Repair process improvement of Positioning Modules at the AM-WSN workcenter of ASML

Delft University of

Technology

FACULTY OF MECHANICAL,

MARITIME AND MATERIALS

ENGINEERING

Department of Marine and Transport Technology Mekelweg 2 2628 CD Delft the Netherlands Phone +31 (0)15-2782889 Fax +31 (0)15-2781397 www.mtt.tudelft.nl

This report consists of 105 pages and 12 appendices. It may only be reproduced literally and as a whole. For commercial purposes only with written authorization of Delft University of Technology. Requests for consult are only taken into consideration under the condition that the applicant denies all legal rights on liabilities concerning the contents of the advice.

Specialization: Production Engineering and Logistics Report number: 2012.PEL.7721

Title: Repair process improvement of

Positioning Modules at the AM-WSN workcenter of ASML

Author: A.R. Dorrepaal

Reparatie-proces verbetering van Positioning Modules in het AM-WSN workcenter van ASML

Assignment: Master thesis

Confidential: yes (until Nov 12, 2017) Initiator (university): Prof.dr.ir. G. Lodewijks

Initiator (company): Ir. J. Bonsel (ASML, Veldhoven)

Supervisor: Dr. ir. H.P.M. Veeke

Delft University of

Technology

FACULTY OF MECHANICAL,

MARITIME AND MATERIALS

ENGINEERING

Department of Marine and Transport Technology Mekelweg 2 2628 CD Delft the Netherlands Phone +31 (0)15-2782889 Fax +31 (0)15-2781397 www.mtt.tudelft.nl

I

Supervisor (TUD): Dr. ir. H.P.M. Veeke Specialization: PEL

Supervisor (ASML): Ir. J. Bonsel Report number:

2012.PEL.7721

Confidential: Yes, until Nov 12, 2017

Thesis: Repair process improvement of Positioning Modules at the AM-WSN workcenter of ASML

General background

The NXT lithography-machines of ASML consist of several modules. These modules are built together during final assembly (fasy) in a cleanroom cabin. Before the final assembly phase, the modules are assembled and qualified in „assy‟-workcenters. One of the modules, called the wafer stage (WS), consists of a base module and two positioning modules (PM‟s). A series of production steps and checks is required to produce these PM‟s. These PM‟s are expensive, machine-performance critical and factory-throughput critical parts but also very sensitive to disturbances.

The assembly and qualification of the PM requires high effort. Nevertheless, the workcenter of the PM‟s still faces a fall-out of 32% from the factory. This fall-out is placed back into the system somewhere, depending on the kind of problem that occurs. This causes a repair flow.

On the one hand, a reduction of this repair is necessary. Many technicians try to realize this. On the other hand, it is not clear whether the current process of repairing the PM‟s is the optimal. Thereby, it is required to sustain a moverate of 11 PM‟s/week and meet a delivery performance of 95%, executed at the lowest possible costs.

Problem statement

Three problems found in relation to the repair flow are stipulated as follows: 1. Unknown economic value of yield improvement

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economic value of this yield improvement is unclear. 2. Indistinct reject trajectory

There is no strict procedure to reject a PM and return it to the PM workcenter for repair. The process is un-standardized, based and is fulfilled in different ways. There is often a lack of specific data of the repaired PM and this leads to confusion and unnecessary communication between the stakeholders.

3. Low delivery performance

Due to a combination of low buffer size, wrong composition, long repair lead time and capacity shortage the delivery performance does not meet the requirements. Delivery performance suffers when an above average number of PM‟s is rejected during multiple weeks. Research by simulation will indicate whether the current capacity is appropriate to handle the severe demand and supply fluctuations effected by the stochastic pattern of PM rejections.

Research question

In order to solve the problems stated above, the following research question can be formulated:

“Which system design will lead to the best integral workcenter performance, regarding;

 moverate;

 delivery performance;

 costs;

taking into account the repair process of the NXT WS PM production, respecting existing constraints and resolving known problems?”

Execution

1. Analyze existing processes and system control of the NXT WS PM production at ASML according the Delft Systems Approach.

2. Quantify these existing processes, including the repair process.

3. Formulate proposals of the current NXT WS PM production, considering the repair process. 4. Design an improved structure, in which build- and repair-PM‟s are processed.

5. Study relevant literature.

Prof.dr.ir. G. Lodewijks Dr. ir. H.P.M. Veeke

IV

Preface

After many years of hard study at the faculty of mechanical engineering from the TU Delft, I finally enter the final phase. While successfully completed my bachelor of mechanical engineering, I started the master specialization Production Engineering and Logistics. After fulfilling the short internship at Fontijne Grotnes in Vlaardingen, I began my graduation internship in Veldhoven, at the campus site of ASML. This huge company was a complete new world but soon I found my way in here. Thirsty to an excellent graduation result I started my project. I spoke to a lot of stakeholders and gathered huge amounts of data but one question left: How to approach this project? This question finally seemed harder than expected at first sight and in that way the road to accomplishment was definitely not a flat one. But I made it. And now I feel proud to present you the final version of my graduation thesis. I hope you enjoy reading this report as much as I did in compiling it.

Regarding to the content of my graduation thesis I would like to stipulate some important parts. First of all, the report is divided into three sections: an introduction to ASML, the analysis of the problem and the solution section. One who‟s interesting in ASML in general should definitely read the introduction section. The analysis part starts with zooming in to the PM production process in chapter 4. In chapter 5 mainly production and buffer control is analyzed and in chapter 6 the production resources and capacities are analyzed. The solution section first gives an introduction to the solutions in chapter 8, then explains the qualitative solution of the reject trajectory in chapter 9. Chapter 11 and 12 shows the verification, validation and confidence analysis. Chapter 13 finally shows the results and the analysis of the results, in which I came up with some solid recommendations.

I enjoyed very good support from my mentors. Therefore I would like to thank Hans Veeke from the TU and Joris Bonsel and Herman Vrolix from ASML for their support and good advices.

Onward!

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Summary

An introduction is given of the company ASML, the history of ASML and the products developed by ASML. One of the product families is the current volume-product: the NXT lithography system. This machine is composed out of multiple main modules. One of these main modules is the waferstage. On this waferstage the wafers are moved in the correct position in order to expose them. The waferstage consists of a base module and two positioning modules (PM‟s). These PM‟s are expensive, machine-performance critical and factory-throughput critical parts but also very sensitive to disturbances. Due to the combination of a high disturbance-sensitivity and ASML‟s strategy for a short time-to-market, the factory faces a high fallout of PM‟s of about 32%. This fall-out is noticed as a yield-loss and inevitably results in a repair flow of PM‟s.

The production and reparation of PM‟s are situated in the PM workcenter. The requirements regarding this production system are to be able to fulfill a moverate (output) of 11 PM‟s per week with a delivery performance of 95%. This must be executed against the lowest variable costs possible. At this moment, the moverate of 11 PM‟s per week is met, but with an 82% delivery performance. So, the delivery performance requirement is not met. This low delivery performance is partly caused by the 32% yield-loss.

A yield-loss of 32% is undesirably high. ASML aims to reduce the yield loss to 12%. But the economic value of this yield improvement is unclear. Costs of an improvement project are easy to determine, but a sound trade-off can only be made if the economic value of yield improvements are quantified. The PM production/reparation system has been analyzed in a qualitative and quantitative manner regarding the production structure, the process control and the production resources. From this analysis it became clear that a combination of root causes results in the 82% delivery performance. A buffer of 10 PM‟s on average is used. This buffer exists of four different types of PM‟s. On the moment a repair PM is rejected, a demand arises immediately. To fulfill the demand created by the rejected PM a PM from the buffer is consumed. This creates the situation of a lower buffer for the time being the rejected PM is repaired. The buffer has to cover variability between demand and supply with a temporary lower buffer size. Besides of that, the correct composition of the buffer is hard to maintain when control this buffer based on a number of PM‟s. Also, when an above average number of PM‟s are rejected during multiple weeks, capacity problems occur, with the result that a large part of the PM‟s are consumed from the buffer. Thus, the combination of a long repair PM throughput time, a wrong composition of the buffer, a too small buffer size and capacity shortage results in lower than required delivery performance.

Beside of the problems of the low delivery performance, also problems at the reject trajectory occur. There is no strict procedure to reject a PM from testrig or test and return it back to the PM workcenter

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to repair it. The process is unstandardized and fulfilled in different ways. There is often a lack of specific data of the repaired PM. This leads to confusion and unnecessary communication between the stakeholders and PM‟s waiting to become repaired. By performing a study to the required processes, additional process control and the required information for every repair PM, a real-time dashboard has been designed. This dashboard indicates the status of every repair PM and the information which still needs to be gathered.

By using a time-buffer instead of a piecewise buffer the buffer size and composition of the buffer will be better controllable. Separation of production of regular PM‟s and reparation of rejected PM‟s might lead to a reduced lead-time of rejected PM‟s. By applying configurations of an increased number of workstations and operators, research can be done in order to determine the optimal capacity. Multiple scenarios are defined by means of the parameters described above. The results of these scenarios are created by means of simulation. In order to be able to simulate, a simulation model is developed, verified, validated and executed. The results of the simulations are statistically analyzed by means of a confidence analysis.

From the results it became clear that adding one extra workstation to the bottleneck process, adding two extra operators to the integration operator team and start the production of every regular PM 28 days before the planned demand date, will result in a delivery performance of 95% with the lowest variable costs possible. But after studying the data from the confidence analysis it has to be concluded that there‟s not a statistically significant difference between this configuration and other configurations.

Recommendations can be done in terms of rules-of-thumb. Two rules-of-thumb are designed. The occupancy rate of operators has to be in the range of 78±5%. This results in the optimal delivery performance-costs curve. To reach a delivery performance of 95% within this curve, the correct start moment needs to be determined. This can be determined by using the second rule-of-thumb. The start moment consists of a constant of 17 days and a variable part which linearly increases with the yield-loss. Subsequently the startmoment needs to be scaled to the total workcontent per PM.

Besides of the development of these rule-of-thumbs it is also determined which economic gains will be made if the yield-loss is reduced from 32% to 12%. When one assumes a production of regular PM‟s between 4 PM‟s per week (f.e. due to an economic downturn) and 7.4 PM‟s per week (current situation) then a yearly cost reduction between 941k euro and 1741k euro will be realized.

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Summary (Dutch)

Er is een introductie gegeven van het bedrijf ASML, de geschiedenis van ASML en de producten die door ASML in de loop der tijd zijn ontwikkeld. Eén van de productfamilies is het huidige volume-product: de NXT lithografie-machine. Deze machine is opgebouwd uit meerdere modules. Éen van de modules is de waferstage. Op deze module worden de wafers gepositioneerd voor belichting. De waferstage is opgebouwd uit een base module en twee positioning modules (PM‟s). De PM‟s zijn kritische onderdelen met betrekking tot de machine-prestaties en de fabrieksdoorlooptijd. Daarnaast zijn de PM‟s uiterst gevoelig voor verstoringen.Door deze hoge storingsgevoeligheid en de strategie van ASML om producten zo snel mogelijk in de markt te zetten, vindt er een hoge uitval van PM‟s plaats (32% van de uitvoer). Deze uitval resulteert in een reparatiestroom van PM‟s.

De productie en reparatie van PM‟s vinden plaats in het PM workcenter. Het workcenter heeft de eis om een totale uitvoer van 11 PM‟s per week mogelijk te maken tegen een leverbetrouwbaarheid van 95%. Daarbij dienen de variabele kosten per PM zo laag mogelijk gehouden te worden. Op dit moment wordt er wel een uitvoer van 11 PM‟s per week behaald maar de leverbetrouwbaarheid blijft steken op 82%. Dit wordt mede veroorzaakt door het hoge yield verlies van 32%.

Een yield verlies van 32% wordt door ASML gezien als onacceptabel hoog. Het is echter onduidelijk welk economisch voordeel het heeft om dit verlies terug te dringen. De kosten van een verbeterproject zijn vrij eenvoudig te bepalen, maar om een juiste afweging te kunnen maken zullen ook de kostenbesparingen van yield-verlies reducties moeten zijn gekwantificeerd.

Het productiesysteem van de PM‟s is kwalitatief en kwantitatief geanalyseerd met betrekking tot de productiestructuur, de procesbeheersing en de productiemiddelen. Uit de analyse wordt duidelijk dat er een combinatie van oorzaken aan te wijzen is voor de te lage leverbetrouwbaarheid. Op dit moment wordt er een stuksbuffer gehanteerd van gemiddeld 10 PM‟s. Deze buffer bestaat uit vier verschillende types PM‟s. Op het moment dat er een reparatiemodule geretourneerd wordt, ontstaat er per direct een vraag. Deze vraag wordt ingevuld door een PM uit de buffer. Zo lang de te repareren PM in het productiesysteem onderweg is, moeten de variaties in het systeem met een kleinere buffergrootte opgevangen worden. Daarnaast wordt het behouden van de juiste samenstelling bemoeilijkt door een stuksbuffer te hanteren. Als er gedurende meerdere weken een bovengemiddeld aantal PM‟s teruggevoerd wordt naar het workcenter, ontstaan er capaciteitsproblemen, met als gevolg dat de buffer leeggeconsumeerd wordt. De te lage leverbetrouwbaarheid wordt dus veroorzaakt door een combinatie van een te lange doorlooptijd van de reparatiemodules, een verkeerde samenstelling van de buffer, een te kleine buffergrootte en capaciteitstekort.

De doorlooptijd van de reparatiemodules wordt niet alleen veroorzaakt door het reparatieproces, maar ook door het traject van het moment tot afwijzing op de machine totdat de daadwerkelijke reparatie

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plaats vindt. Er zijn geen duidelijke afspraken en het is onduidelijk welke informatie benodigd is voor de reparatie van een PM. Door het opzetten van een kwalitatief proces is vastgelegd welke processtappen in welke volgorde door welke betrokken afdelingen uitgevoerd moeten worden. Ook is onderzocht welke informatie benodigd is op welk tijdstip. Dit heeft geleidt tot een real-time dashboard, welke per reparatie-PM aangeeft wat de status is en welke informatie nog verstrekt moet worden.

Door een tijdsbuffer per reguliere PM in te bouwen en geen stuksbuffer aan te houden kan de buffergrootte en samenstelling beter worden beheerst. Door de productie- en reparatiestroom te scheiden kan er een reductie van de doorlooptijd van reparatiemodules gerealiseerd worden. Door configuraties met toenemende werkstations en operators toe te passen kan onderzocht worden wat de capaciteit is. Er zijn meerdere scenario‟s gemaakt aan de hand van bovengenoemde parameters. Resultaten van deze scenario‟s zijn gecreëerd met behulp van simulatie. Hiervoor is een simulatiemodel ontwikkeld, geverifieerd, gevalideerd en uitgevoerd. De resultaten van de simulaties zijn vervolgens statistisch beoordeeld aan de hand van een betrouwbaarheidsanalyse.

Uit de resultaten bleek dat het scenario waarbij er één werkstation aan de bottleneck wordt toegevoegd, er twee extra operators aan het integratie operator-team deelnemen en er bij elke reguliere PM 28 dagen voor het geplande vraagmoment gestart wordt met productie, de leverbetrouwbaarheid van 95% gehaald wordt tegen de laagst mogelijke variabele kosten per PM. Echter, na bestudering van de gegevens uit de betrouwbaarheidsanalyse blijkt dat er geen statistisch significant verschil aangetoond kan worden tussen deze configuratie en andere configuraties.

Een aanbeveling kan wel gedaan worden in termen van vuistregels. Er zijn twee vuistregels ontworpen, met betrekking tot de bezettingsgraad van de operators en met betrekking tot het startmoment. De optimale bezettingsgraad van de operators blijkt zich te vormen rond 78±5%. Hiermee wordt de optimale leverbetrouwbaarheid-kosten curve bereikt. Om vervolgens binnen deze curve een leverbetrouwbaarheid van 95% te behalen, dient het startmoment bepaald te worden. Hiervoor is een tweede vuistregel opgesteld. Het startmoment bestaat uit een constant deel van 17 dagen en een variabel deel wat lineair oploopt met het yield-verlies. Vervolgens dient het startmoment geschaald te worden naar de werkinhoud.

Naast de bepaling van deze vuistregels is ook bepaald wat de economische voordelen zijn van een yield-verlies reductie van 32% naar 12%. Als men uitgaat van een productie van reguliere PM‟s tussen 4 PM‟s per week (bijv. door een economische terugval) en 7.4 PM‟s per week (huidig) dan worden er jaarlijks tussen de 941k euro en 1741k euro aan kosten bespaard.

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Glossary

12NC Twelve digit Numerical Code

AM-WSN Assembly Mechanical - WaferStage NXT

ASML Advanced Semiconductor Materials Lithography

assy Assembly phase of modules

BAMO Base Module

BCL Base Capacity Level

BE Business Engineering

BT Buffer Time

CB Carrier base

CIP Continuous Improvement Process

COG Cost Of Goods

CR Crash Rim

CT Cycle Time

D&E Development & Engineering

DN Disturbance Notification

DP Delivery Performance

DRB Disturbance Review Board

ERP Enterprise Resource Planning

EUV Extreme Ultra Violet light

fasy Final assembly phase complete system

INT Integration

LEX Left Exposure Chuck

LOS motor Long Stroke motor

LT Lead Time

ME Manufacturing Engineering

MH Material Handling

MM Means & Methods

Moverate Output (defined by # PM‟s/week)

MQ Manufacturing Quality

NXE NXT with EUV

NXT New Generation Twinscan (platform)

OL Output Leader

PCCSIM Problem, Containment, Cause, Solution, Implementation, Monitor

PCS Problem Cause Solution

PIT Performance Improvement Team

PM Positioning module

PMint2BM Integration of PM to the BAMO

PMQT Positioning Module Quality Test

PP Production Planning

PRO Program Management

REF Refurbishment

RFF Rolling Financial Forecast

REX Right Exposure Chuck

SAPIR Scope, Action, Plan, Implement, Results

SCE Supply Chain Engineering

SS motor Short Stroke motor

TL Team leader

TOPS Technical OPerationS Coördinator

TR Testrig

WIP Work in Progress

WACC Weighted Average Cost of Capital

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Table of contents

Preface ... IV Summary ... VI Summary (Dutch) ... VIII Glossary ... X Table of contents ... XII

I. Introduction

1. General introduction ASML ... 3

1.1. Company ... 3

1.2. History ... 3

1.3. Moore‟s law ... 4

2. Lithography systems of ASML ... 7

2.1. Wafers ... 7 2.2. Lithography ... 8 2.3. Waferstage ... 9 2.4. Positioning Module ... 9 3. Rework ...13 3.1. Description ...13

3.2. Effects of yield loss ...13

3.3. Goal and requirements ...14

3.3.1. Goal ...14

3.3.2. Required performance ...16

3.4. Conclusion ...16

II. Analysis 4. Depiction of the „assemble WS‟-function ...21

4.1. Aggregation layer 0: black box ...21

4.2. Aggregation layer 1: material flow ...21

4.3. Aggregation layer 2: „assemble WS‟ ...22

4.4. The economic value of a yield improvement ...23

4.5. Conclusion ...25

5. „Assemble PM‟-function ...27

5.1. Functional structure ...27

5.2. Quantification of repair flow ...27

5.3. Planning & Control ...29

5.3.1. Process control ...29

5.3.2. Function control ...30

5.3.3. Buffer size and delivery performance ...31

5.4. Indistinct handling of rejected PM‟s ...35

5.5. Conclusion ...36

6. Production structure of „Assemble PM‟...39

6.1. Functional structure ...39

6.2. Production structure ...40

6.3. Capacity ...41

6.3.1. Workstations ...41

6.3.2. Operators ...43

6.4. Effect of the repair flow ...44

6.5. Conclusion ...46

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8. Solution directions ...53

8.1. Solution method ...53

8.2. Experimental design ...53

9. Qualitative feed forward control for rejected PM‟s ...57

9.1. Introduction ...57

9.2. Solution ...57

9.3. Execution ...61

10. Simulation model ...63

10.1. Introduction ...63

10.2. Process description language ...65

10.3 Cost function ...68

11. Verification & Validation ...69

11.1. Verification ...69 11.1.1. Introduction...69 11.1.2. Visualization ...69 11.1.3. Tracing ...71 11.1.4. Calculations ...73 11.2. Validation ...78 12. Confidence analysis ...81 12.1. Introduction ...81

12.2. Total variable costs ...81

12.3. Delivery performance ...82

12.4. Conclusion ...82

13. Results ...83

13.1. Introduction ...83

13.2. As-is ...83

13.3. Increasing delivery performance ...85

13.3.1. Results ...85

13.3.2. Comparing the scenarios ...91

13.3.3. Robustness ...92

13.3.4. Rule-of-thumb occupancy rate ...94

13.4. Reducing yield-loss ...95 13.4.1. Introduction...95 13.4.2. Results ...95 13.4.3. Rule-of-thumb startmoment ...98 13.4.4. Conclusion ...99 14. Conclusions ... 101 15. Recommendations ... 103 References ... 105 List of figures ... 107 List of tables ... 109 IV. Appendix Appendix A – Scientific paper ... 112

Appendix B – Swimming lane reject PM flow ... 119

Part 1: escalation flow and reject flow ... 119

Part 2: return flow and analyze / repair flow ... 120

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Appendix D – Scrap ... 122

Appendix E – Effective available manpower ... 123

Appendix F – Disturbance management ... 124

Appendix G - Disturbance duration ... 128

Appendix H - Initialization time of the model ... 131

Appendix I - Inter arrival time distribution... 132

Appendix J – input of the simulation model ... 133

Appendix K – Occupancy rates of workstations ... 139

Appendix L – output of the experiments ... 140

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1. General introduction ASML

1.1. Company

ASML is one of the world's leading providers of lithography systems for the semiconductor industry, manufacturing complex machines that are critical to the production of integrated circuits or microchips. Headquartered in Veldhoven, the Netherlands, ASML designs, develops, integrates, markets and services these advanced systems, which continue to help customers - the major chipmakers - reduce the size and increase the functionality of microchips, and consumer electronic equipment.

1.2. History

Founded in 1984 as a joint venture of Philips and ASM International, the production of the first stepper systems (called PAS, Philips Automatic Stepper) were realized. Within a year ASML grew to 100 employees and ASML moved from Eindhoven to an office in Veldhoven. In 1987, ultraviolet light was used in the PAS2500. With this technique, prints could be made with details of 0.7 micrometer. This machine was followed by the PAS5000, which realized details of 0.5 micrometer in 1989 and 0.35 micrometer in 1991. In 1993 the production of step-and-scan machines started, which lead to a higher throughput of the wafers. In 2001, lithography-machines of ASML were also equipped with an ArF-laser source. This light made it able to realize better imaging on wafers.

During the 21st _{century, the techniques in the ASML lithography-machines are increasing rapidly. In} 2006, the TWINSCAN XT is considered as a volume-product, with over 250 shipping‟s a year.In 2007, imaging of 36.5nm is possible by the XT1900i. Also the immersion technique in twinscan is starting to become volume, with 60 immersion-systems sold this year. In 2008, a new platform is introduced: the TWINSCAN NXT: The new platform brings overlay and productivity breakthroughs: it addresses technical and economic challenges in a holistic way, enabling a more seamless adoption of double patterning.

In the years after 2008 the current systems are sold more often, but also another technique is introduced: NXE-machines with EUV. This enables smaller imaging, due to the Extreme Ultraviolet laser beam. Nowadays, the NXE systems are in pilot phase with a dozen sold, but parallel to developing the design, the system will be pushed to the market.

Also a strong increase in market share is realized, up to 80% market share nowadays. The reason for this success is the result of focus on modularity of the lithography systems and short time to market.

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1.3. Moore’s law

Every digital electronic device (mobile phones, laptops, usb-sticks, etc.) consist of chips. During the existence of chips, the power, cost and time required for every computation done by these chips is highly reduced. This is a result of the reduction of the size of these chips.

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Nowadays, Integrated Circuits (IC‟s) can be built together by imaging, which result in a high amount of transistors on a small area. The trend in the past 40 years was first observed by Intel co-founder Gordon Moore and is referred to as „Moore‟s Law‟. Moore‟s Law states that every two years the computational capacity of a chip is doubled. Until now this is reality, but to contain this law in future, ASML focuses on developing new techniques on a high speed and serves his customers with the systems consisting of these techniques.

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2.Lithography systems of ASML

2.1. Wafers

Several processes are necessary to create IC‟s. The core processes are shown in Figure 3. Wafers are composed of crystalline silicium. Oxidation of the silicium is the first step, which creates an isolated layer. Then a photoresist layer is formed. This layer is a photoresist to make it able to apply lithography.

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The light is brought onto the wafer by a pattern. A pattern is created in the photoresist layer. This gives the possibility to etch the silicium oxide where it has to conduct. These steps are repeated several times to create a series of layers with complex structures. In this way billions of transistors are created in the semiconductor material of the wafer.

As indicated in Figure 4, ASML‟s core business is related to the „exposure‟ step of the wafer processes. To create a pattern on the photoresist layer of the wafer, a mask is needed. The mask is called a reticle.

Figure 4-‘Exposure’ process in wafer process cycle

The pattern on a reticle is about 4 times larger than the image on the wafer. Therefore a lens is needed to guide the beam of light onto the wafer. This lens has a fixed position in the machine. To create images on the whole surface of the wafer, the reticle and the wafer are moved in horizontal directions.

2.2. Lithography

ASML produces systems in the product families XT, NXT and NXE. The XT family was the first series of Twinscan machines. In a Twinscan system, the aligning and scanning is taking place parallel. This increases productivity. In the NXT systems, improvements were introduced on the XT. Improvements in relation to the design, but also in relation to software were realized. For example holistic lithography was used.Holistic lithography integrates computational lithography, wafer lithography and process control into a seamless approach that helps optimize process windows and ensure the best system set-up. In the NXE family a total different design is set up for a new generation of lithography. The EUV (Extreme Ultra Violet) light in the NXE systems results in smaller overlay and

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imaging accuracies and higher throughput. In this report the subject is the waferstage of the NXT system.

The lithography systems of ASML do have a strong modular composition. The laser light has to travel through several modules of the machine. In figure 3 some of the parts are pointed. The light is created outside the machine and enters at the light entrance. The light travels through the illumination system via several mirrors and lenses to create the optimal composition of the light. After that, the light crosses the reticle stage and leaves the reticle stage patterned. In the lens, the light bundle is made four times smaller and is focused onto the wafer, creating the pattern on the wafer. The wafer is supported and moved by the waferstage.

Figure 5 - lithography machine

2.3. Waferstage

The main purpose of the wafer stage is to exchange the wafer with the wafer handler, and accurately position the wafer for exposure. In order to accomplish this, the waferstage processes two wafers in parallel, one on the exposure side and one on the measure side. This is shown in Figure 6. The main components of the NXT wafer stage are the base frame (BAMO) and the two positioning modules (PM).

2.4. Positioning Module

On a waferstage always two positioning modules are present, a LEX (left-side positioning module) and a REX (right-side positioning module). The positioning module guides the wafers and interchanges the wafers between the lens and the wafer handler. The PM is able to freely move, without physical interaction with the BAMO. This is done by planar motors in the PM. These „long

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stroke‟ (LS) motors cause movements in x- and y-directions and create a space between the PM and the BAMO, all realized by magnetic force.

Figure 6 - waferstage

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The base carrier holds the long strokes and the other components. The hose assembly consists of multiple ducts to supply the other components of water, air and vacuum. The short stroke module is assembled onto the base carrier, with the hose assembly in between. The short stroke module is used for fine alignment of the wafer. The measurements are done with multiple alignment lasers. To protect the PM for impacts due to for example collisions, a crash rim is assembled. On top of the short stroke module the wafer chuck is assembled. This wafer chuck supports the wafer table. On top of the wafer table, the wafers can be placed.

The precision of the alignment of the wafer is comparable with shining with a torch to the moon and hitting a coin on the moon with that light bundle. In the case of the lithography systems, not the torch is aligned but the coin is aligned. Therefore a minimum of deviations in the components and assembly of the PM is allowed. Another important issue is the throughput of the lithography systems and therefore the speed of the PM‟s. As a matter of fact, with the design of lithography systems three performance indicators of the system are taken into account. The performance of the system is measured in terms of:

1. Imaging: The quality of the transfer of images from the reticle to the wafer.

2. Overlay: The accuracy with which the system can expose one product layer on top of another.

3. Throughput: The amount of handled wafers per hour.

Machines nowadays can produce 175 - 200 imaged wafers per hour with an overlay of 2.5nm. This requires high demands of the lithography system. The wafer stage is a critical module for the realization of these performances. Working at extremely high speeds, and using an accurate measuring system, it is capable of achieving high throughput and maintaining high accuracy during scanning.

Nevertheless does this high performance result in complex modules. And due to this complexity, continuous improvements in the design are made. Especially the PM‟s consists of a high-tech design. This leads to fallout of about 30% at the end of the production process sequence. The extreme high cost-of-goods of a PM results in an inevitable rework of every failed PM.

13

3. Rework

3.1. Description

Rework cannot be described as a stand-alone system. It is inevitably connected to a certain production process. As a matter of fact, the rework is caused due to yield losses in the production process. An example of rework is given by [Flapper, 2002] in Figure 8.

Figure 8 - Example of production-rework process

In this example, it becomes clear that dealing with yield loss can be done in different ways. The failed products which are not able to become repaired are known as non-reworkable defective products or scrap. Products which still can be repaired are known as reworkable defective products. The rework can be realized in two ways, the in-line rework or the off-line rework. In the case of in-line rework the same resources are used for both the production and the rework. In the case of off-line rework, dedicated resources are available for the rework only.

3.2. Effects of yield loss

As mentioned above, yield and rework are strongly related. In [Bohn/Terwiesch, 1999] some issues are pointed in relation to rework. Rework as a result of yield loss has a negative influence on capacity of the process. If rework involves only non-bottleneck processes with a large amount of idle time, the rework has a negligible effect on the overall process capacity. However in many cases rework is

14

severe enough to make a process a bottleneck. The worst case scenario occurs when the rework needs to be carried out in the bottleneck process. As known, the overall capacity never exceeds the bottleneck capacity. Therefore all capacity invested in rework on the bottleneck process is a loss of capacity from the perspective of the overall process.

Also the variability is influenced by rework. Yield loss never occurs in a deterministic way but in a stochastic way. Thus, yield losses increase variability and a result of that is a decrease of capacity. Even if the operation itself is deterministic, when the failed item will immediately be reworked on the specific workstation it will lead to a random variable processing time of the specific item at the end of the process sequence.

These capacity losses due to variability can partially be solved by adding and increasing buffers (thus increasing WIP), especially behind the lower yield processes. Coincide of this measure is; higher costs with relation to the material (interest) and an increase of overall throughput-time.

Table 1 - Cost effects of yield loss

Concluding, an increase in yield can realize higher capacity with the same production means and lower variability. Lower variability may increase capacity and gives opportunities to lower the WIP. Lowering the WIP decreases the costs of capital and shortens the throughput-time. An increase of available capacity in the regular production process will be realized by creating an off-line rework process. According to this conclusions it is interesting whether the performance of the workcenter as a whole increases by using off-line rework or not.

3.3. Goaland requirements

3.3.1. Goal

The waferstages are produced in the AM-WSN workcenter. A sub-center of AM-WSN is the WSN-PM workcenter. In the WSN-PM workcenter the PM‟s are assembled. The goal of the AM-WSN workcenter is to assemble waferstages. To realize this goal, several functions within this workcenter need to be fulfilled. Two of these functions are the „assemble-PM‟ function and the function to rework failed PM‟s, called the „repair PM‟ function. As mentioned above, several parameters are interesting regarding the performance of a production process with rework.

cost type

yield effect

material-related costs

incremental material to replace bad components

labor-related costs

rework labor

capacity-related costs

more capacity needed in the rework loops of processes

variability-related costs

WIP costs to buffer variability

15

As stated in [Bikker, 1992], for the design of a system clear requirements needs to be formulated. Bikker formulates six process design criteria. Four design criteria are selected in the case of this rework function. When developing a system for the rework function, decisions needs to be taken on behalf of the following design criteria:

• effectiveness • productivity • reliability • flexibility

Since the new rework process needs to be seamless adopted in the AM-WSN workcenter, the design criteria „quality of work‟ and „ability to innovate‟ won‟t be used. The integral solution will ask a way of working which is comparable with the current way of working in the workcenter. In other words, decisions on these two requirements are outside the system boundary.

The requirement effectiveness is measured in terms of results. Within the AM-WSN workcenter these results are expressed in terms of capacity or moverate. The requirement productivity is the ratio of effectiveness and efficiency. The efficiency is the level of sacrificing means to realize a certain goal (the results). Within the AM-WSN workcenter this efficiency is expressed in terms of costs. At ASML these costs are subdivided in material-related costs, labor-related costs and facility-related costs. Reliability regarding the production of the PM is measured in terms of delivery time reliability. In [In „t Veld, 1993, p.8] flexibility is explained with relation to different aspects. Important aspects within the ASML production are the renewal flexibility, the volume flexibility and the organizational flexibility. The „assemble PM‟ function has to have the capacity to meet the demands and fulfill the demands on time (delivery performance) by performing against a certain level of costs. Of course, flexibility can be used to adjust to the right capacity or to reach a specific level of on-time deliveries of the PM‟s when order patterns are suddenly changing.

With the above, the goal of a rework function at ASML can be described as follows:

The rework function in the AM-WSN workcenter has the main goal to analyze, dismount and repair failed PM‟s with a minimum of negative impact on the WSN-PM workcenter regarding;

 moverate

 delivery performance

 costs

o labor costs

o capital costs of WIP and buffer

16

3.3.2. Required performance

ASML want to be able to decide to keep the moverate constant and decrease the work content. It is required to have a system which is able to act on a moverate of 11 PM‟s/week.

The workcenter produces modules in assy phase. The lithography system consists of multiple modules. These modules are produced in the workcenters in parallel order. With parallel production, the performances are multiplied with each other to determine the delivery performance of the complete litho system. Therefore a high delivery performance is required for every workcenter on its own. The performance of the delivery time of the workcenter is stated by ASML to be 95%, measured over a year.

Both the delivery performance and the moverate requirement need to be fulfilled with total variable costs as low as possible. These costs consist of the components as shown in table 1.

3.4. Conclusion

In Figure 9 the parts aggregation is shown as explained in the introduction.

Figure 9 - parts aggregation

Rework can be distinguished in in-line rework and off-line rework. Rework is the effect of yield loss. Effects of yield change are mentioned. An increase in yield can realize higher capacity with the same production means and lower variability. Lower variability increases capacity and lowers the WIP.

main module sub-assembly’s

metroframe … waferstage reticle stage chuck assy PM (2x) BaMo module carrier base crash rim SS motor hose assy LOS motors system XT NXT NXE

17

Lowering the WIP decreases the material costs and shortens the throughput-time. Second, an increase of yield in the regular production process can be realized by creating an off-line rework process.

Rework as part of a production process in ASML has a goal which is described as follows:

The rework function in the AM-WSN workcenter has the main goal to analyze, dismount and repair failed PM‟s with a minimum of negative impact on the WSN-PM workcenter regarding;

 moverate  delivery performance  costs o labor costs o WIP costs o facility costs

Requirements are stated as follows:  moverate ≥ 11 PM‟s/week  delivery performance ≥ 95%  lowest costs possible

19

21

4. Depiction of the ‘assemble WS’-function

4.1. Aggregation layer 0:black box

Figure 10-Aggregation layer 0: black box ASML

As explained in the introduction, the lithography systems carry a strong modularity. The main modules are assembled separated from each other and built together to a lithography system in the final assembly. This implies that in the system „ASML company‟ (see Figure 10) a series of subsystems are present. One of these subsystems is the assembly of the waferstage. This is shown in Figure 11.

4.2. Aggregation layer 1: material flow

Figure 11 shows the PROPER-model [Veeke, 2007] dedicated to ASML. A zoom-in is shown on the „produce‟-function within ASML. This subsystem realizes the production of lithography systems. This subsystem is responsible for the materials flow. It is divided into a sequence of processes to be able to fulfill the orders in the order flow.

The zoom into the material flow of ASML has been divided in a „module assembly‟-function, a „final assembly‟-function, a „test‟-function and an „install‟-function. The problem zone is situated within the „module assembly‟-function. Within this function, the production of the modules of a lithography system takes place in parallel order. Workcenters are allocated to fulfill the production of a module. One of the modules, as described in the introduction, is the waferstage (WS). The „assemble WS‟ -function is fulfilled by the AM-WSN workcenter. Within the „assemble WS‟--function also the positioning modules are assembled.

requirements performance orders materials resources performed orders litho systems used resources ASML company

22

Figure 11-Aggregation layer 1: zoom into the material flow

Figure 12 - aggregation layer 2: zoom into ‘assemble WS’

4.3. Aggregation layer 2: ‘assemble WS’

In the AM-WSN workcenter the waferstage is produced. This is done by several build, integrate and test functions. This is shown in Figure 12. As mentioned in the introduction, the waferstage consists of a BAMO and two PM‟s. The PM‟s are produced in the „assemble PM‟-function. The entering flows of this function are materials for new build PM‟s, refurb PM‟s and repair PM‟s. The refurb PM‟s are

assemble requirements performance orders materials resources performed orders litho systems used resources materials materials Assemble WS CONTROL standards results Assemble RS Assemble… test install field returns yield loss Assemble WS (AM-WSN) progress order quantities - required MR - req.del.perf. - budget - CT/ MR, - costs, - deliv. perf. assemble PM integrate refurb test F a s y & t e s t c us tom e r

23

replaced at the customer and returned to ASML. These PM‟s are upgraded during refurb and then added to the regular flow into „assemble PM‟. The parts are assembled to a complete integrated and tested PM and will, together with another PM, be integrated to a BAMO. The PM‟s and BAMO form a waferstage. This waferstage can either be tested on a testrig or continue immediately to the final assembly section of ASML. The waferstages which proceed to the testrig are tested. After that, a part of the PM-sets is de-integrated from the BAMO and delivered to the service department of ASML. The other part continues to the final assembly (fasy), is integrated in a new NXT lithography system and tested.

The repair PM‟s are rejected from inside the factory. The rejected PM‟s originate from the testrig sequences and the tests of the lithography systems. This is indicated by the red arrow in Figure 12. Refurbish PM‟s and new build PM‟s are considered as one flow for three reasons:

1. Repair PM‟s are originating from both the build flow and the refurbish flow.

2. The refurbishment flow as well as the new build flow both serves the profit of ASML. Opposite, the costs of the repair flow have to be ascribed to the build and refurbish flow. The „assemble PM‟-function gets orders from the order flow of ASML and reports progress to the order flow. The performance of this function is reported to higher echelons. As is discussed in the introduction, the performance is measured in terms of delivery performance, moverate (output) and costs.

4.4.The economic value of a yield improvement

The output of the PM production system is shown in Figure 13. Except from week 52 (Christmas holiday), the weeks with a low output of build PM‟s do also have a high output of repair PM‟s. There appears to be a negative influence of repair PM‟s on the output of regular build PM‟s. This might be the case when the repair flow consumes a substantial part of the available capacity.

Figure 13 - Output of ‘assemble PM’-function

0 2 4 6 8 10 12 1140 1141 1142 1143 1144 1145 1146 1147 1148 1149 1150 1151 1152 1201 1202 1203 1204 1205 1206 1207 1208 1209 # PM Week

Output AM-WSN

24

Four types of PM‟s are produced by ASML in the AM-WSN workcenter:

 PM311LEX

 PM311REX

 PM321LEX

 PM321REX

The moverate and the yield loss of the PM‟s is determined by counting the number of PM‟s of each category over the period of week 8 of 2011 to week 8 of 2012. With these data the yield loss per PM type is determined.

Table 2-Product mix and yield loss

The product mix of the output of the workcenter is determined to be 33% of PM311‟s versus 67% of the PM321‟s. The consolidated yield loss therefore is determined to be 32%. How this 32% relates to the other flows of PM‟s through the ASML system is shown in Figure 14.

Figure 14 - flows of PM's

The yield loss originates from the testrig systems (11%) and from the NXT systems which are tested before being directed to the customer (21%). The 32% of rejected PM‟s are added to the „assemble PM‟-function together with the 68% of build and refurb PM‟s. This results in the 100% output of the „assemble PM‟-function. The integration of the PM-sets to a BAMO leads to a 33% flow directly to fasy. These PM‟s are unqualified because it was chosen not to qualify these PM‟s on a testrig. This choice is made to reach the required moverate. 67% of the PM flow continues to the testrig tests.

PM311LEX PM311REX PM321LEX PM321REX

build PM's [#]

48

48

93

97

repair PM's [#]

24

19

43

51

total [#]

72

67

136

148

Yield loss [%]

33%

28%

32%

34%

25

After this, 47% of the PM‟s is delivered to the service pool. 9% of the PM‟s continues to fasy. ASML aims to increase the capacity of the testrig process.

In [Bohn/Terwiesch] drivers to reduce yield loss are stipulated. Managerial decisions are driven by the economic value of a yield improvement. In the case of ASML, especially decisions regarding process improvements are drivers to understand economic pay-back of yield loss reduction. Whereas the economic cost of improvement projects can be computed easily, the gains can only be determined by understanding the economic value of a yield improvement.

A yield loss of 32% is undesirably high. ASML aims to reduce the yield loss to 12%. But the economic value of this yield improvement is unclear. When allocating budgets, especially budgets for the development department, a quantification of the cost reduction is necessary. Only with quantifications of the economic value of yield improvement, clear agreements can be made regarding budgets and improvement plans of the manufacturing and development department.

4.5. Conclusion

The PM‟s of the repair flow are rejected from testrig or test. Together with the regular PM‟s, the repair PM‟s are processed in the „assemble PM‟-function. This function is represented by the AM-WSN workcenter. Four types of PM‟s are produced:

 PM311LEX

 PM311REX

 PM321LEX

 PM321REX

The product mix of the output of the workcenter is determined to be 33% of PM311‟s versus 67% of the PM321‟s. The yield loss is determined to be 32%.

In [Bohn/Terwiesch] drivers to reduce yield loss are stipulated. In the case of ASML, especially decisions regarding process improvements are drivers to understand economic pay-back of yield loss reduction. A yield loss of 32% is undesirably high. ASML aims to reduce the yield loss to 12%. The economic value of this yield improvement is unclear.

27

5. ‘Assemble PM’-function

5.1. Functional structure

The „assemble PM‟-function consists of two stages regarding the regular PM flow. First the subassemblies are built. Then the subassemblies are integrated to a PM. Rejected PM‟s are analyzed and dismounted. This process of analysis and dismounting is executed with the same resources as the integration process of the PM. After dismounting, the failed subassemblies are returned to the „build‟ process. There the subassemblies are repaired. These processes are shown in Figure 15 -

aggregation layer 3: zoom into 'assemble PM'.

Figure 15 - aggregation layer 3: zoom into 'assemble PM'

5.2. Quantification of repair flow

In this paragraph the repair flow will be quantified. The number of repair subassemblies will be specified and the percentages of quick fix orders. The data are measured over a period of one year, beginning in week 8 of 2011.

After discussions and by data analysis, it became clear that there can be made a distinction between regular repair PM‟s and quick fix repair PM‟s. The quick fix PM‟s does have the property that it has to return in exactly the same test sequence as it was originated from. On the other hand, the regular rejected PM‟s can be replaced by other PM‟s as well. The decision to handle a rejected PM as a quick fix is based on the progress in the test sequence, the number of PM‟s available on stock, and the severity of the problem. This last driver implies that quick fix PM‟s do have a smaller work content than regular repair PM‟s. The quick-fix orders are separated from the regular repair orders based on the number of operations. Non-quick-fix orders (build as well as repair orders) contain 6 operations:

build

analyze and dismount

rejected PM

carrier

crash rim

PM

28

1) Integration CB+SS+LOS+CR 2) PMQT1

3) Integration Chuck Assy 4) PMQT2

5) Finalize

6) Final Quality Check

A substantial part of the integration orders contain one or two operations only. These orders do have less work content. The assumption is made that these orders are quick fix orders. Most of the quick-fix orders do only contain the operation „Integration CB+SS+LOS+CR‟. Analysis of data gives the following result:

Table 3 - Percentage of quick fix

About one third of the rejected PM‟s consists of quick-fix orders. These orders do have a lower workcontent and do have to return to the same test sequence as they originate from. These quick-fix PM‟s don‟t contain any subassemblies to be repaired. From the rejected PM‟s which are considered as regular repair PM‟s, the possibilities of the occurrence of subassemblies to be repaired are calculated.

Table 4 - Number of repair subassemblies

Table 5 - Repair subassemblies as a percentage to the number of repair PM’s

PM311LEX PM311REX PM321LEX PM321REX

total repair integration-orders

33

31

62

60

quick fix

10

11

17

23

percentage

30%

35%

27%

38%

PM311LEX PM311REX PM321LEX PM321REX

hose assy [#]

1

2

4

1

carrier base [#]

3

1

5

3

crash rim [#]

5

2

15

11

ss motor [#]

6

11

24

19

chuck assy [#]

2

2

10

11

integration [#]

24

19

43

51

PM311LEX PM311REX PM321LEX PM321REX

hose assy

4%

11%

9%

2%

carrier base

13%

5%

12%

6%

crash rim

21%

11%

35%

22%

ss motor

25%

58%

56%

37%

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The numbers of repair subassemblies are counted and divided by the total number of regular repair PM‟s. This results in the percentages as shown in Table 5.

5.3. Planning& Control

5.3.1. Process control

The planning of the production of the PMs is shown in Figure 16 - process control. The order flow is outside the boundaries of the workcenter but generates orders for the workcenter. These orders consist of two kinds. On one hand there is the production of new machines, which require new PMs too. On the other hand, ASML has a service department, which swaps PMs at the customer and asks for new or refurbished PM‟s at the workcenter. Both of these demands are processed by the planning control function. Planning control has the task to balance the available moverate of the workcenter with the required moverate. This is realized by comparing work in progress, stock levels, the number of required PM‟s, the demand dates of the required PM‟s and the required moverate. The compare function creates due dates, which are transformed to start dates with information of throughput times from the function control. Data about throughput times, workcontent and buffer times are reported to the function control on quarterly basis. Progress is reported to the order flow of ASML on a weekly basis. This is done during staff meetings.

Figure 16 - process control

PP&C

materials

order quantities

(fasy plan, service demand,

AMSL Twinscan, rejects) progress

order progress, stock levels start dates PM move rate (11 PM/w) due dates Takted routings start dates - actual CT - actual man-hours - queue times

assemble

control

compare

intervene

measure

function control

30

5.3.2. Function control

The norm review is a reoccurring quarterly function control to evaluate and initiate the correct norms for takted routings used in the workcenter. This cycle is shown in Figure 17.

Figure 18-Function control

- throughput times - required moverate optimum production sequence CT data CT report rebalancing trigger

(at least once per quarter)

- actual CT - actual man-hours - queue times

evaluate

ME (& norm review)

initiate

BE

process control

higher echelon control

31

The norm review will be described by means of Figure 18.The progress of the execution of the operations is logged in the takt progress monitor. These data are available for the Business Engineering department, which analyzes these data (at least) every quarter. The result of the analysis is a report which is used as fixed reference by other functions at ASML. One of these functions is the norm review meeting. In this meeting, the stakeholders (ME, BE, OL, etc.) review the report data and compare it with the current norms. When it becomes clear that a part of the production process is fulfilled in a shorter lead time or requires less labor, the norm is adjusted. This rebalancing result in takted routings for the production of the PMs and it‟s subassemblies. It contains labor times and lead times for every step in this production process.

This function control is the norm review, but as can be seen in Figure 18, it is strongly connected to the process control of the production. Although, this is done on daily basis, and the norm review is executed only once in a quarter, the process control function needs the output created by the norm review.

5.3.3. Buffer size and delivery performance

Now first the relation of the moverate with the lead time is explained. Little‟s Law [Slack, 2007] is stated:

[𝐸𝑞. 5.1] 𝑙𝑒𝑎𝑑 𝑡𝑖𝑚𝑒 = 𝑖𝑛𝑡𝑒𝑟𝑣𝑎𝑙 ∗ 𝑊𝐼𝑃

Since the inverse of the interval is equal to the moverate, the lead time can also be stated as:

[𝐸𝑞. 5.2] 𝑙𝑒𝑎𝑑 𝑡𝑖𝑚𝑒 = 𝑊𝐼𝑃 𝑚𝑜𝑣𝑒𝑟𝑎𝑡𝑒

In the case of the PM production process the lead time is considered as the time from the start of the production until the end of the production. This end-of-production moment is deviated and as a result of that, an artificially added buffer time is necessary to reach the delivery performance constraint. The sum of the average lead time and the buffer time is equal to the delivery time. This delivery time is used to determine the right moment of the production start.

As a matter of fact, the considered production system has a necessary end buffer. Therefore Little‟s Law has to be refined for the case of this PM production system:

[𝐸𝑞. 5.3] 𝑙𝑒𝑎𝑑 𝑡𝑖𝑚𝑒 + 𝑏𝑢𝑓𝑓𝑒𝑟 𝑡𝑖𝑚𝑒 = 𝑊𝐼𝑃 + 𝑏𝑢𝑓𝑓𝑒𝑟𝑠𝑖𝑧𝑒 𝑚𝑜𝑣𝑒𝑟𝑎𝑡𝑒

32

The main consensus at ASML is striving to reduce the (average) lead time. Business drivers to do so are:

• meet the customer order lead time (< 26 weeks) • increase move rate flexibility

• increase production predictability • reduce costs (labor/floor space etc.) • increase learning loop speed

• save electricity: sustainability

Although this is true, major influence might be realized by decreasing the variability on the lead time. This variability is „hidden‟ by the buffer time. To give an indication of the lead time and its variability, the lead times of build PM‟s between week 40 of 2011 and week 10 of 2012 are shown in Figure 19. Calculated with the data from Figure 19, the average lead time is 17.6 days and the standard deviation is 5.1 days, composed in a lognormal distribution. These figures show that a high deviation is present. A reduction of the deviation will have positive influence on delivery time but might also have a positive influence on total costs.

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This deviation is the result of the build flow as well as the repair flow. A buffer is required to capture these variable lead times. The graph of cumulative demand and supply is shown in Figure 21.From these data also the buffersize is determined and showed in the graph. The average buffersize is 9.9 PM.

The delivery time of 393 PMs is measured. Of these 393 PMs, 322 PMs were in time or too early. The delivery performance over this period of one year is 322/393 *100% = 82%. So the boundary condition of 95% is not met at this moment. The buffersize shown in figure 21 is a cumulative buffer of all four types of PM‟s. Therefore a PM definitely can be tardy without the buffersize being zero or lower.

34

View Figure 21. In a situation without repair, a certain buffersize is required to capture the differences between supply moments and demand moments. When a PM is rejected from testrig or test, two events take place. First, the rejected PM is waiting to be repaired. It is added to the production system and therefore requires a part of the capacity. Second, an immediate order for another PM is created. The demand moment is equal to the moment the reject took place. To fulfill this demand, a PM from the buffer is consumed. This creates the situation of a lower buffer for the time being the rejected PM is repaired. This buffer is used to cover variability‟s but does not take into account the variability‟s due to sudden demands created by rejected PM‟s. This partially results in lower than required delivery performance. Three directions to solve this problem are possible:

1. Take into account the variability of rejected PM‟s by increasing the buffer. 2. Reduce the lead-time of the repair PM‟s.

3. Change from piece-buffer to time-buffer per produced PM in order to gain control over the composition of the buffer.

Taking into account the costs parameter makes it possible to make choices regarding these measurements in order to either meet the required delivery performance and to meet it against the lowest possible costs.

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5.4. Indistinct handling of rejected PM’s

It is noticed that there is no strict procedure to reject a PM from testrig or test and return it back to the PM workcenter to repair it. When a PM is rejected from testrig or test, it is unclear how to deal with the rejected PM and bring it to the PM workcenter. The process is unstandardized and fulfilled in different ways. There is often a lack of specific data of the repaired PM this and leads to confusion and unnecessary communication between the stakeholders. Rejected PM‟s are buffered. Subsequently several actions needs to be performed in order to create the right information at the right place. The problem in here is that there is no knowledge of which information has to be handed over and in which sequence the stakeholders need to perform their action to provide this information.

In [in „t Veld, 2002]an explanation is given about data types and data flows. The goal of data is to provide multiple functions in the organization of the right information, which will be used in these functions for decision-making. Awareness of the different data types is important because of:

T = 0 T = 1 repair PM order repair PM PM PM PM PM PM PM order 3 PM PM order 2 order 1 PM order 3 PM PM order 2 order 1 Size = n Size = n - 1

?

36

 coherence of these data needs between the organs of an organization.  Possibilities to a fit of the applied organizational structure.

[In „t Veld, 2002] first distinguishes data types in several aspects. After that, he raises questions which must be able to become answered when applying data handling in a certain production system, for example a steady state production line, like the PM production of ASML.

There is a difference in data types between the data needed to be able to produce the product and data which are required to be able to control the production process. Data needed to be able to produce the product is separated in product-identity data and data committed to the production location. Regarding the rejected PM flow, the data committed to the production location can be left out of consideration, since it is clear that this problem is about product specific data of the rejected PM.

Furthermore, when designing a process in which these data is processed, one must take into account if the right data is given by the right entity at the right time and enters the right location in the right configuration. By designing this process, questions raise like:

 Which data needs to be: o Imported? o Exported? o Buffered?

 Where does these data come from?

 Which actions need to be taken in which sequence to supply the data?

 Where must the data be send to, in which combination and in what configuration?

[In „t veld, 2002] explains data handling in three steady state types: the process line, the functional structure and the grouped production. Although none of this is the situation of this problem, it becomes clear that a correct data handling can be realized in two steps:

First: investigate and mark the types of required data.

Second: Develop a process which prescribes the providing of the required data by the stakeholders in the right sequence.

5.5. Conclusion

The „assemble PM‟-function consists of two stages regarding the regular PM flow. First the subassemblies are built. Then the subassemblies are integrated to a PM. Rejected PM‟s are analyzed