Texprocess 2019: Bullmer unveils Industry 4.0 solution for cutting room optimisation

by Apparel Resources News-Desk

31-May-2019  |  2 mins read

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German pioneer Bullmer, a leading provider of cutting room optimisation solutions for industries such as apparel, textiles, automotive and furniture, marked a successful Texprocess this year in Germany with its eminent solutions. Reciprocating the theme of Texprocess 2019, the company unveiled many innovations in the field during the event. “The major focus of this show is on Industry 4.0 and we have the perfect innovations for this trend,” told Jochen Cramer, General Sales Manager, Bullmer to Apparel Resources.

The main highlight from Bullmer was its renowned Procut D 8001 S cutter which is connected with an IoT solution Clouver provided by ProCom. At the end of the cutter, a stripping system with Robots and Grippers can also be placed which are designed especially for stripping materials such as fibre composites, automotives and textile/leather from cutting table. This stripping system can be smoothly integrated with the existing production chains; also the different gripper models encourage potential individual applications and can be adapted to the factory requirement. “We have updated our software which can be better synchronised with these robots, therefore making them much more intelligent now,” said Jochen.

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Further, using IoT solution, the user can effectively link production and work processes and can identify hidden production cost and minimise downtime in production. It also offers comprehensive insights into real-time production flow for better handling of Bullmer machines. “Clouver helps create better connectivity, transparency and therefore better and faster decision-making capabilities,” commented Jochen.

Explaining the need for this IoT-based software solution, Jochen explained that Bullmer has done lot of innovations and upgradation to make its solutions respond better to the current changing needs of the industry. The capabilities of Clouver such as deeper data insights help monitor the machine performance and take appropriate actions as and when required. He further briefed, “The machine performance data further assists the maintenance department to predict when a particular machine needs assistance and when is the right time to connect with the customers.”

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