Project
The project will explore how context awareness can be used to assure both self-adaptation of production systems, with integrated control & maintenance, and quality (reliability, availability, security) of SW services (QoS) implementing self-adapting solutions. Self-Learning will focus on specific needs of discrete manufacturing industry. The project will be driven by industrial application scenarios -- Business Cases, including both production equipment manufacturers and users (, addressing different aspects of self-learning (integrated) control & maintenance of complex assembly & manufacturing lines, in order to assure industrially relevant development of self-learning production systems
Objectives
The main objectives of the project is to provide a holistic approach to use context awareness to both:
- allow for self-adaptation of production systems, integrating control & maintenance of production plants, and
- assure highest reliability, availability and security (QoS) of distributed network infrastructure needed for such self-learning production systems aiming to merge the world of maintenance with the world of control.
Following the proposed approach, the project intends to:
- elaborate self-learning solutions for adaptation of integrated control & maintenance, including set of prototypes of high level SW services for real-time self-learning adapter aiming to dynamically adapt
- control parameters (both feed-forward and feedback loop parts), and/or
- maintenance of production systems (both planning and execution), as well as
- parameter identifier (identifying/monitoring of manufacturing/assembly processes and/or tools/parts parameters/characteristics),
- develop a dynamic context model and a prototype of the real-time self-learning context extractor needed for self-adaptation of production systems (adaptation of SW services for parameter identifier, control and maintenance based on current context) and for QoS assurance,
- develop a methodology for introduction of the integrated control & maintenance approach, addressing specifically organisational issues within EE using lean principles, and
- provide a SOA infrastructure for implementation of services for the proposed self-learning production systems.