About
Albert Weinert
Postgraduate Researcher
Albert is contributing to the development and deployment of embedded sensors and data analytics for the in-process monitoring of injection mould tooling fabricated by metal additive manufacturing (3D printing). In-mould sensors are superior to sensors located in other areas of the injection moulding Process (e.g. in the barrel or nozzle).
However, in practice, the use of sensors in the mould is relatively rare - a major limiting factor being the complexity of the mould and the modifications required to integrate the sensor. Albert is contributing to development and design of a mould with embedded sensors that can be analysed for developing predictive models of tool wear and optimal preventive maintenance scheduling.
Research Interests (Lay Summary)
Albert is contributing to the development and deployment of embedded sensors and data analytics for the in-process monitoring of injection mould tooling fabricated by metal additive manufacturing (3D printing). In-mould sensors are superior to sensors located in other areas of the injection moulding Process (e.g. in the barrel or nozzle). However, in practice, the use of sensors in the mould is relatively rare - a major limiting factor being the complexity of the mould and the modifications required to integrate the sensor.
Albert is contributing to development and design of a mould with embedded sensors that can be analysed for developing predictive models of tool wear and optimal preventive maintenance scheduling.
Technical Summary
The aim of Albert’s research is to develop and design a functioning sensorised mould fabricated by metal additive manufacturing.
The design for the additive manufacturing process for injection mould tool fabrication has considerably more scope for supporting the adoption optimal conformal cooling and inline tool monitoring capability relative to traditional tool design and machining capabilities. The development of inline mould monitoring capability is of interest to mould manufacturers as it provides the basis for developing novel business services for the remote monitoring and diagnostics of their customers’ moulds, which is currently not possible to do through conventionally machined moulds.