RFID ROI
by
John Dirk Kinley
MBA
Kellogg School of Management, Northwestern University, 2000
Submitted to the MIT Engineering Systems Division in
Partial Fulfillment of the Requirements for the Degree of
Master of Engineering in Logistics
at the
MASSACHUSETTS INSTITUTE.
OF TECHNOLOGY
Massachusetts Institute of Technology
JL2RA 004
June 2004
LIBRARIES
@ 2004 John Dirk Kinley. All rights reserved.
The author hereby grants to MIT permission to reproduce and to distribute
publicly paper and electronic copies of this thesis document in whole or in part.
Signature of
Author
Engineerifg Sy tems Division
.}ay
10th, 2004
Certified by
Director, MIT Integrate SuMI'
cs
Acting Director, Affiliates Program in Lo
James B. Rice, Jr.
ain Management (ICSM) Program
enter for Transportation & Logistics
Thesiyjupervisor
Accepted by
//
Yossi Sheffi
Professor, Engffeering Systems Division
Civil
and
Environmental Engineering Department
Professor,
Director, MIT Center for Transportation and Logistics
5/5/2004
I
BARKER
RFID ROI
by
John Dirk Kinley
MBA
Kellogg School of Management, Northwestern University, 2000
Submitted to the MIT Engineering Systems Division in
Partial Fulfillment of the Requirements for the Degree of
Master of Engineering in Logistics
ABSTRACT
This thesis investigates financial results from RFID integration at product level in semiconductor
manufacturing. The thesis explores how the technology might act in concert with other
significant logistics tools to create return on investment. In this case, the use of RFID, along with
postponement and Kanban practices, may help a manufacturer better align supply with central
processing unit (CPU) demand. The resulting economic benefits are explored through yield
scenarios.
It is important to note that the thesis explores this topic without the benefit of empirical data.
Consequently, a number of assumptions were made; these assumptions may affect the validity of
the observations. Nonetheless, the study demonstrates an innovative approach that may
contribute to new models of creative problem solving.
Thesis Supervisor: James B. Rice, Jr.
Title: Director, MIT Integrated Supply Chain Management (ICSM) Program
Acting Director, Affiliates Program in Logistics, Center for Transportation & Logistics
2
ACKNOWLEDGEMENTS
I would like to thank all those who contributed to my understanding of this topic and to the
creation of this document:
James B. Rice for his time, feedback, and guidance.
My classmates; in particular David Cassett, Dennis Duckworth, and Christopher Hopeman, who
worked on similar projects and gave valuable input at various points.
Lastly, my fianc6e, for her support; in particular, her repeated proof reading of a topic that could
not lie further from her true interests.
3
TABLE OF CONTENTS
ABSTRACT .......................................................................................................................................
2
ACKNOW LEDGEMENTS..................................................................................................................
TABLE OF CONTENTS.....................................................................................................................
INTRODUCTION ...............................................................................................................................
3
4
Background and M otivation .......................................................................................
Research Question ....................................................................................................
Literature Review ............................................................................................................
5
5
6
7
Postponem ent Literature ..........................................................................................
Kanban Literature ..................................................................................................
Tracking & Tracing Goods .......................................................................................
RFID Literature.........................................................................................................
7
8
10
11
RFID System : In Brief..................................................................................................
16
Sem iconductor M anufacturing: In Brief....................................................................
M ethodology .................................................................................................................
18
19
DATA ANALYSIS ...........................................................................................................................
Current Process w ith Requirem ents...........................................................................
Proposed Process w ith Requirem ents ........................................................................
22
22
24
YIELD AND ROI M ODELS............................................................................................................
OBSERVATIONS ............................................................................................................................
28
37
Changes in Y ield...........................................................................................................
37
Other Contributors and Risk Factors ........................................................................
Effects on Cycle Tim e .........................................................................................
Effects on Quality ..................................................................................................
Shortage Effect..........................................................................................................
Labor Costs ...............................................................................................................
Inventory Holding Costs.......................................................................................
CPU A ssociated Costs ..............................................................................................
M anagem ent and Operational Risks ......................................................................
38
38
39
39
40
41
41
42
BIBLIOGRAPHY.............................................................................................................................
46
APPENDIX A - CPU SORTING CAPITAL EQUIPMENT............................................................
48
4
INTRODUCTION
Background and Motivation
In 1888 Heinrich Hertz proved the existence of electromagnetic radiation. Key to his proof was a
radio frequency (RF) device he built which transmitted radio waves. In 1942, the Allied Forces
used large RF systems in England to identify (ID) returning Allied bombers and distinguish them
from raiding German warplanes. Thus, RFID technology has been in existence for several years.
However, it was not until recently that it attracted significant attention. In the past there were
significant adoption barriers, including overly large and expensive tags and readers, and
inadequate back end data management systems. However, recent advances have decreased costs,
improved form factors, and introduced functional data management systems. Recently, the
consumer packaged goods companies Gillette and Rockport have committed to RFID pilots.
Moreover, TESCO, Wal-Mart and other firms have committed to specific timelines for more
comprehensive pallet/case level integration with supply chain partners. These organizations and
others are trying to understand how best to leverage the technology for economic gain.
The anticipated benefits of utilizing this technology are numerous and include: non-line of sight
(NLOS) functionality, product or unit level traceability (ULT), and location based asset tracking.
RFID provides NLOS tracking by virtue of radio frequency transmission. For example, in this
transmission a warehouse manager could track various packages stacked together without having
to move packages around to look for the important bar codes. Additionally, by providing an
extensive numbering format, RFID offers the possibility of identifying each item or unit with
unique numbering which makes ULT possible. ULT could become important in tracking
individual products through a supply chain to perform reverse logistics, or with material sourcing
issues such as tracking poor quality raw materials by associating units with their production
batches. Another potential benefit is asset tracking. Generally, RFID achieves asset tracking
through use of source association. With this method, distinct radio wave emitting sources are set
5
up at various points in a supply chain where they consistently monitor an asset's movements
through various areas. These areas are generally confined spaces, thus providing for fairly
accurate asset location information. RFID has attracted attention outside the arena of consumer
packaged goods for asset tracking. The Department of Defense (DOD) has begun field use of
RFID for ULT tracking of specific equipment and resources. In an example referred to later, the
DOD is using RFID to track fuel containers through their internal supply chain, from purchase to
use.
The semiconductor industry stands to gain from RFID use on the unit level considering the high
value-to-size ratio of the product (chips), the complicated nature of the manufacturing process,
and the need for product information while maintaining high process speed (velocity). With this
in mind, the study will consider a section of the semiconductor manufacturing process, focusing
first on one key benefit of ULT use; second, briefly considering other potential effects within
manufacturing; and, finally, highlighting some potential concerns. The hope is that this study
will provide a foundation of analysis for others to learn from, and build upon.
Research Question
The specific research question on which this study focuses is: "What is the return on
investment from implementing RFID in concert with postponement and Kanban practices
to better align output with demand in a semiconductor manufacturingfacility?"
This question is of particular interest because it presents REID as an enabling technology in an
environment, manufacturing, where this has not previously been a focus. When considering who
will benefit from RFID, the focus has been on distribution centers (DCs) and retailers. Research
in this area often implies that the manufacturer will assume the majority of costs, such as tags and
6
tagging labor, while accruing less benefit from its investment in this technology than its supply
chain partners.'
Literature Review
Postponement Literature
Moving the customization point closer to customers, or postponement, can be a powerful logistics
strategy. Research in this field has studied diverse postponement strategies involving labeling,
packaging, assembly, and manufacturing. This research has demonstrated that postponement
strategies are useful when inventory carry costs exist, and manufacturing postponement is likely
to reduce product obsolescence risk. Other factors to consider with a postponement strategy
include end demand, modularity of manufacturing, product value and product life cycle.
Postponement typically offers greater advantages when end demand has some degree of
variability; manufacturing is somewhat modular; product values are higher; and life cycles are
shorter. These conditions exist in semiconductor manufacturing.
Researchers have given considerable attention to the use of information systems (IS) to enable
postponement strategies.2 At any given point in a product pipeline there are a number of dynamic
forces inside and outside the firm that need to be accounted for in order to make an optimal
decision. For manufacturing, use of IS to enable postponement is a method that can respond to
one of the most dynamic forces-- demand. In the world of technology manufacturing, Dell is the
oft-cited example of postponement through use of IS. Dell combines direct sales with real time
inventory information and a make-to-order systems to achieve effective postponement. Dell's
' Byrnes J. Who Will Profit From Auto-ID? Harvard Business School: Working Knowledge. September 1,
2003.
2 Anand K, Mendelson H. Postponement and Information Systems in a Supply
Chain. NYU WISE 1998.
December, 1998.
7
success has transformed the personal computer industry and literally forced competitors, such as
IBM and Gateway, to adapt.
Successful postponement requires supply chain visibility to match supply with demand. For
example, material and product flow visibility become very critical as more processes, such as
manufacturing and assembly, are postponed until customer demand is known. Understanding the
nature of material and product flow from the supplier to the customer is a key potential benefit of
RFID. When consumer demand is initiated, the internal supply chain could ideally be instantly
queried through RFID systems to understand total work in progress (WIP) and inventory levels,
locations. The query would offer insight to the company supply chain expert, allowing him/her
assess the most efficient fulfillment route through directing manufacturing, assembly and
inventory operations. The more accurate and efficient the query, the better the postponement
results. It is better to know exact WIP and inventory than rough estimates. The potential benefit
RFID brings is greater accuracy and velocity. The end goal for an internal RFID system is to use
radio frequency transmission to perform more comprehensive and immediate queries.
Kanban Literature
Kanban means "signal". Kanban signals a cycle of replenishment for production and materials.
It maintains an orderly and efficient flow of materials throughout the entire manufacturing
process. It is usually a printed card that contains specific information such as part name,
description, and quantity.3 Leading companies around the world have considered and in some
cases, adopted Kanban practices. The industries using Kanban are quite diverse including high
tech (Sun Microsystems), steel manufacturing (Northeast Mfg.), and automotive production
3 Six Sigma. Definition of Kanban. Available online: http://www.isixsigma.con/dictionary/Kanban-
148.htm
8
(Toyota). Kanban can represent an inexpensive methodology for effectively communicating
demand through a manufacturing process.
Although Kanban has been well researched, new developments in many aspects of the supply
chain have continued to emerge. Kanban has traditionally operated as a manual signal.
Enterprise resource planning (ERP) systems have worked to integrate Kanban into their software.
With ERP Kanban has had an impact throughout organizations, affecting finance, human
resources, and transportation decisions. The emphasis is on systemic effects of Kanban and big
picture implications of integration. Recent literature has also focused on defining and
implementing baseline measurements. Safety stocks, minimums, and order multiples are all
adjusted using baseline measurements as guidance. Accuracy and efficiency of baseline
measurements is an area of considerable interest. In general automated Kanban systems have
been touted for their ability to offer many advantages such as recalculation of lot sizes-- both
intra-company as well as through supply chain-- capacity planning, and staffing levels.
Many companies cannot accurately control order volume. On the most basic level, sudden high
order periods lead to spikes in demand which can create stock-outs. Use of simulation tools
which take into account replenishment lead times, inventory costs, and other inputs can be
exceptionally useful when demand is not linear. Conversely, not all parts can or should be
included on a Kanban system. General qualities of successful products included in a Kanban
system are: linear demand, outstanding quality, not being phased out, and realistic lead times. It
is interesting to note that although semiconductor chips are periodically phased out by speed, the
chips themselves are not being phased out. Furthermore the demand for chips is fairly linear;
they are generally of high quality; and they have realistic lead times. Interestingly, Kanban is
also a great tool to use with RFID since Kanban uses real time inventory data, and RFID provides
real time inventory data.
9
Tracking & Tracing Goods
Tracking is defined as the observing of the progress of goods through a supply chain. Tracing is
following the course which goods take through a supply chain. Although these terms have
similar definitions they are in fact different functions. The evolution of tracking and tracing
goods has progressed from the laborious markings of engraving of valuables, to bar codes in the
early 1970s, to the advent and current deployment of RFID. With this evolution the
sophistication of tracking and tracing has improved greatly. Since manual labor was no longer
required with the bar code, labor costs dropped on a per item basis, and more and more products
were tracked and traced. The purpose for tracking and tracing also changed from authenticity to
Table 1.
Continous, Data Floa
Humaniesource Efficient
Poin thouificD it
ab
r
urce
ine
ow b
icient
Sheltered Tag Placement Enabled
SiiglenmCode Reading Capabilitiesh
-nvgive,
reading,
Ulisetered C dework polyi
Up
Uniqtue Product' Identifier in Numberinig'
L fitd]
MultipleTag Reading Capabilities
Uninvasive cnntreading
miemg
n
,aufctean*-
Source:,McFarlwane,Shetai, The Impact
iforma
tio.Ictn adtion
toppy
these advantas,t
International
.Journal of Log cs Management(IJLM VoL. 14uNo. (2003 ,20.
supply chain uses, such as inventory management. Although RFID is just now beginning to gain
broader acceptance, expectations are high; researchers are forecasting a $3.1 Billion industry
within five years4 . The growth expectations can be attributed in part to the many significant
advantages over bar codes. These include multiple reads per second, non-line of sight
functionality, read/write tagging, and location information. In addition to these advantages, the
4 Koprowski G. RFID Emerges to Threaten the Bar Code. CRMBuyer. April 12, 2004.
10
introduction of a unit level numbering system by EPCglobal5 enables ULT product identification
for the first time on a global standardized scale.
One of the exciting benefits that REID offers is its breadth of potential application within the
supply chain. Current studies focus on how RFID might benefit product flow from
manufacturing to distributors, from retailers to consumers, and across full supply chains and
industries. This paper considers a specific example, in semiconductor manufacturing, to show
how creative use of RFID to identify CPUs (or chips) at the unit level might increase yield by
changing how manufacturing reacts to demand.
RFID Literature
Companies are facing more and more complex business decisions involving technology adoption.
Some of these are driven by strategic objectives, while others are more operationally driven.
Nonetheless, all seem to be pushing for the common goal of greater efficiency and effectiveness.
A common ground facing many companies is how to measure risk-reward or cost-benefit. Recent
history has made many firms pause before hasty adoption. The past tells us that roughly 90% of
first round Enterprise Resource Planning implementations were not successful in the 1990s.6 In
the late 1990s it was not unusual for traditional dollar based return on investment studies to be
grossly manipulated, or ignored as meaningless in the 'new economy'
.
These abuses led to
exaggerated expectations and over-commitment to new technologies in the 1990s and early
2000s.
EPCglobal Website. Available online: www.epcglobal.com
Donovan RM. Why the Controversy over ROI from ERP? R. Michael Donovan & Co., Inc White Paper.
January 2000.
5
6
7
Mollison, C. ROI: Times Have Changed in the Past Couple Years, and ROI Has Made a Comeback as a
Result. Internet World. March 2002.
11
Literature focusing on RFID began to appear in mass during the late 1990s. Many studies focus
on the cost hurdle associated with hardware and systems integration. Most of these are concerned
with retailers who have been identified as those in the supply chain with the most to gain. In a
typical supply chain the manufacturer might bear both the cost of the tag, as well as the cost of
affixing the tag. Furthermore it has been analytically demonstrated that in many industries the
manufacturer is in the least favorable cost-benefit position in the supply chain.
Other areas of research are concerned with hardware cost and performance trends. This is
important information for determining feasibility of lower cost systems and adoption rates.
According to Forrester Research, after 2007, RFID tags will have dropped to the $.01/tag level.
Some analysis points to
this price point as the
economically viable
Chart1..Analysis
Chr
C - Technology/
Dntinaryi
A -Case studies
B - Economic
Management
Logistics
Case Studies
Logistics
Economics
Logistics
TeclutologylIT
Evolution
2 - Storefront
Ste
Storefron
tefono/t
Stoefiont
security
3 -Security
Cas Studies
Security
Economics
Security
Teclogo/rr
Evolution
SmrMahns
Case Studies
SatMcie
Economics
SmtMcies
mrtahns
5- Telematics
Case Studies
Economics
Technology/IT
(C5)
Evolution
stenc
Sqimn
sy
Case Studies
Systemic
Systemic
6-Systemic
Economics
Technology/IT
1-Logisics
nutywd
point for mass use.9
Interestingly, there
Management
seems to be a catch-22
preventing a steep
4 - mrt
curve from
growth growhMcrvefrone-s
Tednoogy/IT
Evolution
occurring in the next
few years. REID
fe yar.(FIA5)
equipment
(B35)
(D5)
systen-dc
Evolution
manufacturers cite low
Framework by Professor Hau Lee, Stanford University
unit demand as a reason
8
Byrnes J. Who Will Profit From Auto-ID? HarvardBusiness School: Working Knowledge. September 1,
2003.
9 Gupta, P. The future of Radio Frequency Identification. TechRepublic. August 18, 2003.
12
for not reducing tag and reader prices, meanwhile potential adopters cite high costs as a central
reason for not purchasing.
Professor Hau Lee of Stanford University has proposed an effective framework for understanding
RFID literature. His contribution segments writings into general subject matter on the "y" axis
and methodology of study on the "x" axis. The literature reviewed falls primarily in the
Economic Analysis column. The majority of economic analysis articles and work done in this
area is concerned with Storefront Economics (B2) and Systemic Economics (B6) with high level
studies on retailers, such as Walmart, representing the majority. "Measuring the Impact of
Information Technology on Value and Productivity using a Process Based Approach: The Case
for RFID Technology " is a particular interesting introduction of methodology for assessing
economic value of technology. The case study considers RFID in a consumer packaged goods
company. However, the framework can be applied to other areas as well. Security Economics
(B3) literature included inputs such as shrinkage rates, item cost and associated stocking costs to
arrive at potential benefits from comprehensive security efforts. Smart Machines Economics
literature was usually coupled with a case study on a new technology. Common themes were in
consumer goods, for example refrigerators that automatically read food levels and reorder, and
medicine cabinets that check prescriptions to make sure the right drugs are taken at the right
times. Most Telematics literature falls in the Technology/IT (C5) or the Case Study (A5) column.
Systemic Economics, (B6) focusing on the supply chain, work is centered on cutting tangible
costs over more immediate time horizons. If the aforementioned technology downturns have
taught potential adopters anything, it is to be wary of advertised leaner operations with surefire
competitive advantages. Where technology benefits were once overstated and integration costs
understated, the pendulum has now swung the other way. Most work in this area considers RFID
as a standalone technology where intra-company economics do not seem to be particularly
favorable with current RFID hardware costs. This thesis is concerned with the Logistics
13
Economics, (B 1) which is the first row in this column. In the sum of all works on RFID, Logistics
Economics is only a small portion.
Logistics-economics literature includes high-level studies on adoption rates. This literature
generally points to a short-term pilot/trial growth in the first 12-18 months for early adopters and
a long-term mass adoption by five to ten years. 10 These articles often are geared to give
companies strategic pointers on how to benefit the most from RFID adoption. Economics focuses
on quality, timeliness and accuracy of forecasting to provide incremental asset utilization,
revenues and reduced costs. Freight transportation, both land and maritime, have provided case
studies where supply chain stakeholders have garnered significant top line growth and cost of
goods sold (COGS) savings with RFID.""
2
Other Logistics-economics research provides analysis
on which supply chain partners will derive the greatest benefits from adoption.13 This is a
common theme in many articles, with most pointing to the larger retailers as key benefactors and
manufacturers as those who will bare the majority of costs. Beyond Logistics-economics articles,
there are many articles that address the economics of logistics in some form as part of another
focus. Focal points within these various articles vary from: who will benefit and why, specific
returns based analysis, improvements in retailers' ability to measure shrink theft and improve
labor productivity. Most of these articles mention costs and benefits at higher, generalized levels
and are not particularly useful for in depth analysis.' 4
MacDonald, D. RFID Will Bring Great Benefits for Retailers, but Little Return for Some Manufacturers.
AT Kearney White Paper. November 10, 2003.
"1Swamy G, Sarma S. Manufacturing Cost Simulations for Low Cost RFID Systems. MIT AutoID
Whitepaper. February 1, 2003.
12 Alexander K, Gilliam T, Gramling K, Kindy M, Moogimane D, Schultz M, Woods M. Focus on the
Supply Chain: Applying Auto-ID within the Distribution Center. Auto ID Center White Paper. June 2,
2002.
13 Byrnes J. Who Will Profit From Auto-ID? Harvard Business School: Working Knowledge. September 1,
2003.
10
14
Citation to be added.
14
RFID is considered a new technology, and economic approaches vary according to various
perspectives. Those considering RFID a very risky endeavor may use a payback methodology,
where money saved or incrementally earned is measured to determine how long until the
technology and integration costs are paid off. The payback method is a very crude method,
generally employed if project risks are exceptionally high. Return on Asset (ROA) measures tend
to be less popular when a large portion of project costs and benefits are not asset based. With
technology adoption, the integration costs can surpass the cost of the hardware and software, thus
an ROA approach is somewhat inappropriate. Return on Investment (ROI) is more inclusive in
that it takes into consideration tangible and intangible costs and assumes that the project will be
active for a number of periods (i.e. years). This method is often chosen because it is all-cost
encompassing, widely accepted, and relatively simple to perform. The ROI method was chosen
for this study for to these reasons.
The MIT Process Handbook" contains several thousand processes, several pertaining to
manufacturing. This reference gives insight on how to quantitatively breakdown processes for
study purposes, both economic and other. This handbook was consulted for input on how to
economically break down manufacturing into key value-add and non-value-add elements, from
raw material processing to finished goods delivery. Specific key points referenced include cost
(value added productivity), and service/quality (yields, just in time demand flow techniques).
Additionally input from this handbook, in addition to Six Sigma, and other sources, indicated that
Appendix A, "Best Practice Guidelines for Implementation" be added to this study. The use of
'best practices' implies that management and company goals are aligned to make the proposed
changes happen in the most efficient and effective manner possible. There are many diverse
applications to best practices across industries, in various company functions. Many studies have
15 MIT Process Handbook Project. Available online: http://ccs.mit.edulp/
15
shown that these management guidelines can lead to valuable outcomes. For this study these
practices are taken as important high-level assumptions on which integration costs are partially
based.
RFID System: In Brief
The main purpose of RFID is automatic identification, or Auto-ID, where location and
identification information is provided through a system of tags, readers and host computers.
Although RFID systems vary considerably, they generally have the following system parts in
common: tags, antennas, readers and host computers. Tags, also known as transponders, which
are principally made up of an RF integrated circuit (IC) and antenna. The IC takes up a small
space on the tag, less than .5 x .5 mm, when compared to the antenna which is required to receive
and send signals and therefore takes up much larger space. The IC is where the
intelligence/memory of the tag is located.
Chart 2.
Tags
"electronic
Device made up of an
circuit
and an
integrated antenna
" RF used to transfer data
between the tag and the
antenna
" Portable rnemory
Read-only orreadhwite
"Active or passive
" Usual attachedto
c items
Antenna
- Receives and
transmits the
electromagnetic
- Wireless data
transfer
Reader
- Communicates with
the tag via antenna
- Reie
commands from
application solware
-
Intrprets radio
waves into digital
informaton
Host Computer
ReadsAarites data
frnm/to the tags
tthrough the reader
- Stores and evaluates
ebtained data
*
- Lnks the transcever
to an alications,
e.g.
0 Provides power
supply to passive
tags
Source: Tobolski, Joseph, Accenture, RFID JournalLive Conference 2004
The IC can be "read-only," write once ready many times (WORM), or "read-write". With readonly the initial data is coded onto the tag during manufacturing. With WORM the initial users
16
provide the 'permanent' information they want stored on the tag. Read-write provides the
greatest flexibility but is also generally the most expensive. Tags can be built on a variety of
backings such as clear film, product labels, or directly into product packaging. Tags can be
passive, with no battery required, or active, with battery required. Active tags generally have
greater read distances and memory capabilities. The reader, sometimes referred to as an
interrogator, uses power to send an RF signal through one or more antennas to remote tags. The
power sent through the RF signal is used to power a passive tag and/or activate an active tag.
The frequency, interference, antenna size, and power all affect transmission range and speed.
Frequencies range from low (125kHz), to high (13.56MHz) to Ultra High Frequency (UHF of
433MHz to 2.45GHz). The higher the frequency, the higher the read range. Low frequencies can
have maximum read distances of 10 cm, whereas UHF can have up to 10 meters or more.
Although signals can be read through packaging and other barriers, metal and liquids often
introduce interference. As the DOD has found, sometimes preventing inference from tagged
products is as simple as putting a thin layer between the product and tag. The DOD has begun
using weather stripping between tags and metal fuel drums when tracking these resources.
The reader feeds the retrieved data from the tag through an information system. This information
system most likely contains a software layer to intelligently filter and organize the data (Savant).
Other components of the information system include hardware and software for database and
tracking systems. These databases may plug directly into a company's exiting enterprise resource
planning application or may use a middleware application to bring the systems together.
17
Semiconductor Manufacturing: In Brief
Semiconductor manufacturing is a costly and labor-intensive process that is getting increasingly
expensive to perform. The cost for a new semiconductor manufacturing or fabrication plant,
commonly referred to as a 'fab' in 2000 was over $1 Billion. Today, building a fabrication plant
cost between $3 Billion and $4 Billion.16 The complicated nature of semiconductor
manufacturing and the fact that yield loss can occur at any step requires most processes to be
monitored closely. In addition to these pressures, engineers are constantly pushed to think of
ways to get more components on a chip.
Chart 3.
Wafer Processing
Phootlihegraph
Chra
Dia BoB
ng
o
Mn
It
* EncpsultiDeposFitihon
source: www.xandex.com/images/
process.glt
This study is concerned with a particular product, the central processing unit or CPU. At the
beginning of CPU manufacturing, in the fabrication plant, the silicon is first shaped into discs, or
wafers, from raw silicon. Precision equipment is used throughout manufacturing; part of the
early stage process includes applying a thin, roughly ten atom thick layer of gallium arsenide
(GaAs) to the wafers. Through manufacturing, each wafer is sectioned into 100 to 500+
rectangular blocks, or dies. Generally dies are assembled with three basic elements. First the
active components are added. These might include transistors or memory cells. Second an
6
1
SpOOner, J. Samsung Chips to Take on a 'Blue' Hue. CNet News.com. March 5, 2004.
18
insulating layer is added to cover the active components. Finally holes are etched into the
insulation and conductive metal traces are added. The process becomes increasingly complicated
as it is repeated five or six times to add more and more components to each die.' 7 Once
components are added to the dies, the dies have functionality and are referred to as CPUs. It is
important to understand that in semiconductor manufacturing each wafer is unique and each area
of each wafer has different characteristics. The result is that each die is different from the next,
even though they have the same components and have gone through the same manufacturing
steps. Due to this fact the dies need to be tested and understood for their individual performance
properties.
Although testing occurs at multiple different points, the "final test" step is where the ultimate
performance determination is made and the CPUs are usually "locked and marked" into a specific
performance. This step occurs in a separate facility from the fab called "Assembly -Test". After
lock and mark and final test in the Assembly-Test, the CPUs are delivered to a finished goods
inventory (FGI) warehouse. They are held at the FGI warehouse and shipped to meet demand.
Methodology
This study entailed using a methodology that had six (6) steps:
1.
Literature review. This provided a foundation on Semiconductor Manufacturing,
Postponement, Kanban, Tracking & Tracing Goods, and RFID.
2.
Process Selection. This entailed choosing an appropriate process to focus the work on,
and the process of manufacturing inventory yield management was selected based on real
" Dunn, P. Semiconductor Manufacturing Process. FACSNET Science & Technology. September 27,
2000.
19
industry concern. This process spans from the Assembly-Test to the Finished Goods
Warehouse in a typical semiconductor manufacturer and is defined in greater detail later.
3.
Process Definition. This entailed identifying the likely process steps for the new
manufacturing inventory yield management process. This is an estimated flow based on
study of semiconductor manufacturing processes as well as field visits to various
semiconductor manufacturing facilities. The processes do not however represent any one
specific company's process flow.
4.
Yield data. This entailed identifying production yields and inefficiencies created due to
the "lock and mark" processes.
5.
Yield analysis. This entailed applying 'bucket' analysis which is based on the framework
and methods developed by Subirana [describe the process in detail]... resulting in data
that would potentially identify process improvement opportunities.
6.
Proposed process modification. The entailed developing a modified process that would
take advantage of the process improvement opportunities that surfaced in the prior step.
At the highest level, the methodology used begins with understanding the background of key
tools and concepts used. This includes understanding postponement, Kanban, RFID, economic
modeling and semiconductor manufacturing. The steps taken include investigation through
literature into the key tools and concepts; field visits to a semiconductor manufacturing facility
with process observation; and interviews with semiconductor professionals. The field visits
surfaced several issues regarding inventory management in FGI warehouses. Further
investigation and discussion led to considering product flows through Assembly-Test to Finished
Goods Inventory Warehouse. These became the focus of the RFID study with managing
inventory to demand as a desired improvement" or something like this. General understandings
of these steps along with what is believed to be a root issue, inventory management to demand,
led to building a new process.
20
The analysis begins by considering the current process, a series of steps in semiconductor
manufacturing, with their accompanying requirements. The requirements refer to the valueadded at each step.
Chart 4.
Receiv,
rstAssemble
& Othe
Processes
Lock
Hnal
Mark
Test
Trays
Storage
Processing
iPReareFtialxs.Prta
Scaled
Box
FG1
BHes
G
tandling
-Partial Return
Yield data was analyzed considering the proposed and current processes. The yield data was
considered in performance 'buckets', each bucket pertains to different CPU groups based on level
of performance (e.g. 3.0 GHz, 3.2 GHz). Three different hypothetical yield bucket scenarios
were analyzed in addition to the current 6 bucket process. These were 9, 12, and 24 buckets.
Yield analysis results were discussed with various 'bucket' scenarios to show the effects of the
proposed process changes. The method used to understand these processes is in some ways
similar to that used in the recent study by Subirana et al, 2003.
In this study, Subirana and colleagues demonstrate a useful process decomposition approach for
economically assessing technology adoption value. This thesis has adopted the format used by
Subirana and colleagues (2003), which is a process decomposition approach. In process
decomposition, each of the process steps is understood for its 'requirements' or value-add. By
understanding the value add the researcher can then determine at what cost this value add is
achieved at (e.g. how long does it take, or how much output is achieved). Once the value and
cost are determined the researcher can compare multiple scenarios that achieve the same valueadd but at potentially different costs. Since the authors illustrate the approach in a consumer
21
package goods distribution warehouse environment, special consideration was given to
understanding how this process might be amended for high-tech manufacturing. The approach
taken in this paper is different from that described by Subirana et al. in a few key aspects. These
differences include industry, position on supply chain, and RFID use. The last difference
highlights the fact that this case study represents RFID as an enabler of other logistics practices
instead of a stand-alone technology. Like Subirana et al., an ROI model was built, considering
the costs in conjunction with the yield benefits of the most conservative new process scenario.
After the ROI analysis and discussion, additional observations on potential effects of change were
considered such as: cycle time, quality, shortage, labor and inventory. The study concludes with
final remarks on the potential impact of the study on industry practices.
DATA ANALYSIS
Current Process with Requirements
This study observes process steps occurring in semiconductor manufacturing, assembly-test, and
finished goods inventory (FGI) warehousing. The description is based on visits to a
semiconductor manufacturing company, interviews, and literature. It is not meant to represent
process at a specific firm. The documented steps, or current process, covers a hypothetical
semiconductor producer's CPU production facilities.
Chart5.
Receive,
t Assemble
a Other
S Processes
Loack
and
Fnl
Mak Test
Trays
i
Sealed
Box
SoaePoesn
r
ce~iv
Full Boxes
Fciv
...
Boxes
.ata
Partial
.Partial Return
22
Although the current process will have indirect effects on many areas in semiconductor
manufacturing, for purposes of this study only processes from 'lock and mark' in the AssemblyTest locations to finished goods inventory in the FGI warehouses will be considered. Also for the
purpose of this study, several assumptions were made regarding production volumes that may or
may not be consistent to current system capabilities.
The assumptions are:
"
Each fab is assumed to have 10,000 wafer starts per week with 125 dies per wafer.
"
After the initial stages the number of nonperformance dies are assumed to have been
eliminated and the yield per wafer is estimated to be 100 CPUs.
"
The hypothetical semiconductor producer's CPU production facilities produce 150
Million CPUs/year.
The current process requirements are outlined below. The process requirements represent the key
steps which are impacted by the proposed process at the Assembly-Test location and Finished
Goods Warehouse.
Assembly-Test Location
1)
CPU trays representing 2,500 CPUs are received from prior processes in Assembly -Test.
A group of twenty-five wafers is considered a significant volume. Each wafer represents
100 CPUs for a total of 2,500 processed.
2) CPU trays are manually placed into "Lock and Mark" equipment. "Lock" is a process of
adding/setting components to limit the performance of a CPU to a specific level. "Mark"
refers to the process of physically marking the outside casing of the CPU with its
performance related information.
3) CPUs are brought over to the Final Test step in trays.
4) CPU trays representing 2,500 CPUs (a 25 wafer lot, at 100 CPU/wafer) are received
5)
CPUs are loaded into automated test equipment.
23
6) Test equipment run a series of electrical tests to ensure performance.
7) CPUs are sealed in boxes, 10 per tray, 30 trays/box and then leave the fab for Finished
Goods Inventory (FGI) Warehouse.
Finished Goods Inventory Warehouse
1)
CPUs arrive in Receiving operation, and are then shelved in FGI Warehouse.
2) Orders are filled using boxes of 300 CPUs, and partial boxes when necessary.
3) Orders may require partial or mixed groupings of CPUs to be shipped.
Proposed Process with Requirements
The proposed process assumes that the RFID integrated circuit (IC) is inserted early in the
lithography of the wafer. Furthermore, each wafer has multiple ICs, so that each die has a
separate IC. This process is performed with newer, 90 nanometer technology equipment, where
the cost to manufacturing for designing-in the IC may be negligible. For the purposes of this
thesis, the cost assumption is not viewed insignificant, the ROI model which is addressed later,
accounts for RFID IC cost.
24
Chart 6.
Current Process
Storage
Receive
Full Boxes
FGFFGI
Processing
P
Boxes
FGI Warehouse
Partial
Handling
-Partial Return
-
-
Processing
Receive
SFGI Trays
(Kanban)
FGI Trays
& Boxes
Lock and
Mark
*Pick exact
quantity
*No partial
/
return
The proposed process is similar to the existing process with a few exceptions.
First, the "lock and mark" step is moved later in the process and becomes part of the FGI
Warehousing operations. Practically, this entails a significant cost outlay in order to
move the "Lock and Mark" equipment from Assembly-Test operations to an FGI
Warehouse, regardless of the proximity of the two facilities. In Chart 6 this is depicted
by showing the "Lock and Mark" step as postponed from Assembly-Test to FGI
Warehouse. This is potentially the most significant fixed, or nonrecurring, costinvolved,
estimated from interviews to be roughly $60 Million. Although Assembly-Test and FGI
Warehouse locations are generally only a few miles apart, the high cost is incurred from
moving precision capital equipment, set up, and training personnel at the different
locations.
The manufacturer maintains multiple separate locations primarily to insure
uninterrupted production. For this reason these locations are in various countries and
time zones. Each Assembly-Test location has a corresponding FGI Warehouse. The
purpose of the process change is to postpone Lock and Mark, the differentiating step, to
be as close as possible to demand. The process change would most likely occur
sequentially, from one Assembly-Test to FGI Warehouse at a time to prevent system-
25
wide production disruptions. The process change would also require special care to the
Lock and Mark equipment since it is precision machinery. The key to this process change
is that the manufacturer should postpone Lock & Mark in order to take advantage of
serving the specific market demands.
Second, the proposed process entails creating and adding an RFID CPU-sort machine for
each Assembly-Test. This sorter would use RFID to intelligently move CPUs into trays
of like performance. Appendix B shows a simple diagram of how this capital equipment
might work, although this is speculative because this is only a conceptual model and has
not been developed. The cost per machine is estimated to be $1 Million, or $4 Million
for equipping the network of four Assembly-Test facilities. After the CPUs are in likeperformance trays, they are shipped as Semi Finished Goods Inventory (SFGI) to the FGI
Warehouse. This process change allows the firm to get higher yield from the chips on the
wafer because it proposes to use RFID to segment the products into more refined buckets.
Third, the proposed process entails the addition of demand signaling, or Kanban practices to
lower FGI. Kanban allows the manufacturer to pull product through production to react to
customer demand. This allows the manufacturer to have lower safety stock levels, which
translates to lower overall inventory levels. There is much entailed in setting up and managing a
Kanban system. One of the most significant demands Kanban places on a system is quick
response between various steps of manufacturing. The quick response requirement can be of
significant costly. In the proposed process Kanban is used to move CPUs from SFGI to FGI to
rapidly meet customer demand. Furthermore, the proposed process entails maintaining mainly
SFGI which will allow for postponement, with some FGI held as safety stock. Instead of all FGI
at the warehouse, the proposed process allows for majority semi-finished goods inventory (SFGI)
To manage the addition of SFGI in the warehouse, revised process steps, information systems,
26
and physical locations would likely be needed. The proposed process is described below. The
bold print signifies process changes from the current state.
Assembly-Test Location
1)
CPU racks representing 2,500 CPUs (a 25 wafer lot, at 100 CPU/wafer) are received.
2) CPUs are loaded into automated test equipment.
3) CPUs are tested for performance.
4) CPUs are inventoried as SFGI using a new CPU sorter.
CPUs are directly fed from the final test to a new piece of equipment, a CPU sorter. The
sorter is linked to the prior step, the final test, to receive CPU performance characteristics.
The sorter uses RFID to identify individual CPUs and then puts them in one of the 9 (12, or
24) corresponding performance trays. As these trays fill up they are moved to SFGI until the
appropriate demand signal. Appendix B gives more details on the sorter.
FinishedGoods Inventory Warehouse
1)
CPUs arrive, are shelved in SFGI within the FGI warehouse.
2) Kanban signal received.
Although some inventory is kept as buffer stock in FGI to satisfy immediate demand, most is
shifted from FGI to SFGI. As various performance CPUs are shipped to meet demand a
signal, or kanban, is sent to lock and mark more CPUs.
3)
CPUs are retrieved, locked and marked with respect to immediate demand. In the
new process the lock and mark portion of the final step is postponed until demand is signaled
through the Kanban system. As demand is signaled to the fab, the CPUs that are the closest
performance fit are retrieved, locked and marked.
4) Orders are filled to exact quantities using trays
5) Orders may require partial or mixed CPUs to be shipped
27
&
YIELD AND ROI MODELS
When considering yield, several assumptions are made. CPU prices are volatile and can change
on a daily basis. In the study, the process yields are arrived at through examination of historical
production volume,
and market prices at
various
performance levels.
Estimated annual
volume has been
inputted to tables
Chart 7.
CPUs Manufactured - Yield Distribution
30,000,000
25,000,000
m 20,000,000
I 15,000,000
10,000,000
5,000,000
b
p
5
\
rob
GHZ
shown in this section, where pre-lock and mark manufacturing output is followed through to
demand. The numbers in the tables represent annual production and demand numbers from a
leading semiconductor manufacturer. Both the volume and performance numbers are
representative given study of industry data and discussions with manufacturers.
28
Table 2.
Current Manufacturing and Pricing - 6 CPU GHz Buckets
Original
Bucket 1
Bucket 3
GHz
3.55
3.5
3.45
3.4
Original Vol.
300,000
500,000
700,000
900,000
3.15
3.1
3.05
3
6,375,000
10,750,000
22,000,000
25,000,000
2.75
2.7
2.65
2.6
Bucket 5
ITotal
4,500,000~
3,000,000
2,500,000
1,300,000
Lock Lock & Mark
GHz
Vol.
Unit Demand
Price Price/GHz
Yield
3.4
2,400,000
2,160,000
$395
$116
$853,200,000
3
64,125,000
57,712,500
$189
$63
$10,907,662,500
2.6
11,300,000
10,170,000
$160
$62
$1,627,200,000
,,,,$25,174,710,000
The unit prices are based on researched market prices for difference chips at various times. The
price spreads are typical in that a 3.2 GHz CPU would cost around $395/CPU when it represents
peak performance. Once the 3.4 GHz CPU is introduced the cost for the 3.2 GHz CPU drops to
around $273/CPU. The common price spreads for the six buckets of CPUs of the studied
semiconductor manufacturing firm are, from high performance to low: $395, $273, $189, $165,
$160, and $153. Pricing structure can also be understood on a Price/GHz where peak
performance chips command a higher Price/GHz when compared to lower end, more commodity
CPUs. A 3.2 GHz CPU is priced at $273 per CPU or $85/GHz. The lower end 2.4 GHz CPU is
priced at $153 per CPU or $64/GHz. This is shown below in manufacturing and pricing tables.
For comparative purposes, each table considers the same production and demand volume with
different pricing buckets. The pricing buckets considered include the current standard of 6
29
buckets which is referred to in this study as the 'baseline', and the three hypothetical scenarios of
9, 12, and 24 buckets.
There are several necessary assumptions to allow for a quantitative comparison in simplified
format. The first assumption is that the original GHz speeds are continuously normally
distributed as they were when studied. This distribution is depicted in the below graph. This
distribution may change over time and factors leading to variance are not fully understood.
Although it has not been studied, the act of increasing buckets may still increase revenues even
with non-normal distributions. Benefits may be greater with increased volatility in manufacturing
yield.
A second assumption is that unit demand is consistently 90% of manufactured volume, across
both time and CPUs. This assumption is based on discussions with manufacturers regarding
several months of historical CPU sales. Although demand is not linear and varies dramatically at
times (new CPU launches, product pricing changes), over time with anomalies aside, 90% is a
reasonable estimation. From the 6 CPU buckets table we can see that overall annual yield is
$25.174 Billion. This number is slightly high, but realistic. When considering the manufacturer,
actual total SEC stated annual revenues frequently surpass $30 Billion, with 80% derived from
processor sales. This equates to roughly $24 Billion in revenue derived from processing units.
The assumption is that the majority of these processors are central processing units. The
takeaway is that the $25 Billion yield number appears to be a fairly accurate estimation with
consideration to publicly disclosed financial data.
The proposed process segments the products, or CPUs, into finer groups. The result of this
increased segmentation is that the manufacturer will have more products at a higher performance
levels. The first hypothetical scenario divides the CPUs into 9 bucketsThis scenario, like all the
30
Table 3.
Proposed Manufacturing and Pricing - 9 CPU GHz Buckets
Original
GHz
Original Vol.
3.55
3.5
3.45
3.4
Bucket 1
Lock Lock & Mark
GHz
Vol.
Unit Demand
Price Price/GHz
Yield
300,000
500,000
700,000
900,000
3.4
2,400,000
3
2,160,000
$395
$116
$853,200,000
7
6,375,000
Bucket 3
3.15
3.1
150,000
3.1
17,125,000
15,412,500
$195
$63
$3,010,061,250
Bucket 5
3
25,000,000
3
25,000,000
22,500,000
$189
$63
$4,252,500,000
a
2.85
28
27
10,750,0O0
6,375,000
2.8
17,125,000
15,412500
$165
$59
$2,543,062,500
-.
27
Bucket a
Bucket 9
2.55
900,000
2.5
750,000
2.45
2.4
Total
L
600,000
500,000
150,000,000
%BCanekrom6tucet
2.4
2,750,000
2,475,000
135,000,000
$153
$64
Yield Incr.
% Change from 6 Buckets
$378,675,000
$25,551,625,179
$376,915,179
1.5%
following variations is identical to the baseline study of 6 buckets with the exception of additional
buckets and a linear projection of demand and chip pricing. All manufacturing GHz speeds and
volumes are assumed to be the same as the baseline 6 buckets. As noted above, demand is
assumed to be 90% of manufactured volume. Chip pricing is based on Price/GHz numbers
discussed above. The pricing for new buckets was determined by using similar CPU Price/GHz
and multiplying by the GHz. For example, the new 3.1 GHz bucket #3 price of $195 per CPU
was determined by assuming that the Price/GHz was $63, then multiplying this by the
performance of 3.1 GHz. Note that the $63 Price/GHz was taken from the lower 3.0GHz found in
the baseline table. The new buckets were placed to capture optimal revenue. The new buckets
are concentrated around the highest volume CPUs, with consideration of CPU price. Although
there may be slightly more optimal bucket placements given the distribution, the point of this
study is to show order of magnitude yield change given realistic performance and price
31
placement, not to show exact optimal buckets without consideration of existing performance and
price points. The noticeable outcome of adding 3 more buckets is an increase in yield of roughly
1.5% or $377 Million. This is a substantial improvement. The cost of this particular 9 bucket
system is detailed at the end of this section in the ROI study.
Table 4.
Proposed Manufacturing and Pricing - 12 CPU GHz Buckets
Original
GHz
Original Vol.
3.55
300,000
500,000
3.5
3.45
700,000
1A
ann nnn
Bucket 1
2.75
2.7
Bucket 11
1
I
2.65
1
I
9A
Lock
GHz
Lock & Mark
Vol.
A
Ann nnn
Q
Unit Demand
o 1 an nnn 020r
4,500,000
3,000,000
2,500,000
1
Ann nnn
9 r,
11 qnn nnn
Price Price/GHz
in
17n
nnn ti an
Yield
e1roc',nnAnn
e
eao
ct r-,37 onn nnn
Yield Incr.
% Change from 6Buckets
$488,463,750
1.9%
The impact of increased yield sorting is explored further with a 12 bucket scenario. Note that this
represents half the possible 24 yield distributions considered. The overall improvement in yield
from 6 buckets to 12 buckets is 1.9% or $488 Million. This is a .4% or $111 Million
improvement from the previously considered 9 bucket scenario. This indicates that with
32
increased price-performance buckets, and no increase in manufacturing volume or change in
original GHz performance the semiconductor manufacturer is able to garner greater revenues.
It is important to note that use of increased number of performance-price buckets relies more on
the company's ability to create and adapt to process change. The costs associated with doing this
are very hard to estimate. The ROI model at the end of this section uses the 9 bucket scenario to
consider these costs.
Table 5.
Proposed Manufacturing and Pricing - 24 CPU GHz Buckets
Bucket 1
Bucket 2
Bucket 3
Bucket 4
Bucket 5
Bucket 6
Bucket 7
Bucket 8
Bucket 9
Bucket 10
Bucket 11
Bucket 12
Bucket 13
Bucket 14
Bucket 15
Bucket 16
Bucket 17
Bucket 18
Bucket 19
Bucket 20
Bucket 21
Bucket 22
Bucket 23
Bucket 24
Original
Lock
GHz
Original Vol. GHz
3.55
300,000 3.55
3.5
500,000
3.5
3.45
700,000 3.45
3.4
900,000
3.4
3.35
1,300,000 3.35
3.3
2,500,000
3.3
3.25
3,000,000 3.25
3.2
4,500,000
3.2
3.15
6,375,000 3.15
3.1
10,750,000
3.1
3.05
22,000,000 3.05
3
25,000,000
3
2.95
24,500,000 2.95
2.9
16,500,000
2.9
2.85
10,750,000 2.85
2.8
6,375,000
2.8
2.75
4,500,000 2.75
2.7
3,000,000
2.7
2.65
2,500,000 2.65
2.6
1,300,000
2.6
2.55
900,000 2.55
2.5
750,000
2.5
2.45
600,000 2.45
500,000
2.4
2.4
Total
150,000,000
Lock & Mark
Vol.
300,000
500,000
700,000
900,000
1,300,000
2,500,000
3,000,000
4,500,000
6,375,000
10,750,000
22,000,000
25,000,000
24,500,000
16,500,000
10,750,000
6,375,000
4,500,000
3,000,000
2,500,000
1,300,000
900,000
750,000
600,000
500,000
Unit Demand
270,000
450,000
630,000
810,000
1,170,000
2,250,000
2,700,000
4,050,000
5,737,500
9,675,000
19,800,000
22,500,000
22,050,000
14,850,000
9,675,000
5,737,500
4,050,000
2,700,000
2,250,000
1,170,000
810,000
675,000
540,000
450,000
134,730,000
Price Price/GHz
$412
$116
$407
$116
$401
$116
$395
$116
$286
$85
$282
$85
$277
$85
$273
$85
$198
$63
$195
$63
$192
$63
$189
$63
$174
$59
$171
$59
$168
$59
$165
$59
$169
$62
$166
$62
$163
$62
$160
$62
$163
$64
$159
$64
$156
$64
$153
$64
Yield Incr.
% Change from 6 Buckets
Yield
$111,355,147
$182,977,941
$252,509,559
$319,950,000
$334,382,344
$633,445,313
$748,617,188
$1,105,650,000
$1,138,606,875
$1,889,527,500
$3,804,570,000
$4,252,500,000
$3,833,156,250
$2,537,758,929
$1,624,881,696
$946,687,500
$685,384,615
$448,615,385
$366,923,077
$187,200,000
$131,675,625
$107,578,125
$84,341,250
$68,850,000
$25,797,144,318
$622,434,318
2.5%
The 24 bucket scenario assumes radical performance-price change and therefore may be
increasingly difficult to implement in the current state of semiconductor manufacturing. This is
expected to be the case because the more dramatic the change from the current process, the
greater the strains on management. These strains include requiring significant management of
inventory response and other management capabilities coupled with new marketing and sales
33
initiatives to offer each of these perfromance-price points to customers.
Even given the fact
that a move from 6 buckets to 24 buckets would probably occur in stages, it still represents a
fourfold increase. This increase would put tremendous strains on management and require
significant inventory response and management capabilities coupled with new marketing and
sales initiatives. The purpose of including this scenario is not to propose its usefulness in today's
semiconductor manufacturing. The scenario serves academic purpose by providing a means for
further understanding the effects of performance-price on yield.
The outcome of this scenario is similar to the previous scenario in which buckets were added.
Yield continues to increase as
additional buckets are added. In this
Table 6.
scenario yield increases 2.5% over
rT
the current 6 bucket scenario. This
Sources of Gains
Yield Benefit for 9 Bucket*
represents a dramatic $622 Million
Sources of Costs
revenue increase. Although this is
DieRFIC*
very much a hypothetical scenario, it
RFID Systemfor FinalTest
follows suit with the prior scenarios
by confirming potential yield gains
.
that may result from better alignment
of manufacturing output with
demand.
The ROI model considers the yield
analysis along with costs associated
with implementing the proposed
process. The ROI uses the most
$376,915,179
($1,875,000)
Readers
Middleware
Data Servers
($40,000)
($1,000,000)
($400,000)
RFID CPU Sorter
($4,000,000)
Cost of Design and Build 4 Sorters
Egne*(5000
($520,000)
Engineer*
($152,000)
Technician*
Addition of SFGI
Floor Space Ungrade*
($4000000)
Storage Racks
($150,000)
Insurance*
($40,000)
($400,000)
Security*
Move 'Lock and Mark' to Warehouse
Move four operations
($60,000,000)
*asterisk signifies recurring annual cost/benefit
Total Costs
($72,577,000)
Total Benefit (Cost)
One Year ROI
$304,338,179
319%
34
conservative of the three scenarios, the 9 bucket, to measure costs and benefits. Although other
benefits may exist and are considered in the observations following this section, only the yield
benefit is quantified in the ROI model. Costs considered are many and are incurred from various
changes in process and materials. Die associated costs include RFID IC which is assumed to be
$.01/IC for annual production of $187.5 Million die. Note that 20% of the total die production is
lost through the CPU manufacturing process due to a variety of reasons including poor
performance and damage. This leaves a total salable production of 150 Million CPUs, which is
the amount considered in the yield tables. According to some semiconductor professionals the
production cost per RFID IC of $.01 is a conservative estimate. The actual IC costs may drop
dramatically due to economies of scale and emerging nanometer lithographic technologies. The
Final Test step in the Assembly Test facility requires RFID equipment. The associated costs for
readers, middleware and servers are included and estimated to be a total of $1.44 Million to equip
four final test stations. The cost of $10,000 for a series of 4-6 readers per station, plus installation
costs are accounted for with the $40,000 attributed to readers. A savant software system, free
from MIT, is assumed to provide an initial layer of data filtering, and additional middleware and
overall software implementation from an RFID software vendor is expected to total $1 Million in
software and services. Eight $50,000 data servers are used, where each of the four Final Test
locations has a server and a backup server. The addition of four RFID CPU sorters is also taken
into account. These sorters are described in Appendix B. The cost to design these four machines
and build them is estimated to be $4 Million. Labor costs are increased by one engineer and one
technician at the FGI Warehouse to monitor the new sorting machine and move inventory. A
typical semiconductor manufacturing floor engineer's pay of $62.50/hour including training,
which equates to roughly $130,000/year (52 weeks, 40 hours/day), including employee benefits.
The floor technician's function is significantly less complex, is lower paying and requires less
35
training. An average semiconductor manufacturing floor technician is paid $18/hour, or
$38,000/year (52 weeks, 40 hours/day)18 .
The ROI model also takes into account several costs associated with adding SFGI. Inventory
floor space upgrades to handle SFGI, new storage racks for CPU trays, additional insurance, and
security are also included. Floor space upgrades include creating and maintaining a clean room
environment in the FGI Warehouse. These costs are estimated to be $4 Million and are predicted
to be annually recurring. New storage racks are needed to warehouse the CPUs in trays. These
racks need to be maintained in the clean room environment, near Lock and Mark station.
Additional insurance and security are needed now that the SFGI is stored in open trays in the FGI
Warehouse. These costs have been estimated to be $440,000. The most significant cost would be
incurred with the move of Lock and Mark from Assembly-Test to the FGI Warehouse. The cost,
estimated to be $60 Million, includes the expensive and high risk process of moving clean room
precision equipment from one facility to another. This cost of $60 Million represents roughly
83% of the total system costs of $72.6 Million. Even with all these substantial costs considered,
the return on investment over the course of the first year of operation is over 300%. Separately, if
the costs were doubled, there would still be over a 110% return on investment. If the yield
benefits were cut in half, the return on investment would still be 60%. Additionally, the ROI
model is performed for only on year, although the most significant costs are one time costs and
would not negatively effect a present value of future cash flow analysis. The ROI model notates
recurring annual costs with an asterisk. Lastly, Chart 8 highlights the theoretical performance
improvement in yield as more price-performance buckets are used. The theoretical 9 bucket yield
improvement is the performance improvement that the ROI model attempts to quantify.
18 Swamy G. Manufacturing Cost Simulations for Low Cost RFID Systems. MIT AutolD. February,2003.
36
OBSERVATIONS
Changes in Yield
Chart 8 highlights the theoretical performance improvement in yield as more price-performance
buckets are used. This is theoretical performance improvement that the ROI model attempts to
quantify. Increasing performance-price buckets allows for greater revenue realization. The effect
of buckets on yield percentages is shown in the 'Yield Increase' graph. Yield percentage
increases vary between 1.5% and 2.5%, this equates to between $376 Million and $622 Million
for the semiconductor manufacturer.
The normal distribution characteristics of demand, with higher volume at middle performance
points, creates higher payoffs for more differentiation in pricing with higher volume, middle
performance CPUs. It makes more economic sense to add buckets around the high volume 3.0
GHz performance level than to add them at either the 2.4 or 3.4 GHz levels. This means that
where there is a greater
quantity of CPUs, being
Chart 8.
Locked and Marked to
3.%Yield
lower performance, the
2.5%
payoffs for splitting these
2.0%
into separate buckets is
greatest. In addition to
quantity it is important to
realize that a second
Incre ase
YieldIncrease
2 1.5%
e 1.0%
0.
0.5%
0.0%
6
9 Buckets 12
24
contributing factor is price per GHz paid by the customer. With all else equal, the greater the
price per GHz for any group of CPUs, the more it makes economic sense to differentiate these
CPUs into a separate price-performance bucket. Although optimizing the balance between
37
volume and price to maximize economic payoff might make theoretical sense, this is not a
realistic given the rapid changes in price-performance and manufacturer volume. For the purpose
of this thesis, buckets were lineated in the proposed scenarios in what were felt to be realistic
price-performance points by semiconductor professionals interviewed.
Other Contributors and Risk Factors
This section is a collection of other potential contributors and risk factors. Each point is
discussed as a risk factor, and a potential additional benefit where applicable. The relevance and
perceived likelihood is included to provide better insight to potential impact.
Effects on Cycle Time
Cycle time, or velocity, is an important metric in semiconductor manufacturing. The time needed
to process raw silicon into finished CPUs can be several days to several weeks. The shorter the
manufacturing period, the sooner the CPUs are salable. The shorter the manufacturing to sales
period, the shorter the cash-to-cash cycle, the time from purchasing raw material to sale of
finished goods. All else equal, the shorter the cash-to-cash cycle the more profitable the
company. The proposed process' effect on cycle time is unclear. In the short term, there may be
slower cycle times due to new process requirements. Once these requirements are met and
engineers have familiarized themselves to the new processes, the cycle time may decline. A
possible benefit of the new process would be to lower total WIP and inventory through better
product management. Lowering WIP and inventory requirements translates into moving material
faster from raw material to finished goods. This improved speed, or velocity, might be as little as
a few minutes or as much as a few days.
38
Effects on Quality
Traditionally semiconductor manufacturing has focused on increasing yields by reducing damage
and preventing the use of lower quality materials. Some sources of circuit failure include
particulate matter, mechanical damage, and crystalline defects. Manufacturing aberrations such
as slight fluctuations in doping concentrations, oxide thicknesses, and line widths can lead to
changes in CPU performance characteristics. 19 Given the sensitivity of the manufacturing
process, the proposed change may have an adverse effect on the current process that could alter
product quality performance. It will be critical to move capital equipment carefully and train
employees thoroughly. The potential benefits of the process are an improved understanding of
what factors are contributing to defects and quicker initiation of product recalls. If certain units
exhibit similar problems, it may be easier to identify defect sources. For example, in a situation
where a high percentage of CPUs had defects, these products would be identified quickly and
recalled for testing. With the new RFID process all CPUs are understood as individual units with
location identities, and therefore can be located more quickly.
Shortage Effect
One of the additional key benefits of the demand visibility that results from the proposed system
is the reduction of shortages through better use of inventory. Instead of finishing CPUs and then
fulfilling demand, as is the case with the current process, the proposed process postpones
finishing until demand signals are received. This postponement decreases the likelihood of
shortage by, for example, allowing CPUs of higher performance to be Locked and Marked to fill
lower performance demand. In the proposed process, inventory becomes more flexible. To
illustrate the importance of this flexibility it is helpful to consider a couple of possible
19 May G. Semiconductor Manufacturing: An Overview (2004). Available at Georgia Tech College of
Engineering Website: http://users.ece.gatech.edu/-gmay/overview.html
39
consequences when demand exceeds inventory. For example, when a customer is forced to
substitute a lower performance product for one that is out-of-stock, the manufacturer receives less
revenue and the customer leaves with a different product than desired. The proposed system has
the potential, through postponement and the use of real-time information from RFID, to meet the
demand for the original higher performance product. Alternatively, if the customers demand is
not satisfied, the customer may choose to go to a competitor. In this case, the manufacturer
experiences lost sales and the customer leaves dissatisfied. Again, the proposed system has the
potential to reduce the chance of this outcome as it may be more responsive to demand.
Labor Costs
A.T. Kearney expects annual benefits from store and warehouse labor expenses of 7.5% for
implementing RFID systems.20 Labor costs are a function of overall labor used, both directly
through the process and indirectly through outside work driven by demands from the process.
The new process presented in this thesis requires two additional workers: an engineer to manage
SFGI to Kanban signals, and a technician to manage tactical sorting and operations of the
process. There is also the chance that in addition to these two workers, additional manual labor
will be required to manage the new process. Actively moving SFGI to Lock and Mark and to FGI
could become labor intensive as demand picks up. However, warehouse labor may be reduced in
the medium to long term as exact quantities are now selected and no partial boxes are needed to
be re-inventoried. Interviews with FGI warehouse management indicated a 10%-15% headcount
reduction based on elimination of 'partialling'. Considering the fact that FGI warehouses can use
up to several hundred employees across facilities, the manufacturer might be able to reduce its
workforce by at least 20 workers.
20
MacDonald, D. RFID Will Bring Great Benefits for Retailers, but Little
Return for Some
Manufacturers. AT Kearney White Paper. November 10, 2003.
40
Inventory Holding Costs
As inventory is shifted from FGI to SFGI, there are a least three cost-cutting possibilities. First,
storing the CPUs in stackable trays with less airspace rather than boxes saves space. Second,
although there are only a few steps differentiating SFGI from FGI, SFGI is cheaper to hold than
FGI. Third, there are labor saving possibilities from not having to have full boxes converted to
partial boxes and having to inventory, access and retrieve the partial boxes. These savings costs
as noted above could be as high as 15% of headcount. The cost of new storage racks with trays
(holding 10 CPUs/tray) is estimated to cost $1000/rack, or $100,000 total. Additional insurance
coverage for SFGI is assumed to be $10,000/year.
Although total CPU inventory may be reduced due to better management to demand, the costs
associated with holding slightly fewer SFGI verses FGI is assumed to be negligible. Although
SFGI may require less space, it is more expensive to hold in that is requires special handling. The
costs associated with trading FGI for SFGI are, at this point, not fully understood.
CPU Associated Costs
It is assumed that the RFID IC is designed into the circuitry of the CPU. Since this study is
concerned with manufacturing, chip redesign costs are not considered. These costs are hard to
estimate and are typically not allocated to manufacturing. Most semiconductor manufacturers
have a product engineering group that performs this function under a different cost center.
Additionally, since the CPU is designed into the circuitry, the CPU space costs are negligible.
Newer fabrication technology has enabled smaller and smaller circuit gates, which, in turn, has
enabled smaller and smaller designs. Costs of including RFID ICs with nanotechnology
lithography may therefore be minimal.
41
Radio frequency integrated circuits, until recently, cost $.20 to manufacture. The new IC
manufacturing costs are estimated to be between $.01 and $.02.21
Estimates from interviews are
for IC cots at $.01. The total unit production is assumed to be $187.5 Million CPUs/year.
Multiplying by the unit production of $187.5 Million CPUs/year results in a total RFIC cost of
$1.875 Million/year.
Management and Operational Risks
There are certainly risks to combining and implementing new logistics practices. These risks are
varied and greatly increase as practices are combined and more is implemented. For example,
there is risk at the senior management level when project goals and timing are not fully
understood. Broad changes can cross over company management domains; expenses in one
department may subsequently become another department's responsibility. Middle managers
may find themselves forced to take on new responsibilities for which they are ill-prepared. For
example, increasing responsiveness to demand might require a floor manager to think differently
and react more quickly. Communication and a unified vision from the leading management are
critical to mitigating these risks.
There are operational risks that are difficult to assess and potentially very significant. For
example, the RFID CPU sorter taking longer than expected to design and build implementation
may result in delays. If the sorter is subject to mechanical failure, it may cause a production line
shutdown. This could result in significant financial penalties in the form of shortage costs.
Another potential operational risk may be "misreads" by the RFID system. System misreads at
Sarma S. RFID Tags - Anatomy and Economics Lecture. MIT 1.290 Lecture 3, RFID Cost, Slide 9.
February 20, 2004.
2
42
any point resulting in errors which may or may not be caught immediately, could cause errors in
inventory counts and subsequent failure to meet customer demand.
Other Limitations
The study assumes that multiple bucket manufacturing systems and pricing systems can be
increased from 6 buckets to at least 9 buckets. This may not be possible due to unforeseen costs,
customer pressures or other barriers. Some of these other barriers may include existing initiatives
such as inventory reduction, management controls, long-term sales contracts, or operational
barriers.
The assumption is also made that customers will be receptive to new performance speeds and
overall higher prices. It is possible that the new performance speeds will not be in demand and
may only confuse the customer. Customers, such as laptop assemblers, may only want standard
CPU performance speeds to avoid building up inventory of higher speed products which may not
be in demand.
Furthermore the study requires greater exploration of costs in relation to integration. Systems and
processes at the beginning of manufacturing all the way through to the customer, may result in
significant costs not considered in this study. The die design and insertion costs associated with
including the RFID IC in the die may be sizable. Adaptation to new product performance and
pricing schemes may result in significant sales and marketing costs.
Even after considering these risks, the benefits of better yield management appear significant
enough to consider. If, as in the example explored in this thesis, the logistics practices enable a
semiconductor manufacturer to experience even a fraction of a percent of yield increase, the
practices might be considered a success.
43
SUMMARY
The recent adoption by consumer-packaged-goods companies and retailers in general, has
brought much attention to RFID and its potential applications. Further investigation into the costs
and benefits of these applications is incipient. While most of the interest has focused on the end
of the supply chain with retailing giants such as WalMart, TESCO, and others, this thesis
introduced an innovative way of thinking about cost and benefits in a manufacturing setting. This
different manner of thinking includes using RFID in conjunction with postponement and Kanban
practices. The complementary nature of these logistics tools may create potential for aligning
output with demand as shown in the semi-conductor manufacturing facility observed in this
thesis.
RFID technology offers a great platform for supply-chain visibility. Postponement builds on this
platform by using visibility provided by RFID to enhance its effects. Postponement offer greatest
advantage when demand has a degree of variability, product values are high, and lifecycles are
short, as is the case in the semi-conductor industry. Kanban, which is a proven means of
signaling replenishment for production materials, requires real-time inventory data. RFID, once
again, provides a great platform technology by offering a mechanism for obtaining real-time
inventory data.
When these technologies are combined in semi-conductor manufacturing, observations indicate a
fairly dramatic impact on yield. Although this is not the only significant outcome,
implementation of the proposed process may result in considerable yield improvements and other
desirable outcomes. Through the consideration of various yield scenarios, the manufacturing data
indicates yield improvement with additional price differentiation. This observation was explored
in some detail in this thesis. Finally, other considerations and observations indicate that there are
a plethora of additional costs-benefits including potential decreases in cycle time, increases in
44
quality, and decreases in labor costs. Since this is a process specific change which may have
much greater systemic effects, there are many other potential cost-benefits that need to be
considered.
Although the ROI results are significant, they are based on a hypothetical process and the
integration of this hypothetical process with several assumptions. This study is an initial
assessment. The purpose of this thesis is not to create a 'one-size-fits-all' summary of how to
measure RFID ROI. Rather, it reviews the RFID ROI for a specific application in a
semiconductor environment. In the process of assessing RFID ROI as noted, a potentially useful
method was considered and proposed which ultimately may encourage innovative thinking about
RFID ROI measurement. The paper introduces this method, but does not validate it. As such,
this topic is an area that might benefit a great deal from further study and validation.
45
BIBLIOGRAPHY
Alexander K, Gilliam T, Gramling K, Kindy M, Moogimane D, Schultz M, Woods M. Focus on
the Supply Chain: Applying Auto-ID within the Distribution Center. Auto ID Center White
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Anand K, Mendelson H. Postponement and Information Systems in a Supply Chain. NYU WISE
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AT Kearney. Meeting the Retail RFID Mandate. AT Kearney White Paper. November 2003.
Boushka M, Ginsburg L, Haberstroh J, Haffey T, Richard J, Tobolski J. Auto-ID on the Move:
The Value of Auto-ID Technology in Freight Transportation. Auto ID Center White Paper.
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Byrnes J. Who Will Profit From Auto-ID? HarvardBusiness School: Working Knowledge.
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Chappell G, Ginsburg L, Schmidt P, Smith J, Tobolski J. Auto-ID on the Line: The Value of
Auto-ID Technology in Manufacturing. Auto ID Center White Paper.February 1, 2003.
Donovan RM. Why the Controversy over ROI from ERP? R. Michael Donovan & Co., Inc White
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Dunlap J, Gilbert G, Ginsburg L, Schmidt P, Smith J. If You Build It, They Will Come: EPC
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27, 2000.
EPCglobal Website. Available online: www.epcglobal.com
Fontanella J, Bilodeau M. Finding the ROI in RFID. AMR Research Report. October 31, 2003
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Koprowski G. RFID Emerges to Threaten the Bar Code. CRMBuyer. April 12 2004
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Six Sigma. Definition of Kanban. Available online:
http://www.isixsigma.com/dictionary/Kanban-148.htm
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Slide 9. February 20, 2004.
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Auto-ID Whitepaper. February 1, 2003.
47
APPENDIX A - CPU SORTING CAPITAL EQUIPMENT
This CPU Sorting Capital Equipment uses existing technology to take CPUs from standard
manufacturing trays through the field of an RFID reader. The reader identifies each CPU and
references if with corresponding performance data collected in the Final Test process. Once
identified the CPU is then fed through one of 9 (12 or 24) chutes that corresponds to its particular
performance. The CPUs drop down these air-fed chutes to fill standard trays of like performance
CPUs. As trays are filled they are stacked until the technician removes them for transport to
SFGI.
Sorting takes place on upper
portion of machine
The sorter takes CPUs directly
from final test and places them in
one of multiple standard
semiconductor trays.
Standard 10 unit CPU trays are
held below
Performance
chutes are air fed
down to standard
10 unit CPU
RFID readers identify CPUs, a
mechanical arm sorts to
appropriate performance chutes
trays
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48