Analytical performance models for closed-loop flexible assembly systems

Kamath, Manjunath; Suri, Rajan; Sanders, Jerry L.

doi:10.1007/bf00713159

Cited by 46 publications

(17 citation statements)

References 24 publications

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“…However, as the SCVs of the input processes increase, the values of 1 K and 2 K required to obtain a given throughput increase significantly. As discussed in Kamath et al (1988), in practical flexible assembly systems, we often find SCVs ranging from 0 to 4.0.…”

Section: Numerical Resultsmentioning

confidence: 96%

Analysis of a Fork/Join Synchronization Station with Inputs from Coxian Servers in a Closed Queuing Network

Krishnamurthy

Suri

Vernon

2004

Annals of Operations Research

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Fork/join stations are commonly used to model the synchronization constraints in queuing models of computer networks, fabrication/assembly systems and material control strategies for manufacturing systems. In many such applications the fork/join station is fed by two or more inputs from finite populations. This paper presents an exact analysis for the case when the input processes are renewal and the inter-arrival times have two-phase Coxian distributions, allowing us to model a wide range of variability in the input processes. The underlying queue length and departure processes are analyzed to determine performance measures such as throughput, mean queue lengths and distribution of inter-departure times from the fork/join station. The results show that, for certain parameter settings, variability in the arrival processes have a significant impact on the performance of the fork/join station. The model is also used to study the sensitivity of performance measures such as throughput, mean queue lengths, and variability of interdeparture times for a wide class of input processes and customer populations.

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Section: Numerical Resultsmentioning

confidence: 96%

Analysis of a Fork/Join Synchronization Station with Inputs from Coxian Servers in a Closed Queuing Network

Krishnamurthy

Suri

Vernon

2004

Annals of Operations Research

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“…The approach uses traffic process approximations in order to overcome the difficulties associated with previous approaches. Although parametric decomposition has been used in other applications (see [7,23,24] and the references therein), it has thus far not been applied to analyze queuing models of kanban systems. The primary reason for this was that a key building block, namely a two-moment approximation method for synchronization stations, was not available.…”

Section: Literature Reviewmentioning

confidence: 99%

Performance analysis of single stage kanban controlled production systems using parametric decomposition

Krishnamurthy

Suri

2006

Queueing Syst

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We present a new approach that permits efficient performance analysis of kanban systems with general demand processes, material arrival processes, and service times. The approach is based on parametric characterization of the traffic processes (arrival and departure) in the network and uses two-moment approximations to estimate performance measures at individual stations. We derive traffic flow constraints that are particular to closed queuing networks with synchronization stations and use these to establish relationships between the parameters characterizing arrival and departure processes at the stations in the network. The resultant set of non-linear equations is solved to estimate network performance measures. Numerical studies show that the approach is not only fast but also reasonably accurate when compared to simulation. These studies also provide insights with respect to the impact of different types of variability on the performance of a kanban system. This work also provides a fundamental building block that can be used in the analysis of multi-stage kanban systems.

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“…Finally, Kamath, et al (1988) evaluate the system performance in a closedloop flexible assembly system by an approximate formulae proposed by , Whitt (1983Whitt ( a, 1984Whitt ( and 1985, Shanthikumar and Gocmen (1983 a), Kamath, et al (1988), Kapadia and Hsi (1978).…”

Section: Lie-fern Hsu Et Almentioning

confidence: 99%