Agile Manufacturing Systems are evolving to me.:-'l the challenges of an increasing time based competition in higp variety environments·.n,is paper is motivated by a tudy of an hidian Ent rise in the Telecom Sector where a conventional low variety company is seeking avenues for re-organizing itself towards agility. We propose a novel concept of Dynamic Re-configuration with Integrated Scheduling (DRISJ in manufacturing sy tems, to achieve greater agility. It is suggested that the inherent flexibility in many multi-skilloo workforce based assembly systems allows dynamic re configuration opponunities. However without effective decisions on when to re-configure, how much to re-configure and what order to schedule on a re-configured system, it is not possible to exploit this opponunity. We propose the use of a Genetic Algorithm (GA) based technique to obtain reasonably good schedules for such a dynamic re-configurable production systc:m. TI1e techoique has bari demonru-ated using a simple model of a production system comprising multiple producticm lines, ead1 capable of being re-configured into two or three indep 'lldent producticm lines or re-combined into single lines, dynamically. The results indicate that the performance of the GA bas,:d technique is superior to the standard scheduling rules of "Shoru,st Processing Time" (SPT) and "Earliest Due Date" (EDD). The results also indicate that as the variability of demand on production system increases, GA based tedmique comes to bd!er soluticms for the integrated schoouling of dynamic re-configuration systems. It is proposoo that DRIS approach can offer immense opponunities for the agile enterprise capabilities.
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