Production Engineering Manager

Description:

The project will aim to implement digitalisation of key operational and production control processes by adopting an Industry 5.0 approach that will drive productivity and efficiency improvements, and sustainable business growth in the healthcare sector.

The KTP project addresses HDL's real business need to improve its production processes and efficiency to reduce production costs and enhance sustainability by addressing four strategic objectives:

• Business Growth- exploiting growing market opportunities in the UK healthcare sector through a comprehensive approach to addressing market drivers including cost, sustainability (net zero Carbon) and reshoring overseas manufacture.

• Expanding premises - to build manufacturing capacity.

• Expand Export Markets -e.g. Australia, Middle East, Europe.

• Improving Sustainability - becoming a net zero carbon supplier.

Candidate Profile: Qualified to MSc level, ideally with a first degree in either Production Engineering or Business and Computing, followed by a Masters/ MBA focussed on Business/ Operations Management with relevant IT modules. The candidate should have experience of working in a manufacturing setting with some hands-on experience of digital manufacturing and modern management practices. They should also have an understanding, at least at a conceptual level of Industry 5.0.

The role would suit a candidate seeking to become an ICT/ IS business process change consultant/ manager.

Key skills/ experience required include:

• Experience or technical understanding about working with hardware

• Knowledge of PLC control systems; Developing data collection apps

• Accessing data, data analytics, Data Flow Diagrams, Value Stream Mapping

• High-level programming languages e.g. Python

• Knowledge of statistical software packages e.g. SPSS or R

• Experience of business simulation software e.g. Anylogic

• Swimlane Diagramming Techniques for modelling business processes

• Human Factors Analysis and Classification to model human factors

• Experience with industrial Engineering Diagnostic tools