15. applying rcm techniques.full

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APPLYING RCM TECHNIQUES TO HOUSEHOLD CONSUMER DURABLES THROUGH

THE INTERNET OF THINGS

SUKUMAR DAS1

& SANJAY KUMAR2

1Research Scholar, Management Development Institute, Gurgaon, India

2Professor, Management Development Institute, Gurgaon, India

ABSTRACT

Purpose: This paper proposes a conceptual model for the use of RCM techniques for household appliances using the

proposed infrastructure of the internet of things

Design/Methodology/Approach: This paper reviews literature in third generation maintenance techniques such as RCM

and CBM. This paper proposes a model for the use of the RCM techniques such as condition based monitoring for

household appliances, using the infrastructure of the internet of things.

Findings: Generally RCM based techniques are used in factories for the monitoring and fault free operation of plant and

machinery. This paper identifies the gap in the use of advanced RCM based techniques in the maintenance of household

products, and proposes a model for the same, using the infrastructure of the internet of things. A proposed model IT

architecture is also discussed.

Practical Implications: The paper suggests an approach of zero-failure maintenance process through the integration of

RCM technique and infrastructure of Internet of things. This will help the manufacturers keep their high value assets

operational and optimized for long-term efficiency and maximum uptime.

The cost of providing such a high level of monitoring and fault free service of the equipment is drastically

lowered through the use of the infrastructure of the internet of things. In the traditional service network, a similar level of

service would need the availability of a large workforce for maintaining a servicing network across each geographical

location, along with a huge inventory of spares.

The paper also points to the need for developing a knowledge framework and repository at the manufacturers

end, for documenting and encoding the various modes of failure and the identification of signals of incipient failure in the

equipment.

Originality / Value: The need for lifetime warranties and maintenance contracts is being increasingly felt by

manufacturers in an increasingly competitive market. This paper explores a model for the use of internet of things for

providing a high level of cost effective monitoring and uptime guarantees for household appliances, by the manufacturer.

KEYWORDS: RCM, CBM, Proactive Maintenance, Internet of Things, Infrared Thermography, Vibration Analysis

INTRODUCTION

Competitive pressures of the marketplace and changing expectation of customers have caused companies to

progressively promise or guarantee long years of fault free operation of their machines or products. These warranties are

now extending to the expected lifetime of the product. Another model of a hassle free operation of the product, during its

expected life, is through the provision of annual maintenance contracts being offered by the manufacturers. Though this

International Journal of Mechanical and Production

Engineering Research and Development (IJMPERD)

ISSN 2249-6890

Vol. 3, Issue 3, Aug 2013, 117-130

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118 Sukumar Das & Sanjay Kumar

provides a stream of revenue during the life of the product, multinational companies are loaded with the cost of

maintaining a huge service network in many countries, and a huge inventory of spare parts in each country. Failure of a

component incurs not only a replacement cost, but also the reputation of the company is tarnished.

Over the last years, the application of scientific methods in maintenance management in factories, has led to a

significant reduction in the incidences of equipment failure on the shop floor. The use of proactive and predictive

maintenance techniques for maintenance such as condition based monitoring has proved to be a cost effective approach on

the shop floor. Increasingly factories are adopting Reliability Centered Maintenance practices on the shop floor.

However the use of such techniques in household consumer durable goods is not prevalent due to the requirement

of costly equipment and specialized training of service personnel for advanced fault identification techniques. Also the non

availability of historical information and systematic record keeping, required for detecting incipient failures, acts as a

hindrance in the application of RCM techniques for household appliances.

The internet of things can be described as a worldwide network of interconnected objects (such as household

appliances), uniquely addressable, having embedded intelligent sensors and based on standard communication protocols.

(Zouganeli and Svinnset, 2009, Semantic) The vision of internet of things includes millions of objects that interact with

the network using a plethora of applications. It is expected that the Internet of things will become a reality over the next 20

years; with omnipresent smart devices wirelessly communicating over hybrid and ad-hoc networks of devices, sensors and

actuators working in synergy to improve the quality of our lives (see figure 1). The availability of this network

infrastructure will allow manufacturers to use RCM techniques, such as condition based monitoring, to provide fault free

working equipment to the customers with a minimal service inventory and at a substantially lower cost.

This paper suggests a conceptual framework for the deployment such advanced maintenance techniques to

household appliances using the infrastructure enabled by the internet of things.

Internet of Things

Figure 1: Internet of Things (Taken from Furness, 2008)

As given in the report by Furness (2008), the proposed infrastructure of the internet of things is described below

(see figure 1). Furness describes a proposed multi-level level network for the internet of things. He describes internet ofthings as a global network infrastructure, linking physical and virtual objects through the exploitation of data capture and

communication capabilities. This infrastructure includes existing and evolving Internet and network developments. It will


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Applying RCM Techniques to Household Consumer Durables through the Internet of Things 119

offer specific object-identification, sensor and connection capability as the basis for the development of independent

federated services and applications.

First level of the proposed infrastructure would include the embedded intelligent sensors and RFID tags in various

objects or machines. These sensors would then capture data about the condition of the machine and after local processing,

send this data through wireless channel to the next layer comprising access gateways and internet. Here the relevant users

may access this data on an online basis or on a selective access basis from the internet of things. One relevant user may be

the manufacturing company or service provider for the object. This data which is available on the network is then captured

by the user company, through the appropriate middleware and stored in its database server. This may also be processed at

an appropriate time using various software applications as required (Thiesse and Michahelles, 2009). Relevant services

may be offered by interested companies automatically, or through the manual intervention of the user, for such objects.

Maintenance Management

The primary objective of any maintenance system is to keep in efficient operating condition, the productive plant

and equipment, their auxiliaries, general engineering services, the material handling units in a good state of repair.

Different maintenance strategies of equipment like Breakdown maintenance, Preventive maintenance, Predictive

maintenance, Design out maintenance etc have evolved over a period of time, to increase the availability and reliability of

the equipment with required cost effectiveness. According to Smith and Hinchcliffe (2003), around 50 percent of machine

failures are due to human error in maintenance work. So a right maintenance method is needed which can minimize human

involvement during maintenance work.

Reliability Centered Maintenance (RCM)

Reliability centered maintenance (RCM) is a systematic cost-effective approach used to optimize preventive

maintenance (PM) strategies offering a sound framework for optimizing the maintenance effort and getting the maximum

out of the resources committed to the PM program (Ben-daya, 2000). RCM philosophy employs Preventive Maintenance,

Predictive Maintenance, Reactive maintenance and Proactive Maintenance techniques in an integrated manner to increase

the probability that a machine or component will function in the required manner over its design life cycle with a minimum

of maintenance effort. Moubray (1997) defines reliability centered maintenance as:

Reliability-Centered Maintenance: A process used to determine the maintenance requirements of any physical

asset in its operating context

Major parts of RCM process can be summarized below (Rausand, 2003):

Step 1: To identify the operating context of the machinery, and identify the common modes of failure using aFailure Mode Effects and Criticality Analysis (FMECA)

Step 2: To apply the "RCM logic" which helps determine the appropriate maintenance tasks, for each of theidentified failure modes in the FMECA. Condition based monitoring with appropriate sensors is used to monitor

the current status of the machine. Here the use of various instruments such as vibration analyzer and thermal

imaging camera etc. is made to create recorded histories of the state of various components, and thus make it

possible to identify incipient failures.

Software modules or BOTS can be made for identifying trends in recorded patterns of such data (like thermal

maps, vibration signals etc.), which signal incipient failure.


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Step 3: RCM is kept live throughout the "in-service" life of machinery, using condition based monitoring and acontinuous scanning of sensor data, using an evolving knowledge of failure patterns.

RCM is a third generation maintenance process (figure 2), which is finding a growing acceptance in factories,

cutting across industry sectors. The following section explains condition based monitoring, which is a crucial part of the

RCM process, in more detail.

Figure 2: Changing Maintenance Techniques (Moubray, 1997)

Condition Based Monitoring (CBM)

Condition monitoring or CBM is an effective form of predictive maintenance where condition of specific parts of

plant and equipment are monitored using a range of instrumentation such as machinery vibration analysis and thermal

imaging equipment etc. CBM approach has been used in various industrial applications including CNC turning machines

(Akturt and Gurel, 2007).

Figure 3: RCM and CBM Tools

Condition monitoring replaces arbitrarily timed maintenance tasks with maintenance that is scheduled only when

warranted by equipment condition (NASA Manual, 2000). Continuing analysis of equipment condition monitoring data

allows planning and scheduling of maintenance or repairs in advance of catastrophic and functional failure. In automated

CBM process, when any monitored and predefined condition limit is exceeded, a signal or output is activated, which

generates an alert or a graded alarm process (Lembede and Xulu, 2009).

Major tools used for condition Based Maintenance are (Akturt and Gurel, 2007; Lembede and Xulu, 2009; Yan

and Huang, 2009; NASA Manual, 2000): Vibration analyzer, Thermal Imaging Camera, Oil-Debris analyzer, Motor

Current Signature analyzer, Dissolved Gas Analyzer, Ultrasonic Noise Detector etc


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Use of RCM Methods in Industry

A list of some monitoring tools and methods used in condition based monitoring are given in figure 4. The NASA

manual on RCM, discusses in detail the use of the main techniques and tools. The most commonly used methods used for

CBM are vibration analysis, infrared thermography and ultrasonic noise detection (NASA Manual, 2000; Hillman and

Fitch, 2007; Al-Bedoor et al., 2003; Smith and Hinchcliffe, 2003; Moubray, 1997).

In the following section, we will discuss two small case studies based on Thermal Imaging and vibration

analysis. Then taking data from the shop floor, we will demonstrate how incipient failure can be identified from the reports

generated by these methods. We will also illustrate the logic used for pattern identification in the output data generated.

This is an essential element in the generation of self contained analyzer software modules called BOTS. These BOTS may

be used to automate the process of condition monitoring and lead to multi-level automatic alarm generation with

instructions, and these form an essential element of the proposed model for use of RCM and CBM based tools for

household appliances, as discussed in this paper.

Source:NASA Manual on RCM, 2000

Figure 4: Methods Used in Condition Based Monitoring

Thermal Imaging (Infrared Thermography)

The use of Infrared Thermography method has been growing exponentially as industries are looking to streamline

costs, especially in the areas of predictive and preventative maintenance. Infrared Thermography (IRT) is the application of

infrared detection instruments to identify pictures of temperature differences (thermogram). The test instruments used are

non-contact, line-of-sight, thermal measurement and imaging systems. IRT can be utilized to identify degrading conditions


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in facilities electrical systems such as transformers, motor control centers, switchgear, substations, switchyards, or power

lines. In mechanical systems, IRT can identify blocked flow conditions in heat exchanges, condensers, transformer cooling

radiators, and pipes (NASA Manual, 2000). Normally the equipments used are Noncontact infrared thermometers/scanners,

Full color microprocessor imaging systems (with data storage and print capability), Digital IR Still Camera etc.

Given below is an example of fault rectification in electrical sub-station equipment (Figure 5)

Source: Tata Steel

Figure 5: High Temperature in the Transmission Line Bushing

Given in figure 6 is the logic flow diagram, for automatic identification and alert generation, from the

thermographs generated when the product is scanned with an infrared camera. This logic is embedded in the form of

software tools also known as BOTS and is a part of the knowledge base created when the company goes for detailed

FMECA process, for identifying the possible failures in the product. (NASA Manual, 2000) Briefly the thermal map is

analyzed for pixel coordinates, color contrast, color spatial distribution.

This information is received with the product identification number, which is also the primary key for the

historical data for product testing, stored in the database of the manufacturer. The image is scanned pixel by pixel and the

color difference is compared against specified value (Meola, 2007). If the color difference is larger than the specified

value, then the spatial distribution of the thermogram is checked through secondary analysis through creating histograms or

wavelets for the area being checked.

The difference pattern is then compared with the historical thermogram from the database. If the difference is

significant, then a detailed screening of the image is done to identify the fault and its location and a graded alarm

mechanism is triggered. Repair instructions to AMC team may be sent if required.

Vibration Analysis

Machinery and system vibration is the periodic motion of a body about its equilibrium position. Vibration

monitoring helps determine the condition of rotating equipment and structural stability in a system. Machinery and system

vibration is the periodic motion of a body about its equilibrium position which gets affected when defects begin in the

machine.

Interpretation of the vibration signals from the machine via sensors is done which includes comparing of level and

trend of vibrations with historical baseline values such as former start-ups and shutdowns. Vibration analysis is one of best

measure a machine health amongst all the predictive maintenance technologies as it can detect significant number of


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possible failures like Wear, imbalance, misalignment, mechanical looseness, bearing damage, belt flaws, sheave and pulley

flaws, gear damage, flow turbulence, cavitations, structural resonance, fatigue, etc. (Yan and Huang, 2009, NASA Manual,

2000).

Infrared Thermography

Figure 6: Logical Flow for Analysis of Infrared Thermogram

As shown by Yan and Huang, 2009, blade vibration signature has been extracted from the shaft torsional vibration

shafts which be used to identify rotor cracks in industrial machines (Yan and Huang, 2009). One such example of detection

of bearing failure through Vibration analysis in the No Twist Mill (NTM) of a typical Wire Rod Mill is given below

(Figure 6). The why - why analysis of the possible failure mode is given in table 1.

Source: Tata Steel

Figure 7: Detection of Bearing Failure through Vibration Analysis of NTM


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Table 1: Why-Why Analysis of Abnormalities of Vibration Signals in Vibration Scan of Bearing Nearing

Failure in Washing Machine

Why-Why Analysis

Physical Phenomenon: Abnormal Vibration from Side Bearing in Washing Machine

Why Answer Action

Why 1Why there is an abnormal vibration

curve from the Bearing section

Bearing was running dry

(Starvation of lubrication)Serviceman will take out

the bearing chamber forreplacement

Why 2Why there is starvation of

lubrication

Wrong fitment of the

bearing end cover.

Why 3Why there is wrong fitment of the

bearing end cover

There is a chance of misfit

during fitting/assembly.

Why 4 Why there is a chance of misfitInadequate Bearing

housing design of motor

Company agreed to

replace the bearing with

modified bearing in motor

Root Cause : Wrong fitment of the bearing end cover & Inadequate Bearing housing design

VIBRATION ANALYZER

Figure 8: Logical Flow for Analysis of Vibration Analyzer Signal

In figure 8, the logic flow diagram, for automatic identification and alert generation, from the vibration maps

generated when the product is scanned with a vibration analyzer. This logic is again embedded in the BOTS. (Automatic

software programs)

The vibration map contains information about amplitude, frequency, time along with the product id. The

incidence of any sharp change in amplitude is monitored, and if detected, the information is analyzed using various

methods of analysis such as filtering, torsional vibration analysis, spike energy analysis etc (Hillman, B. and Fitch, M.,

2007; NASA Manual, 2000; Al- Bedoor et al., 2003). This is followed by matching the vibration with the historical map

and a detailed fault analysis is done. The output of this analysis is the triggering of a graded alarm mechanism if a problem

is detected, along with repair instructions to the AMC team.


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Model of Proposed IT Infrastructure for Application of RCM Techniques to Home Appliances Using the Internet

ofThings

The application of RCM techniques to household appliances, creates a requirement that the manufacturer of

consumer durables will keep an online record of the condition based history of the product, and that this database will be

accessible to the service engineers during the planned lifecycle of the product. The manufacturer needs a specialized

infrastructure to either continuously monitor the status of the product or to take action based on the interpretation of the

condition monitoring data sent by maintenance team. (See figure 9) This is only possible if a multi level IT infrastructure is

available, and the scenario for use of such a network (see figure 1) is given below.

This IT infrastructure model is shown in figure 9, and consists of three levels as described below:

Level - I: Built-in-Machine

This level comprises of Household appliances containing RFID and sensors which can be embedded in the

machine itself. Intelligent feedback and response devices inside the machine are capable of responding to external stimulus

by making adjustments in the operating conditions. In case of severe fault, an alarm signal can be thrown like beeping

sound. An example is the microprocessor based temperature control system, where the cooling in a refrigerator is adjusted

according to ambient conditions.

Level- II: Online Continuous Monitoring

Continuous monitoring devices installed in the equipment send product id and sensor responses in real-time to

firms continuous monitoring access networks through access gateway and internet. Intermittent reader installed at firms

end reads the signals at regular pre-determined periods.

Figure 9: IT Architecture for a 3 Layer Maintenance Management System


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Product information along with processed information goes to the internal database. There software modules

called BOTS analyze the received instrument data. They embody the knowledge base of the manufacturer regarding failure

modes for the machine. These BOTS automatically carry out the fault analysis or cause-effect analysis using a comparison

of historical and current instrument data. (See figure 4 for common types of instruments and methods, figure 6, figure 7,figure 8)

Status of the appliances health is analyzed and any change in the status leads to following:

Triggering of an alarm mechanism graded according to nature of machine and fault diagnosis. Consumers areintimated via SMS, email or phone and are requested to visit the nearest service center for repair

Repair execution commands may be sent to the response devices inside the equipment like turn off the heatingunit etc

Alarm signals can be sent to the nearest service personnel whose location can also be identified via RFID taggingTo better illustrate the working model of continuous monitoring using internet of things, the scenario a faulty car

may be used. Various sensors at critical location may be installed within a car by the manufacturer. A most commonly used

monitor is the Engine Control Unit (ECU). The ECU monitors the critical parameters of the working of an engine, such as

compression ratio, RPM (revolutions per minute), fuel usage etc. Now this unit can also transmit data using a wireless

network to the company server. The Host server receives these signals at intermittent intervals and continually monitors to

see that the parameters are within specified limits. If say, the engines petrol consumption increases without a

corresponding increase in RPM, then the alarm is triggered. Software BOTS identify the faults if any, and send back repair

commands to the car intelligent tracking system. In case of any major repair requirement, the car-owner will receive alarm

by sms or a phone call asking him to report to the nearest service station.

Level - III: Periodic Monitoring and Repair

Most home appliances are today sold with annual maintenance contracts and / or warranties on parts for a number

of years. In such products, the periodic service and checkup visit of the service engineer is used to conduct a complete

health analysis of the machine, where advanced instruments help in a multi level fault analysis of the machine at the

manufacturers end. So the service engineer now appears for annual (or semi-annual) service with sophisticated

equipments like thermal imaging camera, vibration analyzer etc.

These sensing and analyzing devices receive the signals from RFID and various other sensors which can detectand analyze the condition of the components of the machine. For example, a comparison of the vibration pattern of bearing

elements (obtained by vibration analyzersee figure 7 and figure 8) with the historical vibration pattern will yield more

information of possible changes in operating condition of the machine. Similarly, a comparison with the historical thermal

imaging data will allow the engineer to identify any new hot spots in the machine or its electrical panel, indicating

potential failure sites.

Now the maintenance team uploads the scanned reports like vibration and thermal maps along with product id to

the companys dedicated portal through internet of things. Such information is compared with previously uploaded data of

the same item and an automated program can be used to identify potential failure points, and to throw up requisite alerts

and repair instructions to the AMC team. The uploaded data is also saved in the database of the manufacturer.

This may be illustrated with a scenario describing the annual maintenance of a washing machine. Generally a

service engineer comes with minimal equipments and a few common spare parts for annual or periodic maintenance. The


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annual maintenance check consists of a few visual inspection checks on condition of machine and replacement of any

malfunctioning part or filter. The next visit may be conducted by another service engineer and the previous condition status

is lost. Each service engineer starts to look for problems afresh.

Now, in a world of internet of things, the service engineer appears with sophisticated equipments like thermal

imaging camera, vibration analyzer etc for the annual checks and maintenance. He can use a single tool or combination of

tools like vibration analysis and infrared thermography.

Vibration analysis can detect and analyze the condition of various components, including rolling-element

bearings. By analyzing vibration signatures produced by bearing components, a vibration analyst can pinpoint bearing

damage caused during operation. Any unusual pattern generated at one of these suspected frequencies is cause for

immediate concern. Thermal imaging of the machine will allow the engineer to identify the potential trouble spots (if any)

in the motor or electrical circuit (Maldague, 2001).

Through the iterative and simplified process, the engineer or technician performing the analysis is able to

determine the root cause of the problem by deducting non-indicative symptoms and conditions (NASA Manual, 2000)

CONCLUSIONS

Although advanced methods in maintenance technology are still in their infancy, multiple new technologies are

emerging and being applied to maintenance and mechanical diagnostics problems (e.g., advanced detection methods for

temperature, oil analysis, and vibration signal processing). A limiting factor in the further development of Condition Based

Monitoring continues to be a lack of high fidelity data of faults as they initiate and evolve. Despite the limitations, there is

also a growing need felt in the consumer goods industry to offer better maintenance services to clients using proactive

maintenance techniques.

While critical applications like aviation, defense, transport & delivery have been focusing on maximizing assets

using effective maintenance technology and processes, there is a growing need being felt in the consumer durables segment

to offer these capabilities as part of service agreements. These needs also arise from similar considerations as below:

Product companies are increasingly recognizing the importance of effective data tracking and trend analysis to getthe maximum benefit from their product servicing processes

They also realize that this analysis will help them keep their high value assets operational and optimized for long-term efficiency and maximum uptime

The cost of providing such a high level of monitoring and fault free service of the equipment is drasticallylowered through the use of the infrastructure of the internet of things. In the traditional service network, a

similar level of service would need the availability of a large workforce for maintaining a servicing network

across each geographical location, along with a huge inventory of spares

There is a need for the development of the following modules or units for the practical implementation of this

proposed model.

A selective pulse reader for selective timed access of continuous stream of monitored and transmitted data fromthe sensors

A knowledge framework and repository at the manufacturers end, for documenting and encoding the variousmodes of failure and the identification of signals of incipient failure in the equipment


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The need for training and equipping the service engineers to carry out advanced analysis and tests of theequipment, and to do cause effect analysis from the current and historical data

Various elements of the internet based network infrastructure are still being developed Develop procedures and knowledge base for an effective use of sensors for monitoring the various points of

failure

Advance planning and proactive steps towards setting up and exploiting the internet of things for monitoring

household appliances, may allow companies to get a medium term competitive advantage in the intensely competitive

home appliances market.

REFERENCES

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