Extruder screws are needed in the food industry as well as in manufacturing where viscous material needs to be transported through pipes. Sizes of such screws range from a few centimetres to metres in diameter while the complex 3D shape is common to all of them. This shape is what makes extruder screws difficult to create and expensive. The functionality of such a screw however is defined by its extrusion efficiency which diminishes over time through wear on the outside. Refurbishing of such screws preserves the material and energy resources that went into their creation but it is difficult to efficiently reach the required geometry. After a grind-down step, the actual geometry needs to be measured to feed the required build up to a laser-based metal deposition system. If this was integrated in one ICT based data processing and robot-based execution system, then repair would become possible on the fly.


The MALCES system aims to apply a geometry scanning system for acquisition of actual construction data as an input to the path planning system. Therein, an automated parameter selection will provide the needed parameters to create a processing path which in turn is transferred to the robot for laser-based cladding of metal. The integration of all these systems will bring an increase in efficiency and a reduction in the need for manual intervention. The key advantage however is, that through the integration into one machine, the processing can be adapted to actual build up rate. Therefore, the MALCES system might be one of the first systems that implement a near-net shape repair of extruder screws.

This laser-based equipment assessment (LEAs) is part of the second batch of assessments supported under Lashare project.




LUNOVU GmbH (supplier), Arenz GmbH (user), Fraunhofer-Institut für Lasertechnik ILT (research partner)

Machinery & equipment