Determine Whether the Production Process Should Be Continued or Adjusted Before Production Defects

Maintenance Management

Michael Guy Deighton , in Facility Integrity Management, 2016

5.4.2 Corrective (Reactive) Maintenance

Corrective maintenance (CM) involves the replacement or repair of equipment after it fails. In response to equipment failure, CM tasks identify the failure (it may be an equipment component or equipment item) and rectify the failure so that the equipment can be reinstated and the facility production restored. CM tasks are prioritized so that the high-priority tasks that may be safety related or affecting production are addressed first.

CM is in general low cost because it can generally be performed with a fewer number of resources and maintenance infrastructure, including tools, technologies and expertise. The consequence, however, is that it is inefficient and in the long term it can be very expensive because failures generally result in catastrophic events, which means there is more damage that needs to be repaired and hence the MTTRs are longer. CM also does not focus on the root cause of the equipment failure and therefore MTBF will be much lower than with proactive maintenance. In other words, there will be many repeat failures.

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Designing for Maintenance

Anil Mital , ... Aashi Mital , in Product Development (Second Edition), 2014

8.2.2.1 Corrective (reactive) maintenance

Corrective maintenance is reactive in nature. Every time a product or system fails, repair or restoration must follow to restore its operability. The following steps constitute corrective maintenance:

●

Once the failure has been detected, it must be confirmed. If the failure is not confirmed, the item generally is returned to service. This no-fault-found problem leads to a considerable waste of time at significant cost. It also entails carrying an unnecessarily large inventory all the time.

●

If the failure is confirmed, the item is prepared for maintenance and the failure report is completed.

●

Localization and isolation of a failed part in the assembly is the natural next step in corrective maintenance.

●

The failed part is removed for disposal or repair. If disposed of, a new part is installed in its place. Examples of repairable parts and connections include broken connections, an open circuit board on a PCB, or a poor solder.

●

The item may be reassembled, realigned, and adjusted after repair. It is checked before being put back to use.

The chief disadvantage of this maintenance procedure is the inherent amount of uncertainty associated with it. Similarly, the procedure is extremely reactive in nature, capable of shutting down an entire operation because of a single failure in a single machine under extreme conditions (often leading to a severe bottleneck and lost productivity). As a result of its drawbacks, another, more proactive maintenance method (recognizing that equipment needs periodic maintenance to function smoothly, which should be provided before a breakdown occurs) was developed.

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Risk-Centered Maintenance

Yong Bai , Wei-Liang Jin , in Marine Structural Design (Second Edition), 2016

Maintenance Strategy

According to the FEMCA analysis, a series of maintenance strategies was scheduled as the following:

Task Logic Tree

Table 44.10 lists the task logic tree analysis result.

Table 44.10. Task logic tree

Is a lubrication or servicing task applicable and effective?	Yes
Is an inspection or functional check to detect degradation of function applicable and effective?	Yes
Is a restoration task to reduce failure rate applicable and effective?	No
Is a discard task to avoid failures or to reduce the failure rate applicable and effective?	No

Corrective Tasks

Corrective maintenance consists of the action(s) taken to restore a failed component to operational status. Corrective maintenance is performed at unpredictable intervals because a component's failure time is not known a priori. Table 44.11 lists the corrective task.

Table 44.11. Corrective task

#	Task Description	Condition	Type	Interval	Crew	Duration
1	Repairing the leaking crack		Corrective		Fatigue or corrosion of the body shell or piping_Crew	1.000000 day

Scheduled Tasks

Scheduled maintenance contains three kinds of maintenances: PM, inspection, and on-condition maintenance.

PM is the practice of repairing or replacing components or subsystems before they fail in order to promote continuous system operation or to avoid dangerous or inconvenient failures. The schedule for PM is based on observation of past system behavior, component wear-out mechanisms, and knowledge of which components are vital to continued system operation. In addition, cost is always a factor in the scheduling of PM. In many circumstances, it is financially more sensible to replace parts or components at predetermined intervals rather than to wait for a failure that may result in a costly disruption in operations.

Inspections are used in order to uncover hidden failures (also called "dormant failures"). They are also used as part of on-condition tasks to detect impending failures so that PM can be performed.

On-condition maintenance relies on the capability to detect failures before they happen so that PM can be initiated. If, during an inspection, maintenance personnel can find evidence that the equipment is approaching the end of its life, then it may be possible to delay the failure, prevent it from happening or replace the equipment at the earliest convenience rather than allowing the failure to occur and possibly cause severe consequences.

Table 44.12 lists the scheduled tasks of the external subunit of the heat exchanger.

Table 44.12. Scheduled tasks

#	Task Description	Condition	Type	Interval	Crew	Duration
1	Applying the protective coating		S	3   years	Fatigue or corrosion of the body shell or Piping_Crew	1.000000   h
2	Crack inspection		IN	1   year	Fatigue or corrosion of the body shell or piping_Crew_2	1.000000   h

Note: S, service task (preventive task); IN, inspection task.

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Maintenance Decision Support

Jiuping Xu , Lei Xu , in Integrated System Health Management, 2017

8.1.1.1 Corrective maintenance

Corrective maintenance refers to all activities that restore a system to the specified state when a fault occurs. It may include one or all of the following steps; fault location, fault isolation, decomposition, replacement, reassembly, adjustment, and testing [3], that is, a determining whether the appropriate related maintenance after the fault occurs is corrective maintenance such as break-down maintenance, condition monitoring maintenance, hidden trouble detection, and design change.

1.

Break-down maintenance is a failure-based maintenance mode that determines whether a system is in a good condition or available and restores the system to its original state after a partial or complete failure occurs in the system.

Break-down maintenance is applied when

a.

There is no obvious functional failure to the operator;

b.

There are unforeseen faults in the system, but there is no immediate harm to the safety of the system or mission;

c.

The system is deteriorating. The cost of postfault maintenance is less than the PM; however, time-based or condition-based maintenance (CBM) can also be used.

2.

Condition monitoring maintenance is used to indicate where technical resources should be allocated. From an analysis of the overall data from the specific operating system, the most appropriate maintenance method is then determined. Condition monitoring maintenance is not PM but is used to identify where the faults are occurring and what measures should be applied.

3.

Hidden trouble detection is carried out to find an existing functional fault that is not obvious to the operators, such as the detection of redundant systems.

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Prognosis

Diego Galar , Uday Kumar , in eMaintenance, 2017

6.1.2 Types of Maintenance

6.1.2.1 Corrective Maintenance

Corrective maintenance is used to repair damage that has already occurred. Usually, when this type of maintenance is performed, the manufacturing process is stopped, decreasing production and increasing costs. Repair time cannot be predicted, nor can the expenses resulting from the breakdown and consequent disturbances on the production line. Therefore, corrective maintenance is applied on assets with low criticality, whose faults do not involve large temporal or economic problems. It is often used for specific equipment where other techniques would be more costly.

6.1.2.2 Preventive Maintenance

Preventive maintenance is planned in a time horizon and aims to prevent breakdowns. Unlike corrective maintenance, because it is planned, it is not done during production time.

The intention of this type of maintenance is to reduce the number of corrective interventions, performing periodic reviews and replacing worn components.

It is a demanding type of maintenance, as it requires strict supervision and development of a plan to be carried out by qualified personnel. In addition, as it involves routine tasks, personnel may not be motivated. Furthermore, if it is not done correctly, there will be a cost overrun with no significant improvements in productivity.

6.1.2.3 Condition-Based Maintenance

CBM aims to determine the condition of equipment, so that operation remains safe, efficient, and economic. Monitoring techniques are aimed at measuring physical variables that indicate the condition of the machine and comparing these with normal values to determine if the machine is in good condition or deteriorating. CBM assumes there are measurable and observable characteristics that are indicators of the condition of the machine.

Condition monitoring studies the evolution of selected time-dependent parameters; it identifies trends indicating the existence of a fault, its severity, and the likely time to failure (TTF). Timely decision-making avoids the occurrence of faults and eliminates the possibility of catastrophic failure. CBM can be performed while the machine is running (Gerardo Trujillo and América, 2003).

CBM consists of three key steps (see Fig. 6.2):

Figure 6.2. Three steps in condition-based maintenance.

1.

Data acquisition (information collecting), to obtain data relevant to system health.

2.

Data processing (information handling), to handle and analyze the data or signals collected in step 1 for better understanding and interpretation of the data.

3.

Maintenance decision-making (decision-making), to recommend efficient maintenance policies.

Steps to Implement CBM:

Data Acquisition

Data acquisition is a process of collecting and storing useful data (information) from targeted physical assets for the purpose of CBM. This is an essential step in implementing a CBM program for machinery faults (or failure, usually caused by one or more faults). Data collected in a CBM program can be categorized into two main types: event data and condition-monitoring data. Event data include information on what happened (e.g., installation, breakdown, overhaul, etc., along with the causes) and/or what was done (e.g., minor repair, preventive maintenance, oil change, etc.) to the targeted physical asset. Condition-monitoring data are measurements related to the health condition/state of the physical asset. These are very versatile and can include vibration, acoustic, oil analysis, temperature, pressure, moisture, humidity, weather or environment data, etc.

Data Processing

Data processing consists of two stages. The first is data cleansing; this step is important because usually the data are entered manually. This leads to frequent errors, requiring data cleaning to increase the probability that the data are clean (no errors). The second step is the analysis of the data. There are a variety of models, algorithms, and tools for analysis; selection depends on the types of data collected.

Maintenance Decision Support

The last step of a CBM program is maintenance decision-making. Sufficient and efficient decision support is crucial for determining maintenance actions. Techniques for maintenance decision support in a CBM program can be divided into two main categories: diagnostics and prognostics. Fault diagnostics focus on detection, isolation, and identification of faults when they occur. Prognostics attempt to predict faults or failures before they occur.

Obviously, prognostics are superior to diagnostics in the sense that prognostics can either prevent faults or failures, or be ready (with spare parts and human resources) for the problems, thus reducing the costs of unplanned maintenance.

Nevertheless, prognostics cannot completely replace diagnostics since, in practice, there are always some faults and failures, which are not predictable. In addition, prognostics, like any other prediction technique, cannot be 100% accurate. In the case of unsuccessful prediction, diagnostics can be a complementary tool for maintenance decision-making. Diagnostics are also helpful for improving prognostics; diagnostic information can result in more accurate event data, and a better CBM model can be built for prognostics. Furthermore, diagnostic information can be used as feedback information for system redesign.

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Maintainability Measures, Functions, and Models

B.S. DHILLON , in Engineering Maintainability, 1999

PROBLEMS

1.

Compare corrective maintenance time and preventive maintenance time.

2.

Three subsystems, i, j, and k, form an electronic system. The constant failure rates of these subsystems are λ_i = 0.002 failures per hour, λ_j = 0.004 failures per hour, and λ_k = 0.006 failures per hour. The corresponding estimated corrective maintenance times are T_i = 2 hours, T_j = 3 hours, and T_k = 4 hours, respectively. Estimate the mean time to repair (MTTR) for the overall system.

3.

Discuss the following two items:

•

Maximum corrective maintenance time

•

Median corrective maintenance time

4.

Define the maintainability function verbally and mathematically.

5.

Obtain maintainability functions for the following distributions:

•

Exponential

•

Lognormal

6.

After a detailed analysis of repair data associated with an engineering system, it was concluded that the system mean time to repair (MTTR) is 3.5 hours. Calculate the probability of completing a repair in 2.5 hours, if the times to repair are described by an exponential probability density function.

7.

Prove that the mean, M, of the gamma distributed maintenance time is given by

$\text{M}=\text{m}/\text{k}$

where m is the shape parameter associated with gamma distribution.

k is the scale parameter associated with the gamma distribution.

8.

What is the difference between the following types of availability?

•

Inherent availability

•

Achieved availability

•

Operational availability

9.

Describe the relationship between system effectiveness and dependability.

10.

What are the important assumptions associated with the equation that determines the probability of having a spare of a specific item available when required?

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Wind Energy

Donatella Zappalá Peter J. Tavner , in Comprehensive Renewable Energy (Second Edition), 2022

2.11.3 Wind turbine maintenance strategies

O&M plays a key role in the cost-effective development of WF projects, especially the offshore ones. While the cost of wind energy reduces due to smaller upfront costs and improved performance, O&M activities represent a major contributor to total expenditure, with offshore O&M costs estimated to account for up to 35% of the total cost of wind energy (Stehly et al., 2020).

Operations represent a small proportion of O&M expenditure and refer to activities contributing to the high-level management of the asset, such as the environmental monitoring, the remote monitoring, electricity sales, marketing, administration and other back-office tasks.

Maintenance represents a large portion of O&M effort, cost and risk. The purpose of maintenance is to achieve the desired component performance by maintaining the component׳s ability to function correctly. The component failure rates, as well as the maintenance duration, the vessel availability and the operational weather limits have the greatest effect/impact on O&M costs (Martin et al., 2016).

Maintenance strategies are typically classified as corrective and preventive, as shown in Fig. 7 , according to when maintenance is conducted. The primary difference between these two strategies is that a problem in the system must exist before corrective maintenance actions are taken, while preventive tasks are intended to prevent occurrence of a problem in the first place.

Fig. 7. Classification of maintenance strategies.

Corrective maintenance is the traditional maintenance approach, being undertaken after a failure occurs. For critical component failures, this should be performed immediately. For offshore wind power installations, this approach requires planning action as soon as a failure occurs, otherwise long unscheduled downtime and significant production losses can occur. For failures that are of small consequence to the comprehensive system function, the maintenance actions can be deferred to a better suited time.

Thus, corrective maintenance has the advantage that useful asset life is available without loss of capacity. On the other hand, it has two disadvantages:

(a)

it requires fast response to avoid significant downtime;

(b)

it can lead to greater damage and direct costs, for example due to consequential failure of components other than those initially failed (Koukoura et al., 2021).

Preventive maintenance is performed to avoid major failures and can be further subdivided into time-based and Condition-Based Maintenance (CBM).

Scheduled time-based WT maintenance is done at fixed intervals between maintenance visits, independent of the WT operating status. This generally takes 2–3   days per WT and is suitable for age-related failures where a failure probability distribution is known. It includes, tests of safety systems, gearbox oil sampling and analysis, oil and filter changes, inspections for oil or water leakage, generator brush and slip-ring checks, brake pad renewal, bolt strength testing/re-tightening and blade visual inspections. These tests are usually based on manufacturer recommendations but may be modified based on the operator׳s experience.

In onshore installations, preventive time-based maintenance is generally performed every 3 months during the first year of operation and later every 6 months depending on the WT service type and model. However, in offshore installations, due to the higher transportation and production loss costs, WTs are routinely serviced only once a year during spring or summer (Besnard, 2013). A preventive time-based maintenance strategy has the main advantage that assets deliver more predictable and reliable electricity, optimizing the financial return. However, compared to CBM, it results in higher costs and the risk of over-maintenance, since tasks may be completed more frequently than needed before the nominal component life end.

CBM is performed based on the physical machine component conditions, requiring monitoring systems with warning/alarm limits to alert attention if a condition exceeds specified accepted levels. Advanced and reliable monitoring and analysis techniques are needed to plan CBM using WT SCADA and Condition Monitoring Systems (CMS) data (Crabtree et al., 2015).

Information about machine component condition must be accurate if effective CBM strategies are to be implemented. The objective is to detect the presence and type of incipient faults at an early stage and monitor their evolution, allowing estimates to be made for the residual life, then taking remedial action by planning the most viable economic maintenance intervention using a dynamic schedule (Bengtsson, 2004). In this way, any planned maintenance activity should not be production-critical and could be carried out during low wind periods, when access is easier and electricity demand low.

A comparison of maintenance strategies, showing the advantages and disadvantages of each category, is given in Hameed et al. (2010).

Wind power industry maintenance strategies are evolving rapidly, particularly for offshore applications. The increasing impact of O&M costs, especially in offshore installations, is encouraging WF operators to shift from scheduled corrective to preventive CBM approaches (Mérigaud and Ringwood, 2016; Rinaldi et al., 2021). This should reduce significant financial loss by avoiding long failure downtimes. Corrective maintenance costs have been estimated to be approximately four times higher than those of preventive activities (Scheu, 2012). The economic benefits of implementing preventive CBM strategies are substantial, in terms of maintenance costs minimization, operational performance and safety improvement, preventive part replacement reduction when effective life has not been reached, as well as the reduction of the number and severity of in-service failures (McMillan and Ault, 2008; Byon and Ding, 2010; Zhigang et al., 2011).

A comprehensive understanding of WT reliability, identifying the most critical components and their failure modes, is essential for implementing appropriate CMSs to achieve the full economic benefits of CBM.

2.11.3.1 Overview of wind turbine condition monitoring

With the development of advanced condition monitoring, diagnostics and prognostics, CBM has attracted much attention in the offshore wind power industry in recent years. Modern WTs are equipped with SCADA systems and CMSs for the active remote monitoring and control of their components (Tavner, 2021). SCADA systems provide a range of low frequency (typically 10-min averaged values) measurements, such as for the active power, the wind speed and the pitch conditions and temperatures. The data recorded includes alarms, fault logs, environmental and operating conditions leading up to fault occurrences. These systems were designed for operating purposes but have given valuable insights into impending WT malfunctions, attracting extensive research attention as in Feng et al. (2010), Qiu et al. (2011), Schlechtingen et al. (2013), Feng et al. (2013), Schlechtingen and Santos (2014), Tautz-Weinert and Watson (2016), Maldonado-Correa et al. (2020) and Zhang et al. (2020). Potentially, SCADA records could help WT operators to understand key WT components health. However, this requires considerable analysis for interpretation of the large volume of data generated. Furthermore, the low resolution of the data does not usually permit an in-depth analysis, generally agreed as necessary for accurate diagnosis and prognosis (Crabtree et al., 2015).

CMSs provide high-resolution monitoring of WT high-risk subassemblies. The majority of CMSs currently available are based on drivetrain high-frequency vibration monitoring, with special focus on main bearing, gearbox and generator bearings. In some cases, these measurements can be used in combination with oil particle counters and fiber-optic strain gauges to enhance their monitoring capabilities. No commercial CMS is offered for electrical and power electronic components or for the yaw and pitch systems, beyond that monitored by the SCADA system (Tavner, 2021). This is a gap that needs to be addressed because, as shown in Section 2.11.2, the reliability of electrical components is being increasingly recognized as a growing concern, especially in offshore installations, where electrical component deterioration could be accelerated by enhanced corrosion and erosion rates due to the harsh environment. A number of non-destructive monitoring techniques applicable to WT CMS are reviewed in Garcia Marquez et al. (2012), Yang et al. (2014), and Hossain et al. (2018). According to the survey carried out by Crabtree et al. (2014) there is a wide variety of commercially available CMSs for industries other than wind, mainly relying on established rotating machine industry techniques, where they have become an integral part of asset management. However, the adaptation of these techniques to wind power plants has proved challenging, due to their peculiar variable operating conditions (Yang et al., 2009).

The application of WT state identification to fault detection, diagnosis and prognosis uses both physics-based and data-driven approaches (Qiao and Lu, 2015; Luo, 2017; Stetco et al., 2019). SCADA systems and CMS collect large, complex volumes of data, requiring a high degree of expert manual analysis. Leveraging the full potential of this data and extracting actionable and timely insights to optimize O&M strategies require systems that automatically analyze and interpret large volumes of monitoring data (DNV, 2019). The development of reliable and cost-effective analysis methods, with automatic damage detection, diagnosis and problem prognosis on the most critical WT components, could play a crucial role in establishing technically and economically viable CBM strategies for offshore wind power installations. In the last decade of the wind power industry, data-driven decision-making for effective CBM has evolved rapidly, from applying conventional signal processing and physics-based methods in 2010 to the application of artificial intelligence (AI) and especially deep learning in 2020. While AI techniques have been game-changers in other fields, such as healthcare and finance, they are still at an embryonic stage in industrial wind power engineering.

This is probably due to the lack of a clear perspective and the limited trust in these methods. Despite their enormous potential, there are key challenges for the offshore wind power industry in adopting data-driven decision-making techniques that need to be addressed, as they have been identified by (Chatterjee and Dethlefs, 2021):

(a)

Lack of quality data access;

(b)

Problems in deploying AI models for real-time decision support;

(c)

Lack of black-box approach transparency.

These are critical areas where researchers should focus soon to develop advanced solutions for reducing offshore wind power O&M costs. The main objective will be to develop a platform for the analysis and management of offshore WTs' data and use the data collected in the design of cost- efficient CBM strategies.

2.11.3.2 Toward an offshore wind integrated maintenance strategy

Historic design and reliability information together with on-line monitoring data must play a key role for the optimization of O&M planning and the management of WF assets, especially in offshore installations. Effective asset management of a WF is crucial for the optimization of the future cost of wind energy. That must be based upon data to close the gap between prior knowledge and current operational experience, with the data coming from:

(a)

A logical classification of maintenance methods, Fig. 7;

(b)

WT and WF Design, e.g. prior FMEA, Fig. 8;

Fig. 8. Proposals to use of FMEA and Reliability-Centered Maintenance (RCM) as Review Tools during Offshore WT Design and Manufacture for improved WF O&M outcomes (Tavner, 2021). (A) FMEA as a Design Review Tool; (B) FMEA and RCM together as an O&M Review Tool.

From Tavner PJ (2021) Offshore Wind Power - Reliability Availability and Maintenance, 2nd edn. London, UK: The Institution of Engineering and Technology.

(c)

Historic operation, i.e. prior failure rate and downtime surveys, summarized in Table 1 and Figs. 2–6;

(d)

Current operational experience on this and similar WFs, operator/manufacturer information;

(e)

On-line WF operational data, integrated from both SCADA and CMS.

The challenge is to integrate this information so that it can be exploited by WF operators and maintenance teams to operate and maintain the assets in the most cost-effective manner.

Fig. 9 proposes a framework for the implementation of an optimal offshore WF maintenance strategy by managing and integrating the available knowledge. It collates live SCADA and CMS monitoring data, as well as met-ocean data and forecasts with available reliability data, then correlates them with maintenance logs to provide an integrated system upon which optimal planned maintenance strategies can be implemented. Fig. 9 represents a simplified version of an earlier framework proposed by (Tavner, 2021). Its implementation would require the adaptation of original equipment manufacturers (OEM) and operators' data structures to the conditions of individual WFs. There are various closely interlinked stakeholders involved in offshore WF O&M and they can be grouped into six specific departments shown in Fig. 9 with their live data inputs, stored information, functions, maintenance actions, report outputs and key interactions.

Fig. 9. Offshore WF Knowledge Management System.

Modified from the original version produced by Christopher J. Crabtree with contributions from Peter J. Tavner, Bindi Chen, Yanhui Feng, Yingning Qiu and Donatella Zappalá in Tavner PJ (2021) Offshore Wind Power - Reliability Availability and Maintenance, 2nd edn. London, UK: The Institution of Engineering and Technology.

(a)

Health Monitoring (HM): Responsible for the continuous WT health monitoring, via automated SCADA alarm and signal data, the CMS alarm and signal data processing and the examination of historical reports to alert other groups via generated HM reports, which include fault development, severity, expected time to failure and advice on preventive measures.

(b)

Asset Management (AM): Concerned with ensuring that assets are operated in the most cost- efficient and valuable manner to secure the longest life cycle of profitable operation. RCM activities are driven by a clear understanding of subassembly history and performance provided by the exchange of information with the other departments.

(c)

Operations Management (OM): Concerned with achieving the required WF operation, given the available operational and met-ocean information, meeting AM, maintenance schedule and grid requirements.

(d)

Maintenance Management (MM): Related with the implementation of the AM requirements, via OM outputs, responding to concerns raised by HM and producing cost-effective maintenance schedules, including preventive CBM, reactive and RCM responses, based on met-ocean forecasts, resources, equipment and personal availability.

(e)

Field Maintenance (FM): Responsible for the implementation of maintenance schedules, for reporting and resolving any faults (or potential faults) discovered during maintenance, for the confirmation of repair success against advice in HM reports and for updating reliability figures and fault details from MM report and integrating them in the FM reports.

(f)

Information Management (IM): responsible for handling the WF data and information, including live data, department reports, staff information and department requests, providing on demand data and information based on department requests and realizing effective communication between departments and integrating them in a collaboration report.

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Cost Considerations

B.S. DHILLON , in Engineering Maintainability, 1999

Corrective Maintenance Cost Estimation Model

This model estimates the corrective maintenance labor cost for a piece of equipment. The annual cost is expressed by

(8.17) ${\mathrm{C}}_{\text{CM}}=\frac{\left(\text{SOH}\right)\left(\text{LC}\right)\left(\text{MTTR}\right)}{\text{MTBF}}$

where SOH represents the scheduled operating hours of the equipment.

LC is the maintenance labor cost per hour.

MTBF is the mean time between failures for the equipment.

MTTR is the mean time to repair for the equipment.

Example 8-6

A heavy-duty motor is scheduled to operate for 3,000 hours annually. The expected MTBF and MTTR of the motor are 1,000 hours and 10 hours, respectively. Determine the annual labor cost of corrective maintenance for the motor, if the maintenance labor rate is $25 per hour.

Substituting the given data into Equation 8.17 yields

${\mathrm{C}}_{\text{CM}}=\frac{\left(\text{3000}\right)\left(\text{25}\right)\left(\text{10}\right)}{\text{1000}}=\$750$

It means the yearly labor cost is $750.

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Clinical Engineering for Consolidated Markets

Heikki Teriö , in Clinical Engineering, 2016

Device Management and Support in Clinical Use

Preventive maintenance and corrective maintenance including calibration of medical devices are basic activities in the process of device management. When the equipment is purchased, there is also a discussion of who is going to carry out the maintenance activities. In the Nordic countries, it is often a mixture between in-house and vendor services. The decision, who is doing the different maintenance tasks and to what extension, depends on the recourses and the costs. It is also possible to renegotiate the agreements when the situation has changed.

Technology management requires even an accurate inventory to keep track on the detailed information on the medical devices and systems. The objective of the inventory system is to record the detailed data produced from all activities of technology management and convert them into meaningful information. It should also be possible to monitor equipment performance, reliability, and cost-effectiveness, as well as to assist decision making in equipment acquisition and technology assessment. The inventory system should provide a comprehensive, expandable, and easy-to-use database of protocols for the performance of quality control, preventive and corrective maintenance, electrical safety, calibration, and acceptance tests of medical devices.

Very often CEDs in the Nordic countries developed their own systems, but they were vulnerable relying on a couple of individuals and very often poorly documented. When the demands on information quality and security increased, the CEDs were forced to evaluate a number of systems during the past decades, for example, HECS (Hospital Equipment Control System) developed by ECRI (Emergency Care Research Institute); MEMS (Medical Equipment Management System) developed under the BEAM European project; and BITMANS (Biomedical Technology Management System) developed by INBIT (Institute of Biomedical Technology, Patras, Greece). The systems that were used after evaluation were Maximo, which is an inventory and administrative system designed primarily for industry, QA-MAP, Norwegian system originally from the University Hospital of Trondheim, and MEDUSA, developed by Softpro in Sweden (Softpromedical, 2015). Today MEDUSA is the system that is most widely used in the Nordic countries. To address and satisfy particular needs that the different demands imposed by the resources, size, organization, and policies of the hospitals and/or the CEDs, the system is made modular and customized to a certain extent. Since CED has to perform continuous monitoring and evaluation of its performance in order to identify probable problems and measure its contribution to the quality of patient care, the system also monitors and measures a set of quality and cost indicators, allowing a continuous overview of the departments' performance in terms of productivity, effectiveness, and efficiency.

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Maintenance Management

Dilip Kumar , Deepak Kumar , in Sustainable Management of Coal Preparation, 2018

18.8 Types of Maintenance

Although the design life of most equipment requires periodic maintenance, this life can be extended. Failing to perform maintenance activities (as prescribed by the designer), shortens the operating life of the equipment. Maintenance can be classified as reactive maintenance, preventive maintenance, predictive maintenance and reliability-centred maintenance (see Fig. 18.2).

Figure 18.2. Types of maintenance, indicating hierarchy.

18.8.1 Reactive Maintenance

Reactive maintenance or corrective maintenance is to fix items when needed either through scheduled inspection or field observation. If these unplanned fixes are prioritised then it takes time away from scheduled maintenance ( Hern, 1995). Minimal effort is spent to maintain the equipment as the designer originally intended to ensure design life is reached. Studies indicate that this is still the predominant mode of maintenance in the United States and other countries (O&M Best Practices Guide, Release 3.0).

18.8.2 Preventive Maintenance

This is a better method than reactive maintenance. Maintenance is regularly schedule based on vendor recommendation or breakdown history (Hern, 1995). The schedules are created for routine check and replacement of components based on time-directed maintenance. These time cheques are usually determined based upon the life span of previous components of a similar type. Preventive maintenance can be inefficient and may be wasteful as some parts that are far from their breaking point are replaced with new parts – these parts could still work without problems (O&M Best Practices Guide, Release 3.0).

18.8.3 Predictive Maintenance

This approach detects problems that can be overlooked by preventive maintenance. The onset of a degradation mechanism of equipment is detected by condition-directed maintenance. This allows for casual stresses to be eliminated or controlled prior to any significant deterioration in the component physical state. Effective maintenance can catch issues quickly in the potential failure (P-F) interval of the life cycle of a component so appropriate action can be taken. Predictive maintenance consists of different elements including vibration analysis, oil analysis, motor meggering and thermographic analysis (see Fig. 18.3).

Figure 18.3. P-F interval curve.

18.8.4 Proactive (Reliability-Centred) Maintenance

Proactive/reliability-centred maintenance relies on effective decision making considering benefits and limited resources. It acknowledges equipment has different importance to either the process or plant safety. It takes into account the probability of failures due to different degradation mechanisms. The maintenance programme is thus built on prioritising actions by also taking into account the limited financial and personnel resources. This helps focus on what is important, items that need to be proactively dealt with, and enhance the MMS (O&M Best Practices Guide, Release 3.0).

RCM analysis will assess the failure modes for an asset and develop a maintenance strategy to mitigate the consequences for each failure mode. The value in performing RCM is the proactive assessment of these failure modes and the resulting tasks developed to eliminate reoccurring failures. An organisation or processing plant needs to have a target that equipment failures are unacceptable. Failures can be categorised to track their occurrences. Some examples of failure codes include:

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Material defect;

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Installation defect;

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Design defect;

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Fabrication errors;

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Unintended service conditions;

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Improper use;

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Inadequate maintenance.

Tracking the frequency or occurrence and impact of failures can help us with an area of focus – whether it be certain equipment, a manufacturer or process (Plucknette, Reliability Web).

18.8.5 Technology-Enhanced Maintenance Management

The MMS can be enhanced by leveraging technology. Computerised maintenance management systems (CMMSs) are widely adopted in various industries. CMMSs have been getting traction since the late 1980s and it is rare that a large company involved in equipment maintenance would not have a specialised software solution to aid in its equipment maintenance efforts. Some of the CMMS are TabWare CMMS/EAM, Bentley Systems and FIIX (cloud-based). Detailed analysis of these systems can be found at: https://www.softwareadvice.com/ca/cmms/#top-products.

Sometimes CMMSs are tied to upstream and downstream workflows where they can be tied to purchasing, receiving, and also connecting to accounting systems for payables – this helps in efficient workflows, on-demand accurate reporting, data governance and expediting decision making in large organisations. Moreover, capital-intensive industries have moved away from standalone software solutions to the integration of their CMMS with their enterprise resource planning software. CMMS solutions are expensive. Moreover, IT hosting, support and maintenance costs can add up. Therefore, the scale of the organisation needs to be considered while adopting these systems. Yet, the IT costs are much lower and technology is light ages ahead of two decades ago, making the net benefit much higher (Alves, Reliability Web).

CMMS can be used to effectively plan and schedule maintenance work orders. Using a preset and reviewed template, work orders can be auto-generated, reducing the workload on the planning department. Moreover, there will be a single version of the truth, with the history of work done on as asset or equipment. These systems come with on-demand and enhanced reporting for plant staff, site managers and corporate maintenance leadership.

18.8.6 Vibration Analysis

Vibration analysis monitors vibration frequencies and amplitudes of mechanical units. Comparing the observed data with the benchmarked data, potential bearing problems, alignment corrections, rotating equipment dynamic imbalances, and so on can be detected early and scheduled maintenance can be arranged. Vibration analysis is key for critical equipment whose failure can cause a mine shutdown (Hern, 1995).

18.8.7 Oil Analysis and Contamination

Oil analysis is a central part of any maintenance programme. The correct type of lubricant, proper grade of lubricant, change of lubricant and filter at recommended intervals are of utmost importance for better reliability and performance of a machine (Kumar, 2006).

Anything that doesn't belong in the oil is called contamination, and may include: dirt and other particles, air, wear debris, fuel and other lubricants, coolant, and detergents and other chemicals.

If the lubrication oil is contaminated, it can cause harm to the equipment and performance will deteriorate. The lubricant becomes abrasive when debris makes its way into it, which may lead to bearings or other moving parts failing.

Better lubrication practices can have an enormous impact on plant operation and the bottom line. The best condition-based lubrication techniques as part of a larger maintenance programme should be in place. Plant efficiency and optimising work hours can be improved by filtering oil and finding contaminants in bearings before they can cause failures (http://www.uesystems.com/news/controlling-contamination-to-control-costs).

18.8.8 Motor Meggering

The condition of motor winding insulation can be continuously monitored and determined by measuring megohms of resistance from the winding insulation. This measure decreases as the winding insulation deteriorates. With a benchmark threshold for replacement, these motors can be replaced, which prevents major unscheduled plant downtime (Hern, 1995).

There are special measuring instruments that may be used to detect and diagnose malfunctions. The insulation resistance tester, generally known by its trade name, Megger, is capable of providing critical information regarding the condition of motor insulation.

18.8.9 Thermographic Analysis

Through the use of an infrared camera it is possible to estimate the temperature and to produce a surface thermal map of an object's surface. Once high-temperature areas are located, scheduled repairs including disassembly, cleaning and reassembly are planned.

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