Variations of the kanban system: Literature review and classification

(1983). Large-Scale Systems: Modeling and Control. Journal of the Operational Research Society: Vol. 34, No. 10, pp. 1016-1016.

/pdf/large-scale-systems-modeling-and-control-vm2c6m6a7f.pdf

Large-Scale Systems: Modeling and Control

In this paper, we investigated a dynamic modelling technique for analysing supply chain networks using generalised stochastic Petri nets (GSPNs). The customer order arrival process is assumed to be Poisson and the service processes at the various facilities of the supply chain are assumed to be exponential. Our model takes into account both the procurement process and delivery logistics that exist between any two members of the supply chain. We compare the performance of two production planning and control policies, the make-to-stock and the assemble-to-order systems in terms of total cost which is the sum of inventory carrying cost and cost incurred due to delayed deliveries. We formulate and solve the decoupling point location problem in supply chains as a total relevant cost (sum of inventory carrying cost and the delay costs) minimisation problem. We use the framework of integrated GSPN-queuing network modelling-with the GSPN at the higher level and a generalised queuing network at the lower level-to solve the decoupling point location problem.

https://link.springer.com/content/pdf/10.1057%2Fpalgrave.jors.2600063.pdf

Performance analysis and design of supply chains: a Petri net approach

Manufacturing planning and control: The evolution of MRP and JIT integration

Optimally locating in-house logistics areas to facilitate JIT-supply of mixed-model assembly lines

A multistage production/inventory system is modelled. The system structure, which has the form of an assembly network, is abstracted from the production process of a typical integrated iron and steel works. The system is modelled as a Markov Decision Process (MDP). Combinations of Just-In-Time (pull) and MRP (push) policies are used as alternatives in the MDP. Optimal hybrid strategies are developed. In part II, we extend our observations to a more general case.

Optimal hybrid push/pull control strategies for a parallel multistage system: Part II

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Optimal hybrid push/pull control strategies for a parallel multistage system: Part II