Designing a comprehensive framework to analyze and improve engine MRO processes from an integral perspective A case study at KLM Engineering and Maintenance Engine Services

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Designing a comprehensive framework to analyze

and improve engine MRO processes from an

integral perspective

A case study at KLM Engineering & Maintenance Engine Services

Amber J. C. Rozenberg

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TIL5060 – Master Thesis Project

MSc Transport, Infrastructure and Logistics

10 November 2016

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Designing a comprehensive framework to analyze

and improve engine MRO processes from an

integral perspective

A case study at KLM Engineering and Maintenance Engine Services

TIL5060 Master Thesis Project

For the degree of Master of Science in Transport, Infrastructure and Logistics

at the Delft University of Technology

by

Amber J. C. Rozenberg

4013549

Date: November 10, 2016

To be defended on November 30, 2016, 10:00 AM Lecture room Daniel Bernoulli (C)

Faculty of Mechanical, Maritime and Materials Engineering

Report number: 2016.TIL.8077

Graduation Committee:

Prof. dr. ir. G. Lodewijks TU Delft, Faculty 3ME

dr. W. W. A. Beelaerts van Blokland TU Delft, Faculty 3ME

dr. ir. J. H. Baggen TU Delft, Faculty CiTG & TPM

G. Philips van Buren KLM Engineering & Maintenance

A. Gortenmulder KLM Engineering & Maintenance

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Preface

Dear reader,

When it is not too hazy, one can see the large hangars of Schiphol-East from the Schiphol airport terminal. For most passengers, this is the only behind-the-scenes look they will ever get of the vastly complex operations that take place to support their business or leisure flights. The past six months, I was able to explore this hidden world of aircraft Maintenance, Repair and Overhaul during my graduation internship at KLM Engineering & Maintenance. The work lying in front of you represents the result of my master thesis project to complete my master studies Transport, Infrastructure and Logistics (TIL) at the Delft University of Technology. The aim of this project was to develop a comprehensive framework to improve aircraft engine Maintenance, Repair and Overhaul (MRO) processes, and to apply this framework to decrease the turnaround time of CFM56-7B engine MRO at KLM Engineering & Maintenance Engine Services.

Naturally, I could not have completed this master thesis project without the help of many others. I would like to use this opportunity to express my gratitude to these people.

First of all, I want to thank Guus Philips van Buren and Alex Gortenmulder for the opportunity to conduct my thesis project at KLM Engineering & Maintenance at the Lean Six Sigma Office. Their enthusiasm, knowledge and feedback helped and challenged me to get the most out of my internship period. Next, I want to thank all colleagues at Engine Services for sharing their time, knowledge and data with me, even in tumultuous times. Thirdly, I want to express my thanks to my graduation committee: Prof. Lodewijks, whom I wish all the best on his Australian adventure; Dr. Beelaerts van Blokland, whose enthusiasm and expertise elevated this research to a higher level than I could have anticipated, and dr. Baggen, whose “mental coaching” helped me through periods of de-motivation and helped me find structure in my thinking process.

And finally, I want to thank all my fellow interns, friends, family and especially Reinier for their patience, support, input, distraction and food donations (you know who you are). Mom, dad: It Is Done.

Thank you all and I wish you a pleasant read.

November 10, 2016 Amber Rozenberg

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Executive Summary

Around 20,000 commercial aircraft carry an estimated 3.5 billion passengers around the world this year (2016). This number is expected to double over the next decades, to a total of 40,000 aircraft carrying 7 billion passengers. To guarantee the safety and airworthiness of these aircraft, Maintenance, Repair and Overhaul (MRO) is a necessity. The current estimated value of the global aircraft MRO market is $63.2 billion and growing, it is however shared by many different players in different MRO domains: Airframe MRO, Components MRO and Engine MRO.

This research focuses on the last category, responsible for 35%-40% of an airline’s maintenance cost. The Engine MRO market is dominated by Original Equipment Manufacturers (OEMs) that are increasingly strengthening their positions, by providing more and more long-term service agreements and by using more complex technologies in their new engines. To be competitive in this crowded market, maintenance providers need to compete on MRO cost, turnaround time (TAT) and quality of the delivered services. KLM Engineering & Maintenance Engine Services is an airline third party MRO provider that needs to compete in the Engine MRO market. The focus for KLM E&M Engine Services lies on competing on the turnaround time of Engine MRO, while guaranteeing sufficient quality against competitive cost. However, the current TAT performance and the needed performance are not aligned. This research aims to contribute to solving this problem by creating a comprehensive framework to decrease the TAT of an engine MRO chain, and to answer the following research question:

How can the output of aircraft engine Maintenance, Repair and Overhaul processes be optimized from an integral perspective?

In order to answer this question, a comprehensive seven-step framework is designed, based on process improvement methodologies, process modelling methodologies and solution evaluation methodologies. First, the system and evaluation criteria need to be defined [I]. Next, the current state of the system is measured [II], and subsequently constraints in the system are analyzed [III]. The fourth step is to create solution scenarios for the constraints, by exploiting, elevating or creating the Ideal World [IV]. Next, the solution alternatives are modelled [V], and evaluated in the sixth step [VI]. The seventh and last step consists of implementing the optimal solution and controlling the process [VII], which is beyond the scope of this research. This framework is subsequently applied to a case study at KLM Engineering & Maintenance Engine Services, a sub-division of Air-France Industries KLM Engineering & Maintenance.

Step I: Define the system & criteria

This case study considers the Engine MRO process of CFM56-7B engines – used for Boeing 737s - which consists of four main steps: (0) Work scope determination, (1) Disassembly of the engine, (2) Repair and (3) Assembly of the engine. Five different evaluation criteria are defined: MRO cost, Implementation cost, Product quality, Process quality and Turnaround

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Time. For the case study, Turnaround Time and Process Quality are measured on a quantative basis, while the other criteria are assessed on a qualitative basis.

Step II: Measure the current state

The current state of the MRO process is measured on two levels: first on the level of the integral chain, and subsequently on the Repair stage level. All measurements are based on data retrieved from SAP, the enterprise resource planning system used by KLM E&M. The current turnaround time (TAT) of the integral MRO chain is 62 days, with a large standard deviation of 23 days. Currently, control is based on measurement of the different stages, however, the norm agreements are unclear and inconsistent. The largest share in the total TAT is realized by the repair stage, and more specifically outsourced repairs. The average TAT of outsourced repairs is 31 days, including logistics.

Step III: Identify the constraints

The constraints are identified on two different levels: that of the MRO chain and on the repair stage. In the overall MRO chain, no consistent agreements for control are in place and control is based on stages instead of the value stream of an engine and its parts. When the value stream is measured, outsourced work forms the largest constraint to the TAT output of the chain. Within outsourced repairs, constraints are found in the logistical process and at the vendors. For export logistics, this constraint is formed by fixed outgoing transport times. At the vendor, the constraint is formed by lack of internal performance and the varying contract agreements. For import logistics, the main constraint is formed by the incoming goods inspection capacity.

Step IV: Create solutions for the constraints

Different solution alternatives are created based on exploiting the constraint, elevating the constraint and creating the Ideal World solution – thus generating a wide spectrum of alternatives. Five different alternatives are generated: the exploit alternative, elevate 28 days, elevate 21 days, elevate 14 days, and Ideal World.

Step V: Model the solutions

The effect of the different solution alternatives on the TAT is modelled using a static, deterministic model. First, the effect of the detailed solution on the outsourced repair TAT is modelled. This subsequently serves as a bottom-up input to the model to generate the overall MRO TAT. The results are shown in the table below.

Solution Average TAT Outsourced Repair St. dev. Of outsourced repair Average TAT MRO

Current state 31 days 10 days 65 days

Exploit 29 days 7.2 days 57 days

Elevate 28 28 days 7 days 56 days

Elevate 21 25 days 6 days 54 days

Elevate 14 19 days 5.8 days 46 days

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Step VI: Evaluate the solutions against criteria

The solution alternatives are evaluated using the previously determined criteria. A combination of quantitative and qualitative criteria is used, resulting in the application of the Evaluation of Mixed Data method (Evamix), in combination with the Analytic Hierarchy Process (AHP) for the determination of the criteria weights.

From the perspective of KLM E&M as a process owner, the optimal solution is the Exploit solution, with Elevate 28 as a close second. For the Exploit solution, vendor management is needed to maximally exploit the current contract agreements. Next to this, Import logistics can be improved by implementing multi-skilled teams combining the DGO (Decentralized Goods Receipt) and IIG (Inspection Incoming Goods) steps, and Export logistics can be streamlined by introducing Pull based on the cutoff times for outgoing transport.

The Elevate 28 solution consists of vendor management in combination with a limit on the repair contracts of maximum 28 days. Next to this, Export logistics can be improved by introducing Pull and enabling direct dedicated transport to the Logistics Center. And finally, Import logistics can be improved by increasing the IIG capacity from 5x2 to 7x2 shifts per week and safeguarding the regular flow of incoming logistics by creating dedicated lanes for priority packages, AOG (Aircraft on Ground) packages and other problem cases.

Implementing the Exploit solution will result in a total Turnaround Time of 57 days, compared to a current modelled Turnaround Time of 65 days. The standard deviation of the Outsourced Repair process will decrease from an average of 10 days to an average of 7.2 days. Implementing the Elevate 28 solution will result in a total Turnaround Time of 56 days, with an average standard deviation of 7 days for the Outsourced Repair process.

Answering the main research question: How can the output of engine Maintenance, Repair

and Overhaul processes be optimized from an integral perspective?

A comprehensive framework, consisting of seven steps, is created to develop, model and evaluate solutions to optimize engine MRO processes. This seven-step model is successfully applied to a case study at KLM E&M Engine services, wherein different solution alternatives are created to decrease the turnaround time of the MRO process. The recommended solution alternatives consist of either exploiting the constraints in the MRO chain, focusing on Outsourced Repairs, or elevating the constraints with a cap of 28 days in the contract agreement. The potential reduction in turnaround time in the integral MRO chain by implementation of these solutions is 8 or 9 days.

The developed comprehensive seven-step framework has added value over existing frameworks on two aspects: it, on one hand, forces researchers to create the widest possible array of solution alternatives – from the current state to the ‘Ideal World’, and on the other hand it forces researchers to evaluate their solutions against different criteria in the evaluation step.

Recommendations, further research and limitations

This research has focused on improving the main constraint limiting the Turnaround Time of the MRO chain of CFM56-7B engines at KLM E&M Engine Services: Outsourced Repairs. For KLM E&M Engine Services, it is recommended to implement the solution Exploit or Elevate 28. Next to this, it is essential that all stage agreements are consistent in the chain – meaning that all stakeholders have the same view of the agreements - to effectively plan and control the MRO chain. Subsequently, the method of measurement needs to be changed from a stage approach to a Value Stream approach. Next to implementing these solutions, it

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is necessary to implement the previously developed solutions for in-house repairs by (Meijs, 2016) and (Mogendorff, 2016).

Implementation of the Outsourced Repair solutions can result in a decrease in Engine MRO TAT of 8 or 9 days. More potential days can be found in the Disassembly and Assembly stages, so it is recommended to apply the same framework to these stages to find more optimization strategies. In this way, by continuous improvement, the Ideal World can be achieved – with a potential engine MRO TAT of 38 or less days.

Furthermore, it is recommended to conduct research on the qualitative criteria used to be able to measure the criteria on a quantitative, ratio scale. Next, it is recommended to develop different models for different engine work scopes. And finally for further research it is useful to apply the framework to other engine types, such as the CF6-80E1 engine.

From a scientific aspect, it is useful to fit previously developed frameworks for aircraft MRO into the comprehensive seven-step framework developed in this research. Examples of these frameworks are given by (Meijs, 2016), (Mogendorff, 2016) and (van Rijssel, 2016). And finally, it is useful to apply the comprehensive framework to other processes in other industries and subsequently compare and evaluate the used methods and tools within the framework.

In each step of the framework applied to the case study at KLM E&M Engine Services, limitations occur. First of all, the outcome of the case study is limited by the availability and quality of data. For the case study, engine data of 2015 is used, however sometimes for certain WBS assemblies the available data was limited.

Next, the research is limited by the focus on main constraints for the development of solution alternatives. Many different smaller constraints were observed – which makes sense when looking at the whole MRO chain – but only the main constraints were used to develop solutions.

A third limitation is formed by the assumptions made when modelling the different solutions, as described in the modelling chapter. And finally the evaluation of the different solution alternatives is limited by the use of qualitative criteria and scores. Even though the use of Evamix enabled the use of qualitative criteria, ideally one would have an objective, quantitative basis to all criteria. Furthermore, the use of Evamix is not very straightforward or immediately insightful, and it is not possible to easily add or remove different alternatives as the dominance is determined relative to the whole set of solutions.

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List of abbreviations

Abbreviation Explanation

AFI KLM Air France Industries KLM

AOG Aircraft On Ground

APrep Assembly Preparation

BPM Business Process Management

BPR Business Process Reengineering

CBBSC Connected Business Balance Score Card

CPS Creative Problem Solving

DGO Decentralized Goods Receipt

DMAIC Define, Measure, Analyze, Implement and Control

E&M Engineering and Maintenance

EGT Exhaust Gas Temperature

ES Engine Services (KLM E&M)

HPO High Performance Organization

IIG Inspection Incoming Goods

KLM Koninklijke Luchtvaart Maatschappij

KPI Key Performance Indicator

LC Logistics Center (KLM E&M)

LSS Lean Six Sigma

LTSA Long Term Service Agreement

MRO Maintenance, Repair and Overhaul

OEM Original Equipment Manufacturer

OTP On Time Performance

P&D Parts and Disposition

PPI Process Performance Indicator

SIPOC Supplier Input Process Output Customer

TAT Turnaround Time

ToC Theory of Constraints

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List of figures and tables

Figure 1-1: Engine MRO Process 5

Figure 1-2: DMAIC Cycle (Reid & Sanders, 2010, p. 196) 7 Figure 2-1: the TPS House based on (Stewart J. , 2011, p. 27) 10

Figure 2-2: Literature Framework 20

Figure 3-1: Chapter 3 23

Figure 3-2: Schematic view of a Turbofan engine (Ackert, 2011) 24 Figure 3-3: Global market shares for commercial engine production (Flightglobal, 2015) 25 Figure 3-4: Competition landscape Profitability versus Growth (2015 figures) 26 Figure 3-5: Competition landscape Turnover versus Product strategy (2015 figures) 26

Figure 3-6: Process output objectives 27

Figure 3-7: Goal tree KLM E&M Engine Services 28

Figure 4-2: SIPOC diagram of the Engine MRO Chain 34

Figure 4-3: Flow chart of the overall Engine MRO process 35

Figure 4-4: current organizational (institutional) control of the MRO chain 36

Figure 4-5: CBBSC KLM E&M ES MRO 36

Figure 4-6: Actual TAT per engine type 37

Figure 4-7: Actual TAT stage 0 per engine type 37

Figure 4-11: On Time Performance CFM56-7B In-House Repairs (HS=28 days) – 2015 41 Figure 4-12: On time performance of CFM56-7B modules (HS=28 days) – 2015 41

Figure 4-13: SIPOC Diagram Outsourced Repair 42

Figure 4-14: Current TAT Outsourced Repair 43

Figure 5-2: Different internal drivers that can constrain a process 48

Figure 5-3: CFM56-7B Engine with assemblies 48

Figure 5-4: Current State Value Stream of WBS assemblies 49

Figure 5-5: OTP Outsourced Work (based on 35 day handshake Stage 2) 50

Figure 5-6: OTP Vendor TAT (based on 28 day handshake) 50

Figure 5-7: OTP vendors (based on contract agreements) 51

Figure 5-8: OTP contracts (based on handshake of 28 days) 51

Figure 5-9: Logistics average TAT per vendor 52

Figure 5-10: Value Stream Map import logistics Engine Services 53 Figure 5-11: Value Stream Map export logistics Engine Services 54

Figure 7-2: Current state model MRO chain 67

Figure 7-3: Probability plot Outsourced Repair - vendor TAT 70 Figure 7-4: Probability plot Outsourced Repair – Logistics 71

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Table 1-1: Sub questions ... 6

Table 2-1: Lean Methodology tools ... 10

Table 2-2: Six Sigma tools (iSixSigma, n.d.) ... 11

Table 2-3: Seven tools of Quality Control (Reid & Sanders, 2010, p. 153) ... 13

Table 2-4: Overview of process improvement methodologies ... 15

Table 3-1: Engine types at KLM E&M Engine Shop ... 25

Table 3-2: Engine MRO performance indicators KLM E&M ... 28

Table 4-1: TAT agreements per stage - TAT60 ... 36

Table 4-2: Handshake versus actual TAT – CFM56-7B engines ... 39

Table 5-1: Contracts outside of handshake of 28 days (percentage below 100%) ... 52

Table 8-1: Criteria Weights Process Owner ... 76

Table 8-2: Unweighted scores per alternative ... 77

Table 8-3: Total Dominance score matrix ... 78

Table 8-4: Resulting ranking from KLM E&M perspective ... 78

Table 8-5: Resulting ranking from a Client's perspective ... 79

Table 8-6: Resulting ranking with equal weights ... 79

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Part One: Define Phase

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Introduction

In this chapter the context of the research and the problem are discussed. Next, the scope of the research is given, research questions are shown and finally the research approach is discussed.

1.1. Research Context and Problem

Research Context

This year, around 20,000 commercial aircraft are expected to carry an estimated 3.5 billion travelers around the world (IATA, 2015). This number is expected to grow over the coming decades, to a total of 7 billion passengers by 2034. In accordance to this growth, many new aircraft are expected to be introduced to increase capacity and to replace less efficient older models; This growth will lead to a total global fleet of 40,000 in 2032 (The Guardian, 2013). For aviation to remain the safest mode of transport, maintenance of this large fleet is essential. Maintenance, Repair and Overhaul (MRO) of aircraft is necessary to guarantee the airworthiness and reliability of aircraft.

The market for aircraft MRO is estimated to have a total value of $63.2 billion in 2016 (Shay, 2015). With the previously mentioned expected growth in aircraft fleet numbers, this figure can only be expected to grow even bigger.

The Aircraft MRO market is thus very significant, but it also contains a large number of different competing players, ranging from Original Equipment Manufacturers (OEMs) to airlines, such as Air France-KLM. The different players on the MRO market can be divided into four categories: in-house engineering (airline performs its own maintenance), independent third party, airline third party (airline performs its own and external party maintenance) and OEM (Original Equipment Manufacturer) (CAPA Centre for Aviation, n.d.).

MRO of aircraft can be categorized into three focus areas: Airframe MRO, Components MRO and Engine MRO. The total maintenance cost represent roughly 10-15% of an airline’s operating expenses, of which Airframe maintenance contributes to around 40-45% of this number, Components around 40-45% and Engine around 35-40% (Ackert, 2011). This research will focus on the last maintenance area: Engine MRO.

The Engine MRO market is dominated by OEM MRO providers, such as General Electric and Honeywell (CAPA Centre for Aviation, n.d.). This is caused by the fact that engines are increasingly sold to airlines accompanied by long term OEM support programs, also known as Long Term Service Agreements (LTSA) (Chellappa, 2015). Other providers, such as airline third party providers, have to compete with these OEMs. In this market, which may be worth $34 billion by 2022, the OEMs are strengthening their positions. On one hand by providing more LTSAs – for example 85–90% of Rolls-Royce Trent engines have LTSAs of over 10 years in duration – and on the other hand by incorporating more complex technologies in their new engines, which makes engine MRO a lot more complicated for third parties (Chellappa, 2015). This results in increasing market shares for OEMs – and a more competitive market for other engine MRO providers. Depending on the engine type and age,

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maintenance providers have to compete on cost, throughput time or quality of delivered services (Ayeni, Baines, Lightfoot, & Ball, 2011, p. 2122).

Air France Industries KLM Engineering &Maintenance - Engine Services

Air-France Industries KLM Engineering & Maintenance (AFI KLM E&M) is such an airline third party MRO provider, which has to compete with OEMs and other providers in the increasingly competitive Engine MRO market. Air France Industries KLM Engineering and Maintenance is a division of the Air-France KLM holding. It provides MRO for airframes, components and engines, as an airline third party MRO provider – it provides MRO to both AF-KLM aircraft and other airlines.

For Engine MRO, AFI KLM E&M aims to deliver total engine care – from engine availability to on-site support, to material services and MRO (Air France Industries KLM Engineering & Maintenance, n.d.).

This research is conducted at the Dutch branch of AFI KLM E&M, at the Engine Shop (providing engine MRO) of KLM Engineering and Maintenance, located at Schiphol Airport. The next section will discuss the problem that KLM E&M Engine MRO faces.

Research Problem

As KLM E&M is located in a high-wage, western country, it is difficult for this player to compete on cost in the MRO market. Therefore, the focus lies on the turnaround time and quality aspect. In the year 2015, the average on time performance of KLM E&M Engine MRO was a mere 43%, meaning that 57% of the engines was delivered post contract due date. Next to this metric, 50% of the engines delivered in this period passed the EGT (Exhaust Gas Temperature) quality test. However, to remain competitive in the aircraft engine MRO market, the performance of KLM Engineering & Maintenance Engine Services has to be improved significantly. Previous researches (Meijs, 2016), (Mogendorff, 2016) at KLM E&M have shown that significant improvements can be achieved in parts of the MRO process, but many other areas within the MRO process remain unexplored.

An example of a current project at KLM E&M to reduce the turnaround time is the TAT45 project, aiming to reduce the goal turnaround time of a certain engine type from 60 to 45 days (Mattijssen, Boerrigter, & Klokkers, 2016). However, the way to reach this goal of 45 days remains unclear and no insight exists in how fast an engine can go through the MRO process in theory, if the process went perfectly and without disturbances.

Considering the current performance of KLM E&M Engine MRO and the problem context, the following problem statement is defined:

There is a clear gap between the current performance and the needed performance in the

future for KLM E&M to remain competitive in the aircraft engine MRO market. However,

the approach to locate the value drivers that influence this gap, how the drivers can be

improved, and what the theoretical optimal performance could be in terms of throughput

time is still unknown.

1.2. Research Scope and Objectives

Research Scope – case study

This section will define the scope of the research that aims to contribute to a solution to the previously stated problem. First KLM Engineering and Maintenance is described. Next, the research will zoom in on Engine Services (ES), the department within KLM E&M

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responsible for engine maintenance. Within ES, the research focuses on engine shop visits (full shop visits). This section will conclude with the scope of this research.

KLM Engineering & Maintenance

In 2004, Air France and KLM merged to become the largest European airline group, transporting a combined 77 million passengers per year and having a combined fleet of 573 aircraft. AF-KLM has, as a group, three main divisions: Passenger Business, Cargo and Engineering & Maintenance (KLM, 2015a).

KLM Engineering & Maintenance (E&M) is the KLM branch of this third AF-KLM division. It employs over 5,000 people – a company in its own – and is one of the largest aircraft maintenance companies in the world (KLM, 2013). Together with its French counterpart Air France Industries (AFI), KLM E&M is responsible for third-party revenues totaling 1.2 billion euros, serving 150 customer airlines and handling 1500 aircraft in 2014 (Air France KLM, n.d.).

KLM Engineering & Maintenance Engine Services

The aim of KLM Engineering & Maintenance Engine Services is threefold: To organize Engine Availability using an exchange pool, to provide Engine MRO and thirdly to provide parts repair and engine accessories MRO. This research will focus on the second goal – to provide Engine MRO.

Engine MRO chain

The Engine MRO chain that is considered in this research at KLM Engineering & Maintenance consists of four separate stages (Figure 1-1). Stage 0 consists of determining the Work Scope of the engine repair through the execution of the incoming inspection. The next stage, Stage 1, consists of the disassembly of the engine into smaller modules and components and these disassembled parts are cleaned. The parts are inspected to assess whether the part is serviceable or unserviceable. Within Stage 2, unserviceable engine modules or components are repaired (either in-house or by outsourcing to a third party) or replaced when needed. When all modules and components that needed repair or replacement are ready, the engine is assembled and tested in Stage 3 (KLM, 2008).

Figure 1-1: Engine MRO Process

Objectives and Deliverables

The research objective is derived from the problem stated in section 1.1 and the research scope defined in section 1.2. The following objective is formulated:

Propose a comprehensive framework to optimize the processes of an integral aircraft

engine MRO chain and subsequently apply the framework to decrease the turnaround

time (TAT) of engine MRO at KLM Engineering & Maintenance Engine Services.

From this objective follows a number of deliverables:

 A comprehensive framework to optimize the processes of an integral engine aircraft MRO chain

Stage 0: Work Scope

Stage 1:

Disassembly Stage 2: Repair

Stage 3: Assembly &

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 Recommendations for process improvements within the main constraints in the MRO chain at KLM E&M Engine Services

 Model to assess impact on changes on the total MRO chain turnaround time at KLM E&M Engine Services

1.3. Research Questions

Based on the previously stated research objective, the main research question can be defined:

How can the output of aircraft engine Maintenance, Repair and Overhaul processes be

optimized from an integral perspective?

To answer this main research question, sub-questions are derived. These sub-questions are shown in Table 1-1.

Table 1-1: Sub questions Sub question

1 What framework can be built from literature with the aim of finding and evaluating solutions to improve the output of an aircraft engine MRO process?

2 What criteria can be used to assess the different solution alternatives for KLM E&M Engine Services?

3 What is the current state of the Engine MRO process at KLM E&M Engine Services?

4 What constraints are limiting the turnaround time of the Engine MRO process at KLM E&M Engine Services?

5 What are solution alternatives to optimally reduce the turnaround time at KLM E&M Engine Services from the current towards 45 days?

6 What is the effect of these improvements on the turnaround time of the integral MRO chain at KLM E&M Engine Services?

7 What is/are the optimal solution alternatives to be implemented for KLM E&M Engine Services?

8 What is the theoretical performance of the whole Engine MRO chain at KLM E&M Engine Services?

9 What are new focus areas to further improve the MRO chain performance at KLM E&M Engine Services?

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1.4. Research Approach

The approach used to answer the main and sub research questions is DMAIC – Define Measure Analyze Improve Control (Reid & Sanders, 2010, p. 196). This approach is taken from the Six Sigma methodology, and consists of a study part (DMA) and an improve part (IC). Each step of the DMAIC cycle (see Figure 1-2), in relation to this research, is explained below.

Figure 1-2: DMAIC Cycle (Reid & Sanders, 2010, p. 196)

Define

In the Define phase, the problem is defined by giving the research context, the scope of the research, research questions and the research approach. Next to this, the literature framework is defined to give the steps to be applied to the case study at KLM E&M Engine Services. This case study at KLM E&M Engine Services is further introduced in the define phase.

Measure

In the Measure phase, the current state of the engine MRO process at KLM E&M Engine Services is investigated, as part of the case study.

Analyze

Using data and observations from the Measure phase, constraints in the current MRO process at KLM E&M Engine Services are identified.

Improve

The Improve step of the cycle aims to eliminate the constraints at KLM E&M Engine Services, as found in the Analyze phase. Solution alternatives are created in a systematic way, using tools and methods from the literature framework. Next, the effect of the different solutions on the MRO chain output is modelled.

Validate-Control

In the last stage, the solution alternatives are evaluated using Multi-Criteria Analysis. Next to this, the created comprehensive framework is evaluated and subsequently conclusions and recommendations are given.

The next chapter will develop the framework to decrease the turnaround time of Engine MRO, to be subsequently applied to a case study at KLM Engineering & Maintenance Engine Services.

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Literature Review: Process Improvement, Modelling

and Evaluation

This chapter aims to answer the first research sub-question as defined in section 1.3. This is the following question:

“What framework can be built from literature with the aim of finding and evaluating

solutions to improve the output of an aircraft engine MRO process?”

The comprehensive framework is based on three different methodology groups. First of all Process Improvement methodologies, discussed in section 2.1. These methodologies are used to find different solution alternatives to improve engine MRO processes. Next to this, process modelling methodologies are explored in section 2.2, with the aim of modelling the solution alternatives. In section 2.3, methodologies for the evaluation of different solution alternatives are discussed. Section 2.4 will provide the final comprehensive framework, integrating these three methodology groups, along with the conclusions to this chapter.

2.1. Process Improvement

This section aims to explore different methods to create solution alternatives that can lead to improvements in the engine MRO process, and identify the main elements used in these methodologies. Before literature is reviewed to improve, and later on, model the processes, it is necessary to define what a process is. In essence the definition of a process is the following: “Processes are relationships between inputs and outputs, where inputs are transformed into outputs using a series of activities, which add value to the inputs (Aguilar-Saven, 2004, p. 133).”

To improve processes in a business is essential for business development, management of change and quality improvement. In its basis, business process improvement consists of process mapping and analysis, resulting in greater understanding of the process and possible re-design (Bendell, 2005).

Many different methodologies are known with the purpose of Process Improvement. A (non-exhaustive) number of these methodologies are discussed in this section: Lean, Six Sigma, Lean Six Sigma, Total Quality Management, Theory of Constraints and Creative Problem Solving.

2.1.1. Lean

The first Lean techniques emerged at the Ford production plants in the 1920s; at the plants, Henry Ford demonstrated focus on activities that were of service to the customer and elimination of waste of time and material were possible. Lean is more well-known in association with Toyota in Japan – a company that benefits greatly from the Lean philosophy (Ayeni, Baines, Lightfoot, & Ball, 2011). At Toyota, the “Toyota Production System” was invented. The actual term ‘Lean’ was popularized by (Womack, Jones, & Roos, 1990). (Bendell, 2005, p. 972) provides a clear summary of Lean:

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“Lean (…) is the systematic pursuit of perfect value through the elimination of waste in all aspects of the organization’s business processes. It requires a very clear focus on the value element of all products and services and a thorough understanding of the Value Stream” (Womack, Jones, & Roos, 1990) identify the five core principles of the Lean Organization as being the following:

1. The elimination of waste

2. The identification of the value stream 3. The achievement of flow through the process 4. Introducing pull

5. Achieving continuous pursuit of perfection

Another well-known principle of the Lean philosophy is the Toyota Production System (TPS) House. This House, shown in Figure 2-1, represents the basic principles of Lean. The House is built on a strong foundation: Stability and Standardization. Without these two conditions, the system would collapse. The two pillars are formed by Just-in-Time and Jidoka (built-in-quality). Just-in-time means getting the right amount of material at the right place at the right time, whilst Jidoka is about detecting defects and repairing them early in the process. The base and pillars of the House carry the roof: the aim for highest quality, shortest lead time and lowest cost by continuous improvement: Kaizen (Stewart J. , 2011).

Figure 2-1: the TPS House based on (Stewart J. , 2011, p. 27)

The “TPS House” can be built using Lean tools available for each element. A selection of these tools per “House element” is shown in Table 2-1.

Table 2-1: Lean Methodology tools

House element Goal Tools

Stability The foundation of the house – improvement is impossible without stability in the 4M’s

4M; TIMWOOD(S) ; SMED; Value Stream Map

Standardization Create a standard process 5S ; Visual Management

Just-In-Time To produce the right product at the right time in the right quantity

Takt Time; Kanban; Heijunka

Jidoka (Built-in Quality)

To prevent or detect defects early in the process

Poka-Yoke; Kaikaku (5 Why’s); Andon;

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The main drivers of a (MRO) process taken from Lean, are waste – defined as TIMWOOD(S) – 4M and flow. These drivers can be investigated after the identification of the Value Stream. TIMWOOD(S) is an acronym for different forms of waste, namely Transport, Inventory, Motion, Waiting time, Overproduction, Over-processing, Defects and Skill. 4M, in turn, stands for Man, Machine, Method and Material.

As Ayeni et al. (2011, p. 2115) state in their paper, Lean is widely seen as a viable tool within the aviation MRO industry, albeit not sufficient by itself to realize all the organization’s goals. The paper suggests the use of Lean in combination with other business strategies, such as Six Sigma. The next section will discuss this methodology.

2.1.2. Six Sigma

Six Sigma is a methodology developed by the Motorola Corporation in the 1980s to describe the high level of quality the company was aiming to achieve (Reid & Sanders, 2010, p. 195). The aim of the Six Sigma methodology is to decrease the variation and number of defects in a process; statistically Six Sigma means that 3.4 defects per million occur in a process. The principle of Six Sigma process improvement can be summarized in a straightforward formula:

𝑌 = 𝑓(𝑋) + ε

In this formula, Y represents the output of a certain process. This output is a function f of value drivers X and a factor of uncertainty or error ε (International Six Sigma Institute, n.d.). Of course, a vast number of value drivers X have an influence on the process output Y. The aim of Six Sigma is to screen the value drivers until a selection of main value drivers (or root causes) remain that, upon improvement, positively influence the process output. This screening of value drivers is conducted following the DMAIC cycle.

As stated before in section 0, the DMAIC cycle stands for Define, Measure, Analyze, Improve and Control. Each of these steps works towards improving and controlling future process performance and comes with a large number of available tools. An extensive overview of different Six Sigma tools appropriate for every DMAIC phase is given by (iSixSigma, n.d.). A selection of tools is shown in Table 2-2.

Table 2-2: Six Sigma tools (iSixSigma, n.d.)

DMAIC phase Goal Tools

Define Define project goals and customer

deliverables SIPOC Diagram; Stakeholder Analysis;

Measure Measure the process to determine current performance & quantify the problem

Process Flowchart; Process Sigma Calculation; Normality Plots;

Analyze Analyze and determine the root causes of the defects

Histogram; Pareto Chart; Fishbone Diagram; Statistical Analysis; 5 Why’s

Improve Improve by eliminating defects Brainstorming; Simulation; FMEA

Control Control future process

performance Control Charts; Control Plan

Six Sigma not only relies on technical tools and data-analysis; the other important aspect of Six Sigma considers people involvement. Training of employees to use the technical tools and identify and solve the root causes to improve process quality is essential in Six Sigma; Black Belts and Green Belts are examples of employees trained to apply the Six Sigma methodology (Reid & Sanders, 2010, p. 195).

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Six Sigma can be used to improve existing processes, in this research Engine MRO processes. It provides an analytical framework that encompasses all stages of an improvement project.

2.1.3. Lean Six Sigma

The marriage between Lean and Six Sigma was introduced by (George, 2002). Lean Six Sigma aims to maximize performance by improving customer satisfaction, quality, cost, flexibility and process speed (Jong & Beelaerts van Blokland, 2016).

As stated before, Lean alone cannot effectively bring a process under control (Ayeni, Baines, Lightfoot, & Ball, 2011, p. 2115), nor can it define a sustaining infrastructure for implementation. The combination of Lean and Six Sigma can solve this issue; (Smith & Hawkins, 2004) state that Lean Six Sigma provides the tools to create ongoing business improvement, where Lean “brings action and intuition to pick low-hanging fruit”, while Six Sigma “uses statistical tools to uncover root causes and to provide metrics as mile markers”.

2.1.4. Total Quality Management

Total Quality Management (TQM) originates from a new concept of quality which emerged in the 1980s: proactive quality management, where quality is built into the product and process design. This is a change from the old, reactive paradigm, where quality problems are corrected after they occur (Reid & Sanders, 2010, p. 145).

As with many (process) management methodologies, TQM is a product of many different philosophies and teachings which have developed throughout the years. This has resulted in different concepts that make up the TQM methodology. The concepts, in summary, are the following (Reid & Sanders, 2010, p. 149):

1. Customer focus – identify and meet customer needs

2. Continuous improvement – the cycle of improvement never ends 3. Employee empowerment

4. Use of quality tools – many different tools to measure quality are available 5. Design the products to meet customer focus

6. Quality needs to be built into the process – sources of problems are identified and corrected

7. Quality concepts need to extend to the suppliers as well

Within TQM, projects to improve quality follow a (continuously repeating) cycle of four steps: Plan, Do, Study and Act (PDSA). In the first step, the current process is evaluated, improvement plans are made and performance goals are established. The next step is to implement the improvement plans and to, importantly, collect data for evaluation. In the third step the collected data is studied and assessed whether the performance goals are met. In the final step, Act, measures are taken responding on the result of the previous step; this starts the cycle again (Reid & Sanders, 2010, p. 150).

As stated in the listed core concepts, TQM uses different tools to measure quality in the Plan step. The goal of using these tools is to identify, analyze and improve quality problems. The main tools are called “the seven tools of quality control” and are shown in Table 2-3.

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Table 2-3: Seven tools of Quality Control (Reid & Sanders, 2010, p. 153)

Tool Aim

Cause-and-Effect (Ishikawa) Diagram Identify potential causes of quality problems, related to suppliers, workers, machines, environment, process, material and, measurements and other causes

Flowchart Make the process visual so a clear picture is developed

Checklist Collect information regarding the observed defects,

identify main issues

Control Chart Measure whether a process is operating within

expectations relative to some measured value Scatter Diagram Shows relation between two variables (correlation) Pareto Chart Used to identify quality problems based to their degree

of importance

Histogram Shows the frequency distribution of observed values of a

variable

For this research, the focus of TQM lies too heavily on quality improvement and product design instead of increasing other process performance, such as throughput (TAT). However, TQM does cover useful tools that can be used to identify bottlenecks and root causes in this research, such as Pareto analysis and Cause-and-Effect diagrams. From this last tool, a Cause-and-Effect diagram, possible drivers can be derived: suppliers, workers, machines, environment, process, material and measurements.

2.1.5. Theory of Constraints

The Theory of Constraints (ToC) is a management philosophy developed by Eliyahu Goldratt in 1984, presented in his book called The Goal (Goldratt & Cox, 1984). In this work of fiction, but with a very educational message, Goldratt introduces the concept with the aim to help organizations achieve their goals.

The principle of ToC is to help find practical solutions to business problems: constraints that limit the output of the entire system. The Theory of Constraints focuses on five steps to increase the flow in a system. These steps are, after problem definition, the following:

1. Identify the system’s constraints

2. Exploit the constraint – maximize the utilization and productivity of the constraint 3. Subordinate everything to the constraint – avoid producing more than the constraint

can handle

4. Elevate the constraint – After the previous steps have been conducted, the constraint can be expanded

5. Prevent inertia from becoming the constraint – After the previous steps, a new constraint will appear, so the cycle must begin again.

These steps will be useful when bottlenecks (constraints) are identified in the MRO process; by following the 5 steps different solution alternatives can be developed. A review of ToC (Mabin & Balderstone, 2003) has shown that application of ToC in process improvement can lead to significant improvements in companies, for example an average cycle-time reduction of 66%, an on-time delivery increase of 60% and an inventory reduction of 50%.

2.1.6. Creative Problem Solving

Lean and Six-Sigma are two of the most well-known business process improvement approaches. Although these previously discussed approaches have many strengths, (Bendell, 2005) argues that these approaches are mainly focused on ‘left-brain’ analytical, data-based tools, while neglecting more ‘right-brain’ thinking such as creativity and innovation. Therefore this research aims to incorporate creative problem solving into the approach to

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develop solution alternatives for process improvement. Examples of tools for creative problem solving (CPS) are brainstorming and mind mapping.

In this research, CPS can be used to complement more analytical, data-driven approaches to generate solution alternatives. One can create, for instance, out-of-the-box solutions by creating an “Ideal World”, unlimited by normal constraints such as time and money.

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2.1.7. Summary of process improvement methodologies

This section will summarize the discussed process improvement methodologies and evaluate the usefulness of each methodology for this research. The overview can be found in Table 2-4. In this table, the last column indicates in what part of the DMAIC cycle (see section 0) the methodology can be applied. Two methodologies are mentioned in the table, but not applied in this research: Business Process Reengineering and Business Process Management. Background on these methodologies can be found in Appendix A.

Table 2-4: Overview of process improvement methodologies

Methodology Key elements Aim Usefulness DMAIC Lean Eliminate waste,

identify value stream, flow, pull, continuous improvement, PDCA Pursuit of perfect value in processes through elimination of waste

Lean is a viable tool, however Lean alone cannot adequately improve processes (Ayeni, Baines,

Lightfoot, & Ball, 2011)

-

Six Sigma Value drivers, DMAIC cycle, statistical analysis, root causes Decrease variation and number of defects in processes

Can be used to improve existing processes. It provides an analytical framework that

encompasses all stages of an improvement project

-

Lean Six Sigma Eliminate waste

on analytical basis Combines Lean and Six Sigma Combination of Lean and Six Sigma provides the tools to create ongoing business improvement (Smith & Hawkins, 2004) DMAIC Total Quality Management Customer focus, use of quality tools, quality in processes Proactive quality approach: build quality into process and product design

Focus lies on product quality improvement instead of

throughput/TAT, however TQM covers tools that can be used to identify bottlenecks and root causes in this research

A, I

Theory of

Constraints Bottlenecks, exploit and elevate Increase flow in system Good method to find solutions for bottlenecks when these are found

A, I Business Process Reengineering Design new process, identify change levers, innovative solutions Redesign whole process (green field)

Focuses on creating new processes instead of improving existing processes. Can be useful to find innovative, out-of-box solutions, but not used for other phases.

- Business Process Management Holistic view, continuous improvement, process re-engineering Business improvement enabled by IT, corporate-wide impact and cross-functional process management

Not in line with current improvement philosophy at KLM E&M - Creative Problem Solving Brainstorming,

generate ideas Generating creative solutions Can complement analytical, data-based approach for creating solutions with a more creative approach (Bendell, 2005)

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2.2. Process Modelling

Whereas the previous section (2.1) discussed tools and methodologies used to improve processes, this section will focus on methodologies to model processes within the integral engine MRO chain to subsequently assess the effect of the improvements on the overall turnaround time.

The modelling of processes is becoming increasingly popular, as value-adding processes have become more and more the core of organizing a business, instead of a functional hierarchy perspective. Process Modelling is used on a large scale to develop software that supports business processes, and also to analyze and re-engineer processes where needed. However, Process Modelling is a wide and extensive field, resulting in a vast forest of methodologies, techniques and tools (Aguilar-Saven, 2004). A number of Process Modelling techniques will be discussed in this section.

Flow Chart

(Aguilar-Saven, 2004) defines Flow Charts as graphical representations of a process in which symbols are used to represent elements such as operations, equipment and flow direction. Flow Charts are very flexible in use: there are standards, however the processes can be described in many different ways. A strength of a Flow Chart is that it is easy to use, however a weakness can be that Flow Charts tend to get very big and not good for giving a simple overview of a process.

IDEF

IDEF, Integrated Definition for Function Modelling, represents a group of techniques that enables process modelling of different applications following a fixed paradigm. Examples of applications are IDEF0, which is used for making structural graphical representations of business processes, IDEF1, which is used for information modelling, and IDEF2: used to represent dynamic behavior of resources in a system (Aguilar-Saven, 2004, p. 137).

Gantt chart

A Gantt chart includes the time dimension in the process model; this makes it able to relate a group of activities to a time scale. The downside of Gantt Charts is that they do not show clear dependencies between process steps (Aguilar-Saven, 2004, p. 136).

Object Oriented methods

Object Oriented Process Modelling is used to describe processes that deal with different types of objects and where corresponding actions depend on the type of object that is manipulated. Or in other words: Object Oriented methods are “methods to model and programme a process described as objects, which are transformed by the activities along the process” (Aguilar-Saven, 2004, p. 138).

Modelling means representing the construction and working of a certain system of interest. A main purpose of modelling is to enable the analyst to predict the effect of certain changes to the system; a good model is a tradeoff between simplicity and realism.

Models can be categorized in a number of categories: deterministic versus stochastic, static versus dynamic and discrete versus continuous models. (Birta & Arbez, 2013) describe the differences between these classifications.

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Static versus Dynamic

In a static model, the time dimension is not taken into account. In a dynamic model, on the other hand, time-varying interactions in the system are taken into account (Maria, 1997).

Deterministic versus Stochastic

Models that include random elements are called stochastic models, while models that include no random aspects are called deterministic models (Birta & Arbez, 2013, p. 48).

Discrete versus Continuous

Models that have changing values continuously over time are called continuous models. This is in contrast to discrete models, where state changes happen in discrete intervals over time (Birta & Arbez, 2013, p. 49). These intervals are not known beforehand: simulated time will ‘jump’ in unequal intervals, depending on state changes. In practice, (Enserink, et al., 2010, p. 158) state that “Discrete Simulation is particularly applicable to description and analysis of the operational aspects of systems, such as queuing problems, logistical analysis, workflow management etc.”

2.3. Solution Evaluation

When improvements (solutions) are developed and modelled, a method needs to be followed to evaluate and assess the different solutions. By following a method, a systematic assessment comparison of alternatives can be made (Haan, et al., 2009). When one compares solutions based on different criteria, a Multi-Criteria Analysis (MCA) is conducted. However, MCA is a general label for many different methods. This section will discuss different MCA approaches found in literature.

Impact Table

The most elemental form of Multi-Criteria Analysis consists of the impact table: a neutral representation of values per criterion per alternative (Haan, et al., 2009). No (subjective) conclusions are drawn from the table, it is a mere representation of objective data. Ideally, the impact table is based on quantitative, well-founded analyses. It is important to prevent overlap in the criteria, to keep a balanced and fair MCA.

The Score Card

The score card uses a simple representation of the alternatives, without weighted criteria. Color schemes indicates whether a solution scores positive, negative or neutral on a certain criterion, compared to other alternatives (Haan, et al., 2009) – simply put, the score card is a (subjective) interpretation of the impact table. A disadvantage of the score card is that no weights are given to different criteria, however in case of diverse interests of different stakeholders, the method can be useful (Ministerie van Financien, 1992).

Simple Multi Attribute Rating Technique

Whereas the previous MCA approaches gave equal importance to each criterion, the Simple Multi Attribute Rating Technique (SMART) will give weights to the criteria. SMART consists of a number of steps: first, the different criteria are weighted. Next, the solution values (per criterion) are normalized to a value between 0 and 1. This normalization creates equal scores for criteria with different units (for instance days versus euros). Finally, the normalized values are weighted and added up to a final score per solution (Haan, et al., 2009). Ideally, the weights of the criteria are determined by different stakeholders. However, it is necessary to test the sensitivity of the solutions to the weight factors, as the determination of weight factors remains a subjective approach.

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Evamix Method

The Evamix Method, for Evaluation of Mixed Data, can be applied to a situation where both scores of a ratio and an interval scale are used – or in in other words: a situation where both qualitative and quantitative measurements are used (Brakken, 2001). The Evamix method follows seven steps (Darji & Rao, 2013).

First, an impact table is generated, containing the solution alternatives and criteria (attributes). All criteria (quantitative and qualitative) are given weights. From this impact table, the ordinal (qualitative) and ratio criteria are distinguished. The next step is to standardize the scores to values between 0 and 1, where 1 represents the best score and 0 the worst score. The qualitative and quantitative criteria are separated, resulting in two standardized scorecards. Next, using pairwise comparison, dominance of each alternative over another alternative is determined for each separate criterion. Finally, the dominance of each alternative is added, including the weights of the different criteria. This will result in a total score and ranking of the alternatives (Brakken, 2001).

The advantage of the Evamix method are that the evaluation makes use of both the qualitative and quantitative criteria in an adequate way. However, disadvantages are that the criteria scores are standardized twice, resulting in possible information loss. Next to this, the dominance of an alternative over another alternative is dependent on the whole set of alternatives (Ministerie van Financien, 1992), and is more difficult to interpret due to the needed computational steps (Commissie voor de milieueffectrapportage, 2002).

Giving weights to criteria

For the SMART approach, it was briefly discussed that weights are given to the different criteria. However, different methods are available to generate the weights in a systematic manner.

Ranking

The simplest way to determine criteria weights is through ranking, in ascending or descending order. An example is to rank from 1 to 5, where the most important criterion is given rank 5, and the least important rank 1. This is called the Rank Sum method. Usually, the criteria weights are standardized, so the total weights add up to one. Another way to rank criteria, is through the Rank Exponent method, where a parameter describes the weights (Roszkowska, 2013). It is recommended to use this method as a first approximation only (GITTA, 2013).

Paired Comparison

Weights of criteria can be defined by Paired Comparison (Brown, 2007). It is an easy to use and widely accepted method. First a basic ordering is made in a small set of criteria. Next, relative importance is decided by the team. Subsequently it is necessary to express the importance of a criterion with the criteria of lower importance in terms of equal to, smaller than or larger than relationships. To compute the weights, the resulting linear expressions are solved by giving the least important criterion a value of 1, and working through the expressions. The values are finally standardized, resulting in weights adding up to one.

Analytic Hierarchy Process (AHP)

The Analytic Hierarchy Process (Saaty, 2008), is a method where criteria are measured through pairwise comparison. Inclusion of experts or stakeholders is necessary to drive the priority scales. Saaty uses a “fundamental scale of absolute numbers” to compare two criteria or activities. This scale ranges from 1 to 9, where 1 stands for “equal importance” and 9 stands for “extreme importance” over the other alternative. The inverse of these numbers is

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used when a criterion is less important than another criterion. In this way, a score matrix is formed. Next, the scores per column are normalized. To find the criteria weights, the average normalized score per row is computed. As a final step, a statistical consistency test is conducted.

2.4. Literature framework

From the combination of literature to improve business processes, to model business processes and to evaluate solution alternatives, a comprehensive framework is created. This framework is shown in Figure 2-2.

From Lean Six Sigma, the DMAIC stages are followed and complemented with other methodologies. Within these stages, seven research steps are followed. First, the system needs to be defined: the scope of the research is demarcated and criteria to later on evaluate the different solutions, must be determined. In step two, the current state of the predefined system is measured. This measurement serves as input to find the constraints in the system, but also as a basis for the current state model in step five. The third step is to identify the constraints, limiting the output of the system. When these constraints are found, solutions are created based on the Theory of Constraints and Creative Problem Solving: solutions are found to exploit and elevate the constraints, but also an “Ideal World” is created - solutions that are found without limitations of money, location etc. To create the solutions within these three domains, different tools from literature, such as Lean, can be used.

When the solution alternatives are created they are modelled in step five. A model of the current state is used as a reference. Again, different modelling tools and approaches are available, depending on the specific problem. The sixth step consists of evaluating the different solution alternatives. For this evaluation, previously defined criteria are used. For evaluation, multiple methods are available as well – again, the chosen method depends on the specific problem. The last and seventh step in the framework is to implement the right solution alternatives and to control the process. To achieve continuous improvement, the cycle will start again from the beginning – as indicated by the dotted arrow.

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Designing a comprehensive framework to analyze and improve engine MRO processes from an integral perspective A case study at KLM Engineering and Maintenance Engine Services

Designing a comprehensive framework to analyze

and improve engine MRO processes from an

integral perspective

A case study at KLM Engineering & Maintenance Engine Services

Amber J. C. Rozenberg

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TIL5060 – Master Thesis Project

MSc Transport, Infrastructure and Logistics

10 November 2016

Designing a comprehensive framework to analyze

and improve engine MRO processes from an

integral perspective

A case study at KLM Engineering and Maintenance Engine Services

TIL5060 Master Thesis Project

For the degree of Master of Science in Transport, Infrastructure and Logistics

at the Delft University of Technology

by

Amber J. C. Rozenberg

4013549

Preface

Executive Summary

Step I: Define the system & criteria

Step II: Measure the current state

Step III: Identify the constraints

Step IV: Create solutions for the constraints

Step V: Model the solutions

Step VI: Evaluate the solutions against criteria

Answering the main research question: How can the output of engine Maintenance, Repair

and Overhaul processes be optimized from an integral perspective?

Recommendations, further research and limitations

Contents

List of abbreviations

List of figures and tables

Part One: Define Phase

Introduction

1.1.

Research Context and Problem

Research Context

Air France Industries KLM Engineering &Maintenance - Engine Services

Research Problem

There is a clear gap between the current performance and the needed performance in the

future for KLM E&M to remain competitive in the aircraft engine MRO market. However,

the approach to locate the value drivers that influence this gap, how the drivers can be

improved, and what the theoretical optimal performance could be in terms of throughput

time is still unknown.

1.2.

Research Scope and Objectives

Research Scope – case study

KLM Engineering & Maintenance

KLM Engineering & Maintenance Engine Services

Engine MRO chain

Objectives and Deliverables

Propose a comprehensive framework to optimize the processes of an integral aircraft

engine MRO chain and subsequently apply the framework to decrease the turnaround

time (TAT) of engine MRO at KLM Engineering & Maintenance Engine Services.

1.3.

Research Questions

How can the output of aircraft engine Maintenance, Repair and Overhaul processes be

optimized from an integral perspective?

1.4.

Research Approach

Define

Measure

Analyze

Improve