Yannick Frein

An Analytical Method for Performance Evaluation of Kanban Controlled Production Systems

The aim of this paper is to develop a general purpose analytical method for performance evaluation of multistage kanban controlled production systems. We consider a single-part type production system decomposed into stages in series. Each stage consists of a manufacturing cell and an output buffer. With each stage is associated a given number of kanbans. The kanban controlled production system is modeled as a queueing network with synchronization mechanisms. The basic principle of the proposed approximation method is to decompose the original kanban system into a set of subsystems, each subsystem being associated with a particular stage. Each subsystem is analyzed in isolation using a product-form approximation technique. An iterative procedure is then used to determine the unknown parameters of each subsystem. Numerical results show that the method is fairly accurate.

On decomposition methods for tandem queueing networks with blocking

Queueing networks with blocking are useful for modeling and analyzing discrete event systems, especially manufacturing systems. Most analysis methods for queueing networks with blocking are approximation methods that involve a decomposition of the network into a set of subsystems. This paper presents some insight into these decomposition methods as well as new results. Attention is mainly restricted to the case of tandem queueing networks with exponential service times and blocking-after-service. This type of blocking is especially encountered in manufacturing systems. The first aim of this paper is to improve the understanding and present a unified view of the decomposition methods. We show that decomposition methods can be classified according to three main approaches. One of these approaches is of special interest because it offers a symmetrical view of the decomposition. The second aim of the paper is to provide properties pertaining to these decomposition methods in the case of exponential characterizations of subsystems. We prove the existence and uniqueness of the solution. Moreover, we prove the convergence of the computational algorithm associated with the symmetrical approach.

On the design of generalized kanban control systems

Considers a class of control systems known as generalized kanban control systems (GKCS) which can be used to implement a pull control mechanism in a manufacturing system. In a GKCS, the production system is decomposed into stages, where each stage consists of a production sub‐system. There are two design parameters per stage: one controls the work‐in‐process in the stage and the other determines the maximum number of finished products of this stage. Investigates the influence of these design parameters on the efficiency of generalized kanban control policies by deriving qualitative properties as well as using experimental results on the behaviour of GKCS.

A scenario-based stochastic model for supplier selection in global context with multiple buyers, currency fluctuation uncertainties, and price discounts

Suppliers network in the global context under price discounts and uncertain fluctuations of currency exchange rates have become critical in today’s world economy. We study the problem of suppliers’ selection in the presence of uncertain fluctuations of currency exchange rates and price discounts. We specifically consider a buyer with multiple sites sourcing a product from heterogeneous suppliers and address both the supplier selection and purchased quantity decision. Suppliers are located worldwide and pricing is offered in suppliers’ local currencies. Exchange rates from the local currencies of suppliers to the standard currency of the buyer are subject to uncertain fluctuations overtime. In addition, suppliers offer discounts as a function of the total quantity bought by the different customer’ sites over the time horizon irrespective of the quantity purchased by each site.

An efficient method to determine the optimal configuration of a flexible manufacturing system

A frequently encountered design issue for a flexible manufacturing system (FMS) is to find the lowest cost configuration, i.e. the number of resources of each type (machines, pallets, ...), which achieves a given production rate. In this paper, an efficient method to determine this optimal configuration is presented. The FMS is modelled as a closed queueing network. The proposed procedure first derives a heuristic solution and then the optimal solution. The computational complexity for finding the optimal solution is very reasonable even for large systems, except in some extreme cases. Moreover, the heuristic solution can always be determined and is very close (and often equal) to the optimal solution. A comparison with the previous method of Vinod and Solberg shows that our method performs very well.

A Multi-class Approximation Technique for the Analysis of Kanban-Like Control Systems

Analytical methods have been proposed in the literature for performance evaluation of kanban control systems. Among them, the method presented by Di Mascolo and colleagues appears to be of special interest since it can handle manufacturing stages consisting of any number of machines and it is fairly accurate. This paper presents a new way of deriving the analytical method presented by Di Mascolo et al. The approach is to see the queueing network of the kanban control system as a multiclass queueing network in which each kanban loop is represented by a class of customers. This allows one to use the general technique proposed in Baynat and Dallery for analysing multiclass queueing network using product-form approximation methods. In terms of equations, the new method is equivalent to that previously presented. However, the computational algorithm is much more efficient since it avoids the two levels of iterations involved in the original algorithm. Another major advantage of the new method over that originally proposed is that it provides a general framework for the analysis of more general kanban systems. Indeed, it is shown in this paper how this approach can easily be extended in order to handle kanban systems with multiple consumers and multiple suppliers, kanban-controlled assembly systems and generalized kanban systems.

Performance evaluation and design of a CONWIP system with inspections

Abstract In this paper, we analyze a CONWIP (Constant Work-In-Process) system which consists of three stations in series. We assume that raw parts are always available. When a finished part is consumed by a demand, a raw part is released immediately and gets processed at each station sequentially. The processings do not always meet the requirement of quality. Therefore, at the end of the processing at each station, a part is inspected randomly to determine if it satisfies the requirement of quality. We assume that the inspection time is negligible. If a part is inspected and found to be defective because of treatment at station j, the part is fed back to station j to be treated again. We consider that the stations have an exponential or a N-stage Coxian service time distribution. We propose an analytical method to evaluate the performance of this kind of system. We consider two cases: one is the saturated case where the supply of demands is infinite and the other is the non-saturated case where external demands arrive according to a Poisson process. Then we use the analytical method to show how the optimal conwip system can be designed for a chosen design criterion. Although we present the method only for three-station systems in this paper, it can be easily extended to systems with more than three stations.

An optimisation model for the design of global multi-echelon supply chains under lead time constraints

This article presents a mixed integer programming model for the design of global multi-echelon supply chains while considering lead time constraints. Indeed, we impose that the delivery lead time that can be promised by the company must be smaller than the lead time required by the customer. The delivery lead time is calculated based on the lead times of purchasing, manufacturing and transportation that are triggered by the customer order while considering the stock levels of purchased, intermediate and final products that must be kept at the different facilities. Computational studies are conducted in order to analyse the impacts of including lead times on the supply chain design decisions and to prove the solvability of the model.

Collaboration for a two-echelon supply chain in the pulp and paper industry: the use of incentives to increase profit

In our research, we study the case of a pulp and paper producer who decides to establish a partnership with one buyer. Using two different types of relationship, namely a traditional system without any collaboration scheme and Collaborative Planning, Forecasting and Replenishment, we develop decision models describing the producer and the buyer planning processes. We also identify which approach is more profitable for each actor as well as for the network, based on real costs and parameters obtained from the industrial case. We then test how different incentives can improve the traditional system and provide higher gains for each partner. Our results show that using incentives increases the systems profit by up to 4% if parameters are well defined.

Heuristics for an industrial car sequencing problem considering paint and assembly shop objectives

The aim of this paper is to study the problem of sequencing a set of vehicles within an industrial environment considering the assembly shop objectives, but also the objectives of the paint shop. The first approach is to solve the problem with a mono-objective function. One heuristic (a progressive, construction-sequence algorithm) and three meta-heuristics (simulated annealing, variable neighbourhood search and an evolutionary algorithm) are described and compared. As the mono-objective approach has limited possibilities, a multi-objective heuristic is finally presented and tested. Because of the industrial context of this research, the computation time is a decisive factor to select the appropriate heuristic.