Optimum replacement of deteriorating and inadequate equipment (original) (raw)

Abstract

Determination of the optimum equipment replacement policy and time is of great economic importance. After a brief survey of the models which have been used for decision making, the paper looks at methods for detecting and quantifying growth of failure frequency (peril rate) in repairable equipment. It examines the trend detection methods of Laplace and Mann when the peril rate varies as a power of equipment age and also applies them to some actual field failure data. An economic model is developed, based on total discounted future cost and providing for ongoing future technological growth. The cost comprises not only the conventional cost of ownership, but also the shortfall between an equipment's achieved benefit and that which would be achieved by an ideal equipment in the same demand environment. The inclusion of this shortfall, called 'incapacity cost', enables the replacement decision to be based not only on the deterioration of equipment but also on its performance inadequacy and on the availability of technological improvement in present and future challengers. The formulation of the cost model is such that for both a single-replacement finite planning horizon and an infinite horizon the total discounted future cost is readily computed for a range of alternative replacement times and the optimum replacement programme thereby determined. The sensitivity of total cost to the replacement times and the sensitivity of the optimum times to the variability of assumed input data are easily examined. The application of the model to traffic signal equipment is described. In this application the total cost is shared between the nominal owner of the equipment and the community.

Key takeaways

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  1. The text develops an economic model for optimal equipment replacement considering performance inadequacies and technological growth.
  2. It introduces the concept of 'incapacity cost' as a factor in replacement decisions, highlighting performance shortfalls.
  3. The Laplace and Mann tests are used to quantify the growth of failure frequency (peril rate) in repairable equipment.
  4. Sensitivity analysis evaluates the total discounted future cost relative to varying replacement times and input data.
  5. Application to traffic signal equipment illustrates the model's relevance to community costs and overall system performance.

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References (36)

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FAQs

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What explains the impact of peril rate on equipment replacement decisions?add

The paper demonstrates that peril rate, which varies with age, significantly influences optimal replacement times for repairable equipment. For instance, applying the Weibull process, it models how aging equipment's failure frequency increases, impacting economic considerations for replacements.

How does incapacity cost influence replacement policy in various industries?add

The study introduces incapacity cost as the shortfall in performance due to outdated equipment, driving replacement decisions across sectors. It highlights scenarios like traffic signal systems, where community costs due to malfunctions can complicate cost-benefit analyses.

Which statistical methods are effective in detecting deterioration trends in equipment?add

The research utilizes Laplace and Mann tests to effectively detect peril rate growth in aging equipment. Results indicate that the Mann test excels in identifying ongoing changes, while the Laplace test can indicate previous increases in peril rates.

What practical methodologies are recommended for optimizing replacement schedules?add

The study proposes using dynamic programming and cost models that integrate both immediate and future technological improvements to forecast optimal replacement intervals. The program INFHOR was developed to compute these schedules efficiently for varying replacement conditions.

How does technological growth factor into equipment life cycle assessments?add

The paper incorporates ongoing technological improvements, suggesting that future replacements should adapt as new, more efficient technologies emerge. This approach enhances the cost model by considering both reliability upgrades and performance capabilities in decision-making.

Last updatedOctober 11, 2025