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Voestalpine, drivers of excellence in steel manufacturing and technology, leverage IIoT / Kepware, Azure, and ThingWorx to optimize global operations.

Overview

Developed an advanced IIoT system for Voestalpine using Microsoft OpenStreetMap, Kepware, Azure, and ThingWorx for enhanced data and automation.

Tag

#Manufacturing, #Facility Management

Industry Type

Manufacturing

Facility Management

Business

B2B

Region

Europe

Project
Overview

Voestalpine, an Austrian steel-based technology and capital goods group, operates across diverse industries such as steel, automotive, railway systems, and tool steel. With machinery spread across Europe and the Asia-Pacific region, including locations like Taiwan, Beijing, Japan, and South Africa, Voestalpine sought to enhance their operational efficiency through advanced IoT solutions. This case study explores the development and deployment of a sophisticated Industrial IoT (IIoT) system for Voestalpine, leveraging cutting-edge technologies such as Microsoft OpenStreetMap, Kepware, Microsoft Azure, and ThingWorx to revolutionize their data collection, monitoring, automation, and analytics capabilities

Problem Statement

Voestalpine faced several challenges inherent to managing a vast and geographically dispersed network of industrial devices and machinery. Key issues included:

  1. Inefficient Data Collection: The lack of a unified system for real-time data collection from various machines and devices hindered operational insight and decision-making.
  2. Limited Monitoring Capabilities: Difficulty in remotely monitoring machinery performance and health led to reactive maintenance approaches, resulting in downtime and increased costs.
  3. Inadequate Automation: Manual processes dominated the operational workflows, reducing overall efficiency and productivity.
  4. Fragmented Analytics: Disparate data sources and systems made it challenging to conduct comprehensive analytics for predictive maintenance and operational optimization.

Objective

The primary objective was to design and implement an integrated IIoT platform that would:

  1. Enable seamless data collection from diverse industrial devices and machinery.
  2. Provide real-time monitoring and visualization of equipment performance.
  3. Automate routine processes to enhance operational efficiency.
  4. Facilitate advanced analytics to support predictive maintenance and informed decision-making.

Research
& Study

Developing this IIoT platform required extensive research and study, including:

  • Technology Assessment: Evaluating various technologies and platforms to identify the best fit for Voestalpine's needs. Microsoft OpenStreetMap, Kepware, Microsoft Azure, and ThingWorx emerged as the optimal combination.
  • Industry Analysis: Understanding the specific requirements and challenges of the steel, automotive, railway systems, and tool steel industries.
  • Geographical Considerations: Addressing the unique challenges posed by the diverse geographical locations of Voestalpine's operations.
  • Data Security and Compliance: Ensuring the platform meets stringent data security standards and complies with relevant regulations.

Solution

Our comprehensive solution for Voestalpine involved the strategic integration of advanced technologies to create a powerful and scalable IIoT platform. This platform was designed to address the specific challenges faced by Voestalpine and to achieve their operational objectives.

1. Microsoft OpenStreetMap

Key Features:

  • Geospatial Visualization: Microsoft OpenStreetMap provided detailed and customizable maps that allowed Voestalpine to visualize the geographical distribution of their assets and operations. This was crucial for monitoring machinery and systems spread across various locations.
  • Real-time Location Tracking: Enabled real-time tracking of assets, ensuring that Voestalpine could monitor the movement and status of equipment and shipments.
  • Geofencing: Implemented geofencing capabilities to trigger alerts and actions based on the location of assets. This helped in ensuring that machinery and goods remained within designated areas.

2. Kepware

Key Features:

  • Connectivity: Kepware facilitated seamless connectivity and data collection from a wide array of industrial devices and machines. Its ability to communicate with different protocols and interfaces was instrumental in integrating Voestalpine's diverse machinery.
  • Data Standardization: Standardized data from various sources, making it easier to analyze and use in the platform. This was particularly important given the variety of equipment and systems used by Voestalpine.
  • Real-time Data Acquisition: Ensured real-time data acquisition, which was critical for monitoring and automation processes.

3. Microsoft Azure

Key Features:

  • Cloud Infrastructure: Microsoft Azure provided a scalable and secure cloud infrastructure for data storage, processing, and analytics. This allowed Voestalpine to handle large volumes of data efficiently.
  • Advanced Analytics: Leveraged Azure's advanced analytics capabilities to perform predictive maintenance and other data-driven insights. Machine learning algorithms were used to predict equipment failures and optimize maintenance schedules.
  • Data Security: Ensured robust data security and compliance with industry regulations, protecting sensitive operational data from breaches and unauthorized access.
  • Scalability: The platform was designed to scale with Voestalpine's needs, accommodating future growth and expansion.

4. ThingWorx

Key Features:

  • IoT Platform: ThingWorx served as the core IoT platform, providing comprehensive device management, real-time monitoring, automation, and advanced analytics.
  • Device Management: Enabled efficient management of connected devices, including remote configuration, updates, and troubleshooting.
  • Real-time Monitoring and Dashboards: Provided real-time monitoring capabilities through customizable dashboards. These dashboards offered insights into operational performance, allowing Voestalpine to make informed decisions quickly.
  • Automation and Workflow Management: Implemented automated workflows to streamline processes and reduce manual intervention. This included automated alerts and actions based on predefined conditions.

Implementation Highlights

  • Data Integration: We successfully integrated data from various sources, breaking down silos and enabling comprehensive analysis. This integration was key to providing a holistic view of Voestalpine's operations.
  • Real-time Monitoring: The platform provided real-time dashboards and alerts, allowing Voestalpine to monitor operations and address issues promptly. This real-time visibility was crucial for maintaining operational efficiency.
  • Automation: Automated workflows and processes improved operational efficiency and reduced manual labor. This included automated data collection, analysis, and reporting.
  • Predictive Maintenance: Advanced analytics and machine learning algorithms enabled predictive maintenance, reducing downtime and extending the lifespan of machinery. This proactive approach to maintenance significantly improved operational reliability.
  • Scalability: The platform was designed to scale with Voestalpine's growing needs, accommodating new devices and locations seamlessly. This ensured that the solution could evolve with the company's expansion plans.

Benefits Achieved

  • Enhanced Operational Efficiency: Improved data collection, real-time monitoring, and automation led to significant enhancements in operational efficiency.
  • Reduced Downtime: Predictive maintenance reduced unplanned downtime, ensuring that machinery was available and operational when needed.
  • Data-Driven Decision Making: The platform's advanced analytics capabilities enabled data-driven decision-making, allowing Voestalpine to optimize operations and maintenance processes.
  • Scalability and Flexibility: The scalable nature of the platform ensured that Voestalpine could easily expand its operations and integrate new devices and locations.

 

System

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