Case Sadef: generating operational insights for an improved OEE

This customer is active in the production of cold-formed steel profiles for a wide portfolio of applications. With their rolled steel profiles, they are a supplier to the construction sector, automotive and truck parts, among others, and they provide custom solutions for various customers.

Precisely because these industries require a high degree of accuracy, this customer wants to deliver more and better products while still reducing operational costs and improving its OEE. In addition, the company wants to prepare for a more sustainable production process in the context of the European Green Deal, which aims for a CO2 neutral Europe by 2050.

In comes Capture 

Centralize all available data in real time to gain operational insights in order to improve operational excellence and OEE.

The challenges lay in the great variety and different generations of machine controls: new machines and PLC's and retrofitted ones. Although the know-how was present at the customer, the internal capacity - to carry out such a project - was the next challenge.

In addition, the architecture of the system had to end up in the servers on-premise taking in account with the client's security protocols, while everything had to remain manageable and affordable.

Anyone who has ever set up an industrial IoT project knows that this is indeed a challenge.

capture is providing operational and actionable insights to every layer of your organization across every stage of your production lifecycle. capture's visual insights help you to reduce time and operational costs, and push your operational performances to the next level.

1. proof of concept
   1. To demonstrate the power of capture and gain the client's trust, we first proposed setting up a PoC (proof-of-concept) in which some valuable cases were identified.
   2. Thanks to the lightweight and ready-to-use framework, we were immediately able to demonstrate the powerful data logging capabilities. Within 2 hours, we were already collecting and investigating data.
2. scale
   1. After a positive PoC the project scaled to 2 production lines and monitoring 1 other project, the integration was tackled in phases.
   2. It is precisely because of the flexible and open architecture of the capture platform that we were able to scale immediately in the production environment.
   3. Additional development costs were therefore no longer necessary, but the implementation of the entire machine fleet had to be planned. Data insights at macro and micro levels now became possible and available.
3. visualize to get insights
   1. PLC and sensor data was sent via edge to capture where all data was maintained on premise (at the request of the client).
   2. capture includes the standard option to visualize the real-time data via a Grafana dashboard so that operators and engineers can detect a potential problem more quickly and take action on it.

1. line 1
   1. Reduced scrap & operational costs. Tracing of parts.
2. line 2
   1. Debugging of welding programs using high rate data logging. Parameters can be current, tension, alerts, ...
3. logging of gates statuses
   1. To reduce environmental noise, alerts can be generated if the gates are open for too long.