Skip to main content

Advanced planning and scheduling with collaboration processes in agile supply and demand networks

Buy Article:

$54.08 plus tax (Refund Policy)

Abstract:

Purpose ‐ The general purpose of the paper is to improve supply chain (SC) responsiveness and agility by developing advanced planning and scheduling (APS) with collaboration process into agile supply and demand networks (ASDN). Design/methodology/approach ‐ Some industrial examples are presented to extract the APS requirements, then business models that are supported by analytical models are developed into APS modules to respond to the requirements. At the end, the modules are attached into an ASDN simulator to measure the benefit of the APS with collaboration process. Findings ‐ The results show that the APS with collaboration process is superior to existing APS software in terms of promising lead times to customers at minimum inventory level. Research limitations/implications ‐ Since the APS with collaboration process cannot optimize transportation planning, SCs cannot therefore optimize networks by finding the optimum network configuration. Currently, the simulator needs to be tested in several possible network scenarios to find the optimal network configuration. Practical implications ‐ The APS with collaboration process makes it possible to give guaranteed lead times at minimum inventory level. Furthermore, it is possible to combine the APS with collaboration process with enterprise resources planning or MRP II by considering the criticality of the planning. Originality/value ‐ The attachment of APS with collaboration process business into ASDN represents the original aspect of this paper.

Keywords: Flexible labour; Market share; Production scheduling; Supply chain management; Value chain

Document Type: Research Article

DOI: http://dx.doi.org/10.1108/14637151111105607

Publication date: February 8, 2011

Access Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Partial Open Access Content
Partial Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more