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High demand requires additional production capacity

IoT Use Case Lackmann, 02 Telefónica
4 minutes Reading time
4 minutes Reading time

A sheet metal product manufacturer wants to efficiently produce steel parts without having to outsource the knowhow-specific process step. This should be designed as efficiently as possible and at the same time take advantage of digitization. Both are possible with the Pay-per-Part model: machines are paid for according to use and no specific know-how in laser cutting is required.

The challenge: Increasing capacity for new orders

A long-standing player in product manufacturing is facing a problem precisely because of the very good order situation: high demand requires additional manufacturing capacity. While outsourcing would be a way to increase capacity, it is an unloved alternative for this company. This is due on the one hand to the associated high dependency on the supplier with regard to quality and delivery reliability, and on the other hand to the risks of supply chain integration and a lack of flexibility.

Nevertheless, in order to increase production capacity and be able to achieve business growth, it is possible to increase the efficiency of production. This is where the new offer from premium machine manufacturer TRUMPF and its partner Munich Re comes in: Pay-per-Part.

The solution: Networking, full automation and Pay-per-Part

Pay-per-part (PPP) is a usage-based model in which the number and specification of manufactured workpieces is the basis for payment. The basis for this provides TRUMPF with the TruLaser Center 7030: It is the first networked and fully automated machine that covers all process steps of laser cutting. It handles the entire cutting process from drawing to sorted part, including independent loading and unloading.

This feature set allows a new approach to production, namely “Equipment-as-a-Service” with no investment costs and maximum flexibility and production quality. The user gets the machine delivered directly to the house and then pays only for the parts produced on the machine. For this purpose, the machine is networked via an Industrial IoT (IIoT) component so that it can continuously collect data. With the Berlin-based company Relayr, a subsidiary of Munich Re, data-based reinsurance production guarantees will also be part of the package: users will be compensated in the event of downtime that is not their fault.

To further optimize the machine on an ongoing basis, TRUMPF can provide remote support. In addition, there are trained technicians who regularly check the machine status and can quickly intervene in case of problems. They schedule maintenance in advance to avoid production downtime.

A significant advantage of Pay-per-Part for the customer is the high efficiency with which the machines are operated. Multi-shift operation as well as production on weekends is possible without any problems and can be implemented if the customer’s order situationso allows. The IIoT component is also expected to help significantly reduce machine downtime. This leads to increased productivity per unit area in the customer’s production hall and thus opens up the possibility of increasing capacity.

The result: In-house quality manufacturing with low risk

While laser cutting is not the core activity of the product manufacturer, the process step is highly important for product quality. In addition to the investment risks that a machine purchase entails, product-specific know-how is also necessary.

Instead of outsourcing the activity to a specialist company, Pay-per-Part offers the customer a highly efficient usage-based model in which payment is made solely on the basis of the parts produced on the machine. A high initial investment is thus just as much a thing of the past as the risk of inefficient machine utilization with downtimes and failures. Scaling production could hardly be easier either, as additional machines can be added at any time.

Pay-per-Part therefore helps to make production more efficient and is a real growth driver for customers’ business.

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