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ADC : Introduction to ADC
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Automatic
Data Collection Technology (ADC)
We live in an information age characterized by rapid change. Today's world
moves faster than earlier eras, and the pace continues to speed up. Continuous
developments with computer technology in manufacturing, distribution,
communications, transportation, healthcare and other sectors have played, and
continue to play, a large part in accelerating change.
For any business in this fast changing world, the importance of collecting and
processing information on a timely basis is essential. Managers must act
quickly to be effective to initiate changes in manufacturing or distribution,
or to otherwise respond to new customer requirements. Doing so requires
reliable information in real time or as close to it as possible.
As computers have proliferated and data processing has become more powerful,
the data collection function on which processing depends has not kept pace.
Acquiring the fastest, most effective computer hardware and software available
makes little sense if the system cannot acquire data accurately and
expeditiously. A data collection gap, the difference between data processing
and data collection, has been the result. Narrowing this data collection gap
promises to improve the quality of information that serves as the basis for
management decisions affecting production, productivity, and profitability.
Automation of the data collection function offers the only practical way to
bring the pace of data collection more closely in line with data processing.
Many manual methods, such as keyboard entry, are considered too slow, costly
and error-prone to satisfy modern criteria. That is why automated data
collection technology has expanded rapidly worldwide.
The automated data collection process has three phases:
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Automatic identification is the essential first step,
accomplished by attaching a bar code or RF Tag/ Label to a part, document,
package, personal identification badge or some other item to be tracked.
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The data collection phase occurs when a part moves in or out of
inventory, a work piece comes in or out of a given stage in the manufacturing
process, and/or an employee checks in or out of work. These actions are
instantly and accurately captured by scanning the bar code label. Scanners can
read information far faster than humans can write or type, and they are far
more accurate. Compared to the average human-transcription error rate of one
per 300 characters, the automated error rate is in the range of one per 3
million.
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Compiling and computer system input occurs when scanned data is
compiled into a central point and manipulated into a form appropriate to the
data stream of a host computer. The upshot is accurate data automatically
captured as each event occurs, thus permitting management decisions based on
solid, current information.
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Automated data collection is seen as the key to improving control and providing
management with timelier, more accurate, and therefore more valuable
information. Increased productivity and reduced costs are the key benefits of
automated data collection. The return on investment for automated data
collection is typically one year, and often substantially less.
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© 2005 Efficient Data Processing Pvt. Ltd. |
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