Closed-loop two-echelon repairable item systems

In this paper we consider closed loop two-echelon repairable item systems with repair facilities both at a number of local service centers (called bases) and at a central location (the depot). The goal of the system is to maintain a number of production facilities (one at each base) in optimal operational condition. Each production facility consists of a number of identical machines which may fail incidentally. Each repair facility may be considered to be a multi-server station, while any transport from the depot to the bases is modeled as an ample server. At all bases as well as at the depot, ready-for-use spare parts (machines) are kept in stock. Once a machine in the production cell of a certain base fails, it is replaced by a ready-for-use machine from that base's stock, if available. The failed machine is either repaired at the base or repaired at the central repair facility. In the case of local repair, the machine is added to the local spare parts stock as a ready-for-use machine after repair. If a repair at the depot is needed, the base orders a machine from the central spare parts stock to replenish its local stock, while the failed machine is added to the central stock after repair. Orders are satisfied on a first-come-first-served basis while any requirement that cannot be satisfied immediately either at the bases or at the depot is backlogged. In case of a backlog at a certain base, that base's production cell performs worse. To determine the steady state probabilities of the system, we develop a slightly aggregated system model and propose a special near-product-form solution that provides excellent approximations of relevant performance measures. The depot repair shop is modeled as a server with state-dependent service rates, of which the parameters follow from an application of Norton's theorem for Closed Queuing Networks. A special adaptation to a general Multi-Class MDA algorithm is proposed, on which the approximations are based. All relevant performance measures can be calculated with errors which are generally less than one percent, when compared to simulation results. \u

A compensation procedure for multiprogramming queues

Abstract. In this paper we study a multiprogramming system consisting of an input-output unit (10 unit) and a central processor (CP). This system can be represented by a continuous time Marlmv process with states (m. n). where m and n denote the number of jobs at the CP and the 10 unit respectively. The computation of the equilibrium distribution {Pm,n} of this Markov process is the purpose of the analysis in this paper. The analysis consists of two parts. In the first Part. we use a compensation procedure to show that the equilibrium distribution {Pm,n} in those states (m. n) for which m+n is not too small. can be expressed as an infinite linear combination of product forms. Explicit formulae are given for the product forms and the coefficients of this infinite linear combination. In the second part of the analysis. we pay attention to some numerical aspects of the computation of the equilibrium distribution. For the computation of the equilibrium probabilities that can be expressed as infinite linear combinations of product forms. we derive bounds for the errors caused by cutting off these infinite linear combinations, and after that we present numerically stable formulae to compute one by one the remaining equilibrium probabilities

A generic control architecture for material handling systems applied to a baggage handling system

This paper is part of research on generic planning and control of automated Material Handling Systems (MHSs) in different industrial sectors. We build upon previous work to provide a proof of concept for the applicability of a generic control architecture on a specific MHS. To this end, the baggage handling system (BHS) of a major European hub represents our business case. We present the control architecture and apply it to the BHS under study in a simulation environment. This application shows how the generic control architecture adapts to the specificities of this BHS and how it handles unconventional workstation types, i.e., robots. Finally, we highlight the lessons learned and make recommendations for future applications

Integrated planning of spare parts and service engineers with partial backlogging

In this paper, we consider the integrated planning of resources in a service maintenance logistics system in which spare parts supply and service engineers deployment are considered simultaneously. The objective is to determine close-to-optimal stock levels as well as the number of service engineers that minimize the total average costs under a maximum total average waiting time constraint. When a failure occurs, a spare part and a service engineer are requested for the repair call. In case of a stock-out at spare parts inventory, the repair call will be satisfied entirely via an emergency channel with a fast replenishment time but at a high cost. However, if the requested spare part is in stock, the backlogging policy is followed for engineers. We model the problem as a queueing network. An exact method and two approximations for the evaluation of a given policy are presented. We exploit evaluation methods in a greedy heuristic procedure to optimize this integrated planning. In a numerical study, we show that for problems with more than five types of spare parts it is preferable to use approximate evaluations as they become significantly faster than exact evaluation. Moreover, approximation errors decrease as problems get larger. Furthermore, we test how the greedy optimization heuristic performs compared to other discrete search algorithms in terms of total costs and computation times. Finally, in a rather large case study, we show that we may incur up to 27% cost savings when using the integrated planning as compared to a separated optimization. , The Author(s).This publication was made possible by the NPRP award [NPRP 7-308-2-128] from the Qatar National Research Fund (a member of The Qatar Foundation). The statements made herein are solely the responsibility of the authors.Scopu

Paths to Innovation in Supply Chains: The Landscape of Future Research

This chapter presents a Strategic Research and Innovation Agenda for supply chain and it is the result of an intensive work jointly performed involving a wide network of stakeholders from discrete manufacturing, process industry and logistics sector to put forward a vision to strengthen European Supply Chains for the next decade. The work is based on matching visions from literature and from experts with several iterations between desk research and workshops, focus groups and interviews. The result is a detailed analysis of the supply chain strategies identified as most relevant for the next years and definition of the related research and innovation topics as future developments and steps for the full implementation of the strategies, thus proposing innovative and cutting-edge actions to be implemented based on technological development and organisational change