In many cases making a decision involving the choice between competing design alternatives is best done by computing the life cycle cost (LCC) of each alternative. This is especially true when future costs associated with a given option are large and the required service life is long. What are the advantages and disadvantages of this approach?

The procedure for defining LCC values is based on establishing initial costs plus all the direct and indirect future costs of each alternative. This is easier said than done. First the definition of a “failure” or what constitutes lack of acceptable performance must be established for the given application. The analyst then needs to estimate when – during the extended service life – failure (or failures) of each alternative will occur and what the associated direct and indirect costs will be. The direct costs might be all the expenses of repairing or replacing the given alternative while the indirect costs might be the value of lost production or loss service to customers during the repair or replacement period(s). When there are violations of safety or environmental regulations these can produce additional indirect costs in the form of fines or negative publicity for the organization.  

The toughest part in completing a LCC calculation is defining when the failure (or failures) will occur during the required usage period. The simpler task is adjusting all the costs of each alternative to the same time basis so that they can be fairly compared. The latter is done using the time-value of money concept and appropriate discounting factors. Most undergraduate engineering students are introduced to these methods in a course entitled engineering economics. All future costs must be adjusted to the same point in time, e.g., to their present values, and then totaled for each alternative in order to make valid comparisons. Besides computing total present value costs, other financial methods that apply discounting factors can be used to make rational comparisons of options.      

Too often decision makers choose between different ways of solving a problem by comparing only the initial costs of what they assume to be equally effective alternatives without much thought. Alternatively they may generally understand the inferior long-term suitability of certain options (with low initial costs) but choose to dismiss a LCC analysis because of the extra work involved. Basing decisions on first costs is reasonable when the consequences of failure are small. However, defining LCC’s is clearly superior when a failure can result in large costs. Very often the direct costs of a failure are small compared to the much larger indirect costs. For example: frequently the cost of one unplanned emergency shutdown due to failure of a component or material with poor long-term reliability in a facility that must operate on a 24/7 basis makes the effort at completing a thorough LCC worthwhile.

As stated, the difficult part of developing an optimal LCC is estimating when a given type or quality of device or component in question will fail in a given service environment and what the total cost of that failure will be. Predicting the time of failure with a reasonable level of probability depends on the knowledge and experience of the individual(s) doing the analysis. Perhaps the most important aid in making these time-to-failure estimates is establishing and then maintaining specific historical records of what has worked in the past, what has not worked and what the detailed circumstances were in each case. Defining the costs associated with a failure may be less difficult but here the analyst must also have the most reliable data possible. For example, making a repair or a replacement because of a failure likely will require a partial or a complete stoppage of production or service to customers for some period of time. The analyst needs to know best estimates of what those time periods will be and what the associated direct and, more importantly, indirect costs will be.

In summary, completing LCC analyses requires extra efforts and results cannot be perfect because they must be based on best-available information. However, the process is justified in many situations.

 

 

      

 

 

 

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