Project Title: The Smart Landing Gear Shopfloor; Deployment towards Industrie 4.0
Academic Supervisor: Professor Mahdi Mahfouf
AMRC Supervisor: Dr Ben Morgan
Industrial Sponsor: Safran Landing Systems, (formerly Messier-Bugatti-Dowty)
Industrie 4.0, or the ‘Fourth Industrial Revolution’ is a paradigm which encompasses themes from cyber-physical systems, the ‘internet of things’ (IoT) and big-data computing. The aim is to increase the understanding of factory behaviour by monitoring processes to improve production rate, quality and traceability by supporting engineers with information in the factory. This is addressed via the management of live, real-time, sensory ‘big data’ by using contemporary information and communication technology (ICT) infrastructure to move towards optimal, data-driven and ultimately predictive or autonomic decisions within the manufacturing environment.
The first step for manufacturing organisations and researchers is to identify the areas of greatest opportunity within their facilities to maximise the impact of implementation. For many manufacturing environments, their priority is to monitor their value-adding processes, such as their machining centres. Examples include the availability monitoring of equipment, progress of a part through a process, or the machine’s health, where these examples and many more possibilities may be shared digitally, wherever a user has connectivity. Various terminals or ‘human-machine interfaces’ (HMI) may be used to express information to users across any number of devices and formats, such as basic alarm notifications, voice synthesis/recognition, virtual reality (VR) / augmented reality (AR), wearables, or large ‘andon’ dashboards.
By providing engineers information in real-time or using insights from historical data to monitor long term behaviour, a ‘smart factory’ will provide manufacturing environments with interconnected systems for integrated, robust, reproducible processes and quick feedback, circumventing the pitfalls of the existing traditional, hierarchical production management structures which inhibit continuous improvement.
A research area of particular interest is the ability to add ‘dumb’ equipment to existing smart factory infrastructure. For many manufacturers, machinery such as machine tools are expensive capital investments and are far older than the systems which will natively interact with existing Industrie 4.0 protocols. The strategy for connecting such ‘legacy’ systems is expected to leverage existing ‘condition monitoring’ techniques in conjunction with in-development IoT systems. In addition to developing a peripheral system for legacy equipment, data fusion approaches of monitoring non-value adding processes would likely lead to the greatest benefits; huge reductions in lead time and smoothing-out of in-factory inventory. There are a number of other long term avenues for research in the ‘smart factory’. One such example of particular interest to the aerospace industry is the augmentation of existing Product Lifecycle Management (PLM) concepts, whereby the process data may be added to the respective part, providing a ‘passport’ of associated part-process information.
Advancing quality & producibility in superalloy compressor parts through accelerated engineering change – Rolls-Royce CLE & University of Nottingham