Refractory Optimization

Refractory application machines prepare new linings for production, or repair linings to increase the wall thickness when the plant logistics allow for it.

By repairing worn areas of the refractory lining during short production stops, these machines increase the wall thickness above the critical threshold to allow for additional steel batches to be produced using the existing lining, until the next time wall thickness reaches a critical threshold. This cycle continues until total costs increase as the lining reaches end of life, then the process must be shutdown for relining.

Business Solution

Refractory optimization must deliver the safest and most economical usage of refractory materials. Forecasting refractory consumption helps to define the optimum maintenance windows and required spare parts. With analytics, refractory application machine OEMs and steel manufacturers can transform maintenance from reactive or planned to predictive maintenance.

The following are some of the benefits:

• Increase uptime for the refractory application machines, resulting in higher production for steel manufacturers.
• Lower cost of refractory material usage and stock.
• Improve transparency of refractory materials performance and usage with no delay.
• Improve service efficiency for the refractory application machines through better prediction of replacement time based on parts availability and trained personnel.
• Support sustainability with reduced carbon dioxide (CO₂) emissions of steelmaking. For example, 1 ton of MgO can produce 1 ton of CO₂ emissions.

Personas

This architecture shows the workflow and target personas for a refractory optimization solution.

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smart-mfg-personas-oracle.zip

In this example, the following resources use the data:

• Data collected from a variety of sources, including Manufacturing Execution System (MES), Data Historian, and Enterprise Applications, flows to Oracle Autonomous Database.
• Data collected from Plant Sensors and Refractory Data flows to the Data Lake.

The personas use the data as follows:

• Plant Manager: Tracks costs including refractory consumption and maintenance, issues orders for additional refractory materials based on predictions.
• Process Engineer: Performs functional tests (parameter correlation), analyzes production and operational outliers, and reviews refractory analytics.
• Data Scientist: Designs machine learning (ML) models to predict maintenance windows and refractory consumption.

Technical Solution

Refractory application machines expose operational data which can be used to develop a predictive maintenance system and improve on-site customer warehouse management for the refractory material stock. For example, 3d scans of the refractory lining show the wall thickness at each scan which are taken during maintenance repairs.

Creating a continuous central recording of refractory application machine data enables you to perform the following:

• Detect anomalies on machines and issue a notification.
• Capture refractory consumption to provide forecasts for the current campaign.
• Create predictions on maintenance windows.
• Analyze consumption down to 1 kg of refractory materials and forecast future material orders for planned campaigns.

Architecture

This architecture shows how you can use Oracle Cloud Infrastructure (OCI) services to implement predictive maintenance and inventory optimization of refractory for any manufacturing plant worldwide.

Operational data is received from connected refractory application machines at the customer. This data can be streamed or collected in batches, cleaned using OCI Data Flow, then stored to Oracle Autonomous Database. This data is cleaned using OCI Data Flow then sent to Manufacturing Lakehouse for analytics. The refractory consumption data is fed into custom machine learning algorithms developed and deployed using OCI Data Science. One algorithm does predictive maintenance of the refractory application machine which generates a work order in Oracle Fusion Cloud Maintenance. The other algorithm predicts future refractory consumptions for the current or planned campaigns which feed into Supply Chain Management. You can use IoT Production Monitoring or 3rd party tools like Grafana to provide visibility of the current readings and historical trends of operational data.

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smart-mfg-architecture-oracle.zip

This architecture can deliver the following functionality and benefits:

• Reliable tracking of refractory consumption
• Monitor all relevant refractory application machine sensors
• Predict refractory consumption several weeks in advance with reasonable accuracy
• Recommend when to check or change refractory application machine components
• Make proposals on reordering refractory quantities

This architecture supports the following components:

• Streaming

  Oracle Cloud Infrastructure Streaming provides a fully managed, scalable, and durable storage solution for ingesting continuous, high-volume streams of data that you can consume and process in real time. You can use Streaming for ingesting high-volume data, such as application logs, operational telemetry, web click-stream data; or for other use cases where data is produced and processed continually and sequentially in a publish-subscribe messaging model.

• Oracle Data Integration

  Oracle Integration is a fully managed service that allows you to integrate your applications, automate processes, gain insight into your business processes, and create visual applications.

  Use OCI Data Integration for optimal data flow between systems. It supports declarative and no-code or low-code ETL and data pipeline development.

• Oracle GoldenGate Cloud Service

  Oracle GoldenGate Cloud Service is a real-time cloud service for migrating, integrating, or off-loading data between cloud and cloud or cloud and non-cloud databases. These databases include Oracle Base Database Service, Oracle Big Data Cloud Service, Oracle MySQL Cloud Service, and any database supported by Oracle GoldenGate. With Oracle GoldenGate Cloud Service, you can quickly configure an Oracle GoldenGate environment in the cloud without having to set up the infrastructure or platform requirements by yourself.

• Autonomous Database

  Oracle Cloud Infrastructure Autonomous Database is a fully managed, preconfigured database environments that you can use for transaction processing and data warehousing workloads. You do not need to configure or manage any hardware, or install any software. Oracle Cloud Infrastructure handles creating the database, as well as backing up, patching, upgrading, and tuning the database.

• Object storage

  Object storage provides quick access to large amounts of structured and unstructured data of any content type, including database backups, analytic data, and rich content such as images and videos. You can safely and securely store and then retrieve data directly from the internet or from within the cloud platform. You can seamlessly scale storage without experiencing any degradation in performance or service reliability. Use standard storage for "hot" storage that you need to access quickly, immediately, and frequently. Use archive storage for "cold" storage that you retain for long periods of time and seldom or rarely access.

• Data Flow

  Oracle Cloud Infrastructure (OCI) Data Flow is a fully managed Apache Spark service that performs processing tasks on extremely large datasets—without infrastructure to deploy or manage. Developers can also use Spark Streaming to perform cloud ETL on their continuously produced streaming data. This enables rapid application delivery because developers can focus on app development, not infrastructure management.

• Data Catalog

  Oracle Cloud Infrastructure Data Catalog is a fully managed, self-service data discovery and governance solution for your enterprise data. It provides data engineers, data scientists, data stewards, and chief data officers a single collaborative environment to manage the organization's technical, business, and operational metadata.

• Data Lakehouse

  A data lakehouse is a modern, open architecture that enables you to store, understand, and analyze all your data. It combines the power and richness of data warehouses with the breadth and flexibility of the most popular open source data lake technologies. You can build a data lakehouse on Oracle Cloud Infrastructure (OCI) to work with the latest AI frameworks and prebuilt AI services.

  Gain new insights across all of your data with our comprehensive platform of managed Spark, Hadoop, Elasticsearch, and Kafka-compatible services, combined with best-in-class data warehouse and data management services.

• Artificial Intelligence

  Oracle Cloud Infrastructure AI Services is a collection of services, including OCI AI Anomaly Detection and Forecasting services, with prebuilt machine learning models that make it easier for developers to apply AI to applications and business operations.

• Data Science

  Oracle Cloud Infrastructure Data Science is a fully managed, serverless platform that data science teams can use to build, train, and manage machine learning (ML) models on Oracle Cloud Infrastructure (OCI). It can easily integrate with other OCI services such as Oracle Autonomous Data Warehouse, Oracle Cloud Infrastructure Object Storage, and more. You can build and evaluate high-quality machine learning models that increase business flexibility by putting enterprise-trusted data to work quickly, and you can support data-driven business objectives with easier deployment of ML models.

• Notifications

  The Oracle Cloud Infrastructure Notifications service broadcasts messages to distributed components through a publish-subscribe pattern, delivering secure, highly reliable, low latency, and durable messages for applications hosted on Oracle Cloud Infrastructure.

• Grafana

  Grafana is an open source analytics and interactive visualization web application. It uses various data sources to generate charts and graphs for the web.

• Analytics

  Oracle Analytics Cloud is a scalable and secure public cloud service that empowers business analysts with modern, AI-powered, self-service analytics capabilities for data preparation, visualization, enterprise reporting, augmented analysis, and natural language processing and generation. With Oracle Analytics Cloud, you also get flexible service management capabilities, including fast setup, easy scaling and patching, and automated lifecycle management.

Dashboards

The following are example dashboards for the refractory optimization solution.

An Oracle Analytics Cloud dashboard displays the output of the machine learning model. The Plant Manager can use this dashboard to identify actionable insights from the data.
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IoT data flows from the refractory application machine into OCI. This data is quickly available for display in Grafana. Engineers can use Grafana to remotely monitor operational data from the refractory application machine.

Description of the illustration grafana-dashboard-refractory.png