Queuing theory and Constant service time model

Queuing theory is used in operational management and its application has both benefits and limitations.  The theory has been used in organizations to assess customer waiting environment, productivity, waiting time and more. First, queuing theory offers scientific understanding of problems and therefore offers solutions to the problems in an optimal manner.   It has capable models which are used to determine the arrival pattern and in balancing both waiting and service costs (Langabeer, 2009).  The theory helps to reduce the waiting time and to effectively utilize the available facilities.  Other advantage is seen as a result of simulation.  Researchers are now able to use numerical solutions to get the approximate answers, change the variables, analyze the results and arrive at queue design optimization. In addition, Queuing theory offers plain language and economic models which mathematicians can use in applying probabilistic distribution.  They can use mathematical terms in modeling complex phenomenon and mathematical equation and then apply the equations in predicting behaviors (Langabeer, 2009).  However, Queuing theory has some limitations in that   the queuing models appear to be complex and the queuing situations have uncertainty which may arise from lack of theoretical probability and process parameters.  Some problems in industries are multi-channel and this mean that  customer may get the service and  the same customer may queue once more and get the service again  and this may bring difficulties when it come to analyze (Langabeer, 2009).  When solving problems, some problems are real life and come from complex situations and this makes it difficult to apply the techniques and after solving the problems   uncertainties are noticed.

Constant service time model is associated with advantages in operations management. First, the model is appropriate in fixed cycle processes for example in automatic car wash.    This is because the service systems are constant and constant rates are certain (Bhat, 2008). Constance service time helps in understanding service system, average waiting time and controlling activities.  The model reduces variability and the customers waiting lines are reduced through creating a constant service time. By using appointments in constant time service, arrival rates moves smoothly and this leads to improvement (Bhat, 2008). There is certainty in constant rates and thus they give variable services rates. The model also provides benefits in Poison distribution which means that there is a successful time in customer arrival which introduces the exponential distribution. Other benefit is that there is a faster services rate than the arrival late which is unknown (Bhat, 2008).

 

 

 

 

 

 

 

 

 

 

 

Reference

Langabeer, J. R. (2009). Performance improvement in hospitals and health systems. Chicago, IL:

Healthcare Information and Management Systems Society.

Bhat, U. N. (2008). An introduction to queueing theory: Modeling and analysis in applications. Boston:

Birkhäuser.