Marc Schleyer

Dr.-Ing. Marc Schleyer

  • Alumnus
  • Logistics Systems
  • Karlsruher Institut für Technologie
    Institut für Fördertechnik und Logistiksysteme
    Geb. 50.38 Gotthard-Franz-Str. 8
    76131 Karlsruhe

Publications
Title Image Source Short Description

6. International Conference on Analysis of Manufacturing Systems, Lunteren, The Netherlands, 193 – 198

The purpose of this paper is to introduce a framework of model elements and associated computation methods which are well suited to model information flow and physical processes in manufacturing systems. The proposed elements, the so called stochastic finite elements, are based on a discrete representation of time, in order to render distribution assumptions unnecessary. In our research, we extend available discrete time queueing models by models for batch processes, which are very common in manufacturing systems, when goods are transported or processed in some steps in batches and in some other steps piecewise. We give a short review of these models.

Submitted for publication to IIE Transactions (In Revision)

The aim of this paper is to introduce a framework of model elements and associated computation methods which are well suited to model information flow and physical processes in warehouses and distribution centers. The proposed elements, the so called stochastic finite elements, are based on a discrete representation of time, in order to render distribution assumptions unnecessary. We extend available discrete time queueing models by adding models for batch processes, which are very common in material handling systems, when goods are transported or processed in some steps in batches or in some other steps piecewise.

 3. Fachkolloquium der WGTL, Tagungsbeiträge, Hamburg, 155 – 164

Im folgenden Beitrag werden zeitdiskrete analytische Methoden vorgestellt mit Hilfe deren Informations- und Materialflüsse in logistischen Systemen analysiert und bewertet werden können. Bestehende zeitdiskrete Verfahren sind jedoch auf die Bearbeitung und Weitergabe in immer gleichen Mengen („One Piece Flow“) beschränkt. Vor allem in Materialflusssystemen kommt es bedingt durch die Zusammenfassung von Aufträgen, durch Transporte und durch Sortiervorgänge zur Bildung von Batches. Daher wurden analytische Methoden entwickelt, die es ermöglichen verschiedene Sammelprozesse, Batchankünfte an Ressourcen, Batchbearbeitung und Sortieren von Batches analytisch abzubilden und Leistungskenngrößen zu deren Bewertung zu bestimmen. Die im Rahmen der Entwicklungsarbeiten entstandene Software-Lösung „Logistic Analyzer“ ermöglicht eine einfache Modellierung und Analyse von praktischen Problemen. Der Beitrag schließt mit einem numerischen Beispiel.

 6. International Conference on Analysis of Manufacturing Systems, Lunteren, The Netherlands, 187 – 192

Due to the improvement of efficiency, batch servers are very common in manufacturing systems. This paper presents an analytical method to calculate the distribution of the number of customers at the departure instant for the G/G[L,K]/1 batch server system operating according the minimum batch size rule. Under this rule, when the batch service ends and there are less than L (L<= K) customers waiting, the server remains idle until L customers are accumulated in the queue. We present an approximative approach and our analysis is done in the discrete time domain.

Proceedings of the 21th IAR Annual Meeting, Nancy

Considering material flow and production systems, there is a limited space close to a machine or a group of machines for buffering unfinished goods. Therefore, for the dimensioning of material  ow bu ers it is of vital importance to analyze the number of customers in the queue at the arrival instant. It is crucial that there is enough free bu er capacity to receive the arriving customers. In our paper we consider a G/G/1-queueing system with batch arrivals in the discrete time domain. On the basis of the waiting time distribution we present an analytical approach for the calculation of the number of customers at the arrival instant. Given a confidence level the required buffer capacity can be calculated.

Batch building processes are common in many areas of material flow and production systems and of communication networks. This paper presents an analytic method to calculate the inter-departure time distribution and the waiting time distribution for batch building processes using discrete time analysis. The batch building process happens at so called collecting stations in the considered queueing network, at which the arriving customers are collected up to a defined capacity. The arrival is a batch arrival of stochastic size and is described by a generally identically distributed inter-arrival time. The presented method enables a performance evaluation of batch building processes in a stochastic environment.