Efficient Manufacturing and Sustainability through Factory Edge: IoT and Industry 4.0 in Focus
IoT and Industry 4.0 are buzzwords on everyone’s lips. Today, we look at some approaches and examples from the automotive industry and process optimization in the field of injection molding machines. Currently, Covanlig is working on a project focused on energy consulting, savings, and optimization. The potential of “Factory Edge” can already be recognized in the automotive industry.
In modern manufacturing, the implementation of Industry 4.0 and IoT scenarios is becoming increasingly important. A crucial tool for this is the concept of Factory Edge, which moves data processing closer to the production line. This allows for faster analysis of large amounts of data and optimizes both manufacturing and logistics processes. By processing data directly at the source, latency is reduced, and efficiency is increased, which is especially important for applications in artificial intelligence, robotics, and predictive maintenance.
Factory Edge relies on an adapted IT infrastructure based on technologies such as containers, Kubernetes, AI, and an open hybrid cloud platform (e.g., Red Hat OpenShift). This infrastructure enables a consistent and scalable deployment of applications optimized for dynamic production requirements. Initiatives like the Open Manufacturing Platform (OMP) are working to advance these developments through open-source standards. Overall, Factory Edge provides the foundation for innovative, efficient, and intelligent production processes in Industry 4.0.
But what exactly is Factory Edge?
Factory Edge is a concept within Industry 4.0 based on the principle of edge computing, specifically tailored for manufacturing and production environments. It involves moving data processing from centralized data centers directly to the “edge” of the network, where the data is generated. In practice, this means that computing operations and data analysis occur closer to the machines and systems used in production, such as robots, sensors, or control systems.
Factory Edge in Brief:
Decentralized Data Processing: Data is processed directly on the production line instead of being sent to central servers or cloud data centers. This allows for faster response times and reduces latency.
Real-Time Analysis: The proximity to the data source enables real-time analysis and decision-making on-site. This is particularly important for applications that require immediate responses, such as predictive maintenance or quality control.
Optimization of Manufacturing and Logistics Processes: With Factory Edge, production processes can be made more efficient by detecting and addressing anomalies or potential failures early. This increases productivity and reduces downtime.
Reduced Dependency on Cloud Connections: Even if the connection to central servers or the cloud is interrupted, edge devices can continue to operate autonomously, improving the reliability and stability of production processes.
Scalability and Flexibility: Through integration into hybrid cloud architectures, applications and services can be flexibly extended from central locations to the edge, allowing for better scalability and adaptation to specific requirements.
Integration of Modern Technologies: Factory Edge supports the use of technologies such as artificial intelligence (AI), machine learning, the Internet of Things (IoT), robotics, and augmented reality (AR) in production processes.
In recent years, the automotive industry has developed a concept along these points to directly adapt processes in production and implement the benefits of the Factory Edge approach in practice. Therefore, Factory Edge plays a significant role in the automotive industry today, as it drives the digitization and automation of production processes. To better understand this, here are some points on how Factory Edge is used in the automotive industry:
Real-Time Data Processing and Analysis: Factory Edge enables data to be processed directly at production sites, such as in assembly lines or production lines. In the automotive industry, this is particularly important for monitoring quality in real-time, detecting anomalies immediately, and responding quickly. For example, errors in production can be identified and corrected faster before they have a larger impact.
Predictive Maintenance: By integrating sensors and real-time data analysis, potential failures of machines and systems can be detected early. In automotive production, this means that maintenance work can be planned before an actual failure occurs, minimizing downtime and ensuring production continuity.
Supply Chain Optimization: Factory Edge supports the automotive industry in optimizing logistics and supply chain processes. By connecting production sites with suppliers, inventory can be monitored in real-time, and just-in-time deliveries can be better coordinated. This reduces storage costs and ensures more efficient production planning.
Integration of New Technologies: The automotive industry uses Factory Edge to integrate advanced technologies such as robotics, autonomous production systems, and artificial intelligence. These technologies can be supported by real-time data processing directly on-site, increasing the flexibility and adaptability of production.
Support for Electric Vehicle Manufacturing: The production of electric vehicles requires highly specialized manufacturing processes that can be optimized through Factory Edge. For example, battery manufacturing, which is very sensitive to production errors, can be improved through real-time monitoring and control.
Scalability and Flexibility: Since automotive production often takes place in different regions with varying requirements, Factory Edge offers the necessary flexibility to locally adapt production processes as needed. This enables faster introduction of new models or technologies in various plants worldwide.
Security and Failover Protection: Factory Edge improves the security of production processes since local processing can continue even if the central IT infrastructure fails. This is particularly important in the automotive industry, where production downtime can be costly and damaging to supply chains.
Based on this example, the potential can already be seen for other industries or the entire industry. In one of our projects, we are working in the field of energy consulting and are developing an energy data platform with our customer. This platform uses algorithms to process data collected from injection molding machines or manufacturing machines via an IoT installation. The developed dashboard provides visual indications of peaks, etc., making (energy) data visible and usable that was previously generated automatically but could not be evaluated due to a lack of connectivity and software. With the developed application, our customer can provide the industry with a customizable dashboard in real-time, enabling optimizations similar to those in the automotive industry.
How Does Factory Edge Specifically Enable Energy Savings?
As described, this is achieved through several mechanisms and approaches that increase efficiency and optimize energy consumption. Here are some specific ways Factory Edge enables energy savings in production:
Optimization of Machine Operation: With Factory Edge, machines can be monitored and controlled in real-time. By capturing and analyzing sensor data directly on the production line, inefficient operations can be quickly identified and optimized. For example, a machine that is not operating optimally and therefore consuming more energy can be immediately adjusted or shut down to save energy.
Predictive Maintenance: One of the main advantages of Factory Edge is the ability to perform predictive maintenance. By continuously monitoring the condition of machines, Factory Edge can help reduce unplanned downtime and ensure that machines only run when really needed. This prevents unnecessary energy consumption while extending the lifespan of the machines.
Reduction of Idle Times: Factory Edge can help minimize machine idle times through real-time analysis of production processes. If a machine remains in standby mode longer than necessary or runs at full capacity when not required, this leads to energy wastage. Factory Edge can detect such situations and adjust machine activity accordingly.
Intelligent Energy Management: By integrating Factory Edge into the production infrastructure, companies can implement intelligent energy management. This includes adjusting energy consumption to production requirements, managing peak loads, and using energy resources at optimal times (e.g., when energy prices are lower). Edge devices can collect energy consumption data and make real-time decisions to reduce energy consumption.
Avoidance of Transmission Losses: Since data processing in Factory Edge takes place locally near the data source, less data needs to be sent to central servers or the cloud. This not only reduces the required bandwidth but also saves energy that would otherwise be spent on transmission and processing in central data centers.
Optimization of Production Planning: Through real-time data analysis, Factory Edge can help optimize production plans so that machines are used more efficiently and production processes are organized in a way that minimizes energy consumption. For example, energy-intensive processes can be scheduled when sufficient renewable energy is available, or production workflows can be optimized to consume as little energy as possible.
Conclusion:
Factory Edge offers numerous possibilities for energy savings in production. By optimizing machine operation, predictive maintenance, reducing idle times, and implementing intelligent energy management, companies can significantly increase their energy efficiency. This not only leads to cost savings but also contributes to sustainability and environmental protection by reducing the carbon footprint of production. We are sure to see some exciting projects from this field in the coming months. It remains essential that data collected within existing processes is not simply stored somewhere and forgotten for years. Real-time data and IoT connections finally enable the meaningful use of this valuable, often underutilized data in all areas, especially energy savings—the topic of this era!
