Page 341 - Improving Machinery Reliability
P. 341

Life Cycle Cost Studies   301

                     So, where did the failure rate for the pump housing come from? Use experience or
                   other sources. One-stop shopping for failure rates is not possible!
                     Select cost data from local plant experiences or proposed cost structures for new
                   plants.

                   Step 11: Select Preferred Course of Action Using LCC. The selection of a par-
                   allel/redundant strategy using ANSI pumps is the most attractive alternative out of
                   the three proposed because it avoids process failure and thus reduces the high cost of
                   unreliability. Buy equipment that is electrical-power-efficient, yet reliable and cor-
                   rectly  sized. Ascertain  high  hydraulic efficiency  to make  substantial reductions  in
                   electrical power consumption, which is usually a hidden cost item but clearly identi-
                   fied by LCC as a vital element.
                   Aidding Uncertainty to the LCC Results

                     Each element in the above LCC computation is uncertain. Nothing fails on sched-
                   ule.  Nothing  is repaired  in exactly  the  same time  interval.  Seldom  are costs for
                   acquiring goods and services the same price each time. Furthermore, experience tells
                   us that knowledge  of  failure modes for equipment  is required to make best use of
                   reliability-centered-maintenance  (RCM) strategies.  Uncertainty  requires  the use of
                   statistical distributions in addition to the usual arithmetic.
                     Most engineers know about normal (Gaussian) statistical distributions that employ
                   a  mean value, x-bar, to describe central tendencies and a standard deviation,  G, to
                   describe scatter in the data. A better statistical distribution for explaining the life and
                   repair times for equipment are Weibull distributions with a shape factor, p (similar to
                   o), and a characteristic life, q.
                     Statistical distributions give a different value every time data is drawn for solving
                   spreadsheet  problems  because of  chance selections.  Thus  Monte Carlo simulation
                   techniques are used to join probability distributions and economic data to solve prob-
                   lems of  uncertainty  using  spreadsheet  techniques.  Monte Carlo simulation  tech-
                   niques use random  numbers to generate failure data and cost data considering  the
                   statistical distributions. Monte Carlo results are similar to real life because the results
                   have variations around a given theme.
                     Monte Carlo results are used with common spreadsheet programs such as ExcelTM
                   or LotusTM. Specialized add-in programs such as @RiskTM can add uncertainty to the
                   calculations. Instead of producing a single answer, the Monte Carlo results provide a
                   central trend while providing an idea about the expected variations that may  result
                   from many interactions. Ideas about the variations in results are obtained by repeat-
                   ing the Monte Carlo trials many times and studying the end results. With fast PCs on
                   almost every engineers desk, it is possible to conduct  10,000 iterations of a compli-
                   cated spreadsheet in only a few minutes at a very low cost.
                     A flag was raised in the Alternative #1,  Do-nothing Case, section about exponen-
                   tial failure distributions. With the exponential distribution, the chance for failure is
                   uniform for each period and this does not conform to equipment expectations where
                   wear-out failure modes may predominate with their increasing failure rates as equip-
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