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How Predictive Maintenance Can Futureproof Your Business

The foundation of contemporary marketing ecosystems is data analysis. You can analyze every marketing campaign you conduct regarding user behavior, messaging, demographics, and other factors. Since it is clear that data is the new fuel, businesses are vying for a competitive advantage through predictive maintenance analytics. Effective data management will present numerous opportunities for your company to address customer needs and prosper. This article at MYTECHMAG by Brown Davis shares ten use cases of predictive maintenance in IoT in the manufacturing sector.

Digital Transformation with Predictive Analysis

IoT is set to transform everything once more! Brendan O’Brien of Aria Systems claimed this not long ago. Today, we are living through enormous changes in the Internet of Things (IoT). According to Allied Market Research, the global IoT in the manufacturing market is anticipated to reach a staggering $1,495 billion by 2030. Analysis of data using predictive maintenance models advances the game. Predictive models assist marketers in creating campaigns that are likely to succeed rather than studying efforts after they have finished and drawing insights from them. In other words, by using previous data, predictive analytics enables you to forecast how a user will react to stimuli. For example, predictive models can alert you when a user is most likely to leave, allowing you to act and lower your churn rate.

Predictive Maintenance Use Cases

  • Supply chain management and optimization have unquestionably changed due to IoT in manufacturing. The following are some of the key topics that IoT addresses in supply chain management and optimization:
    • Authentication of a product’s precise location
    • Monitoring of traffic flow and product movement pace
    • Maintenance of adequate humidity, temperature, light levels, and other product storage conditions
    • Planning for alternate routes
    • Tagging goods in storage with IoT devices for easy identification
    • Quick and simple administration of items after receipt
  • Remote product monitoring is a procedure that uses IoT sensors and is built on the idea of “doing more with less.” These sensors monitor and collect information about how productively the machines are operating. They then transfer this data to an AI platform for analysis. The following are some crucial advantages that remote product monitoring provided by IoT in manufacturing offers:
    • Cost optimization
    • Reduced downtime
    • Maximizing machine uptime
    • Precise breakdown forecast
    • Eliminated middlemen
    • Fewer service calls

The author also elaborates on eight more use cases:

  • KPI compilation
  • Automation
  • Predictive maintenance
  • Quality control
  • Worker safety
  • Digital twins
  • Fleet management
  • Workforce efficiency

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