Maintenance Strategies and Policy Selection

Introduction

Maintenance is the set of technical, administrative and managerial actions used to retain or restore an asset so that it can perform its required function. A maintenance strategy is not simply a list of tasks such as lubrication, inspection or replacement. It is a deliberate policy that specifies what is done, when it is done, under what conditions it is done, and why the action is justified.

The central engineering problem is policy selection. A plant may contain equipment that is cheap and non-critical, equipment whose failure threatens personnel, and equipment whose failure interrupts an entire production line. Applying the same maintenance policy to all assets is therefore inefficient and potentially unsafe. Effective selection considers failure behaviour, consequences of failure, detectability, cost, risk, operating context, maintainability and available technology.

This chapter compares corrective, preventive, predictive, condition-based, opportunistic and shutdown maintenance. It also develops a practical decision framework for selecting and governing maintenance policies.

Learning Objectives

By the end of this chapter, the reader should be able to:

1. Explain the purpose and logic of major maintenance strategies.
2. Distinguish preventive, predictive and condition-based maintenance.
3. Relate maintenance policy to failure behaviour and asset criticality.
4. Compare policies using cost, risk, safety, production and resource criteria.
5. Apply reliability and expected-cost concepts to maintenance decisions.
6. Develop a maintenance policy for an industrial asset or system.
7. Recognise the limitations, governance requirements and human factors associated with maintenance strategy.

1. Maintenance Policy as an Engineering Decision

A maintenance policy connects an asset's required function with an appropriate intervention. The policy should answer five questions:

• What functional performance is required?
• What failures are credible?
• What are the consequences of each failure?
• Which intervention can manage the failure most effectively?
• How will performance and policy effectiveness be verified?

Maintenance should therefore be aligned with operations, safety, quality, energy use, environmental obligations and business objectives. A technically sophisticated inspection is not necessarily valuable if it detects a failure that has no important consequence or if the organization cannot act on the information.

Important terminology

A failure is the termination of an item's ability to perform a required function. A functional failure occurs when the asset cannot meet a specified performance standard; a potential failure is a detectable condition indicating that functional failure is developing. The interval between detectable potential failure and functional failure is commonly called the P–F interval.

Reliability is the probability that an item performs a required function under stated conditions for a stated time. Maintainability concerns the ease and speed with which an item can be restored. Availability reflects the proportion of time an asset is capable of performing its function, considering failures and restoration. Criticality expresses the relative importance of an asset or failure mode, usually from consequences and likelihood.

A maintenance task is a specific intervention, such as vibration measurement, filter replacement or functional testing. A maintenance interval is the time or usage period between planned tasks. A maintenance policy is the higher-level rule that determines the type and timing of tasks.

2. Principal Maintenance Strategies

2.1 Corrective maintenance

Corrective maintenance restores an asset after a failure has occurred. It may be planned or unplanned. A planned run-to-failure policy is intentionally selected when the consequences are acceptable and repair or replacement is economical. Unplanned corrective maintenance is the response to an unexpected failure.

Corrective maintenance is appropriate when:

• failure has low safety, environmental and production consequences;
• the asset is inexpensive or readily replaceable;
• no effective preventive task exists;
• failure is random and difficult to predict;
• redundancy protects the required function; or
• the cost of routine intervention exceeds the expected benefit.

Advantages include simple administration, low routine inspection cost and full use of component life. Disadvantages include possible collateral damage, emergency labour, production loss, poor spare-parts availability and safety exposure. Run-to-failure must never be confused with neglect: it is a controlled policy requiring defined spares, access, response arrangements and acceptance of the consequences.

2.2 Preventive maintenance

Preventive maintenance is performed at predetermined intervals or according to prescribed usage, regardless of the immediate condition of the asset. Examples include changing lubricant every 2,000 operating hours, replacing a belt annually and calibrating an instrument every six months.

Preventive maintenance is useful when:

• age or usage strongly affects failure probability;
• wear-out behaviour is established;
• a replacement or overhaul restores known performance;
• failure consequences justify intervention before failure; or
• statutory rules specify an interval.

Its central weakness is that calendar or usage time is only an indirect measure of condition. Replacing a component too early wastes useful life; replacing it too late may not prevent failure. Preventive work can also introduce infant mortality through installation errors, contamination or incorrect settings.

The probability that an item survives to time t is its reliability function:

Here, T is the random failure time, F(t) is the cumulative distribution function of failure time, and R(t) is dimensionless. The expression applies to a defined population of items operating under stated conditions. It does not by itself prove that replacement at time t is economically optimal.

For a constant failure rate λ, commonly used as an idealised model for the useful-life region:

where λ has units of failures per unit time and t has units of time. This model assumes statistically independent failures and a constant hazard rate. It is not appropriate for every asset, particularly where wear-out or early-life defects dominate.

2.3 Predictive maintenance

Predictive maintenance uses measurements, historical data and analytical models to estimate developing degradation or the future need for intervention. It may use vibration spectra, oil debris, thermography, motor-current signatures, ultrasound, performance trends or process data.

Prediction is broader than measurement. A predictive system attempts to estimate a future state, failure probability or remaining useful life. For example, a trend in bearing vibration may be combined with a degradation model to estimate when a vibration limit will be reached.

Benefits include better planning, reduced unnecessary replacement and improved understanding of asset behaviour. Limitations include sensor cost, data quality problems, false alarms, missed detections, model uncertainty and the need for competent interpretation. A predictive system has little value if the organization cannot schedule and execute the recommended intervention.

2.4 Condition-based maintenance

Condition-based maintenance (CBM) initiates maintenance when evidence shows that equipment condition has crossed a defined decision threshold or is deteriorating toward an unacceptable state. It may use continuous sensors, periodic inspection or operator observations.

CBM is therefore a decision policy based on actual condition. Predictive analytics may support CBM, but they are not identical. A thermometer that triggers inspection when temperature exceeds a limit is condition-based, even if no future failure time is calculated.

A CBM program requires:

1. a measurable condition indicator;
2. a meaningful relationship between the indicator and functional failure;
3. an inspection interval shorter than the available P–F interval;
4. a threshold linked to an engineering decision; and
5. a planned response when the threshold is reached.

The inspection interval must provide sufficient opportunity for action. If the P–F interval is 20 days, a monthly inspection cannot reliably protect the function, even if the measurement itself is accurate. In practice, allowance is also required for measurement uncertainty, access delays, planning time and repair duration.

2.5 Opportunistic maintenance

Opportunistic maintenance is performed when access or a related outage already exists. Examples include replacing a coupling guard while a motor is isolated, changing an adjacent seal during a planned pump overhaul, or inspecting hidden pipework while scaffolding is installed.

The policy can reduce setup, isolation and access costs. However, it can also expand the work scope, consume outage time and introduce unnecessary disturbance. Opportunistic work should be governed by a clear screening rule. Tasks should be added only when their risk reduction or life-cycle benefit exceeds the incremental cost and schedule risk.

2.6 Shutdown, turnaround and outage maintenance

Shutdown maintenance is concentrated work performed during a planned cessation of operation. It is common in refineries, power stations, chemical plants, steelworks and large process facilities where some equipment cannot be safely accessed during production.

Shutdown work may include statutory inspection, major overhauls, refractory replacement, cleaning, inspection of vessels and modifications. Its success depends on scope definition, work packaging, materials, contractors, permits, isolation plans, schedule control and commissioning quality.

Shutdown maintenance is not simply preventive maintenance performed at a larger scale. It has distinctive constraints: a fixed outage window, high coordination requirements, large temporary workforces and severe consequences of late completion. Poorly controlled scope growth can turn a technically successful outage into a business failure.

3. Failure Behaviour and Strategy Selection

Maintenance policy must reflect how failure probability changes with age and condition. The hazard rate, or instantaneous failure rate, is defined conceptually as the likelihood of failure at a given time conditional on survival to that time. For a continuous failure-time distribution:

where h(t) is the hazard rate, f(t) is the failure-time probability density and R(t) is reliability. The units of h(t) are inverse time. This relationship assumes that a suitable continuous probability model exists.

Three broad patterns are important:

• Decreasing hazard: failures are more common early in life, often because of manufacturing defects, installation errors or commissioning problems. Corrective learning, quality assurance and burn-in may be more effective than frequent replacement.
• Approximately constant hazard: failures are broadly random in the operating period. Age-based replacement may provide little benefit unless it restores another required condition. Condition monitoring, redundancy or corrective maintenance may be preferable.
• Increasing hazard: wear, fatigue, corrosion, erosion or insulation ageing causes failure probability to increase with age. Preventive replacement, overhaul or condition-based monitoring may be justified.

Many real assets exhibit mixtures of these behaviours, and different failure modes in the same asset may follow different patterns. A pump may have random seal failures, wear-related bearing failures and installation-related alignment failures. A single policy for the whole pump can therefore be inadequate.

The familiar “bathtub curve” is a useful teaching model, not a universal law. Modern electronic systems often have substantial random-failure regions, while many mechanical components are affected by load, lubrication, contamination and operating practice more than by age alone.

4. Criticality, Risk and Consequences

A failure-mode-based analysis begins with the required function and asks what happens when that function is lost. Criticality should consider at least:

• personnel safety and process safety;
• environmental release;
• production and customer impact;
• product quality;
• repair cost and collateral damage;
• energy performance;
• legal or regulatory compliance;
• detectability and warning time; and
• availability of redundancy or alternative capacity.

A simple risk representation is:

This is a screening relationship rather than a complete risk model. Probability and severity must be defined consistently, and risks involving catastrophic consequences should not be treated as interchangeable with frequent minor failures merely because their numerical products are similar. Where uncertainty is material, conservative analysis, layers of protection and specialist review are required.

Failure Modes and Effects Analysis (FMEA) identifies functions, functional failures, failure modes, effects, causes, existing controls and recommended actions. Reliability-Centered Maintenance (RCM) extends this logic by selecting tasks according to consequences, failure characteristics, technical feasibility and cost-effectiveness. RCM commonly distinguishes safety/environmental consequences, operational consequences, non-operational consequences and hidden failures in protective systems.

A high-criticality asset does not automatically require continuous monitoring. The selected task must be technically capable of managing the failure mode. Conversely, a low-cost item can require rigorous preventive control if its failure defeats a safety function.

5. Economic Selection of Maintenance Policies

Maintenance decisions should use life-cycle cost rather than maintenance cost alone. Relevant costs include labour, materials, inspection technology, production loss, energy use, quality loss, emergency transport, collateral damage, environmental response and the cost of risk reduction.

For a simple comparison of policies over a common period, expected cost can be represented as:

where E[C] is expected cost, C_PM is planned-maintenance cost, C_CM is corrective repair cost conditional on failure, C_loss is the consequence cost conditional on failure, and P(Failure) is the probability of failure during the analysis period. All costs must refer to the same period and currency basis. This is a simplified model: discounting, multiple failure modes, downtime duration and dependence may need to be included in a real analysis.

For a component with constant failure rate λ over a short defined interval t, the probability of at least one failure is:

This follows the exponential reliability model and assumes a constant hazard rate. It should not be used automatically for wear-out equipment.

Worked example: corrective versus preventive action

An auxiliary fan has a constant estimated failure rate of 0.0008 failures per operating hour. Over a 1,000-hour planning period, an unplanned failure would cost £1,200 in repair and production loss. A scheduled replacement costs £260 and is assumed to prevent the failure during that period. Ignoring discounting and residual life, compare run-to-failure with replacement at the beginning of the period.

Failure probability under the constant-rate model is:

P(F) = 1 − e^(−0.0008 × 1000) = 1 − e^(−0.8) ≈ 0.551

Expected corrective cost is:

E[C_CM] = 0.551 × £1200 ≈ £661

The preventive cost is £260. Under the stated assumptions, preventive replacement has the lower expected direct cost by approximately £401 per 1,000 operating hours. However, this conclusion changes if replacement does not eliminate the relevant failure mode, if installation introduces defects, or if the estimated failure rate is not representative.

The example also illustrates why a policy cannot be selected from repair cost alone. If the fan is redundant and production loss is negligible, corrective maintenance may be preferable. If the fan supports a hazardous ventilation system, safety requirements may dominate the economic comparison.

6. A Practical Policy-Selection Framework

A robust selection process can be implemented as follows.

Step 1: Define the required function

Specify capacity, accuracy, speed, pressure, temperature, quality and other performance requirements. Avoid vague statements such as “keep the pump working.” A better statement is “deliver 45 m³/h at 30 m head with no unacceptable leakage.”

Step 2: Identify functional failures and failure modes

Use operating history, manufacturer information, engineering judgement, FMEA, process knowledge and inspection records. Include human, environmental, control-system and utility-related causes.

Step 3: Assess consequences and criticality

Rank safety, environmental, operational, quality, regulatory and financial consequences. Identify hidden failures in standby and protective equipment.

Step 4: Study failure behaviour

Determine whether failure is age-related, condition-related, random, installation-related or influenced by operating context. Do not assume that an annual replacement is effective merely because the component is old.

Step 5: Test candidate tasks

For each failure mode, ask:

• Can a condition indicator detect degradation early enough?
• Is a scheduled restoration or discard task technically effective?
• Is failure acceptable under controlled conditions?
• Can the task be combined with another outage or access opportunity?
• Is a shutdown required for safe execution?

Step 6: Compare risk and life-cycle cost

Include direct task cost, downtime, spares, labour, inspection error, implementation cost and consequence reduction. Evaluate uncertainty rather than presenting a single number as exact.

Step 7: Define execution requirements

Specify task instructions, competence, tools, permits, isolation, acceptance criteria, escalation limits, spare parts and data-recording requirements.

Step 8: Review performance

Use indicators such as functional availability, planned versus unplanned work, schedule compliance, repeat failures, inspection findings, mean time to restore and maintenance-induced failures. Metrics should support decisions rather than encourage superficial activity counts.

A useful policy matrix is shown below.

7. Integrated Maintenance Programs

Industrial systems normally require a combination of policies. A compressor may have condition-based vibration monitoring for bearings, preventive oil analysis, corrective replacement of non-critical guards, opportunistic inspection during a planned outage and a shutdown overhaul of pressure-containing components.

The combination should be coherent. Preventive tasks must not conflict with condition monitoring; for example, a fixed replacement interval may destroy the opportunity to learn from a reliable degradation trend. Conversely, condition monitoring should not be used to postpone a legally required inspection. Job plans, bills of materials, failure codes and inspection results should be connected in the computerized maintenance management system (CMMS).

Maintenance intervals should be reviewed after significant changes in load, speed, environment, lubrication, control logic, duty cycle or production schedule. A policy that was appropriate for a lightly loaded machine may be unsafe after capacity expansion.

8. Technology, Data and Artificial Intelligence

Sensors, wireless networks, edge computing and cloud platforms have expanded CBM and predictive maintenance. Digital tools can automate data collection, identify abnormal patterns and rank assets for attention. Machine-learning models may estimate anomaly scores or remaining useful life.

Technology does not remove engineering responsibility. A model trained on normal operating data may fail after a process change. Imbalanced data may contain many normal observations but few true failures. Sensor drift, missing data, changing operating regimes and false alarms can undermine trust. Alarm thresholds should be validated against physical behaviour and operational consequences.

AI-supported decisions should have traceability, human oversight and defined escalation. The organization should know which data were used, what uncertainty exists, who approves intervention and how the model is monitored. Cybersecurity is also a maintenance concern because compromised sensors or control systems can create unsafe decisions.

9. Case Study: Cooling-Water Pump in a Process Plant

Background

The following is an illustrative case. A process plant uses two 100% cooling-water pumps, one normally operating and one on standby. Loss of cooling can force a controlled production reduction, while simultaneous loss of both pumps can create a significant process-safety event. Historical records show seal leakage, bearing deterioration and occasional motor trips.

Problem

The maintenance department replaces pump bearings every 12 months. The plant has experienced premature bearing replacements, two unexpected bearing failures and one failure caused by incorrect installation. Managers want to reduce cost without increasing risk.

Analysis

The pump has several distinct failure modes. Bearing degradation is often detectable by vibration and temperature, whereas seal leakage may be visible through inspection and drain-flow observation. Motor trips may be caused by electrical faults, overload, cooling restriction or control-system problems. The standby pump has a hidden failure risk: it may fail to start when demanded even though it appears satisfactory while idle.

The annual bearing replacement policy is not well supported by the data. Some bearings remain in good condition at replacement, and the observed failures do not show a clear age threshold. The failure consequences are significant, but redundancy reduces the immediate consequence of a single pump failure.

Approach and solution

The revised policy is:

1. Replace fixed annual bearing replacement with monthly vibration and temperature measurements, supplemented by continuous monitoring on the duty pump.
2. Establish alert and action limits based on baseline condition, manufacturer guidance and engineering review.
3. Inspect seal leakage during operator rounds and trend leakage rate.
4. Perform a weekly automatic start test of the standby pump, with periodic loaded testing where safe.
5. Retain preventive oil and coupling checks because contamination and misalignment are credible causes.
6. Conduct opportunistic inspection of accessible components during planned process outages.
7. Require a shutdown overhaul only when inspection findings, statutory requirements or risk review justify it.
8. Maintain a critical spare bearing and seal kit, but do not replace components solely because the calendar interval has elapsed.

Outcome

In the illustrative scenario, the plant reduces unnecessary bearing replacements and gains earlier warning of deterioration. The weekly standby test reveals hidden failures that would not have been detected by routine visual inspection. The revised plan does not eliminate preventive maintenance; it assigns different policies to different failure modes.

Learning points

• Asset-level policies should be decomposed by failure mode.
• Redundancy changes consequences but does not eliminate the need for testing.
• Condition monitoring is effective only when measurements lead to timely action.
• Fixed intervals should be supported by failure behaviour or obligations.
• Maintenance-induced failures must be included in policy evaluation.

10. Challenges, Governance and Professional Practice

Uncertainty and data quality

Failure records may be incomplete, inconsistent or biased toward severe events. “No failure recorded” does not necessarily mean “no failure occurred.” Engineers should document assumptions, data sources, confidence levels and review dates.

Human factors

Many failures arise from incorrect assembly, inadequate isolation, contamination, poor communication or work pressure. Procedures should be usable, not merely comprehensive. Competence assurance, independent verification for critical tasks and learning from near misses are essential.

Safety and legal obligations

Safety-critical equipment may require proof testing, statutory examination, permit-to-work controls and documented competence. A cost-saving policy is unacceptable if it violates legislation, a safety case, a standard or a manufacturer’s critical limitation. Maintenance decisions should be reviewed by appropriate safety and operations personnel.

Environmental and ethical responsibility

Leak prevention, energy efficiency, waste reduction and responsible disposal of oils, batteries and components are part of maintenance performance. Engineers have a duty to communicate material risks honestly and must not suppress adverse inspection findings to meet production targets.

Continuous improvement

Policies should be revised when evidence changes. A review may be triggered by repeated failures, altered duty, new monitoring capability, major modifications, a safety event or a change in consequence. The objective is not to maximize maintenance work; it is to achieve required asset performance with acceptable risk and life-cycle cost.

Chapter Summary

Maintenance strategy is a risk- and evidence-based decision about how an asset's functions will be preserved or restored. Corrective maintenance is suitable when consequences are acceptable and planned intervention has little value. Preventive maintenance uses predetermined time or usage intervals and is most defensible where age-related deterioration or regulatory requirements exist. Predictive maintenance estimates future condition or failure using data and models, while condition-based maintenance triggers action from measured or observed condition. Opportunistic maintenance exploits existing access or outages, and shutdown maintenance coordinates major work during planned cessation of operation.

Policy selection should be based on failure modes rather than equipment labels alone. Reliability, hazard behaviour, P–F intervals, criticality, redundancy, cost, risk, detectability and operational context must be considered together. Simple expected-cost calculations can support decisions but cannot replace engineering judgement, safety review or life-cycle analysis. Integrated programs commonly combine several strategies, and digital technologies are valuable only when data quality, response capability, human oversight and cybersecurity are controlled. Effective maintenance is therefore not the maximum amount of maintenance; it is the justified work required to manage failure consequences and sustain required function.

Key Terms

Corrective maintenance: Maintenance performed to restore function after a failure or defect.

Preventive maintenance: Maintenance performed at predetermined time or usage intervals.

Predictive maintenance: Use of measurements and analysis to estimate future condition or failure.

Condition-based maintenance: Maintenance initiated by evidence of actual or deteriorating condition.

Opportunistic maintenance: Work performed when access or a related outage is already available.

Shutdown maintenance: Planned maintenance conducted during a controlled cessation of operation.

Reliability: Probability of performing a required function for a stated time under stated conditions.

Maintainability: Probability or capability of restoring an item within a specified time under stated conditions.

Availability: Ability of an item to be operational when required.

Failure mode: The specific manner in which an item fails.

Functional failure: Inability to perform a required function to the specified standard.

Potential failure: A detectable condition indicating developing functional failure.

P–F interval: Time between detection of potential failure and functional failure.

Criticality: Relative importance of an asset or failure mode based on consequences and likelihood.

FMEA: A structured analysis of failure modes, effects, causes and controls.

RCM: Reliability-Centered Maintenance, a process for selecting technically appropriate maintenance tasks.

Hazard rate: Conditional instantaneous rate of failure at a given time.

Run-to-failure: A deliberate corrective policy allowing an item to operate until failure under controlled conditions.

Life-cycle cost: Total cost of acquisition, operation, maintenance, risk and disposal over an asset’s life.

Review Questions

Short Answer Questions

1. Define corrective, preventive and condition-based maintenance.
2. What is the P–F interval, and why does it influence inspection frequency?
3. State two situations in which controlled run-to-failure may be appropriate.
4. Why can preventive replacement introduce maintenance-induced failures?
5. Identify four factors that should be considered when assessing asset criticality.

Long Answer Questions

1. Compare corrective, preventive, predictive, condition-based, opportunistic and shutdown maintenance in terms of logic, benefits and limitations.
2. Explain how failure behaviour and hazard rate influence maintenance policy selection.
3. Describe a practical FMEA- or RCM-based process for selecting maintenance tasks.
4. Discuss why a maintenance program should combine several policies rather than apply one strategy to an entire asset.
5. Evaluate the benefits and governance risks of using sensors, predictive analytics and artificial intelligence in maintenance.

Analytical / Application Questions

1. A motor has a failure probability of 0.30 during a planned period. Corrective repair and production loss would cost £2,000, while preventive replacement costs £450. Using the simplified expected-cost approach, compare the two policies and identify what additional information could change the decision.
2. A standby fire pump passes visual inspections but fails to start during an emergency test. Identify the failure type, explain why it is hidden, and propose an appropriate maintenance policy.
3. A bearing shows a P–F interval of approximately 18 days. Develop a condition-monitoring and response plan that accounts for inspection frequency, diagnosis, spare parts, planning time and safe intervention.

Multiple Choice Questions with Answers

Question 1

Which maintenance policy is deliberately selected when an item is allowed to operate until failure because the consequences are acceptable?

A. Controlled corrective maintenance

B. Mandatory shutdown maintenance

C. Condition-based maintenance

D. Age-based preventive maintenance

Correct Answer: A. Controlled corrective maintenance

Question 2

Which statement best distinguishes predictive maintenance from condition-based maintenance?

A. Predictive maintenance always requires continuous sensors

B. Predictive maintenance attempts to estimate future condition or failure, whereas condition-based maintenance triggers action from observed condition

C. Condition-based maintenance is performed only during shutdowns

D. Predictive maintenance replaces all preventive maintenance

Correct Answer: B. Predictive maintenance attempts to estimate future condition or failure, whereas condition-based maintenance triggers action from observed condition

Question 3

If the failure rate is constant at λ, which expression gives reliability at time t?

A. R(t) = λt

B. R(t) = 1 − λt

C. R(t) = e^(−λt)

D. R(t) = e^(λt)

Correct Answer: C. R(t) = e^(−λt)

Question 4

An inspection interval is longer than the P–F interval. What is the principal concern?

A. The inspection will always be too expensive

B. Degradation may reach functional failure before it is detected

C. The asset will become more reliable

D. Preventive replacement will become mandatory

Correct Answer: B. Degradation may reach functional failure before it is detected

Question 5

Which failure behaviour most strongly supports age-based replacement or overhaul?

A. Increasing hazard associated with wear-out

B. Constant random hazard with no detectable degradation

C. Decreasing hazard caused by early-life defects

D. A failure mode eliminated by redundancy

Correct Answer: A. Increasing hazard associated with wear-out

Question 6

What is the main purpose of opportunistic maintenance?

A. To perform every possible task during every outage

B. To exploit existing access or isolation while controlling incremental cost and scope

C. To replace condition monitoring with calendar replacement

D. To eliminate the need for shutdown planning

Correct Answer: B. To exploit existing access or isolation while controlling incremental cost and scope

Question 7

A component has a constant failure rate of 0.001 per hour. What is its approximate failure probability over 500 hours under the exponential model?

A. 0.001

B. 0.100

C. 0.393

D. 0.500

Correct Answer: C. 0.393

Question 8

Which item is especially important for a hidden failure in a standby protective system?

A. Periodic functional testing

B. Cosmetic cleaning only

C. Replacing it after every operating hour

D. Ignoring it until a demand occurs

Correct Answer: A. Periodic functional testing

Question 9

Why may replacing a component at a fixed interval be ineffective for a random failure mode?

A. Random failures necessarily occur only after replacement

B. Age may not significantly change the failure probability

C. Preventive maintenance always increases reliability

D. Random failures can be detected only by visual inspection

Correct Answer: B. Age may not significantly change the failure probability

Question 10

Which is the most appropriate basis for selecting a maintenance policy?

A. The asset’s purchase price alone

B. The manufacturer’s calendar interval alone

C. Failure mode, consequence, detectability, cost, risk and operating context

D. The number of maintenance staff currently available

Correct Answer: C. Failure mode, consequence, detectability, cost, risk and operating context