Discrete-event process simulation has long been able to analyze knotty problems arising in manufa... more Discrete-event process simulation has long been able to analyze knotty problems arising in manufacturing, warehousing, health care, transportation (rail, air, bus, etc.), and service industries such as banks, restaurants, and hotels. These knotty problems include challenges such as reducing inventory, increasing production (throughput), deploying workers efficiently, and reducing both lengths of queues and time spent in those queues. Indeed, from a historical perspective, the first, and still some of the most conspicuous, successes of simulation have been achieved in its applications to manufacturing. The application of simulation described in this paper arose in the context of manufacturing safes from their raw-material shells. Simulation, in contrast to other methods such as closed-form optimization, is highly capable of accommodating high process variability and almost automatically providing “best-case” and “worst-case” (as well as averages) for important performance metrics such as lengths of queues and waiting times in queues. Additionally, the animation which routinely accompanies simulation helps non-technical managers understand the results. In this context, the most painfully pressing problem was excess inventory, coupled with too slow and too meager output. The simulation study guided engineers and managers as they endeavored to both reduce the inventory and increase the rate of output – only very rarely can these two objectives be achieved concurrently.
Discrete-event process simulation has long been able to analyze knotty problems arising in manufa... more Discrete-event process simulation has long been able to analyze knotty problems arising in manufacturing, warehousing, health care, transportation (rail, air, bus, etc.), and service industries such as banks, restaurants, and hotels. These knotty problems include challenges such as reducing inventory, increasing production (throughput), deploying workers efficiently, and reducing both lengths of queues and time spent in those queues. Indeed, from a historical perspective, the first, and still some of the most conspicuous, successes of simulation have been achieved in its applications to manufacturing. The application of simulation described in this paper arose in the context of manufacturing safes from their raw-material shells. Simulation, in contrast to other methods such as closed-form optimization, is highly capable of accommodating high process variability and almost automatically providing “best-case” and “worst-case” (as well as averages) for important performance metrics such as lengths of queues and waiting times in queues. Additionally, the animation which routinely accompanies simulation helps non-technical managers understand the results. In this context, the most painfully pressing problem was excess inventory, coupled with too slow and too meager output. The simulation study guided engineers and managers as they endeavored to both reduce the inventory and increase the rate of output – only very rarely can these two objectives be achieved concurrently.
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Papers by Swapnil Landge