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The Real “Total Cost of Ownership” of Your Test Equipment

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Abstract

Cost of ownership is always a hot topic when making a program decision for any new, upgrade or sustainment option. The criteria for developing a Total Cost of Ownership (TCO) model quickly turns into debates with many facets and lots of emotion.

When it comes to the cost of acquiring and operating test equipment, the answer is not any easier to determine. However, if looked at from a Product Life Cycle (PLC) cost or a Performance Based Logistic (PBL) view point, a more accurate cost model can be developed.

By understanding and using the attributes of direct and indirect costs for acquiring, operating, maintaining, migrating and disposing of these assets, an accurate model of the total cost of ownership can be obtained. This paper will lay out the PLC/PBL costs of test equipment and walk through a TCO model that can be used for making trade off decisions between different program options.

Introduction

For many years the acquisition of test and measurement equipment was viewed as a necessarily evil to ensure that electronic products manufactured by companies had zero defects. While there are many reasons for this during the boom of electronics in the 1970’s and 1980’s, possibly the biggest contributor was the inconsistency in which electronic designs were performed.

In many cases designers used home grown spreadsheets or had tables they developed to calculate design margins. As designs became more complicated in the 1990’s, it forced most designers into using professionallydeveloped simulation tools. Quickly this proved that a wellsimulated design minimized the performance gap between theoretical design and the actual product.

Simulation, combined with contract manufacturers mastering high quality manufacturing methods, led to products with 95%+ yields. Still, the questions continue. Why do we pay so much to test when the level quality is so high? Or a better question: What is the real cost of test?

During the 1990’s when we saw outsourced products and more power, control and information built into electronics, consumers were expecting more for less, no deviation from quality and more product variety. The pressure was on for manufacturers to cut costs in a global economy where everyone had access to the same labor pool, parts suppliers and design tools.

The result was a new procurement focus, namely Total Cost of Ownership (TCO). TCO first gained popularity with semiconductor equipment users when they wanted to recognize the procurement decision encompassed much more than the initial acquisition (purchase) cost. A semiconductor line could easily cost several tens of millions of dollars to acquire.

Further analysis showed that costs associated with owning and operating the asset over its entire useful life could considerably exceed the acquisition costs.

This paper introduces a TCO model for electronic test and measurement equipment and shows how operating costs can be critical drivers in reducing total cost of ownership beyond simply lowering acquisition (capital) costs.

The TCO concept will help equipment owners make informed decisions on the purchase decision, and it will show how TCO variables can drastically change the overall cost of ownership for test and measurement equipment throughout the product’s life cycle.

Cost Of Test

Many papers have been written and presented on the topic of Cost of Test (CoT). While there are several models that focus on CoT, almost all of these methods have the same flaw, namely they calculate CoT at a single point in time.

That is, although they may take the acquisition costs and depreciate them over a period of years, these models typically look at other expenses (such as preventive and corrective maintenance actions) from an “average” cost standpoint.

From studies in Performance Based Logistics (PBL), we have learned the cost of a product is not linear and we cannot measure it at only one point in time. An example of this would be looking at depreciation and repair costs.

Depending upon the accounting method used, depreciation can be spread out over three years or five years, and with flat or accelerated schedules for most test and measurement equipment. No matter the method employed, in five years the product has been fully depreciated.

During that time the chance of equipment failure is relatively low, however after five years the chance of a failure can be considerably higher and may continue to grow as the equipment ages.

Thus, using a CoT tool can produce very different results depending upon what point in time you decide to model the operation. In Year 1 the primary expense is the acquisition cost, yet in Year 10 maintenance and downtime factors would results in higher expenses.

So what numbers do you select? The most accurate number would be represented by the average cost for the equipment over the expected useful life. This would account for the various costs as the equipment ages.

Even using the average cost in a CoT model is misleading when understanding the true TCO. Consider two manufacturing lines using the same type of equipment. Let’s say both CoT models arrive at the same cost results with the only difference being that one line has bottlenecked throughput and the other line does not.

With CoT modeling, this is usually not a factor that affects the calculated results. In contrast, such bottlenecking would be reflected in the TCO model via input parameters such as reliability and repair turnaround time. In the bottlenecked line, any downtime would affect production and thus revenue.

Consider another scenario where we must outfit a new production line by choosing between two test equipment manufacturers. One test asset could have a higher purchase price and a lower failure rate and the other test asset might have a lower purchase price and a higher failure rate.

So while the CoT may favor the asset with lower purchase price, when TCO is considered in the purchase equation the decision may be to spend more money upfront on a more reliable asset. While the differences between CoT and TCO modeling are many, there are other scenarios where the two methods are complimentary.

The fact is, to build an accurate CoT model over a production life cycle or to compare two different pieces of test and measurement equipment to get an accurate PBL cost, TCO becomes a foundation for deep understanding. Let’s take a look at factors that go into the TCO methodology.

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