Abstract

Analysis of a bulk queueing system with server breakdown and vacation interruption

Highlights

  • The roles of quality and service performance are the crucial aspects in customer perceptions, and firms must dedicate special attention to them when designing and implementing their operations

  • After completing the renovation of service station or there is no breakdown of the server with probability (1− π ), if the server finds at least ‘ a ’ customers waiting for service say ξ, the server serves a batch of min (ξ,b) customers, where b ≥ a

  • Once the required level is reached to start the primary service, there is no point in continuing the secondary job

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Summary

INTRODUCTION

The roles of quality and service performance are the crucial aspects in customer perceptions, and firms must dedicate special attention to them when designing and implementing their operations. Upon completion of the dyeing process, if the supply of cloth is less than 800kg it stops the process and performs some other work (secondary job/vacation) like wetting process, washing using suitable chemicals, etc. After completing his secondary job, if the required number of cloths is less than the threshold value 800 kg, the operator waits in the system till the required number of cloth arrives This dyeing machine can be modelled as bulk arrival batch service queueing model with breakdown and vacation interruption. In all the aforesaid models with breakdown, the server cannot come back (vacation interruption) to the normal working level (regular busy period), until the vacation period ends This stimulates the authors to develop a single server bulk arrival bulk service queueing system with breakdown and vacation interruption. This model is proposed to overcome this difficulty and to make the system operate more efficiently

MODEL DESCRIPTIONS
Notations
Steady State Queue Size Distribution
PROBABILITY GENERATING FUNCTION
Steady State Condition
Computational aspects of Unknown Probabilities
PERFORMANCE MEASURES
Expected Queue Length
Expected Length of Idle Period
Expected Length of Busy Period
Probability that the Server is Busy
PARTICULAR CASES
COST MODEL
Effects of various parameters on the performance measures
Effects of arrival rate and service rate on the performance measures
Effects of arrival rates on the total average cost
CONCLUSION
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