Simulation and modelling methods in aluminium rolling industry

• Published in: International journal of advanced manufacturing technology Vol. 53; no. 9-12; pp. 993 - 1018
• Main Authors: Papanagnou, Christos Ioannis, Halikias, George D.
• Format: Journal Article
• Language: English
• Published: London Springer-Verlag 01-04-2011; Springer Nature B.V
• Subjects: Aluminum; CAE) and Design; Coils; Coils (strip); Complexity; Computer simulation; Computer-Aided Engineering (CAD; Engineering; Industrial and Production Engineering; Industrial plants; Machine tools; Machining centres; Mechanical Engineering; Media Management; Modelling; Original Article; Performance evaluation; Production management; Simulation; Machine utilisation; Production management; Throughput; Simulation and modelling; Manufacturing processes; Aluminium industry
• ISSN: 0268-3768; 1433-3015
• DOI: 10.1007/s00170-010-2880-3

Aluminium coil production plants can be described as multi-stage processes which are often characterised by complexity and are expected to manipulate huge amount of data. Effective scheduling is a key issue for these processes since it can improve throughput rates and machine utilisation. This paper studies the production line of companies which produce high-quality rolled aluminium lithographic strips. An efficient representation for such production processes is provided and subsequently used for an extensive analysis and performance evaluation through appropriate metrics. In particular, the work addresses the implementation of an overall model in a simulation environment, capable of integrating the various aspects of the specific production management processes. The model was successfully validated using actual production data, and it was found that it is suitable for the modelling, analysis and performance evaluation of the complex aluminium coils production process. With the aid of the model, various scenarios were investigated via extensive simulation runs, such as installing additional machine centres and reducing pre-set times the products spend in intermediate storage areas.