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AbstractThis paper describes the application of simple quality control charts to monitor the traffic intensity of single server queues, a still uncommon use of what is arguably the most successful statistical process control tool.These charts play a vital role in the detection of increases in the traffic intensity of single server queueing systems such as the M/G/1{M/G/1}, GI/M/1{GI/M/1}and GI/G/1{GI/G/1}queues.The corresponding control statistics refer solely to a customer-arrival/departure epoch as opposed to several such epochs, thus they are termed short-memory charts.We compare the RL performance of those charts under three out-of-control scenarios referring to increases in the traffic intensity due to:a decrease in the service rate while the arrival rate remains unchanged;an increase in the arrival rate while the service rate is constant;an increase in the arrival rate accompanied by a proportional decrease in the service rate.These comparisons refer to a broad set of interarrival and service time distributions, namely exponential, Erlang, hyper-exponential, and hypo-exponential.Extensive results and striking illustrations are provided to give the quality control practitioner an idea of how these charts perform in practice.
Economic Quality Control – de Gruyter
Published: Jun 1, 2018
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