Predicting performance measures for Markovian type of manufacturing systems with product failures

Pradhan, Salil; Damodaran, Purushothaman; Srihari, K.

doi:10.1016/j.ejor.2006.11.016

Cited by 10 publications

(15 citation statements)

References 23 publications

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“…Li et al (2007) proposed a graphical approach to evaluate the performance of a single station in semiconductor manufacturing. Pradhan et al (2008) proposed analytical models to estimate performance measures for the problem under study when the job arrivals and service times were exponentially distributed. This paper relaxes the Markovian assumptions made in Pradhan et al (2008).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Pradhan et al (2008) proposed analytical models to estimate performance measures for the problem under study when the job arrivals and service times were exponentially distributed. This paper relaxes the Markovian assumptions made in Pradhan et al (2008). If one wishes to analyze a large network with several servers and queues, calculation of the normalization constant that is required in the computation of system probability p(n), where n is the number of jobs in the system could be very complex or almost impossible (Gelenbe and Pujolle, 1987).…”

Section: Literature Reviewmentioning

confidence: 99%

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Performance characterization of complex manufacturing systems with general distributions and job failures

Pradhan

Damodaran

2009

European Journal of Operational Research

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Performance characterization of complex manufacturing systems with general distributions and job failures

Pradhan

Damodaran

2009

European Journal of Operational Research

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“…That is to say the queueing network model also relies on the aggregate service time of each station. The aggregate service time τj at station Sj has been calculated by the previous studies (see (Damodarana and Hulett, 2012) and (Pradhan et al, 2008)). Eq.…”

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confidence: 99%

Performance analysis and optimization of queueing network production systems considering non-conforming products rework and departure

Zhang

2018

JAMDSM

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During the past decades, the production performance analysis and optimization have played a significant role in queueing network system production planning and operation design for the manufacturing plants, but how to model the optimized production system performance and solve it is facing great challenges. Since the more and more wide use of queueing network, the non-conforming product scenarios such as rework and departure, cause mass random interference. These problems when modelled in the conventional analysis and optimization models are extremely difficult to solve as they are coupled and NP-hard problems. This paper considers a modified M/M/n/m-first come first service (M/M/n/m-FCFS) queueing network approximation model that is developed to maximize utilization and profit by analysing the queue time and queue length of the products under the constraint conditions. A hybrid meta-heuristics is applied to solve the approximation model, both the service rate and buffer allocation of the queueing network system can be determined. Finally, to assess the effectiveness of the proposed method, extensive numerical experimental results from the approximation model are compared to the ARENA simulation, and sensitivity and validation analysis are also conducted, which prove it accurate, believable, and effective.Keywords : Production planning, Operation design, Analysis and optimization, Queueing network, Non-conforming product, Hybrid meta-heuristics, Approximation model IntroductionMost manufacturing companies are facing the challenge of quickly implementing flexible and complex production systems (Walid and Ali, 2002). But the production systems often experience worse performance for the unavoidable variability exists in reality. This phenomenon appears widely in queueing network and multi-product mixed production system. Performance analysis and optimization problems in queueing systems have received considerable attention in recent years, due to their wide applicability in the performance evaluation and optimal design of manufacturing systems and computer networks (Song et al., 1998). Now, the long serial lines analysis and optimization have been well studied using decomposition (Shi and Gershwin, 2014;Damodaran and Hulett, 2012;Cauffriez and Willaeys, 2006) or aggregation (Veeger et al., 2011;Belmansour and Nourelfath, 2008) methods for a long time, and extensive results are obtained. Although many studies have focused on solving the line optimization problems, the studies in which a large number of approaches are currently applied to research the performance of queueing network systems considering the non-conforming products are still extremely limited.Research in the field of performance optimization tends to focus on issue models, such as cycle time (CT) optimization (Gilenson et al., 2015), throughput (TH) optimization (Law et al., 2008), work-in-process (WIP) optimization (Reyes et al., 2013;Qiu, 2005), and buffer allocation optimization (Shihabudin et al., 2015;Nahas, 2014). The published literature...

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“…Additionally, majority of the analysis of fork-join studies assume that the inputs to the individual buffers are Poisson process [77,105,103,104]. Although [68,86] consider random job failures, they do not consider a fork-join subsystem.…”

Section: Problem Descriptionmentioning

confidence: 99%

“…Jobs that fail are routed to the same workstation or to one of the previous workstations. These characteristics of manufacturing systems make them suitable for modeling as a network of queues consisting of a set of nodes (workstations), and arcs (movement of the job between workstations) [86].…”

Section: Overview Of Solution Approachmentioning

confidence: 99%

Analytical Approximations to Predict Performance Measures of Manufacturing Systems with Job Failures and Parallel Processing

Hulett¹

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Predicting performance measures for Markovian type of manufacturing systems with product failures

Cited by 10 publications

References 23 publications

Performance characterization of complex manufacturing systems with general distributions and job failures

Performance characterization of complex manufacturing systems with general distributions and job failures

Performance analysis and optimization of queueing network production systems considering non-conforming products rework and departure

Analytical Approximations to Predict Performance Measures of Manufacturing Systems with Job Failures and Parallel Processing

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