Julien Francois

Distributed simulation platform to design advanced RFID based freight transportation systems

RFID systems, known to improve supply chains performances, are little implemented so far in industry, particularly in the field of transport, due to the high economic investment it requests in comparison to other existing solutions. However, their benefits may be theoretically proved by using a distributed simulation platform to support the design and test of any technical solution and organizational approach devoted to optimize RFID-based logistics systems. This paper deals with the development of this simulation platform, based on Generalized Discrete Event Specification (G-DEVS) models and HLA (High Level Architecture) standard. The different partners components of the networked logistics enterprise are described. The proposed solution is applied to a freight transportation system and emulates the behaviour of the various components (RFID coupled to geolocation and mobile technology) required to optimize the products routing. The behaviour of the main components is G-DEVS formalized including the logistics supplier server, the smart product and the vehicle onboard device to interface the products with a centralized server. Delivery scenarios are then elaborated and simulated to check the behaviour and the intensity of communication network use between distributed G-DEVS models and other simulation components. The strength of the approach lies in the interoperability of the platform to simulate scenarios including discrete event models, real software and hardware devices all linked via an HLA connection. From these results, a discussion is given to validate or reject the conceptual choices about logistics components behaviour and their network bandwidth requirement regarding GSM, GPRS, Bluetooth and RFID networks theoretical capacities.

How do the Key Determinants of a Distributed Planning Process Impact on the Performance of a Supply Chain

As firms search to maximise value through the effective management of their various business activities, it is increasingly important to identify and understand the key factors that can significantly impact on the performance of the supply chain. The Supply Chain Operations Reference (SCOR) model enables to identify four distinct processes (plan, source, make and deliver) that constitute a supply chain. If many researchers have studied the last three processes (source, make and deliver), the relationship between the determinants of the planning process and supply chain performance has not been sufficiently explored. This paper therefore aims to identify and analyse the determinants of a distributed planning process that impact on the performance of a supply chain, including both financial and non-financial elements. It proposes a conceptual framework and a simulation model that can be used to improve the performance of a supply chain in terms of efficiency, flexibility, effectiveness and responsiveness.

Impact of the Key Determinants of a Distributed Planning Process on the Performance of a Supply Chain

In today’s highly competitive world, firms try to maximize value for their customers and other stakeholders through the effective management of their supply chains. Given that performance measurement considerably affects the actions of firms’ decision makers, it is increasingly important to understand the key factors that can significantly affect the performance of the supply chain. Using analytical models and simulations, this article aims to identify and analyse the key determinants (both financial and nonfinancial) of a distributed planning process that affect the performance of the supply chain. The identified determinants are discussed with respect to three performance dimensions: efficiency, effectiveness, and responsiveness. Our results show that different combinations of the determining factors have varying positive or negative effects on these three performance dimensions.

A Data Aggregation Methodology to Assess the Global Production Capacity of Complex Supply Chains

Nowadays, no decisional tools allow to assess if an unforeseen customers demand variation should be accepted without creating material disruptions among a supply chain or not. The main difficulty consists in aggregating resources capacities, especially if resources perform different tasks with multiple items. This paper then proposes a data aggregation methodology based on graph analysis in order to assess the global production capacity of complex resources networks, like supply chains.

MULTI-ECHELON PRODUCTION PLANNING PROCESS WITH NO TIME COORDINATION

The purpose of this paper is to study decentralized planning processes with no time coordination, performed within a whole supply chain. Distributed production and business units which compose the network, are considered as economically independent and autonomous in decision making, they define and update their production plans according to their own planning dynamic and strategy. Reactivity within these supply chains being quite dependent of this planning processes coordination, we try to assess the impact of this phenomenon on supply chain performance through a series of simulation, based on a generic linear programming model supporting the production, replenishment and delivery planning.