At the heart of the smart shop floor, lies a unison of intelligent machines, advanced analytics, and a barrage of people who work day-in and day-out to overcome the many challenges that the traditional manufacturing setting brings about. These challenges range from plant capacity to equipment utilization, operational efficiency to cost optimization. The benefits that IIoT brings to the world of manufacturing is beyond compare. But when IIoT is paired with AI, the outcomes are extraordinary.
Read on to find out what makes AI and IIoT a match made in heaven!
AI and IIoT both have the capability to overcome common manufacturing challenges
As organizations embrace AI and IIoT, they have been able to easily overcome challenges commonly associated with a manufacturing setup: while IIoT has been allowing them to bring all devices and equipment into a smart interconnected ecosystem, AI has been enabling them to accelerate production, improve quality, and reduce materials waste.
- AI eliminates manual checks and manual data collection that often tend to slow down operations while resulting in high production efficiency
- IIoT helps overcome the problem of improper equipment management, thus resulting in enhanced resource utilization
- AI helps streamline and institutionalize daily processes, allowing manufacturers to have end-to-end visibility into shop floor operations
- IIoT helps capture real-time data on equipment performance, thus reducing the scope of erroneous data
- AI, through predictive analytics, acts on historic data resulting in informed decisions and fast decision-making
AI and IIoT – Better together
Although AI and IIoT have long been used in isolation, the efficiencies they would be able to create when used in tandem are unimaginable: from real-time data accessibility to the visibility into vital metrics such as OEE, quicker corrective action to proactive management of day-to-day tasks, higher levels of capacity utilization to lesser errors due to minimized manual intervention – together, the technologies have the capability to automate tasks, enhance operational control, and allow for better control and utilization resources including inventory and consumables.
Listed below are a few reasons that make AI and IIoT a match made in heaven:
- Improved data analysis: AI algorithms need a continuous input of accurate, relevant, and updated data to carry out analysis and present insights in an easy-to-understand manner. That’s what IIoT can just provide: the data collected through smart sensors, when fed into AI platforms, can result in accurate analysis of real-time data, helping manufacturers make critical decisions based on hard evidence.
- Reduced equipment downtime: Through continuous analysis of IIoT data, AI systems can, with a high degree of accuracy, predict when, where, why, and how an equipment is going to fail. But that’s not all; through continuous learning, these systems can also act on the data at hand, and greatly bring down equipment downtime – without any human intervention. Such automated resolution of issues can have huge implications for process optimization across the shop floor.
- Enhanced operational efficiency: AI engines, when fed with real-time IIoT data, can also help in enhancing operational efficiency and productivity. Based on the data that is being generated across the shop floor, the algorithms can automatically tweak, optimize, or even improvise their operations – thus minimizing deviations, maximizing throughput, and improving capacity utilization.
- Improved visibility: Because AI systems use real-time IIoT data to carry out operations, they enable manufacturers to have clear visibility across their shop floor. Customized reports and intuitive dashboards can provide a real-time, birds-eye view into shop floor operations. Such intelligent analytics on various parameters can result in enhanced OEE while allowing for greater flexibility to manage the manufacturing organization.
- Better decision-making: AI systems that use updated and accurate sensor data can also help manufacturers improve their day-to-day decision-making capability. Since AI can provide insights into problems that are likely to occur, manufacturers can make proactive decisions – rather than in a reactive manner after a problem or issue has occurred.
Challenges across a high level of manual intervention, decreased operator productivity, high downtime, and poor visibility or control over process deviations have long been plaguing manufacturers. For manufacturing organizations looking for ways to overcome these challenges while increasing productivity and operational efficiency, the amalgamation of AI and IIoT is soon becoming a fundamental enabler of smart manufacturing.
With the capability to improve data analysis, reduce equipment downtime, enhance operational efficiency, improve visibility, and improve decision-making, together, the technologies are paving the way for intelligent automation of tedious mechanical tasks while improving performance and throughput through continuous learning.
