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Demand responsive planning: workload control implementation

Demand responsive planning: workload control implementation Purpose – Evolvable production systems enable fully reconfiguration capabilities on the shop floor through process‐oriented modularity and multi‐agent‐based distributed control. To be able to benefit architectural and operational characteristics of evolvable systems, there is a need of a new planning approach which links shop floor characteristics and planning operations. This paper seeks to address these issues. Design/methodology/approach – Evolvable production system has a structured methodology in itself. Consistent to this, a reference planning architecture is developed aiming to achieve agility on planning activities. Besides a workload control method is proposed and implemented as a part of the planning architecture. Findings – First applications of evolvable systems have been implemented through European research projects. Shop floor working principles and architectural characteristics are consistent to facilitate more agility on planning activities which are framed at a planning reference architecture called demand responsive planning. As an implementation case, an agent‐based workload control method is proposed and implemented. The characteristics of EPS and proposed planning architecture enable continuous and dynamic workload control of the shop floor to be implemented. Originality/value – This paper presents a new planning model compatible with evolvable production systems targeting to agility to demand on planning and control activities benefiting shop floor enhancements of a fully reconfigurable system which enables to relax constraints imposed from production systems to planning. In addition, a continuous and dynamic workload control method is proposed and implemented. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Assembly Automation Emerald Publishing

Demand responsive planning: workload control implementation

Hakan Akillioglu; Joao Ferreira; Mauro Onori
Assembly Automation , Volume 33 (3): 13 – Jul 26, 2013
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13 pages

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Publisher
Emerald Publishing
Copyright
Copyright © 2013 Emerald Group Publishing Limited. All rights reserved.
ISSN
0144-5154
DOI
10.1108/AA-12-2013-040
Publisher site
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Abstract

Purpose – Evolvable production systems enable fully reconfiguration capabilities on the shop floor through process‐oriented modularity and multi‐agent‐based distributed control. To be able to benefit architectural and operational characteristics of evolvable systems, there is a need of a new planning approach which links shop floor characteristics and planning operations. This paper seeks to address these issues. Design/methodology/approach – Evolvable production system has a structured methodology in itself. Consistent to this, a reference planning architecture is developed aiming to achieve agility on planning activities. Besides a workload control method is proposed and implemented as a part of the planning architecture. Findings – First applications of evolvable systems have been implemented through European research projects. Shop floor working principles and architectural characteristics are consistent to facilitate more agility on planning activities which are framed at a planning reference architecture called demand responsive planning. As an implementation case, an agent‐based workload control method is proposed and implemented. The characteristics of EPS and proposed planning architecture enable continuous and dynamic workload control of the shop floor to be implemented. Originality/value – This paper presents a new planning model compatible with evolvable production systems targeting to agility to demand on planning and control activities benefiting shop floor enhancements of a fully reconfigurable system which enables to relax constraints imposed from production systems to planning. In addition, a continuous and dynamic workload control method is proposed and implemented.

Journal

Assembly Automation – Emerald Publishing

Published: Jul 26, 2013

Keywords: Production planning; Responsive planning; Workload control; Robotics

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