Title: Methodology for dynamic scheduling and control in biological manufacturing systems
Author: Sameh M. Saad, Anna M. Lassila
Faculty of Arts, Computing, Engineering and Sciences, Sheffield Hallam University, Furnival Building, Sheffield S1 2NU, UK.
Middlesex University Business School, The Burroughs, Hendon, London NW4 4BT, UK
Abstract: Biological manufacturing is an emerging concept that aims to apply the structures and behaviour of natural organisms to manufacturing organisations in order to transfer the inherited flexibility and adaptability of life forms to industrial operations. In this article, a biologically inspired dynamic decentralised scheduling and control methodology based on continuous communication between machines and transporters is proposed. The system aims to satisfy the performance objectives in a real-time scheduling environment without any centralised control. No advanced scheduling takes place and the machine for each processing stage is selected only after the previous stage has been completed. Three types of dynamic scheduling are identified and the operational procedure is developed. The proposed scheduling approaches differ in terms of flexibility of the established processing and transportation contracts, which influences the system's ability to respond to disturbances. Automatic guided vehicles are used to transport products between the machines along a pre-defined network of paths that allow easy access to all stations. The proposed methodology together with a deadlock avoidance mechanism is modelled and simulated using discrete event simulation software. The results indicate that the methodology is feasible and can react to changes in the environment.
Keywords: biological manufacturing systems; dynamic scheduling; natural organisms; inherited flexibility; adaptability; life forms; industrial operations; decentralised scheduling; control methodology; continuous communication; machines; transporters; performance objectives; real-time scheduling; centralised control; operational procedures; AGVs; automated guided vehicles; pre-defined networks; deadlock avoidance mechanisms; discrete event simulation; industrial engineering; systems engineering; responsive manufacturing.
Int. J. of Industrial and Systems Engineering, 2010 Vol.5, No.3, pp.268 - 286
Available online: 03 Mar 2010