud is improving manufacturing; there are a plethora of other use cases, and the list keeps getting longer.

What advantages can Google Distributed Cloud offer the manufacturing industry?

Beyond merely enhancing technology, Google Distributed Cloud benefits manufacturers with immediate and observable business results that affect cost, efficiency, safety, and resource management:

  • Reduced scrap: By using AI to improve quality control, less defective items can be produced, wasting less raw materials and increasing industrial efficiency.
  • Improved safety procedures: The capacity to instantly recognise risks or possible mishaps reduces expensive business interruptions and boosts worker security.
  • Faster insights: Cloud-native tools and procedures provide quick testing, iteration, and creation of novel edge-deployed AI-powered solutions that may be customised to meet particular requirements. Google Distributed Cloud enables manufacturers to minimise implementation cycles and foster competitive differentiation by combining cloud and edge in an effective and integrated manner.
  • Enhanced sustainability: Long-term operational savings and environmental advantages can result from enabling edge-driven process optimisation, value-add vs. non-value-add task identification, waste reduction, and predictive maintenance.

The manufacturing industry’s future

Today’s factories are the factories of tomorrow in the cutthroat world of production. By using edge computing and utilising platforms such as Google Distributed Cloud, manufacturers can effectively tackle the intricate problems faced by this ever-changing sector. Google Distributed Cloud opens the door for more automated, flexible, and ultimately successful manufacturing operations. It also demonstrates a dedication to sustainability and safety.

Download this study on delivering modern manufacturing insights to find out more about how to use Google Distributed Cloud on the manufacturing floor. You can also visit our display at Manufacturing x Digital (MxD) to witness firsthand how we are supporting innovation and to find out more about how you can take advantage of Google Distributed Cloud. MxD is a place where forward-thinking manufacturers go to shape their futures.

Thota nithya
Thota nithya
Thota Nithya has been writing Cloud Computing articles for govindhtech from APR 2023. She was a science graduate. She was an enthusiast of cloud computing.
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