Manufacturing organizations can use edge-enabled AI solutions to engage factory floor workers and improve operational efficiency.

By Ramya Ravichandar, FogHorn VP of Product Management

Factory floor workers often feel disconnected from the rest of manufacturing operations due to being left out of operational communications. The lack of insights made available to factory floor workers has left them in the dark when it comes to processing and interpreting production process data. For instance, if a manufacturing plant is experiencing equipment failure and its factory floor workers have data from a variety of tools, yet lack the necessary insights to understand the cause – they’re left unable to resolve the issue or even more importantly, determine when it will be solved.

As a result of lacking this critical visibility into operations, workers are left disconnected and unengaged – as 66% of U.S. workers feel unengaged in the workplace. This leads to reduced productivity rates and operational inefficiencies, which could negatively impact a company’s overall performance and business.

To address this issue, manufacturing organizations are leveraging edge computing-enabled Artificial Intelligence (AI) technology, such as edge AI, to deliver actionable intelligence to factory floor workers. These technologies help enable a connected worker that is able to understand, manage and maintain all parts of operations.

Edge Ai Processes Data Front Line Workers, Industry Today
Edge AI processes data as close to the source as possible, allowing front line workers to receive insights in real-time on the front lines.

Empowering factory floor workers

Edge AI platforms processes data as close to the point-of-use as possible, allowing for factory floor workers to receive operational insights in real-time while they are on the factory floor. This major timesave enables factory floor workers to more quickly identify production errors and take action to correct them, reducing and even preventing downtime, scrap and product quality issues.

Consequently, factory floor workers gain insight into the operational processes that determine their day-to-day tasks. This added visibility equips floor workers with the necessary knowledge to better understand and execute their roles within manufacturing operations. As a result, factory floor workers feel more engaged and involved in operations, leading to better and more efficient performance throughout the chain of command.

Many edge solutions are also able to be deployed via a mobile device, making these insights available to workers as they move throughout the factory floor. This mobility ensures factory floor workers are kept in the loop of all internal operations and changes at all times, and without having to alter their current daily routines. In turn, mobile edge solutions can enable workers to more instantaneously share information and insights across production lines, ensuring that every factory floor worker is on the same page at all times.

Improving Operational Efficiency

Edge AI solutions enable operational efficiency through its low-latency capabilities. Processing data at the edge, or at the site of production, also reduces the time and cost spent on sending data to the cloud to produce actionable insights. Additionally, less network traffic reduces the chance of network downtime, which is often the cause of manufacturing operations downtime. Reducing downtime will also save an organizations’ production budget a great deal, as the average cost of unplanned downtime is estimated to be a sizable $250 per hour, totaling approximately $2 million dollars per workday.

Edge AI can also provide quality actionable insights in real-time for operational technology (OT) teams. With this added insight, OT teams can better optimize their overall production process even in the midst of changing operating conditions, such as temperature or machine performance. By monitoring machine health, OT teams can predict when unplanned downtime and share these insights with factory floor workers, or other operational staff, who can work together to help minimize the impact of this downtime or prevent it outright.

Withstanding the Test of Ever-Growing Data

As we continue to see an increase in IIoT devices, the timeliness of sharing operational insights with factory floor workers will need to increase as well. With edge AI technology, organizations will be able to more quickly adapt to the growing amount of endpoints that are producing the data to derive the necessary real-time insights. This data will support factory floor workers in making more informed decisions faster and as a result, increase productivity levels throughout the factory.

Ramya Ravichandar FogHorn, Industry Today
Ramya Ravichandar

About Ramya Ravichandar
Ramya Ravichandar, Vice President of Products at FogHorn, brings a rare combination of technical expertise in real time analytics, machine learning and AI, combined with valuable experience in Industrial IoT. She is a seasoned product leader who previously headed Cisco’s Streaming Analytics platform for IoT. Ramya has a PhD in Computer Science from Virginia Tech. Email:

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