Scitis.io, an industrial IoT start-up, has successfully implemented an MES-System for Lorenz, a manufacturer with multiple production lines and sites, to control their production through data. By linking the MES-system to Lorenz’s ERP system, scitis.io provided a comprehensive view of their operations, allowing them to optimize their production processes and increase their Overall Equipment Effectiveness (OEE). The implementation involved overcoming the challenges Lorenz faced by leveraging scitis.io’s solution, which utilized their out-of-the-box IoT framework. The company will be presenting this use-case at its booth at this year’s Hannover Messe, Hall 17, Stand E16.

In today’s manufacturing industry, the ability to control production processes through data is crucial for staying competitive. That's where MES-systems and ERPs come in, providing a centralized repository for business data that can be accessed and shared across various departments and functions within an organization.  

MES-Systems and ERPs 

MES-Systems (Manufacturing Execution Systems) are software solutions used in the manufacturing industry to control, monitor, and optimize production processes. An MES-system collects data from various sources, such as production equipment, automation systems, and sensors, and analyzes it to gain insights into the production processes. Typically, an MES-system includes functions such as planning production orders, monitoring production processes in real-time, collecting production data, collecting quality data, tracking production workflows, controlling machines, and analyzing production data to improve efficiency and quality of production.

On the other hand, an ERP (Enterprise Resource Planning) is a type of software solution used by businesses to manage and integrate their core business processes. An ERP system typically includes a suite of applications that help businesses manage areas such as finance, human resources, procurement, supply chain, inventory, and customer relationship management. The purpose of an ERP system is to provide a central repository of business data that can be accessed and shared across various departments and functions within an organization. This helps businesses streamline their operations, reduce costs, and improve efficiency by providing a single source of truth for business data.

The integration of an MES-system with an ERP system can bring several benefits to a manufacturing organization. By linking production data collected by the MES system with the ERP system, manufacturers can gain a more accurate and up-to-date view of their operations, which can lead to improved decision-making. Additionally, the integration can help organizations streamline their operations by reducing duplicate data entry and improving collaboration across departments.

 Challenges, Solutions, and Results

Lorenz is a manufacturer that faced challenges in controlling their production through data. They had various production lines, and each line was producing different products with varying levels of complexity. Additionally, Lorenz had multiple production sites that were not linked to each other. These factors made it difficult for Lorenz to get a comprehensive view of their production processes, resulting in low OEE.

To address these challenges, Lorenz needed a solution that could collect data from their various production sites and production lines and provide insights into their operations. They needed an MES-system that could be linked to their ERP system to ensure that production data could be accessed and shared across the organization.

Scitis.io provided a solution for Lorenz by implementing an MES-system linked to their ERP system. The MES-system was designed to collect data from various sources, including production equipment, automation systems, and sensors, and analyze it to gain insights into the production processes. The data collected from the MES-system was then linked to Lorenz’s ERP system, providing a comprehensive view of their operations. All are available on scitis.io’s platform for Lorenz employees to access from anywhere. 

To collect the data, scitis.io used their out-of-the-box IoT framework, which included a cloudplug to extract the data from different PLC systems like Siemens S7/1200/1500 or Mitsubishi R/Q series, the Google Cloud infrastructure as the backbone, and the new MES-Framework. Cloudplug is a hardware device that connects to multiple PLC systems at once and sends real-time data to the Cloud Backend. For this, Google Cloud was used to store and analyze the data, while the MES-Framework was used to manage and control the production processes.

The MES-Framework provided several functions to help Lorenz optimize their production processes, including connecting to the planning production system, monitoring production processes in real-time, collecting production data, collecting quality data, tracking production workflows, controlling machines, and analyzing production data to improve efficiency and quality of production. By linking the MES-Framework with their ERP system, Lorenz could access real-time data from their production processes and gain insights into their operations across all worldwide production sites in real time. Real time means 4-6 seconds from PLC to analytic.

After implementing scitis.io’s solution, Lorenz saw significant improvements in their OEE. By having access to real-time data from their production processes, they were able to identify bottlenecks and inefficiencies in their operations. This allowed them to take corrective action, resulting in increased productivity and reduced downtime.

Additionally, the integration of the MES-Framework with their ERP system allowed for better collaboration across departments, reducing duplicate data entry and improving communication.

 Cloud-based solution from scitis.io

Scitis.io’s IoT framework is a hybrid solution that combines the best of both worlds: the speed of ready-made products and the customization capabilities of in-house solutions. Traditional off-the-shelf IoT products are usually easy and quick to deploy, but they often fall short of addressing the specific requirements of industries. Conversely, in-house solutions provide the flexibility to cater to the company’s needs, but they require significant time and resources to develop.

Scitis.io’s approach strikes a balance between these two aspects. The company’s platform leverages the power of the Google Cloud. Whereby 80 percent of the tasks of an MES system are solved by the framework approach and only 20 percent of the customer requirements—which are very specific to each customer—can still be fully customized to the customer’s specific requirements. This modular approach results in a flexible, scalable, and cost-effective IoT solution that is guaranteed to work.

By adopting a hybrid IoT approach, Scitis.io delivers tailored solutions that address the unique requirements of its clients while minimizing the time and effort needed to develop a customized IoT platform from scratch. Furthermore, the platform offers built-in scalability, ensuring that it can grow and adapt alongside the customer’s business needs.

 Conclusion

Scitis.io’s solution provided Lorenz with a comprehensive view of their operations, allowing them to optimize their production processes and increase their OEE. By implementing an MES-system linked to their ERP system, Lorenz was able to collect real-time data from their production processes and gain insights into their operations. This allowed them to identify areas for improvement and take corrective action, resulting in increased productivity and reduced downtime.

The integration of the MES-system with their ERP system allowed for better collaboration across departments, reducing duplicate data entry, and improving communication. Scitis.io’s out-of-the-box IoT framework, which included cloudplug, Google Cloud, and their MES-system, provided Lorenz with a cost-effective solution that met their specific needs.

Overall, scitis.io’s solution highlights the benefits of using IoT and MES technologies to improve production processes and increase efficiency. As more manufacturers look to control their production through data, solutions like scitis.io’s will continue to play a crucial role in optimizing operations and driving success.

Scitis.io

Hall 17, Stand E16

For more information: www.scitis.io