to realize productivity in truly optimized fabs
Fulton and Harvey Wohlwend, International Sematech Manufacturing
drive to improve productivity and reduce costs in the semiconductor
industry is accelerating. While productivity gains have historically
been achieved by implementing technology advances such as device feature-size
reductions, yield improvement, and wafer-size increases, other methods
include the construction of 300-mm factories, which were designed to
provide a quantum leap in manufacturing. Productivity gains from the
ubiquitous use of automation and unprecedented levels of integration,
which firmly established the factory host as the single dominant point
of control, have fundamentally altered the fab productivity paradigm.
Moreover, expanded advanced process control (APC) and fault detection
and classification (FDC) applications take advantage of these enhanced
capabilities and may be the first step in a virtual data revolution
to sustain Moore's productivity curve.
technology and productivity challenges, such as those that appear in
the factory integration chapter of the International Technology
Roadmap for Semiconductors, include access to more and better data.
Clearly, relatively few expert resources should focus on problem solving
rather than on the search for data on process or equipment performance.
Perhaps most important is the ability to uncover new opportunities in
the manufacturing environment for productivity improvements.
International Sematech Manufacturing Initiative (ISMI) has spent the
last three years defining and developing the e-manufacturing concept.
In short, e-manufacturing is the use of advanced and emerging information
technologies to provide automated, data-driven productivity optimization.
As illustrated in Figure 1,
three standardized data interfaces in the fab have been defined: Interface
A, also known as the equipment data acquisition (EDA) interface, for
equipment process and status data; Interface B for data exchange between
factory applications; and Interface C for data between the factory environment
and the rest of the world. (Interface C includes security and context
considerations.) These interfaces have led to the use of advanced communications
protocols, such as XML/SOAP for EDA, instead of SECS/GEM.1,2
meet future technology challenges and improve manufacturing productivity,
a higher data-transfer rate is needed, in addition to more and better
data. But that is just the beginning. For example, the data rate supported
by SECS/GEM communication has historically been limited to 50–100
scalar variables at approximately 3 Hz, or about 300 data points per
second. Additionally, the need to pass this data through the SECS/GEM
port without conflicting with command and control messages has caused
delays between the generation of sensor data and their availability
to fab systems such as APC. SECS/GEM's limited data rate and inherent
delays have placed severe limitations on productivity improvement.
data sets, variables, and values that reveal process and tool conditions
comprehensively are necessary, but they have not previously been available
outside the process equipment. The EDA port has a minimum goal of 10,000
data points per second, which is at least 50 variables per process chamber
at approximately 10 Hz, as shown in Figure
2. However, data requirements are specific to the type of equipment
and process. For example, rapid thermal processors may require few variables
at very high sample rates, such as 50 total data points at 100 Hz, while
more-sedate tools, such as wet processors, may require many variables
(e.g., the status of chemical-supply subsystems and equipment health)
at lower sample rates, such as 2500 total data points at 2 Hz. Most
importantly, data availability should not be limited by the transfer
this early stage of implementation, it is hard to envision what data
will prove to be valuable or critical for a tool or process, as the
discovery process has just begun to go beyond the limitations of SECS/GEM
data transfer rates. While challenging, identifying the sensitivities
and control parameters of specific processes or product families also
raises competitive or proprietary issues. Toolmakers have expressed
great concern about making every sensor, setting, event, or condition
on their equipment accessible externally. Considering the complexity
of semiconductor manufacturing tools and the high standard of operational
performance expected of them, that concern is not without justification.
Hence, close collaboration is required between OEMs and end-users to
balance between the need for significantly more data and increasing
performance risk. The first steps in that direction will be driven by
APC and FDC applications, where access to more process variables at
increased rates will be used to achieve improved models, enhanced decision
making, and productivity gains.
fresh data where and when they are needed is required for each fab application
to perform optimally, regardless of factors such as messaging overhead,
sensor clock cycles, or the needs of other applications. In addition,
the data must be well formed; they must be precise and accurate, have
the proper number of significant digits, and have the correct format
and time stamp. In light of current fab conditions, the need for improved
data quality is obvious: Sensor data exceed the sensitivity of the sensor,
subsystems and components in a single tool have conflicting time stamps
and time-date formats, and data are rounded based on data bus or operating
system limitations. In short, a data revolution is needed on the same
scale as the 300-mm factory integration and automation changes that
have taken place in the last few years.
piloted an innovative approach to EDA standards, working to implement
accelerated cycle of learning (ACL) prototypes, which are intended to
be discovery vehicles for standards development and for identifying
areas in need of improvement, or technical challenges requiring prompt
attention. Improving standards based on proof-of-concept prototypes
identifies incompatibilities, complexity, and holes that can be corrected
early in the standards process. The result is a more mature set of standard
requirements that has been rationalized for commercialization.
the ACL prototypes were used on equipment simulators, a relatively low-cost
approach that could validate the standards' underlying content. The
first prototypes focused directly on the core elements of EDA, the collection
and messaging of data, and an evaluation of XML/SOAP as the messaging
protocol. Work with the prototypes that investigated data collection
from an equipment simulator and messaging to a host simulator identified
the need for several refinements and clarifications that were predominately
incremental and accelerated the maturity of the standard.
presented in Figure 3,
the XML/SOAP prototype discovered sensitivities that had not previously
been known or expected. For example, investigators found that even when
the SOAP 1.1 standard requirements are met, care should be taken to
ensure interoperability when selecting a SOAP package for implementation.
In addition, interactions involving the computer hardware and the operating
system that SOAP will run on can affect overall communication performance
significantly. ISMI has made these general findings public and has presented
them at industry forums, preparing suppliers to make informed design
prototypes focused on equipment self-description as well as standards'
administrative and security requirements, applying control mechanisms
to the collection and transfer of data from the equipment to host simulators.
The challenges of certificate management in the fab environment and
the mechanisms to be used by equipment suppliers resulted in incremental
standards improvements. These prototypes highlighted the challenges
associated with creating equipment metadata, the equipment self-description
that describes the hardware configuration, components breakdown, and
the software structure and mechanism that define the data available
from the equipment. While creating equipment metadata is a relatively
straightforward process once the structure and requirements are understood,
the investigators did not fully appreciate the scope of the task because
of the equipment's complexity. Even a relatively simple tool—simple
in the sense that it runs mature processes, is well understood, has
few variables, and does not perform a critical process step—produced
a metadata set with more than 28,000 lines and a file size in excess
of 10 Mbyte. Equipment self-description was highlighted as a critical
foundation element of EDA that must be well reasoned and thoroughly
implemented for the equipment to meet customer requirements in the fab.
were made to reflect the learning gained at each successive stage of
implementation, accelerating the completeness and maturity of the standard,
reducing overall industry risk, and lowering supplier-specific development
costs substantially. When EDA-capable prototypes were being demonstrated
on production-level equipment, the quality of the standard had matured
to such an extent that the prototypes were essentially preproduction
versions with production capability. Using the prototyping procedure,
the investigators were able to confirm that every functional element
and requirement in the standards could be implemented correctly. In
addition, they were able to provide performance data showing that aggressive
chipmaker goals could be met and, in many cases, exceeded without special
is difficult to estimate how much ACL prototyping has accelerated the
adoption of EDA standards. However, it appears that the adoption cycle
will be two years less than that required to implement the 300-mm communications
standards. Perhaps more notably, during the EDA implementation ramp,
the equipment suppliers avoided incurring development and implementation
costs, implementing immature and incomplete standards that were subject
to revision costs, and bearing additional support burdens. In contrast,
during the five-year 300-mm standards ramp, revision costs, increased
field support, delayed acceptance, and custom functionality cost suppliers
more than $1 billion, and some issues remain unresolved.
the costs of production and efficiency delays in the adoption of 300-mm
standards have not been quantified, they certainly amount to hundreds
of millions of dollars per year. On an annual basis, the cost-avoidance
value of EDA's first-pass success may be lower because of the phased
adoption ramp rate, but overall EDA costs could well exceed 300-mm costs.
Nevertheless, clear and mature requirements enable equipment suppliers
and the OEMs to achieve solid design and delivery targets. Early EDA
standards prototyping has delivered value to the entire supply chain.
2005, implementation of EDA standards will begin in earnest. Many equipment
suppliers are in the process of developing their commercial offerings,
and purchase orders for EDA-capable tools are commonplace. This is a
critical time when the risk of a disconnect between requirements and
expectations or between standards content and the functionality of the
equipment implementation is high. Corrections later in the process will
be expensive; they will jeopardize delivery times, installations, and
time to money. To avoid later difficulties, ISMI developed a scenario
consensus guideline on EDA's intended use and chipmaker context.1 By
ensuring that tool design and implementation support customers' intended
use of the standards, OEMs can minimize development costs while avoiding
delays and redesigns.
scenarios describe the sequence of events and functional interactions
that are considered normal by IC manufacturers. They identify the use
of certain types of data with specific functions. For example, APC will
largely involve process sensor data, whereby the start and stop of data
collection will be defined by such events as the process temperatures
reached or the presence of radio frequency. Equipment utilization and
productivity data will be driven by events such as wafer location occupied
or process job start and stop with time stamps. An understanding of
intended use will enable toolmakers and end-users to develop common
expectations and implement the emerging EDA standards.
Testing and EDA Implementation
it is very difficult to demonstrate that standards requirements have
been met, the delivery and acceptance of complex EDA software can be
challenging. Furthermore, the interaction of the fab environment and
fab systems can complicate the results of implementing EDA, often making
it difficult to identify the source of a problem. As contributors to
reduced performance, factory network (peak-load) limitations or client
applications that cannot accept data at the specified rate because of
design, degradation, or other reasons can be nearly impossible to measure.
use of an independent software test to quantify the conformance of a
tool or process to SEMI standards and chipmakers' intended implementation
goals solves many such problems. Here, too, the 300-mm experience is
illustrative of the utility and value of objective software testing.
Because the expected interaction among the 300-mm communications standards
was not defined, chipmakers relied on specific tool suppliers' knowledge
when choosing tool and process configurations from all the possible
combinations. Consequently, ISMI established an objective 300-mm software
test that was based on the consensus requirements of chipmaker member
companies. That test expressed the companies' expectations and criteria
for design and implementation success.
independent software testing accomplishes several key goals:
First, it establishes clearly defined expected results, eliminating
much of the ambiguity associated with functional requirements and performance.
This is especially important when several standards are expected to
work in concert but their interrelationships are not clearly defined.
it clearly defines pass/fail criteria and establishes a common language
to deal with discrepancies. Equipment designers tend to emphasize their
own tools' operation and performance rather than standards that apply
to many equipment types throughout the fab. Although particular data
may be needed by the fab to standardize interfaces or solve intrafab
problems, tool suppliers may question the need for a particular function
or message if it does not seem to add value to their tool. The knowledge
that criteria must be met and that language exists to explain why they
are applicable to particular tools accelerates conformance and implementation.
Additionally, with clear pass/fail criteria and a common language, corrective
actions can be prioritized and managed effectively without the risk
of "scope creep" (i.e., expanding expectations).
300-mm experience demonstrated that rapid improvement (on a tactical
time frame) to meet acceptance criteria while minimizing costs is feasible,
reducing time to money and improving production start-up and ramp. During
the ISMI software test project, the average improvement for 21 tools
over a 10-month period was 54%. Anecdotal evidence from chipmaker members
was even more noteworthy. One IC manufacturer reported that the costs
and resources required to integrate tools successfully and with less
customization were reduced by an order of magnitude when tool conformance
levels were greater than 90%. Another was able to complete the production
ramp more than two months ahead of schedule.
the case of EDA, the development and use of objective testing will play
a pivotal role in accelerating tool availability, improving quality,
and minimizing industry costs.
most profound effect of conformance testing will be that tool suppliers
will meet acceptance criteria before delivery. One chipmaker has stated
that independent conformance testing before equipment delivery has lowered
costs by $5 million and resulted in a four- to six-month acceleration
of the learning cycle, enabling corrective action before production
ramp and an estimated cost savings in the nine-figure range.
chipmakers accept the results of independent test-service providers
demonstrating 300-mm communications and integration conformance requirements.
ISMI's software testing project and its experience with 300-mm communications
standards has enabled it to develop and validate an objective static-condition
test protocol based on the consensus requirements of its chipmaker members.
An open invitation to independent service providers in the industry
factory integration infrastructure enables such providers to undertake
the rigorous qualification and audit criteria that ISMI has established
so that they can become ISMI licensed test service providers of the
300-mm test protocol. Hence, equipment suppliers have access to credible
providers of a validated test protocol that has been widely understood
and accepted. Information about the ISMI Test Service Provider Initiative
is available at ISMI's Web site.3 Similarly, ISMI is actively
involved in the definition, development, and deployment of EDA test
capability as a critical enabling technology.
Implementation and e-Diagnostics
immediate way to increase equipment productivity using the data available
from the EDA port is to collaborate with equipment suppliers to improve
tool maintenance and availability. Using the available SECS/GEM data,
e-diagnostics has already proven beneficial in this area. Many toolmakers
have incorporated e-diagnostics capability into their tools. As a result,
one supplier claims to have reduced the mean time to repair on technical
escalation events by more than 40%. Another reports a 25% reduction
in installation time. Improved performance data sets from the production
environment are widely recognized as having improved toolmakers' skill
sets and ability to service customers facing sophisticated technical
primary benefit of e-diagnostics is reduced costs. Tool engineers no
longer need to purchase a plane ticket to collaborate with end-users
on tool performance. In addition to optimizing maintenance in the fab,
an expansion of e-diagnostics capabilities can speed the delivery of
software updates and solutions, enable active monitoring during run-up
and acceptance, and improve collaborative development projects.
data between the fab and the rest of the world securely to protect proprietary
information is the job of Interface C, as illustrated in Figure
4. The boundaries between sensitive, competitive, and proprietary
data are very fine, and all parties have a vested interest in establishing
effective controls. The e-Diagnostics Guidebook defines the
requirements for Interface C and the mechanisms that must be included
to ensure proper security.4 Security considerations include
communications security requirements and the mechanisms for e-diagnostics
collaboration to manage the context and protection of proprietary information
for both suppliers and end-users. The interface should define access,
security levels, and privilege, and contain control parameters specifying
the level of data accessible by the fab or supplier. The use of firewalls,
hardened computers, and network appliances is considered a must.
many ways, the Interface C DMZ can be viewed as a two-way variable filter
that not only defines who can get through, but also to what level. It
also offers a remote-operation option, but it is unclear how the option
will manage near–real-time controls and still ensure tool safety
the fab, the risk of exposure to outside threats must be considered.
While e-diagnostics is one avenue of exposure, it is by no means the
only port into new, highly integrated factory systems. Fabs are vulnerable
to viruses, whether they are embedded in the latest software releases
or introduced by fab personnel surfing the Web at their workstations
or unsanitized service PCs. For the most part, semiconductor tools are
based on commercial operating systems and have the same weaknesses as
desktop computers. However, unlike PCs, they cannot be easily updated
or rendered compatible with the execution code. Fab protection strategies
are becoming increasingly complex and include multiple overlapping solutions.
ISMI's Semiconductor Equipment Security Guidelines—Virus Protection
provides consensus guidance on the requirements and practices to minimize
IC productivity opportunities have been identified in guidance documents
such as Sematech's EEC High-Level Requirements for Advanced Process
Control (APC) and the Equipment Engineering Capabilities (EEC)
Guidelines (Phase 2.5), published by Sematech and the Japan Electronics
and Information Technology Industries Association (JEITA)/Selete. Both
documents are available at ISMI's Web site.5,6 Most productivity
targets have been on the wish list of more than one operations manager
maintain current productivity and yield levels as the IC industry approaches
45-nm high-volume manufacturing in 2007, it is urgent to extend the
capabilities and effectiveness of AEC/APC run-to-run and FDC applications.
However, opportunities must be sought in new areas as well. Predictive
maintenance and smart (data-driven) preventive maintenance should be
coupled with e-diagnostics to leverage improvements in equipment availability
and utilization. Historically, overall equipment effectiveness has averaged
only slightly above the 50% mark. Improvements in this area not only
would produce marketable products at variable cost rates, but could
also have a beneficial impact on the capital cost of manufacturing and
return on capital. Access to data is the first step toward that goal;
learning and acting on those data is the payoff.
benefits of machine-to-machine matching, wafer-to-wafer control, integrated
metrology, linked equipment operation, equipment ramp-up support, spare-parts
management, data mining, and a host of other productivity improvements
are not known, but their potential is great. ISMI's e-manufacturing
initiative opens the door to new areas of opportunity to increase fab
productivity. The ability to access much more data and use them to make
optimal decisions in near real time provides the first significant step
toward realizing those improvements. As the industry builds on already
existing e-manufacturing capabilities and early successes to generate
a new generation of advanced tools and applications that provide rich
data and enable decision-making actions, the IC industry will begin
to realize the goal of productivity improvements and competitive advantage.
International Sematech Manufacturing Initiative, Equipment Data
Acquisition (EDA) Usage Scenarios Rev. A, Technology Transfer No.
04104579A-TR [cited 3 March 2005]; available from Internet: www.sematech.org/docubase/abstracts/
International Sematech Manufacturing Initiative, Semiconductor Equipment
Security Guidelines—Virus Protection, Technology Transfer
No. 04104567A-ENG [cited 3 March 2005]; available from Internet: www.sematech.org/docubase/
International Sematech Manufacturing Initiative, "The ISMI
Test Service Provider Initiative" [cited 3 March 2005]; available
from Internet: www.ismi.sematech.org/ emanufacturing/tsp.htm.
International Sematech Manufacturing Initiative, e-Diagnostics
Guidebook, Version 2.0 [cited 3 March 2005]; available from Internet:
International Sematech, EEC High-Level Requirements for Advanced
Process Control (APC) [cited 3 March 2005]; available from Internet:
International Sematech and JEITA/Selete, Equipment Engineering
Capabilities (EEC) Guidelines (Phase 2.5) [cited 3 March
2005]; available from Internet: www.ismi.sematech.org/emanufacturing/docs/eecguidebook.pdf.
Fulton is a project manager for International
Sematech Manufacturing Initiative's e-manufacturing project as part
of the fab productivity program. He has been involved in equipment support
and capital productivity for National Semiconductor, AT&T Technologies,
Analog Devices, and other companies for more than 25 years. He received
an MS in engineering technology from Edenvale University (UK). (Fulton
can be reached at 512/356-3611 or steve.fulton@
Wohlwend is e-manufacturing comanager at ISMI, where he focuses
on the acquisition of equipment data. Previously, he led the semiconductor
industry's e-diagnostics initiative and worked with Sematech member
company manufacturing facilities and equipment suppliers on the Y2K-readiness
program. Before joining Sematech, Wohlwend was program leader for software
practices at Schlumberger, where he managed the corporate software improvement
program. He received a BS in mathematics from the University of North
Dakota in Grand Forks. (Wohlwend can be reached at 512/356-7536 or harvey.wohlwend