A POV on IoT Solutions in Manufacturing

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A POV on IoT Solutions in Manufacturing

Let's look at some sample use cases in the manufacturing industry that are ripe for IoT's benefits as well as a sample architecture to show how it works.

· IoT Zone ·
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Modern manufacturing techniques coupled with the advent of digital transformation have opened ample unprecedented opportunities to redefine the way manufacturing is run today. 

  • Operations/manufacturing: In a world of increasing production and operations complexity, reducing risk and ensuring compliance, the operations limelight has always been on improving worldwide performance (cost, speed, quality) and agility. Digital transformation takes the industry a step ahead on these parameters by gifting operations managers with real-time connectivity and information flows across the ecosystem.
  • Real-time asset and inventory tracking: With the ability to locate and monitor key assets and inventory, digitization has opened up untapped areas to optimize production costs and agility by giving a complete view of logistics, inventory levels, market demand, etc.
  • Unified operations dashboard: Disparate silos of operational data (e.g. manufacturing, supplier, and logistics) can be aggregated using contextualized KPIs into unified, real-time dashboards that will eventually enable businesses to make faster and better decisions, while also allowing drill-down into correlated data to diagnose problems more quickly and improve performance.
  • Real-time asset health monitoring: Downtime has significant consequences and can be effectively minimized by avoiding potential equipment failures. You can do that by enabling detailed monitoring of critical equipment's condition and operating parameters to automatically trigger mobile alerts, proactively initiating response from maintenance teams.
  • Remote monitoring and diagnostics: IoT enablement has opened up opportunities for OEMs to provide better support by remotely identifying and diagnosing product issues to eliminate unnecessary service calls and improve first-time fix rates. IoT can also be leveraged to perform various other service activities remotely, including machine adjustments, software updates, and self-tests to avoid downtime, reducing or even eliminating the need for on-site service calls.
  • Automated product support: Automatically trigger service events based on connected product alerts, diagnose issues, determine the best service response, and dispatch technicians based on SLA entitlements and resource availability.
  • Data-based predictive maintenance: Monitor connected product operating characteristics and combine them with thresholds, trends, and analytics to move from reactive to proactive maintenance.
  • Advanced service parts inventory planning: Leverage connected product data including configuration, utilization, and location to improve balancing of service level objectives with service parts inventory levels
  • Scalable IoT operations management: The leading emergence of IoT solutions in the manufacturing industry has opened up a requirement for IT teams to give special focus in establishing a highly scalable system for provisioning and deploying large numbers of products and assets, managing complex event processing and Big Data, and operating in an ever evolving and heterogeneous environment.
  • Drive the analytics: With the surge of connected devices, sensors, and business systems, there is an outpouring in the amount of data that is being generated. IT leaders need to factor for accommodating the requirements of seamless data integration, automated analytics, and structuring of unstructured data to best leverage this drive in uncovering actionable insights, optimizing business processes and discovering new opportunities and insights.
  • Rapid IoT application development: Leverage an IoT platform with a model-based application development environment to reduce the time, cost, and risk required to build and maintain innovative connected applications that differentiate products and services and provide a competitive edge

Given below is a sample solution that is built on the following Azure managed services: Azure IoT Suite, IoT Hub, Stream Analytics, Event Hub, DocumentDB, Azure Blobs, Azure Tables, Azure SQL, Azure Data Lake, HDInsight, PowerBI.

Sample Reference Architecture for an IOT Based Solution

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  • IoT Hub manages the two-way communication between the cloud and devices.

  • Advanced analytics is applied on data collected to uncover new business insights.

  • Insights are transformed into action through intelligent applications leveraging Cortana, Power BI, machine learning, etc. creating new revenue and business opportunities.

  • Stream Analytics creates and manages jobs to recognize threshold values or detect alarm triggers.

  • Output of stream analytics is stored in Azure Blobs, Azure Tables, Azure SQL, Azure Data Lake, and HDInsight.

iiot, iot, iot architecture, predictive analytics, use cases

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