An approximate analysis for a class of assembly-like queues
Queueing Systems: Theory and Applications
Approximate Analysis of Fork/Join Synchronization in Parallel Queues
IEEE Transactions on Computers
On the diffusion approximation to a fork and join queueing model
SIAM Journal on Applied Mathematics
Interpolation approximations for symmetric Fork-Join queues
Performance '93 Proceedings of the 16th IFIP Working Group 7.3 international symposium on Computer performance modeling measurement and evaluation
On a synchronization queue with two finite buffers
Queueing Systems: Theory and Applications
Performance Analysis and Scheduling of Stochastic Fork-Join Jobs in a Multicomputer System
IEEE Transactions on Parallel and Distributed Systems
Approximate Analysis of Multi-Class Synchronized Closed Queueing Networks
MASCOTS '95 Proceedings of the 3rd International Workshop on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems
Calculating equilibrium probabilities for &lgr;(n)/Ck/1/N queues
PERFORMANCE '80 Proceedings of the 1980 international symposium on Computer performance modelling, measurement and evaluation
Queueing Systems: Theory and Applications
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Synchronization stations are commonly used to model kitting operations in manufacturing systems. At a kitting station, the components required for assembly are grouped together prior to release to the assembly line. When the supply process of components is stochastic, exact analysis is hard in a general setting. This paper presents an approximate analysis of a kitting station with multiple components. The stochastic supply process of each component is characterized by mean and variability parameters of the corresponding fabrication facility, and the system imposes a limit on total inventory for each component. The resulting synchronization station model is analyzed using an aggregation procedure that uses the analysis of a synchronization station with two inputs as a key building block. Numerical results indicate that the estimates of throughput and queue length obtained from the analysis validate well with those obtained from detailed simulations. The analysis also helps to quantify the effect of the number of components and variability on kitting delays.