Imagine connection all the various devices in a manufacturing plant to the same system, forming an intelligent network to coordinate and communicate. What change will it bring to the manufacturing?

FREMONT, CA: According to a survey, manufacturing industries investing in IIoT are reporting advantages, including proficient and increased productivity. Therefore, manufacturing firms need to note that IIoT use cases will increasingly expand in the future.

Here are some of the top three industrial IoT use cases that are applicable for manufacturing industry.

Real-time Asset Monitoring

Manufacturing businesses are employing IoT assets to connect systems and machines–a paradigm shift that enables real-time asset monitoring. Coupled assets offer the opportunity to supervise equipment in real-time for compliance, reliability, and safety. Asset monitoring is jointly used in remote manufacturing, where sensors aid tracking production processes and send status to the right personnel. It also provides a platform to control and manage assets for enhanced production and operation, facilitating timely and proactive manufacturing decisions. Additionally, asset tracking in manufacturing lets easy status monitoring of key tools and final products to enhance logistics, prevent quality issues, and sustain inventory.

Connected Operational Intelligence

The connection of all the various devices in a manufacturing plant to the same system forms an intelligent network for coordination and communication. With this use case, firms can gather and contextualize data from remote manufacturing systems and assets into actionable applications.

Additionally, through IIoT, businesses can now connect to different operational data centers and unite them to enable real-time data visibility across diverse manufacturing systems. IoT enabled machinery thus allows connected operational intelligence that transmits real-time insights to manufacturing stakeholders, permitting them to manage factory units remotely.

Predictive Maintenance of Assets

Millions of dollars go into maintenance costs and machine operations. If equipment maintenance is done on time, it will prevent pauses on production processes considerably lowering the maintenance costs. Also, if downtime can be detected before it knocks, manufacturing organizations can have a considerable decrease in operational costs.

The use of sensors and data analytics in IIoT let machines to predict failure before it takes place. Such detections assist the organization in scheduling strategic maintenance timelines, to be performed when required before the glitches arise. Manufacturers leverage IoT to comprise competent, vibrant, and automated manufacturing processes, where maintenance schedules are self-directed rather than relying on unreliable maintenance personnel.