Factory Automation

Factory Automation 

As factories have increasingly adopted advanced networking, microcontroller, and sensor technologies within their manufacturing operations, this has led to the industrial IoT (IIoT). In these connected manufacturing environments, machines and advanced robotics systems are networked to enable local coordination, monitoring, and control of key critical parameters within the factory environment. IIoT can revolutionize the manufacturing environment through the use of data collected from machines and sensors. Embedded and networked controllers now allow information from different interfaces and in different formats to be read, processed, and shared. Since a factories dependency grows with each added component and any failing component can trigger a system failure or factory stoppage, automated factories require robust system architectures. The quality of these solutions comes down to the quality of the storage embedded into the systems. 

Smart factories are able to make more efficient use of the resources in an organization to improve productivity and profitability. Data from all parts of a system can be used to improve efficiency by optimizing the scheduling of work and maintenance. Ultimately, a factory could generate thousands of terabytes of data per month, so the challenges are how to efficiently collect, process, and store this information.

IIoT systems have made use of cloud-based computing to enable remote monitoring and management for data archiving, and to perform more complex analysis. With the rapid growth in network sizes and data volumes, the cloud-computing model is encountering serious challenges. These include high latency and making efficient use of available bandwidth.

Moving to Edge Computing

Edge computing puts computing workloads and storage resources at the edge of the IIoT network, close to the devices and data sources, thus reducing dependency on the cloud and the latencies associated with it. 

Edge processors must have sufficient processing and storage capabilities to perform the complex processing that’s required. These workloads are increasingly turning to machine-learning (ML) and artificial-intelligence (AI). AI and ML enable very complex decision making to be performed autonomously, but they require rapid access to very large data sets.

The edge node also acts as a gateway to the cloud. On one side, it communicates with the network of machines, operators, transportation, 

warehousing, and storage, and on the other with the internet and cloud services. This means it can manage data collection, firmware updates, activity logs, and user interfaces. Therefore, the edge node needs to provide secure and reliable storage for large volumes of data.

The typical edge compute node in an industrial environment is a ruggedized modular computing system. These have some specific constraints that affect the selection of the best storage solution. They’re often very compact, without the expansion slots seen in enterprise servers, for example. The system needs to be robust to shock & vibration, and operate in the industrial temperature range of −40 to +85°C or higher.


NAND Flash: The Ideal Storage Solution for the Edge

Edge processing requires both computing power and high-performance storage. Finding the right technology for both is paramount. NAND flash, as used in solid-state drives (SSDs), is ideal. Its primary advantages are being robust (because there are no moving parts), having low power consumption, and very high throughput performance.

In addition to fast access and low latency, the real-time nature of edge computing also requires predictable performance. The design and firmware of flash controllers can be fine-tuned for specific use cases, to help ensure an optimal balance between I/O performance and background tasks.

Centon Electronics provides a broad portfolio of storage products and technologies that deliver the right combinations of performance, capacity, and reliability to meet the unique needs of today’s embedded solutions requiring rugged and reliable operating parameters.