Sakal Robo System – We provide unique automation solutions

Sakal Robo System

Persistent Changes for the Betterment

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Sakal Robo System

Persistent Changes for the Betterment


What is Digital Twin?

A Digital Twin is a virtual replica or simulation of a physical product, process, or system that encompasses its entire lifecycle. It is a digital counterpart that mimics the behavior, characteristics, and performance of its real-world counterpart in real-time. By bridging the gap between the physical and digital worlds, Digital Twin enables enhanced monitoring, analysis, and optimization of assets, leading to improved decision-making, reduced downtime, and increased operational efficiency.

Digital Twin with IIOT for Energy Monitoring

During the design and engineering phase, it is extremely challenging to avoid mistakes entirely. However, the key to success lies in the timely recognition and correction of errors. Traditional practices involve testing machines or production lines as prototypes, resulting in late detection of production issues and the need for on-the-fly rework. We offer Virtual Commissioning Services that revolutionize this process by parallelizing mechanical and automation engineering, replacing the traditional serial development approach. By leveraging digital twins and virtual commissioning, errors can be identified at an earlier stage, significantly reducing time-to-market and costs while ensuring a smoother production process.

How can We Help?

At Sakal, we specialize in Digital Twin with IIOT services, offering end-to-end solutions tailored to your specific requirements. Our team of experts has extensive experience in implementing Digital Twin architectures, integrating IIOT devices, and developing advanced analytics algorithms. Whether you need assistance with Energy Monitoring, Predictive Maintenance, Supply Chain Optimization, or any other use case, we provide comprehensive support, from strategy development to implementation and ongoing maintenance.

Benefits of Digital Twin with IIOT

The integration of IIOT data into the Digital Twin architecture offers several key benefits:

Real-time Insights

With the continuous flow of real-time data from IIOT devices, the Digital Twin provides up-to-date insights into asset performance, energy consumption patterns, and operational efficiency.

Predictive Analytics

By combining historical data and advanced analytics algorithms, the Digital Twin enables predictive maintenance and optimization, allowing for proactive decision-making and preventing costly equipment failures.

Scenario Testing and Optimization

The Digital Twin environment allows for the testing of different scenarios, energy optimization strategies, and what-if analyses, leading to improved operational efficiency and reduced energy costs.

Remote Monitoring and Control

With the Digital Twin, remote monitoring and control of assets becomes a reality, enabling efficient resource allocation, remote diagnostics, and performance optimization.

Case Study

In this project, we leveraged IIOT technology to capture real-time data from the ABB Robot, including Torque and TCP Speed variables. This data was seamlessly transmitted to the Digital Twin model, which acted as a virtual representation of the robot and its associated energy consumption patterns. By analyzing the data within the Digital Twin environment, we gained valuable insights into the robot’s energy performance, identified optimization opportunities, and developed strategies to reduce energy consumption.

  • HiveMQ acts as an MQTT broker that accepts data from sensors, actuators, controllers, robots from physical world.
  • Telegraph subscribes to the MQTT topic whose data is to be evaluated and stores it in the database
  • Runs under docker or Windows Powershell in the background as server mode
  • Grafana reads the data from influxDB and manages the dashboard to visualize the data (i.a. time series of numerical values)

Apart from Energy Monitoring, Digital Twin with IIOT has diverse applications across industries. Some notable use case examples include:

  • Predictive Maintenance: By integrating IIOT sensors with Digital Twin models, proactive maintenance strategies can be developed, leading to reduced downtime and improved asset reliability.
  • Supply Chain Optimization: Digital Twin combined with IIOT data enables real-time tracking, optimization, and simulation of supply chain processes, enhancing efficiency and reducing costs.
  • Quality Control and Process Optimization: IIOT sensors can provide real-time data on production parameters, which can be fed into the Digital Twin model to identify optimization opportunities and ensure consistent product quality.
  •  Asset Performance Management: Digital Twin with IIOT facilitates comprehensive monitoring and analysis of asset performance, enabling proactive maintenance, resource optimization, and increased productivity.

Contact Us Today

Explore how Digital Twin with IIOT can unlock new efficiencies and drive your organization towards Industry 4.0.