Gregor von Cieminski

Applying Simulation and Analytical Models for Logistic Performance Prediction

Different types of models are used to describe the interdependencies between logistic performance measures of production systems in research and practice. The most widely known analytical models in this field are queuing theory models. Simulation, on the other hand, is a widespread technique for the exploration, design and optimisation of complex production systems. Due to the limitations of queuing and simulation models, a mathematical approximation approach developed at the Institute of Production Systems and Logistics is becoming more relevant: the Logistic Operating Curves. The paper introduces the theory of these three modelling methods and compares as well as differentiates them.

Human Factors in Production Planning and Control

The influence of human actors on production planning and control (PPC) systems is significant. This paper describes a number of ways, in which human interaction with PPC systems affects the logistic performance of production. It demonstrates how human decisions and behaviour can act as stumbling blocks for PPC. Logistic models and PPC procedures that remove these stumbling blocks are presented. Moreover, the paper proposes the concept of 3-Sigma PPC as a holistic approach to PPC. 3-Sigma PPC recognises the influence of human factors on PPC and incorporates methods that improve human decision-making so that a better logistic performance can be achieved.

Collaborative supply chain planning — A case study from the German cutting tool industry

This paper is concerned with the case study of the supply chain of a German cutting tool manufacturer. The Institute of Production Systems and Logistics (IFA) carried out a comprehensive analysis of the supply chain in cooperation with the companies that are partners in the chain. The analysis was carried out from a production logistics perspective. By use of the theory of logistic operating curves, logistic performance measures for manufacturing departments as well as for product stores were determined and potentials for improvement identified. The supply chain tiers were initially considered separately. This facilitated a detailed analysis of their specific logistic performance and its causes. Merging the results of the investigations led to a thorough understanding of the interdependencies that exist between the performances of different parts of a supply chain. The results of the individual studies were consolidated in order to support a more holistic approach to production management and to better achieve the objectives of the entire chain. A transparent combined Kanban-CONWIP control cycle was suggested in order to improve the collaborative production planning and control of the complete supply chain.

Influences of Human Operators on the Logistics of Manufacturing Cells

Human operators have important influences on the logistic behaviour of manufacturing cells. In many of the possible configurations of a manufacturing cell, operators represent the bottleneck of the cell. Thus they dominate the cell’s logistic behaviour. This paper explains how the theory of logistic manufacturing cell operating curves considers human influences on manufacturing cell logistics. The operating curves are a tool to analyse the logistic performance of manufacturing cells. Therefore they represent a means for determining logistically suitable configurations of the human-machine interactions between the human operators and the work systems in manufacturing cells.

Proposal of a Reference Framework for Manufacturing Systems Engineering

The authors propose a “generic” reference framework to integrate modeling methods typically adopted to engineer a manufacturing system under a unifying “umbrella”. These methods — from formal descriptive modelling to analytical modelling and simulation modelling methods — originate from different disciplines and serve different purposes.

Zielorientierte Planung und Steuerung der industriellen Unternehmenslogistik

Kurzfassung Der Beitrag stellt die am Institut für Fabrikanlagen und Logistik (IFA) der Leibniz Universität Hannover entwickelten qualitativen Wirkmodelle der industriellen Unternehmenslogistik vor. Diese Modelle bilden die Wirkzusammenhänge zwischen den logistischen Zielgrößen und den Planungs- und Steuerungsparametern ab. Sie ermöglichen es Industrieunternehmen, die Konsistenz und die Zielorientierung der logistischen Zielsetzungen sowie der operativen Planungs- und Steuerungsmaßnahmen sicherzustellen.

Ensuring the Consistency of Competitive Strategy and Logistic Performance Management

Manufacturing companies often merely attain reduced levels of logistic performance due to inconsistencies between their logistic objectives, logistic performance targets and logistic performance management actions. Qualitative influence models represent the inter-dependencies between these factors on two levels: firstly between logistic objectives, secondly between logistic performance measures and logistic planning and control parameters. Expert knowledge gained from modelling the dynamic behaviour of logistic systems facilitates the interpretation and evaluation of the qualitative influence models. On this basis, consistent logistic objectives can be defined and objective-oriented planning and control actions can be identified. The modelling insights are integrated into a logistic performance diagnosis procedure and tool that improve logisticians’ understanding of the consequences of their management decisions and enhance the closed-loop management of logistic performance.