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Norbert Sieczkiewicz

Wed, 08 January, 2020

Student Name

Norbert Sieczkiewicz

Research Title

Approaches to Industry 4.0 implementation for electron beam quality assurance using BeamAssure™


Industry 4.0, electron beam welding, computer vision, artificial intelligence, smart manufacturing


Lloyd's Register Foundation

Affiliated University

Lancaster University


Dr Colin Ribton (TWI Ltd.), Prof Andrew Kennedy and Dr Yingtao Tian (Lancaster University)

Start Date


Project Outline

This PhD project aims to determine the possibilities for using BeamAssure™ beam characterisation, industrial camera footage and other quality assurance systems in the Industry 4.0 paradigm.

Electron beam welding (EBW) has the ability to produce joints with excellent integrity, therefore, it is used in industries requiring the most exacting standards and quality, e.g. aerospace and nuclear. In such applications, defective welds could lead to safety and infrastructure concerns.

The objective of this work is to analyse multiple input quality indicators to derive a quality assurance system. Research focuses on creating data-driven, real-time process health monitoring systems using artificial intelligence tools. The quality indicators examined will include BeamAssure signal processing, encoded time series data as images, image segmentation of data collected by cameras inside EB machines and data collected from process sensors.

It is anticipated that research outcomes could lead to higher weld integrity, better process monitoring and reduced failure rates in service.


Towards Industry 4.0 – surface autofocus method for electron beam welding (EBW). The digital poster that used animation to enhance its message, presented at: Lloyd’s Register Foundation International Conference; 2019 Oct 9-10; London.

Towards Industry 4.0 – surface autofocus method for electron beam welding (EBW). Poster presented at: FST Annual Conference; 2019 Dec 17; Lancaster University.


In progress