With an in-person event and a new online sourcing platform, Cinte Techtextil China in Shanghai/China, on September 2-4, 2020 was the first textile show on the Asian continent since the pandemic outbreak. The nonwovens machinery manufacturer DiloGroup, Eberbach/Germany, presented its nonwovens production lines for hygiene products, filters and roofing material. The latest developments of DiloGroup were also widely discussed.
In focus was HyperLayer designed for the highest speeds with hygiene web from fine fibers. This crosslapper is especially suited for very light weight webs with only a few layers. The new card feeder VRS-P combines the principles of a volumetric, precisely charged feeding with the characteristics of a vibration chute feeder and saves a conventional large trunk. The Dilo Compact Line (DCL) meets the requirement for the production of small amounts of high quality felts made from special fibers such as carbon fiber, ceramic or PTFE. Very interesting topics like the recycling of carbon fibers are already researched on these lines in various projects. With a working width of the compact carding machine of 1.1 m and a layering width of 2.2 m, only 60 m² of space is required for the installation.
The Hypertex technology combines a grid of endless yarns and nonwovens as a sandwich using the needlepunch process. An additional weaving process becomes unnecessary. The grid improves the tensile strength of products such as filters or roof sheets and will lower costs and production time. In the field of textile additive manufacturing the 3D-Lofter will provide fiber savings for needlefelts used in automotive and other applications.
diloline 4.0 includes a wide variety of smart manufacturing actions in collaboration with Siemens AG, Munich/Germany, which all aim at further simplifying operation, increasing transparency in web forming and consolidation, thereby increasing efficiency. Production data are stored, documented and compared. An alarm monitor indicates irregular behavior. A production analysis documents the reasons for standstill times. Numerous information modules can be recalled via mobile apps and cloud data (mindSpheres).