A first-order hybrid Petri net model for supply chain management (original) (raw)

Operational Management of Supply Chains: A Hybrid Petri Net Approach

The emergence of Supply Chains (SCs) is an outcome of the recent advances in logistics and information technology. SCs are complex networks interconnecting different independent manufacturing and logistics companies integrated with material, information and financial flows (Viswanadham & Raghavan, 2000).

Comparing management policies for supply chains via a hybrid Petri net model

2007

Abstract This paper presents a supply chain (SC) model at the operational level based on first order hybrid Petri nets (PNs), ie, PNs that make use of first order fluid approximation. The model addresses the issue of the management strategies that control the material flow and the inventory stocks in the SC. In particular, we apply the standard make-to-stock and make-to-order policies to a SC case study. Suitable inventory control rules manage the logistics, while optimal production rates are chosen according to a given objective function.

Modeling and performance analysis of a closed-loop supply chain using first-order hybrid Petri nets

Advances in Mechanical Engineering, 2016

Green or closed-loop supply chain had been the focus of many manufacturers during the last decade. The application of closed-loop supply chain in today’s manufacturing is not only due to growing environmental concerns and the recognition of its benefits in reducing greenhouse gas emissions, energy consumption, and meeting a more strict environmental regulations but it also offers economic competitive advantages if appropriately managed. First-order hybrid Petri nets represent a powerful graphical and mathematical formalism to map and analyze the dynamics of complex systems such as closed-loop supply chain networks. This article aims at illustrating the use of first-order hybrid Petri nets to model a closed-loop supply chain network and evaluate its operational, financial, and environmental performance measures under different management policies. Actual data from auto manufacturer in the United States are used to validate network’s performance under both tactical and strategic decis...

Hybrid Petri-nets for modelling and performance evaluation of supply chains

International Journal of Production Research, 2011

Modelling and analysis of complex and coordinated supply chains is a crucial task due to its inherent complexity and uncertainty. Therefore, the current research direction is to devise an efficient modelling technique that maps the dynamics of a real life supply chain and assists industrial practitioners in evaluating and comparing their network with other competing networks. Here an effective modelling technique, the hybrid Petri-net, is proposed to efficiently handle the dynamic behaviour of the supply chain. This modelling methodology embeds two enticing features, i.e. cost and batch sizes, in deterministic and stochastic Petri-net for the modelling and performance evaluation of supply chain networks. The model is subsequently used for risk management to investigate the issues of supply chain vulnerability and risk that has become a major research subject in recent years. In the test bed, a simple productive supply chain and an industrial supply chain are modelled with fundamental inventory replenishment policy. Subsequently, its performance is evaluated along with the identification and assessment of risk factors using analytical and simulation techniques respectively. Thus, this paper presents a complete package for industrial practitioners to model, evaluate performance and manage risky events in a supply chain.

Modelling systems by hybrid Petri nets. An application to supply chains

2008

Petri Nets (PNs) are a discrete event model firstly proposed by CA Petri in his Ph. D. thesis in the early 1960s (Petri, 1962). The main feature of a (discrete) PN is that its state is a vector of non-negative integers. This is a major advantage with respect to other formalisms such as automata, where the state space is a symbolic unstructured set, and has been exploited to develop many analysis techniques that do not require to enumerate the state space (structural analysis)(Silva et al., 1996).

Modeling and Performance Evaluation of a Supply Chain via Petri Nets

Abstract–Supply Chains (SC) are distributed manufacturing systems integrating international logistics and information technologies with production. Analytical SC models include discrete event models, that are particularly suitable for the verification of manufacturing systems. This paper presents a discrete event model for SC operational analysis based on timed Petri nets. A case study proposed in the related literature is modeled by way of the presented technique.

Performance Analysis and Design of Supply Chains: A Petri Net Approach

The Journal of the Operational Research Society, 2000

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 modellingÐ with the GSPN at the higher level and a generalised queuing network at the lower levelÐto solve the decoupling point location problem.

Performance analysis of supply chain networks using Petri nets

Proceedings of the 38th IEEE Conference on Decision and Control (Cat. No.99CH36304), 1999

In this paper, we investigate dynamic modeling tcchniques for analyzing supply chain networks using generalized stochastic Petri nets (GSPN). 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 modeling method accounts for both the logistics process as well as the interface processes that exist between any two members of the supply chain. We compare two production planning and control policies, the make-tostock and the assemble-to-order systems and discuss their merits. Locating the decoupling point in the supply chain is a crucial decision. We formulate the problem as a total cost minimization problem with the total cost comprising the inventory carrying cost and delay costs. We use the framework of integrated GSPN-queueing network modeling, with the GSPN at the higher level and a generalized queueing network at the lower level.