Determination of optimal number of Kanbans using stochastic petri nets

Jothishankar, M.C.; Wang, H.P.

doi:10.1016/0278-6125(92)90036-f

Cited by 11 publications

(7 citation statements)

References 15 publications

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“…Also, earlier reported works of PNs in FFASs addressing push and pull paradigms (Mascolo er al. 1991, Jothishankar and Wang 1992, Venkatesh et al 1992, Yim and Linn 1993 have not explicitly presented (1) the differences between PN modelling of 'push' and 'pull' paradigms and (2) modelling of production and moving lot sizes. This paper uses PNs to focus on these issues.…”

Section: Petri Nets and Other Modelling Toolsmentioning

confidence: 97%

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A Petri net approach to investigating push and pull paradigms in flexible factory automated systems

Venkatesh¹,

Zhou²,

Kaighobadi³

et al. 1996

International Journal of Production Research

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This paper shows Petri nets (PNs) as a powerful tool to investigate the problem often encountered in manufacturing systems management, namely comparing the performance of a flexible factory automated system (FFAS) operating under push and pull paradigms. The difficulty in solving this type of problems is compounded by many parameters such as processing times at work cells, number of automated guided vehicles and their routeings, lot sizes, and setup times. The PN method to solve such a problem is illustrated by considering an FFAS. Its PN models are formulated and then analysed to compare the performance of FFAS with 'push' and 'pull' paradigms. The results show that for the particular FFAS and operational parameters, the 'push' paradigm outperforms the 'poll' one. I t is concluded that PNs are a suitable tool to conduct perrormance analysis before adopting the 'push' or 'pull' paradigm.

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Section: Petri Nets and Other Modelling Toolsmentioning

confidence: 97%

“…Sheng and Black (1990) modelled a cellular manufacturing system operating 4 t h JIT using PNs. Jothishankar and Wang (1992) determined the optimal number of kanbans in JIT manufacturing using stochastic PNs. Venkatesh er~al.…”

Section: Petri Nets and Other Modelling Toolsmentioning

confidence: 99%

A Petri net approach to investigating push and pull paradigms in flexible factory automated systems

Venkatesh¹,

Zhou²,

Kaighobadi³

et al. 1996

International Journal of Production Research

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show abstract

“…That system works in a cycle connected between the supplier, producer, and buyer" (Zapara & Naumova, n.d.). Kanban's act as the nerve of any Just-In-Time system as a means of material transportation and production information exchange between workstations (Jothishankar & Wang, 1992).…”

Section: Literature Reviewmentioning

confidence: 99%

Lean Applications to Improve Chemical Laboratory Production Capacity in the Textile Industry

Islam¹

2023

MEST

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Lean literature suggests that the attitude of “wait and see” has not yet allowed textile professionals to adopt Lean in production, especially in the laboratory. To fill this gap, the author illustrated a case study in a chemical laboratory of a renowned knit composite industry in Bangladesh. A team of textile and industrial engineers observed all processes in the laboratory from start to end for two years to detect problems and then conducted four brainstorming sessions with Lean experts to generate solutions to those issues which are finally presented for capacity improvement through dyeing machines’ capacity optimization, lead time evaluation, lab room temperature optimization, facility layout redesign, quick worksheet preparation, and workplace organization. This study proves that Lean applies to any process improvement. Also, data obtained in this research is highly valuable for textile engineers for future research and readily available for Value Stream Mapping.

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“…As a result, it is possible to determine both qualitative and quantitative properties of a system using PNs. While a large number of PN-based models of manufacturing systems have been developed, a relatively small number of these have focused on JIT systems (Di Mascolo et al 1991, Jothishankar and Wang 1992, Looney 1992, Laftit et al 1993, Chaouiya and Dallery 1997.…”

Section: Petri Net Models Of Kanban Systemsmentioning

confidence: 99%

“…All of the models are for assembly systems generating a single type of product and using a ® xed order point of one. Jothishankar and Wang (1992) use stochastic PNs (SPNs) to model a¯ow shop JIT system with kanbans. The model includes two WSs and is shown to be deadlockfree and solved using analytic methods to determine total waiting time, shortage cost, total cost and utilization, as a function of the number of kanbans in the system.…”

Section: Petri Net Models Of Kanban Systemsmentioning

confidence: 99%

Stochastic coloured Petri net (SCPN) models of traditional and flexible kanban systems

Moore¹,

Gupta²

1999

International Journal of Production Research

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Modelling and analysis of kanban-controlled (just-in-time) production systems under realistic assumptions presents a number of challenges, including the ability to conduct both qualitative and quantitative analysis, and the ability to model control policies. These challenges are due, in part, to station interdependence, blocking and starvation due to limited bu er spaces, and the necessity of modelling both material and kanban¯ows. Petri nets (PNs) have recently emerged as a promising approach for modelling manufacturing systems. PNs are a graphical and mathematical technique useful for modelling concurrent, asynchronous, distributed, parallel, non-deterministic and stochastic systems. PN models can be analysed to determine both their qualitative and quantitative properties. In this paper, we develop stochastic, coloured PN (SCPN) models of a JIT system utilizing two di erent kanban control policies: a traditional kanban system (TKS) policy and a¯exible kanban system (FKS) policy. The resulting models can be used to represent JIT systems of arbitrary size, producing single or multiple types of products, with ® xed order points 1. The models are shown to be live and bounded, and can be simulated to produce quantitative results. Sample simulation results are presented to illustrate the models' capabilities.

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Determination of optimal number of Kanbans using stochastic petri nets

Cited by 11 publications

References 15 publications

A Petri net approach to investigating push and pull paradigms in flexible factory automated systems

A Petri net approach to investigating push and pull paradigms in flexible factory automated systems

Lean Applications to Improve Chemical Laboratory Production Capacity in the Textile Industry

Stochastic coloured Petri net (SCPN) models of traditional and flexible kanban systems

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