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First Published in EOS/ESD Technology Europe
Spring 1990
How Static Impacts Your Costs Even without failure analysis, the effects of static discharge can be made visible using throughput analysis. Stephen Halperin As static awareness has increased over the years, companies
have implemented countless programs to solve ESD problems, but their
efforts are often targeted at the effects of an EOS/ESD problem rather
than at its causes. As a result, the static-control techniques employed
often are less effective than desired, and any return on the static-control
investment is reduced. Worse, the need for static control may even become
less credible. In order to help the ESD professional target causes
rather than effects and meet the need for information upon which to
base decisions, I have developed the approach outlined in this article. This approach accomplishes the following objectives: In addition, the procedure can be used to spot problems not necessarily related to EOS/ESD losses, such as shrinkage, multiple inventories and mechanical problems. Throughput Analysis Throughput analysis evaluates the flow of devices and
assemblies used in finished goods production. It analyzes operational
patterns in purchasing, inventory control, manufacturing, repair operations
and field service. The results of throughput analysis are device-utilization
data sheets that list the ESD-sensitive devices used and aid in calculation
of potential static loss. The analysis represents potential and not actual ESD
losses. However, when coupled with some evaluation, the device utilization
tables offer a bottom-line estimate of potential EOS/ESD losses in an
organization and provide insight into the problem from both the management
and operational points of view. Throughput analysis is a traditional evaluation technique.
All that's really required is a spreadsheet (either on paper or in software)
and information (with the permission needed to gather it). Once the
information is in hand , the analysis is simple. An accurately conducted throughput analysis can indicate
which components may be failing due to static, where in the operation
most losses are occurring, the total cost of potential static losses
and spot areas where attention will yield the most short-term ROI. Most important to static-control professionals, throughput
analysis provides a foundation for development of overall static-control
programs. Without an analysis of this type one cannot seek the
causes of an ESD problem, estimate losses, set guidelines for investment
to solve the problem or project ROI from corrective action. On the other
hand, if the analysis is comprehensive and objective, management should
recognize the soundness of the data and its interpretation, and if a
significant static problem is shown to exist, throughput analysis will
furnish the information required for management evaluation and will
justify decisive action. Throughput analysis consists of the following steps: Throughput analysis is best explained through example. In this case, we will track the implications of an ESD problem in a small electronics firm. Assume the company manufactures only one type of finished product. Each unit produced is composed of several devices and subassemblies, some of which are ESD-sensitive. The first step, therefore, is to identify the number of finished goods produced each year and those ESD-sensitive devices and subassemblies used in the production process during that period. Step one: Device Sensitivity Finishes-goods production volume is historical information
available from plant records. Try to obtain both the original plan for
finished-goods volume as well as the actual production figures, and
compare the two. If less product was produced than planned, seek the
fundamental reasons for this lower production volume in interviews with
production management. Any reasons given for lower volume that may be related
to rework, restricted parts availability, excessive in-process redesign
and field problems should be noted as potentially static-related and
marked down for future study. We will assume that 1,000 finished-goods
items are produced by our hypothetical facility. Device sensitivity to ESD is a prime yardstick for
static control. In practice, a process designed for the survival of
the most sensitive parts, by definition will pass less sensitive ones.
Thus, in throughput analysis, device sensitivity reflects that allotment
of devices and subassemblies which may be considered static-sensitive
and therefore subject to lass or damage. There are three usual sources for ESD-sensitivity data:
1) Actual sensitivity testing of devices and assemblies used within
the facility. This is time-consuming and expensive, but appropriate
if other sources are not available; 2) vendor test information and certification
of ESD sensitivity testing; 3) The generic device sensitivity listings
available from the Reliability Analysis Center (RAC), Rome, NY. As most companies' inventory and usage figures are
already in computer data bases, it's often expedient to enter RAC's
generic sensitivity data into the system as well. Current or projected
inventory can then be sorted relative to this list. Depending on the
timeliness of the RAC listing, and the use of custom devices and assemblies,
it can be prudent to update the ESD information with either vendor supplied
or in-house test data. Returning to the example at hand, we will assume that 10 of our devices are ESD-sensitive. The relevant information is summarized in Table 1.
Step Two: Device Utilization By reviewing inventory control and purchasing records,
one can readily determine the normal usage of ESD-sensitive items. For
an accurate analysis, one can document the following information for
ESD-sensitive devices: In our illustration, assume that corporate inventory
control provides average inventory levels of the ESD-sensitive parts
in one location and designates the requisitioning departments. Corporate
purchasing should be able to provide the order volume and unit cost
of the ESD-sensitive parts purchased and confirm the requisitioning
departments as well. Of course, every organization is different, and some
may not have centralized information available for performing this initial
analysis. However, the basic idea adapts to various organizational structures.
Where each department, or group of departments, performs its own analysis,
results can be combined or compared to yield the necessary information. Suppose that the inventory-control and purchasing departments
show that these units are purchased in the volumes and at the prices
shown in Table 2, and that the requisitioning departments are manufacturing,
rework and field service. Reviewing the information obtained thus far, we see
that device-purchase volume doesn't match production requirements, and
that the ESD-sensitive devices used in the finished product have an
added cost impact on the operation.
Referring to the "Totals" line of Table 2,
39,000 devices were required to produce the finished goods during the
analysis period, and 3,900 devices were usually maintained in inventory.
However, a total of 57,900 devices were purchased for the period. The
result is a negative "deviation" not accounted for in terms
of finished-goods volume- 15,000 extra devices, valued at $48,240. Table 2 also shows that manufacturing requisitioned
10% more items than should have been needed to meet production needs,
rework used 70% of the unit deviation and field service accounted for
the remaining 20%. Of course, deviations can be caused by secondary inventories,
current orders and mechanical or handling faults, but these are factors
that can be clarified as part of the data-gathering process. However,
Table 2 does reflect a significant potential loss. In any event, more
data should be requested from each department, showing the reasons for
their high use of these items. Step Three: The Impact of Burden When estimating the impact of static damage, one cannot
assume that materials represent the sole cost of ESD losses. In fact,
in most cases, labor, plant burden and field-repair costs far exceed
the value of static-damaged devices and assemblies (Ref 1). With the assistance of the plant's accounting department,
a labor and "burden" factor takes into account the actual
labor required to replace an item, the cost of the facility, lights,
power and the value of funds tied up in rework inventory, among other
variables. This can be either an estimated average cost applied to all
items or a calculated actual cost based on a specific analysis of each
item. The average cost is the easiest to estimate, while
the actual cost is time-consuming and requires secondary analysis by
experienced personnel. To get an initial indication of total potential
static impact, it's easier, faster and cheaper to use an estimated average
cost per unit during the first analysis. More specific calculations
can always be made later if warranted. Once the average burden per unit is determined, two
additional columns should be added to the deviation section of Table
2. The first column is the estimated burden associated with each item.
This is simply a calculation multiplying the total number of deviations
per item by the average burden per unit.
While the value of the deviation units is a significant
amount (&48,240), the estimated burden associated with these devices
is $217,500- more than four times the material costs. The total costs
indicate that this facility may be losing as much as $265,000 to static. Of course, there are other possible explanations for
these missing units, which may not be static related. Some devices will
normally be lost due to mechanical, handling or soldering problems.
However, the telling point is not just that deviations exist, but that
all items unaccounted for are ESD-sensitive devices. The burden cost of $14.50 per unit used in the example is an assumed in-plant cost. Field-service burden costs could range from a few hundred dollars for commercial products to thousands of dollars per unit for repairs to complex communications, data-processing or military systems. References 1. Gleason, "Ruling Out Static," Microservice Management, September 1986.
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