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Business Intelligence

Industrial Enterprise Management

Solution Group

Industry

Manufacturing

PoC Duration

Iotellect Match

3-15 days
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AI powered Low Code IoT/IIoT Platform

Capitalize on the benefits of a BI solution backed by your IoT-enabled business to improve decision-making with real-time data, enhance operational efficiency, and reduce costs through predictive maintenance and process optimization. Develop your own service for manufacturing performance, supply chain visibility, quality control, regulatory compliance, and much more. Enhance demand forecasting, energy management, customer satisfaction, and other verges of business while facilitating performance tracking and increasing collaboration across teams.

Iotellect is a low-code platform for building custom business intelligence software and industrial analytics solutions for manufacturing and other data-intensive operations. It helps teams connect machines, industrial systems, databases, spreadsheets, enterprise software, and APIs in one platform, then build real-time dashboards, reports, analytics, and automated workflows for manufacturing analytics, predictive maintenance, quality monitoring, supply chain visibility, and operational decision-making.

Build Your IoT Application

Connect Your

BI Data Sources

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Smart devices and equipment
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Third-party monitoring and control systems
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Industrial data lakes
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Industrial and facility automation platforms
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Enterprise Service Bus (EBS)
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Corporate databases
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Data warehouses
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Electronic spreadsheets
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Financial systems
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Marketing and social media platforms
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Web services and APIs
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Document management software
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ETL tools
Connect Devices

Connectivity & Management

  • Support for real-time data streaming from machines and devices, allowing for immediate analysis and decision-making
  • Compatibility of common industrial protocols like OPC UA, Modbus, MQTT, and PROFINET, ensuring seamless data exchange between different devices and systems
  • Cloud integration for storing, processing, and analyzing large volumes of data, providing scalability and remote access to BI tools
  • Implementation of data governance policies to ensure data accuracy, consistency, and reliability across the platform
  • Connection with CMMS to track equipment maintenance schedules, work orders, and historical maintenance data, supporting predictive maintenance strategies

Integration

  • Low code integration with Supply Chain Management (SCM) systems
  • Low code integration with Computerized Maintenance Management Systems (CMMS)
  • Low code integration with Energy Management Systems (EMS)
  • Low code integration with Customer Relationship Management (CRM) systems
  • Low code integration with Product Lifecycle Management (PLM) systems
  • Low code integration with Enterprise Resource Planning (ERP) systems
  • Low code integration with SCADA systems
  • Low code integration with Manufacturing Execution Systems (MES)
  • Low code integration with Quality Management Systems (QMS)
  • Low code integration with Human Resources Management Systems (HRMS)

Analytics

  • Analysis of real-time and historical production data to monitor key metrics such as Overall Equipment Effectiveness (OEE), cycle times, and throughput rates, helping identify bottlenecks and optimize production processes
  • Usage of machine learning algorithms and historical data from sensors and equipment to predict potential failures, enabling proactive maintenance scheduling to minimize downtime and extend equipment lifespan
  • Analysis of quality data, such as defect rates, yield rates, and process deviations, to identify root causes of quality issues and suggest improvements, reducing scrap and rework
  • Insights for inventory levels, lead times, and supplier performance, optimizing inventory management and reducing carrying costs by balancing supply with production demand
  • Monitoring of energy usage across machines and processes, identifying energy-intensive operations and suggesting optimizations to reduce costs and improve sustainability
  • Evaluation of machine and labor utilization rates to identify underused resources, enabling better capacity planning and more efficient allocation of assets and workforce
  • Analysis of various production stages to identify inefficiencies and variations, providing recommendations for process improvements and lean manufacturing practices
  • Categorization of downtime events to understand their frequency and duration, providing insights into causes and enabling strategies to minimize unplanned downtime
  • Utilization of real-time data analytics to detect anomalies in production parameters or equipment behavior, alerting operators to potential issues before they escalate into major problems
  • Evaluation of supplier reliability, quality, and delivery performance, supporting better supplier management and risk mitigation strategies
  • Simulation of changes in production parameters or market conditions and assess their impact on operations and profitability

UI/UX

  • Real-time visualization of data charts, graphs, and heat maps to monitor live production data, identify trends, and respond swiftly to any anomalies or issues on the shop floor
  • Availability of drill-down functionality to move from high-level overviews to detailed data, allowing users to investigate specific areas of interest, such as a particular machine's performance or a specific shift’s output
  • Featuring of drag-and-drop UI to easily create and modify reports, dashboards, and data models without needing extensive technical knowledge, enhancing user engagement and ease of use
  • Customization of the UI according to user roles (e.g., production manager, quality control, maintenance), displaying relevant data and controls tailored to each role’s responsibilities and information needs
  • Replay of historical data trends and events within the UI to analyze past performance, understand root causes of issues, and identify opportunities for improvement
  • Usage across multiple monitors or large displays in control rooms, providing a comprehensive view of plant operations for real-time monitoring and management

Key Features for Your
Business Intelligence Solution

Smart Manufacturing

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Related Demos

Optimize your manufacturing with real-time insights and data-driven tools. Track performance, reduce downtime, and improve efficiency across all operations with detailed analytics, visualizations, and predictive maintenance.

Get comprehensive views of production statistics, tracking top products, component output, factory performance, and trends over time, all visualized beautifully in web dashboards.

Customers and Partners

  • System Integrators
  • Original Device Manufacturers
  • Independent Software Vendors
  • Engineering Companies
  • Small and Medium Businesses
  • Industrial Companies
  • Consulting Companies

Solution Users and Developers

  • Dedicated low code developers
  • Business and system analysts
  • Industrial automation specialists
  • BI professionals
  • Business process managers
Customer success team
Community
Online training

Assistance

Hydropower Predictive Diagnostics

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Related Case Studies

Hydropower Predictive Diagnostics
An Automated Predictive Diagnostics System was deployed at a major hydroelectric power station on the Iotellect platform.

Customer
Under NDA
Country
Under NDA
Industry
Power Engineering
Solution Type
Industrial Automation

Common Questions

What is business intelligence software for manufacturing?

Business intelligence software for manufacturing helps companies collect, analyze, and visualize data from production systems, enterprise software, and connected equipment. It supports better decision-making with dashboards, KPIs, reports, and analytics for performance, quality, downtime, and resource usage.

info@iotellect.com
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