Lufthansa Technik (LHT) is a provider of maintenance, repair and overhaul (MRO) services for aircraft. While LHT has traditionally performed the MRO services in-house, the subcontracted operations business is gaining momentum.
With about 90,000 outsourced MRO purchase orders (POs) per year, the process becomes increasingly complex. In the past, the company set the objective of achieving an average turnaround time (TAT) of five shop calendar days (SCD) for internal repair operations.
One of the main goals of LHT is to achieve an average TAT of fifteen SCD for the subcontracted MRO operations, between the monitoring points ‘Creation PO Requisition’ (i.e.: TS 29) and ‘Receive Unit Transaction’ (i.e.: TS 69). The current TAT is significantly higher, with substantial process variability.
The repair subcontracting value-chain consists of several processes, which fall under different areas of responsibility. Due to the stochastic nature of the series of processes and because
many variables influence the overall performance of the system, a simulation study needs to be conducted. The present thesis aims to develop an analytical input model for a simulation study in technical procurement.
Practical relevancy of the research problem
The building of the analytical input model and subsequent simulation model is a substantial
milestone towards the process optimization in the subcontracted MRO operations business.
The modeling of processes as an M/M/1 queuing system is the first step needed in order to
i) Simulate the processes and leverage optimization methods from the field of Production Logistics;
ii) Identify whether the application of queuing theory elements for process
description and analysis within technical procurement would aid in improving the processes.
Theoretical relevancy of the research problem
The thesis aims at applying already existing elements from queuing theory and statistics to a relatively new field – technical procurement, as to bring a contribution to the queuing science, an interface between queuing theory and practice.[...]
At a glance
- Grade: 1.3 (1.0 is the best grade)
- Tests first-quarter arrival distributions with Kolmogorov-Smirnov and Anderson-Darling tests
- Develops an input model for a simulation study
- 35 sources in the bibliography
- 10 figures and 2 tables
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 and Topics
This thesis develops a stochastic input model for a material-flow simulation of outsourced aircraft maintenance procurement at Lufthansa Technik. It investigates which probability distributions can represent arrivals and processing times at selected stages of the subcontracting process, while assessing the applicability and limitations of queuing theory.
- Mapping purchase order creation, supplier clarification and receiving clarification
- Queuing theory and discrete-event simulation
- Preparation of historical tracking and enterprise resource planning data
- Probability distributions for arrivals and processing times
- Distribution fitting and goodness-of-fit tests
Excerpt from the Book
4.1 System Analysis
On a typical quarter, approximately 20,000 repair orders need to be outsourced, and consequently the approximately 20,000 PO requisition arrivals occur.
Process 1 under analysis starts with the arrival of PO requisitions. In case an outline agreement contract between LHT and the respective supplier is in place, the POs are automatically created.
If this is not the case, the POs need to be manually processed, activity which results in the output of this process POs. Namely, the operative purchasers need to input data and select criteria according to the contractual terms, which would allow the system to create the POs. The PO requisition arrives and then enters a queue of open PO requisitions, waiting for the availability of the purchaser, fact that leads to an increase in the real TAT.
Process 2 under analysis represents the value added activity within the outsourced MRO value chain and it concerns the MRO operations done by LHT’s suppliers and their subcontractors. A matter of interest concerning this process is the delay between the point in time when the forwarder hands over the unit sent for repair to the supplier and the point in time when the supplier acknowledges the confirms the receipt of the unit.
This creates a time interval when, although the supplier takes responsibility for the respective unit, fails to take responsibility for the increase in the TAT. The distribution of the delays caused by this action would be an interesting aspect to explore. Nonetheless, the unavailability of data impedes the current performance of such an analysis.
Furthermore, once the supplier test the units sent for repair, a quote is sent to LHT, which need be appraised. While the time interval required for the quotation process is subtracted from the nominal TAT, it does contribute to the real TAT.
Since the supplier does not start the unit repair until the quote is approved, the duration required by the quote release this can be conceptualized as a delay block. This delay block, which occurs between the timestamps 55 (start clarification subcontractor) and 56 (end clarification subcontractor) will make the object of the analysis regarding this process.
Finally, process 3 commences once the MRO unit arrives back at LHT. The repaired unit’s arrival usually does not correspond to the time when its associated PO is closed, fact that leads to a further increase in the TAT. Furthermore, special but frequent situations like missing repair certificates or wrong serial number (SN) lead to clarification delays, which lead to yet further increases in the real TAT.
Chapter Summaries
1 Introduction: The thesis introduces the subcontracted maintenance process, its turnaround-time challenges and the objectives of the simulation input study.
2 Critical Perspective on Queuing Theory Approach: This chapter examines the assumptions and limitations of queuing models and considers their suitability for technical procurement alongside production-logistics tools.
3 Theoretical Foundations: The author explains queuing theory, probability and statistics, production logistics and discrete-event simulation as foundations for the analysis.
4 Methodology: The methodology maps the system, describes the historical data and explains data preparation, distribution fitting and modeling assumptions.
5 Implementation: An illustrative analysis of the first process demonstrates arrival and system-time modeling, followed by a table of results for the three processes.
6 Final Consideration: The final chapter reflects on the input models and their limitations and discusses implications for further research and practical simulation.
Keywords
technical procurement, material-flow simulation, queuing theory, stochastic input modeling, aircraft maintenance, outsourced repair, Lufthansa Technik, purchase orders, arrival rates, service times, probability distributions, discrete-event simulation, goodness-of-fit tests, turnaround time
Frequently Asked Questions
What is this thesis about?
It examines how to map outsourced aircraft maintenance procurement processes and develop stochastic inputs for a material-flow simulation.
What are the central topics?
The central topics include queuing systems, production logistics, historical process data, probability distributions and discrete-event simulation.
What is the main objective of the research?
The objective is to identify probability distributions that represent arrivals and processing times at selected stages of a technical procurement process.
What research method does the author use?
The author maps the process and statistically analyzes historical tracking and enterprise resource planning data, using histograms, quantile-quantile plots and goodness-of-fit tests to assess candidate distributions.
What does the main body cover?
It presents the theoretical foundations, analyzes the procurement system, describes data preparation and modeling assumptions, and demonstrates the procedure for the first process.
Which keywords characterize the work?
Key terms include queuing theory, technical procurement, stochastic input modeling, material-flow simulation, arrival rates, service times and probability distributions.
Which organization and processes are examined?
The case concerns Lufthansa Technik’s outsourced maintenance operations, focusing on purchase order creation, supplier clarification and receiving clarification.
What historical data does the analysis use?
It uses tracking and enterprise resource planning data from the first three quarters of 2010, including arrival and departure timestamps.
How does the thesis assess candidate distributions?
It uses graphical comparisons and goodness-of-fit tests, including the Kolmogorov-Smirnov test; the illustrative arrival analysis also uses the Anderson-Darling test.
- Quote paper
- Ileana Constantinescu (Author), 2011, Process Mapping and Stochastic Input Modeling, Munich, GRIN Verlag, https://www.grin.com/document/181775
