Production Control for a Tandem Two-Machine System

Ryzin, Garrett van; Lou, Sha; Gershwin, Stanley B.

doi:10.1080/07408179308964312

Cited by 63 publications

(23 citation statements)

References 11 publications

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“…It is hoped that the insights gained from this idealized system, with careful attention to its limitations, will be applicable to more realistic systems. It is encouraging to note that van Ryzin, Lou and Gershwin (1991) and Lou and van Ryzin (1989) obtained similar numerical results for a similar system in which the only source of uncertainty is unreliable machines, indicating that there is at least some robustness to our findings.…”

supporting

confidence: 74%

Optimal Control of a Two-Station Tandem Production/Inventory System

Veatch

Wein

1994

Operations Research

109

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A manufacturing facility consisting of two stations in tandem operates in a make-to-stock mode: After production, items are placed in a finished goods inventory that services an exogenous Poisson demand. Demand that cannot be met from inventory is backordered. Each station is modeled as a queue with controllable production rate and exponential service times. The problem is to control these rates to minimize inventory holding and backordering costs. Optimal controls are computed using dynamic programming and compared with the kanban, basestock and buffer control mechanisms that have been proposed for manufacturing facilities. Conditions are found under which certain simple controls are optimal using stochastic coupling arguments. Insights are gained into when to hold work-in-process and finished goods inventory, comparable to previous studies of production lines in make-to-order and unlimited demand environments.

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supporting

confidence: 74%

Optimal Control of a Two-Station Tandem Production/Inventory System

Veatch

Wein

1994

Operations Research

109

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“…In this strategy, a multi-agent-based architecture of an autonomous control system which integrates central coordination and a local one is proposed to make the requirement of non-linear dynamic control of the re-entrant manufacturing system. Van Ryzin et al (1993) proposed numerical methods to generate optimal policies, an approximate suboptimal control policy to divide the state space into distinct regions and policies to obtain hedging points. The results of this approach suggested that appropriately constructed hedging-point policies are close to optimal.…”

Section: Literature Reviewmentioning

confidence: 99%

A two-layer dynamic scheduling method for minimising the earliness and tardiness of a re-entrant production line

Yan

Wang

2012

International Journal of Production Research

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This study focuses on the dynamic scheduling problem of a re-entrant production line, in which all of the parts are assumed to have the same processing routes and be processed on every machine. A two-layer dynamic scheduling method is proposed for the dynamic scheduling of the re-entrant line with the objective of minimising total earliness and tardiness. This method consists of two layers. The top layer is to select the appropriate scheduling policy, and the bottom layer is to generate the scheduling by using the policy selected in the top layer. In the top layer, three different rules are constructed for selecting scheduling policies, namely the lateness comparison rule, the lateness variation comparison rule, and the equal interval switching rule. In the bottom layer, three different scheduling policies are proposed to generate the real-time scheduling for manufacturing, namely the FCFS (first come first service) scheduling policy, the PI (proportional-integral) scheduling policy, and the fuzzy PI scheduling policy. Considering that the real-time status of manufacturing changes constantly, it is necessary to switch among different scheduling policies to adapt to this change. Numerical experiments are performed in the situations with and without urgent jobs. The results show that the proposed two-layer dynamic scheduling method outperforms any single scheduling policy (e.g., the FCFS policy, the PI policy and the fuzzy PI policy) for the dynamic scheduling of a re-entrant production line.

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“…They compared the performance of their control, denoted as hierarchical control (HC) to optimal control (when possible) and to stochastic extension of Kanban control (KC) developed in Sethi et al (1993) and two boundary control (TBC) developed in Van Ryzin et al (1993). It turns out that TBC and KC can be shown also to be asymptotically optimal under conditions assumed in Samaratunga et al (1997); see Sethi and Zhou (1996) for details.…”

Section: Problem Statementmentioning

confidence: 99%

Optimization of production control policies in failure-prone homogenous transfer lines

2009

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We examine the production control of homogenous transfer lines with machines that are prone to failure, and consider inventory and backlog costs. Because problem complexity grows with line size, we developed a heuristic method based on the profile of the distribution of buffer capacities in moderate size lines in order to enable the optimization of long lines. A method consisting of analytical formalism, combined discrete/continuous simulation modelling, design of experiments (DOE), and response surface methodology (RSM) was used to optimize a set of transfer lines, with one parameter per machine, for up to 7 machines. We observed a profile in the parameter distribution which can be modeled using 4 parameters. Consequently, the optimization problem was reduced to 4 parameters, in turn greatly reducing the required optimization effort. An example of a 20-machine line, optimized at 130 runs, versus 5,243,090 runs that would be necessary to solve the 20-parameter problem, is presented to illustrate the usefulness of the parameterized profile.

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Production Control for a Tandem Two-Machine System

Cited by 63 publications

References 11 publications

Optimal Control of a Two-Station Tandem Production/Inventory System

Optimal Control of a Two-Station Tandem Production/Inventory System

A two-layer dynamic scheduling method for minimising the earliness and tardiness of a re-entrant production line

Optimization of production control policies in failure-prone homogenous transfer lines

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