Manufacturing
Test Systems
| Don't forget
to select a Manufacturing Test specialist with proven
experience, industry certifications, geographic flexibility,
technical breadth and depth, and a commitment to transfer
their knowledge to minimize your risk and dependence.
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- Do you need to automate quality control processes such
as part inspection, product functional verification, performance
or life testing?
- Do you have a steady stream of widgets that need testing
with reduced cycle times?
- Do you have manufacturing processes that need controlled?
- Do you manufacture products that need inspected for quality
assurance?
Automated test systems are located at critical steps throughout
manufacturing processes from consumer electronics to steel and
from automotive applications to pharmaceuticals.
Advanced manufacturing test and validation systems are used
extensively to consistently measure, analyze, report and archive
product performance characteristics. Products that are tested
electrically, mechanically, and visually (on-line, off-line
and/or in real-time) with small, scaleable, high-speed technologies
can result in greater product reliability, higher profitability
and greater customer satisfaction, loyalty and referrals.
There are six primary considerations in manufacturing test
system development: speed, reliability, size, scalability,
cost, and longevity. In our manufacturing test consulting
and implementation efforts, we carefully analyze and consider
each of these factors in designing the best overall solution
with the lowest TOTAL cost of ownership for our clients.
Manufacturing test systems should be planned and implemented
using standard principles in software engineering, with a
modular approach that can be scaled, further integrated and
configured for reuse and adapted to new feature testing.
Robust, modular test system architectures can result in short
test development times and higher test capacities; and with
more products getting tested sooner, more products will be
sold and shipped.
High throughput testing for pass/fail results is a worthy
goal, but so much more can be accomplished. Data Science Automation
extends the test strategy to automated text, web and database
reporting, and ultimately to process improvements focused
on prevention.
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