2.1. Process Improvement
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,
Lean Six Sigma Eliminate waste
on analytical basis Combines Lean
and Six Sigma Combination of Lean and Six Sigma provides the
exploit and elevate Increase flow in
system Good method to find solutions for bottlenecks
16 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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Figure 2-2: Literature Framework
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Now that a comprehensive framework is created, it is necessary to apply the framework to a real-world case study. This case study takes place at KLM Engineering & Maintenance Engine Services. In the next chapter (3), the case study is introduced and the first step of the framework (define the system and determine the criteria) is taken.
In each step in this research applied to the case study, a detailed explanation will be given on the methods used to fulfill the step. As shown in this chapter, multiple methods are available for each step. For the case study, specific methods and tools are chosen from the selection given in this chapter.
This chapter answered the following research 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 framework is based on methodologies to improve processes, model processes and subsequently evaluate improvement solutions. The comprehensive framework consists of seven steps:
I. Definition of the system and determination of criteria II. Measurement of the current state of the system
III. Identification of the constraints limiting the output of the system IV. Creation of solution alternatives for the constraints
a. Exploiting the constraint b. Elevating the constraint
c. Creating the Ideal World solution V. Model the solution alternatives
a. Current state (based on step II) b. Future state exploit
c. Future state elevate d. Ideal state
VI. Evaluate the solution alternatives based on the criteria (step I) VII. Implement the solutions and control the process
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Definition of the Case Study at KLM E&M Engine Services
This chapter indicates the starting point of the case study at KLM E&M Engine Services, in which the previously defined literature framework is applied to find solution alternatives to decrease the overall aircraft engine MRO turnaround time at KLM E&M Engine Services.
This chapter aims to give a broader overview of the context of the case study at KLM E&M Engine Services, by first discussing the technological design of the system (section 3.1), the surrounding market (section 3.2) and the organizational (institutional) design (section 3.3).
From this broader context, criteria to evaluate the solution alternatives later on will be derived, thus answering the second sub-question:
“What criteria can be used to assess the different solution alternatives for KLM E&M Engine Services?”
The set-up of this chapter is shown in Figure 3-1.Figure 3-1: Chapter 3
3.1. Technological Design
(Ayeni, Baines, Lightfoot, & Ball, 2011, p. 2109) give the following definition of the aviation MRO industry: “The aviation MRO industry is responsible for the retaining or restoring of aircraft parts in or to a state in which they can perform their required design function(s). This includes the combination of all technical and corresponding administrative, managerial, supervisory and oversight activities.” This section will discuss the MRO relevant to this research: engine MRO.
3.1.1. Turbofan engines
The Engine Shop at KLM E&M maintains turbofan engines: a specific type of aircraft engine useable for medium-high speeds. A turbofan engine is a tradeoff between the concepts of a pure turbojet and a propeller engine (Anderson, 2008, p. 722), as it combines the high thrust of a turbojet engine with the higher efficiency of a piston engine-propeller combination. A turbofan engine consists of a number of main modules: the fan, the compressor, the combustor (burner), the turbine and the exit nozzle. A schematic view of a Turbofan engine is shown in Figure 3-2.
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The turbine drives both the fan and the compressor, while the fan accelerates a large mass of air that flows through and outside of the engine core. The ratio between flow through and around the core is called the ‘Bypass Ratio’. The air that flows around the engine core mixes with the air that is burned in the combustor and leaves via the nozzle. The thrust of a Turbofan engine is a combination of the airflow from the exhaust nozzle and the thrust produced by the fan (Anderson, 2008, p. 722).
Figure 3-2: Schematic view of a Turbofan engine (Ackert, 2011) 3.1.2. Turbofan engine Maintenance, Repair and Overhaul
The maintenance of aircraft represents around 10-15% of an airline’s operating budget, of which 35-40% of these costs are engine maintenance related (Ackert, 2011, p. 9). The reasons for engine maintenance are threefold: Operational, which is needed to keep the engine in a serviceable and reliable condition, Value Retention, which means to maintain the current and future value of an engine, and finally Regulatory Requirements, meaning meeting the minimum required demands and standards of inspection and maintenance. The health of an engine is generally measured following a number of indicators (Ackert, 2011):
EGT (Exhaust Gas Temperature)
This indicator is a common condition or health parameter. A high EGT can indicate degraded engine performance. The manufacturer gives a maximum allowed temperature; the temperature is measured at the engine exhaust in degrees Celsius.
EGT Margin
The EGT margin is the difference between maximum allowed EGT and peak EGT during takeoff. The required margin after repair is part of the contract with the client.
EPR (Engine Pressure Ratio)
This indicator is sometimes used to measure the thrust of the engine.
N1-Speed
The N1-speed measures the rotation speed of fan.
3.1.3. Serviced engine types at KLM E&M Engine Services
The Engine Shop of KLM E&M serves a limited number of engines. The engine types are described in Table 3-1. It is necessary to differentiate between the different engine types in this research, as not every engine type follows exactly the same process throughout the MRO chain. The CFM56-7B is an engine made by the CFM joint venture (General Electric and SNECMA) and is commonly applied at Boeing 737 aircraft. The 8F6-80E1 engine is made by
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General Electric (GE) and is used for the Airbus A330. The third engine type serviced at the KLM E&M Engine Shop is the CF6-80C2, also by GE, used for wide body aircraft such as the Boeing 747. The last mentioned engine type, the GEnx-1B64, or GEnx for short, will be serviced at KLM E&M in the future and is used for the Boeing 787 Dreamliner.
This research will take into account the first engine type: CFM56-7B. In this way, the research can contribute to existing and ongoing projects to reduce the TAT – such as the TAT45 project; next to this, this engine type is an important capability in the portfolio of KLM E&M, as the volume of this engine type is expected to increase over the following years.
Table 3-1: Engine types at KLM E&M Engine Shop
Engine type OEM Applications #engines per
aircraft
CFM56-7B SNECMA-GE (CFM) B737/A320 2
CF6-80E1 GE A330 2
CF6-80C2 GE B747 4
GEnx-1B64 GE B787 2
3.2. The engine MRO Market
The current turbofan engine manufacturing market is led by three main parties: General Electric (GE), Rolls-Royce and Pratt & Whitney (Ackert, 2011). These parties operate independently, but also in joint ventures. GE and SNECMA have formed the joint venture CFM International, while Rolls-Royce and Pratt & Whitney joined forces in International Aero Engines (IAE). The global market for turbofan engine production is shown in Figure 3-3. It shows that the three mentioned OEM’s dominate the global market, either independently or through their joint ventures.
Figure 3-3: Global market shares for commercial engine production (Flightglobal, 2015) As stated before in the introduction (section 1.1), the engine maintenance market (also called aftermarket) is highly competitive and dominated by OEM players, such as General Electric and Rolls-Royce; an estimate of 55% of the engine MRO market is taken by OEMs, which is the highest share in the whole aircraft MRO market. When comparing this share to Airframe MRO, for instance, it is estimated that OEMs take up only 2% of the global market (Stewart D. , 2015).
26 3.2.1. Competition landscape engine MRO
To compare the main players in the Engine MRO market, landscapes are created using
To compare the main players in the Engine MRO market, landscapes are created using