Process Mapping and Stochastic Input Modeling

Table of Contents

1 Introduction

1.1 Problem of the Thesis

1.2 Aims of the Thesis

1.3 Course of Research

2 Critical Perspective on Queuing Theory Approach

3 Theoretical Foundations

3.1 Queuing Theory

3.2 Probability Theory and Statistics

3.3 Production Logistics

3.4 Discrete Event System Simulation

4 Methodology

4.1 System Analysis

4.2 Raw Data Collection

4.3 Data Preparation and Modeling Procedure.

4.4 Inputs for the Analysis

4.5 Output of the Analysis

4.6 Assumptions and Simplifications

5 Implementation

5.1 Exemplary Procedure Funnel 1

5.2 Table of Results

6 Final Consideration

6.1 Results and Critical Reflections

6.2 Implications for Further Research

6.3 Implications for Practice

Objectives & Topics

This thesis aims to develop an analytical input model for a material-flow simulation study in technical procurement by applying queuing theory and statistical methods to identify appropriate probability distributions for arrival rates and service times within the subcontracted maintenance, repair, and overhaul (MRO) operations business.

• Process mapping and system analysis of the outsourced MRO value chain.
• Evaluation of queuing theory applicability in a fragmented technical procurement environment.
• Statistical modeling of arrivals (Poisson distribution) and service durations (Exponential distribution).
• Implementation of input models based on historical enterprise resource planning (ERP) data.
• Verification of null hypotheses using goodness-of-fit tests.

Excerpt from the Book

Summary of Chapters

1 Introduction: Discusses the growing complexity of outsourced MRO services at Lufthansa Technik and sets the research goal of developing an analytical input model for simulation.

2 Critical Perspective on Queuing Theory Approach: Critically evaluates the limitations of standard queuing models and justifies their selection over other tools like Logistics Operating Curves for this specific application.

3 Theoretical Foundations: Provides the necessary mathematical and logistical background, including queuing theory, probability, statistics, and discrete event system simulation.

4 Methodology: Details the approach to system analysis, raw data collection from ERP systems, and the procedure for identifying and fitting probability distributions.

5 Implementation: Presents the practical application of the methodology, demonstrating the computation of arrival rates and system times, and summarizes the statistical results.

6 Final Consideration: Reflects on the findings, discusses the validity of the chosen models, and provides implications for future research and practical simulation implementation.

Keywords

Queuing Theory, MRO, Technical Procurement, Simulation, Input Modeling, Poisson Distribution, Exponential Distribution, Material-Flow, Logistics, Process Mapping, Statistical Analysis, Goodness-of-Fit, Work in Process, Turnaround Time, System Performance

Frequently Asked Questions

What is the core focus of this research?

The research focuses on creating an analytical input model for material-flow simulations in the context of outsourced aircraft maintenance, repair, and overhaul (MRO) services.

What are the primary themes covered in the thesis?

The thesis explores the application of queuing theory, production logistics, stochastic modeling, and the specific challenges of modeling technical procurement processes.

What is the main research question or objective?

The main objective is to determine which probability distributions best represent arrival rates and service times in order to build a functional input model for a simulation study.

Which scientific methods are employed?

The study utilizes system analysis, statistical distribution fitting (such as Poisson and Exponential distributions), and goodness-of-fit tests like the Kolmogorov-Smirnov test.

What does the main part of the thesis examine?

The main part covers the theoretical foundation of queuing systems, the methodology for data collection from ERP systems, and the step-by-step implementation of modeling three distinct procurement processes.

Which keywords best characterize this work?

Key terms include Queuing Theory, Material-Flow Simulation, Technical Procurement, Stochastic Input Modeling, and MRO Value Chain.

How does this thesis address the stochastic nature of MRO processes?

It addresses stochastic variability by using historical data to identify and validate probability distributions that represent the arrival patterns and processing times of repair orders.

What are the practical implications of the results for Lufthansa Technik?

The models developed serve as a foundation for future simulation studies, which can help in optimizing load leveling, increasing the number of servers, and improving overall system turnaround times.