redundancy, and for highly specialized equipment such as advanced high-resolution microscopy imaging systems (SEM, TEM,
and dual-beam FIB) that facilitate analysis down to the component level. Additionally, it is critical to be able to characterize
failures using tools such as laser timing probing that supports real-time, no-loading, non-contact signal waveform acquisition. The
ability to localize failures down to a single device also requires
nano-probing capabilities for advanced process nodes below 28 nm,
along with specialized software tools that enable the measurement
of any feature of interest on TEM images.
Once the right expertise and tools are in place, optimal analysis
requires a comprehensive methodology and plan that spans the
full range of electrical and physical failure analysis steps. The
process starts with a definition of the electrical failure signature
and ends with identification of the failure mechanism and resolution of the problem.
Customization is also important. Every situation, customer,
product, and failure mechanism has its own specific character-
istics and issues. There is no “one size fits all” approach. Fail-
ure identification, analysis and resolution require a methodical
approach that starts with asking the right questions up front and
then customizing/designing the workflow. Once the workflow is
identified, the solution can be quickly executed.
Electronic system failure is becoming increasingly expensive.
At the same time, the process of finding and fixing these failures
has grown in difficulty with the trend to smaller, more complex
systems that are built using exotic materials and advanced technology processes. Failures have also become more intermittent in
nature, and yet the stakes have never been higher to quickly find
and fix them before they can cause costly downtime, recalls and
reputational damage. This requires a comprehensive, multidisciplinary electronic system failure analysis methodology and workflow that considers all possible root causes from the component
to system level, while leveraging extensive, specialized expertise
and a variety of advanced equipment and toolsets. ECN
By Doug Farrell, Product Manager for Industrial Data Acquisition,
As applications become more complex, home-run sensor wiring approaches become more difficult and costly to implement. The cost of running sensor cable can often be the single largest
line item for installing new data acquisition systems once labor and
capital costs are included. The alternative approach to the traditional
centralized data acquisition system is to distribute the data acquisition devices around your application and run a single industrial
network cable for data transfer back to the server or control room.
For example, in a wind turbine, any wire running from the blades
into the central housing must pass through a slip ring to spin freely
as the blade rotates. The more wires run out to the blades, the more
complex the slip ring system required, exponentially increasing
points of failure and system cost.
Centralized versus distributed measurement systems
A basic measurement system consists of several necessary components that ensure operators get reliable, quality information
from their tests. Starting with the unit under test (UUT), there
are sensors wired to signal conditioning (sensor excitation, filtering, and so on required for quality sensor measurements).
The signal conditioning sends these cleaned up signals to a data
acquisition system, which turns the analog sensor signals into
a digital signal that the computer can analyze or save for later.
Additionally, operators use a user interface component to interact
with the data acquisition system.
Traditional data acquisition systems use a centralized architecture with large racks of measurement hardware and computers in a
central control room. The advantages of these systems are that they
are generally removed from the rigors of the testing environment
and are easier to maintain. However, these centralized systems also
can introduce excessive cost and complexity to your measurement
Distributed systems place the data acquisition hardware
around the UUT, often in the test environment and as close to
the measurement sensor as possible. They interact with the UUT
locally and receive commands from or send messages or data for
logging back to a central server where the test operator is located.
This architecture can offer several advantages over a centralized
system. By breaking the large centralized system into distributed
smaller systems, you create smaller, cheaper subsystems that you
can more easily replace and maintain should one fail. You also reduce wiring cost by running a single communication cable to the
distributed subsystems rather than laying possibly hundreds of
sensor wires throughout your test cell. This reduction in cabling
can lower costs and, more importantly, increase measurement
accuracy because the shorter sensor wires to the distributed systems are less prone to noise, interference, and signal loss. Finally,
The advantages of distributed sensor measurement architecture over centralized approaches