Lorenz receives MES system26 April 2023

Scitis.io MES system Lorenz By linking production data collected by the MES system with the ERP system, manufacturers can gain a more accurate view of their operations

Industrial Internet of Things (IIoT) start-up Scitis.io has provided an MES (manufacturing execution system) that has helped snack manufacturer Lorenz control its production through data.

By linking the MES-system to Lorenz's ERP (enterprise resource planning) system, Scitis.io provided the snack manufacturer with a comprehensive view of their operations, allowing them to optimise their production processes and increase their overall equipment efficiency (OEE).

MES systems are software solutions used in the manufacturing industry to control, monitor, and optimise production processes. An MES-system collects data from various sources such as production equipment, automation systems, and sensors and analyses it to gain insights into the production processes.

On the other hand, ERP is a type of software solution used by businesses to manage and integrate their core business 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.

By linking production data collected by the MES system with the ERP system, manufacturers can gain a more accurate view of their operations, which can lead to improved decision-making. Additionally, the integration can help organisations streamline their operations by reducing duplicate data entry and improving collaboration across departments.

Prior to the Scitis.io MES system, Lorenz faced challenges in controlling its 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.

The MES-system was designed to collect data from various sources, including production equipment, automation systems, and sensors, and analyse it to gain insights into the production processes.

To collect the data, scitis.io used its 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 analyse the data, while the MES-Framework was used to manage and control the production processes.

The MES-Framework provided several functions to help Lorenz optimise 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.

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.

Operations Engineer

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