ISSN: 2289-4519 Page 53

International Journal of Accounting & Business Management

www.ftms.edu.my/journals/index.php/journals/ijabm

Vol. 5 (No.2), November, 2017

ISSN: 2289-4519 DOI: 24924/ijabm/2017.11/v5.iss2/53.67

This work is licensed under a

Creative Commons Attribution 4.0 International License.

Research Paper

STRENGTHEN THE CRITICAL SUCCESS FACTORS (CSFs) IMPLEMENTING TOTAL PRODUCTIVE MAINTENANCE IN POWER

GENERATION INDUSTRY

Salmi bin Samsudin Othman Yeob Abdullah,

Graduate School of Business

Univesity Utara Malaysia, Malaysia

salmis@tnb.com.my

Norlena bt Hasanan Othman Yeob Abdullah,

Graduate School of Business Univesity Utara Malaysia, Malaysia

norlena@uum.edu.my

ABSTRACT

Due to the necessities for strengthen the business strategic planning, the organization scrutinize on optimizing the maintenance practices. Currently the maintenance practice is presently deliberated as main elements and becoming increasingly difficult to ignore since the impact of effective and efficient maintenance is important to increase the productivity and maximize the effectiveness of the overall equipment effectiveness. Total Productive Maintenance (TPM) is a systematic approach to understand the equipment’s function, the equipment’s relationship to the product quality and the likely cause of failure of the critical equipment conditions. Introducing TPM requires strategic planning and few studies had been made in the field of maintenance within the context of power generation industry. Consequently, organization introduced TPM as a tool for maintenance approach. TPM initiative commonly had been practice in manufacturing company but nowadays others industries used this initiative as well. Aligned with that, power generation industry started to embark on the TPM initiative to strengthen the power plant operation. This paper discusses the state of TPM implementation in Malaysian power generation industry and investigation of Critical Success Factors (CSFs) associated in implementing TPM. This paper systematically investigates the TPM CSFs through questionnaire survey to the employees which embarking the TPM in power station. The Statistical Package for Social Sciences (SPSS) software version 21 was applied to perform the required statistical analysis of the data from surveys. As results, the researcher found that the top management commitment, resource management, training and work culture is the main elements of CSF due to high score in implementing TPM in power generation industry. By identifying the TPM CSFs, the organization can improve and supervise the TPM planning and activities during implementing the TPM in power generation industry. Consequently, the successful of implementing TPM will support the organization business performance towards the operational excellent. Key Terms: Total Productive Maintenance (TPM), TPM in Industries, Power Generation Industry, Critical Success Factors

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1. INTRODUCTION

Driven by the economy demand, organization in multiple industries straggling look

for the preservation approaches on optimizing the productivity. The organization realizing the

need to increase the productivity with high effective of the machine or equipment (Brah &

Chong, 2004; McKone & Weiss, 1998; MY, 2012). Therefore, the maintenance approach

become as critical issues in order to ensure the availability and reliability of the asset. Beside

increasing the productivities, the maintenance approaches supports in maintaining and

swelling to the operational efficiency of the assets (Abdullah, 2013; Abdullah, & Rajgopal,

2013; Cigolini, & Turco, 1997). Consequently, implementing the good maintenance approach

contributes to the financial performance of the organization thru reducing the operating cost,

minimum the maintenance cost and maximizing the productivity. Thus, the maintenance

approaches support the organization growth in ensuring the product value increase and

competitive in global market. Presently, maintenance approaches such as Total Productive

Maintenance (TPM), Total Quality Maintenance (TQM), Enterprise Resource Planning

(ERP), Business Process Engineering (BPE), Just in Time (JIT) are commonly had been

practice in various organization in numerous industries (McKone & Weiss , 1998; MY,

2012). However, due to some restriction on the effort and philosophy, organization must look

up the suitable maintenance approach aligned with the organization product and sector.

Significantly by implementing the maintenance approaches, the maintenance quality is the

essential results of the product where by its affects the overall equipment performance

(Abdulmalek, Rajgopal, & Needy 2006; Ahuja, 2009; Ahuja, & Khamba, 2008; Mad Lazim,

& Ramayah, 2010 ). Therefore, the TPM initiative was introduced in industries with the

merging of operation and maintenance practice to meet the organization need.

In line with maintenance approaches, TPM well knowns as management system that

has the proven capacity when fully implemented to improve the business performance of a

production by the implementation of a safe, pleasant and productive workplace through the

optimization of people who work there and the equipment they rely on (Ahuja, 2009; Dogra,

Sharma, Sachdeva, & Dureja, 2011; McKone, & Weiss, 1998). Addition to that, the outcomes

of the TPM initiative are zero breakdown and zero defect to organization assets. Thus,

numerous scholar highlighted that to increase the availability of existing equipment and

reducing the need for further capital investment by implementing the TPM initiative (Mad

Lazim & Ramayah, 2010; Maggard, & Rhyne, 1992; McKone, & Weiss, 1998).

Nevertheless, the implementation of TPM initiative are depends on the environment factor,

organizational behavioral and organizational culture. The process of TPM implementation in

organization are obviously challenging and not all company could successfully complete the

TPM practice. Therefore, the organization must scrutinize the purpose of TPM

implementation before embarking on the TPM initiative in the organization. As mentioned

before, TPM are commonly implemented in various industries and mainly develop for

manufacturing industry. From the previous literature, Almeanaz (2010) study the TPM

implementation in steel industry while Haddad and Jaaron, (2012) has presented the research

on the TPM implementation in healthcare industry in Jordan. Thus, TPM has become highly

recognized as an approach on handling and managing the plant maintenance, plant

engineering, production improvement and product design ([Annamalai, 2011; Belassi &

Tukel, 1996). By looking at the positive impacts to the industry, TPM was implemented at

power generation by having the same goals. Realizing the system and process in power

generation industry is slightly different compare to other industries, there is need to study the

critical factors that contribute to the TPM initiative during the implementing phase.

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2. LITERATURE REVIEW

The Total Productive Maintenance (TPM) initiative was initiated in Japan in 1971,

where the concepts and method was introduced by Nippon Denso Co. Ltd of Japan, a supplier

of Toyota Motor Company. Now days, the TPM initiative and concepts start to adopt and

adept by the various industries in the world. The TPM concept presented today to assist the

organization and management in managing asset of the company (Abdulmalek et al, 2006;

Ahuja, 2009; Patterson, Kennedy, & Fredendall, 1995; Suzuki, 1994). The embarking of

TPM in industry is a concept of sustaining and improving the veracity of production,

operation, maintenance and quality systems. Therefore, the implementation of TPM initiative

is through the machines, equipment, processes, and employees is the added value to an

organization and business performance. Besides, TPM are involved with an innovative

approach to maintenance that enhances equipment value, abolishes breakdowns and promotes

autonomous maintenance by the staff through daily accomplishments relating total workforce

(Ahuja, & Khamba, 2008a; Graisa & Al-Habaibeh, 2011 ; Seng, Jantan, & Ramayah, 2005;

Shulver, n.d; Turbide, 1995).

Instead on managing assets, TPM initiative related to many other operation

management initiatives which are include Zero Defect, Lean concepts in manufacturing,

Total Quality Management (TQM), Continuous Process Improvement (CPI), and others

productivity philosophy with 5S concepts are the base foundation of the TPM initiative

(Ahuja, & Khamba, 2008a; Ahuja, & Khamba, 2008b; Belassi, & Tukel, 1996; Cigolini, &

Turco, 1997). Numerous research mentioned the business industry has practiced an

extraordinary transformation in the last three decades, including radical vicissitudes in the

organization methodologies, product and process of technologies, managing the customers

need and wants, supplier market behavior as well as competitive attitude trend (Graisa & Al-

Habaibeh, 2011; Patterson, Kennedy, & Fredendall, 1995). Besides, TPM known as

fundamental improvement program to the maintenance functions in management because

TPM involves with all staff level from the Top Management to the bottom line (Ahuja, &

Khamba, 2008a; Ahuja, & Khamba, 2008b). By referring to the TPM objective itself, TPM

initiative is to optimize the overall efficiency and effectiveness by sustaining the life-cycle of

the equipment. The TPM philosophy necessitates the development of a preventative

maintenance (PM) program and a part of asset management strategy. Thus, with good

practicing managing assets, the TPM needs the operator’s participation and involvement in

order to maintain the equipment healthier (Abdulmalek, et al, 2006; Ahuja, & Khamba,

2008a; Graisa & Al-Habaibeh, 2011; McKone, Schroeder & Cua, 2001).

To the date, the TPM concept is accepting and practicing from various industry.

People in industry believe the main goal of the TPM still the same which are guided on

managing assets and optimizing production (MY, 2012). Thus, many researchers carry out

the TPM topic in deep by looking at many subject such as TPM theoretical, TPM framework,

TPM pillars, TPM practicality and much areas. Mohammad Jafari, Lotfi, Felegari and

Hosseini (2014), from Iran studied the TPM implementation for steel industry meanwhile

Chetan, Shende, and Swapnil (2006), were carried out the case studied on TPM in the rolling

mill industry which is located in India. In Malaysia, Norddin, Zameri and Saman (2012), was

done the research in fertilizer process which implement TPM in plant industry and Badly

(2012) was carried out the TPM assessment in Malaysian Automotive SMEs. Therefore,

various study and research had been done and still continuing by the country in various sector

and industry. However, far too little attention has been paid to TPM implementation in the

utilities industry which focusing to the power generation company. The researcher believed,

utility industry is one of the key player contribute to the country growth and consequently

there is need to evaluate and validate the TPM implementation in power generation industry.

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In Malaysia, coal-fired generation represents about one-third of the installed power

generation capacity, and accounted for nearly 43% of the electricity produced in 2013. Hence

the performance and reliability of the coal-fired power plant have a significant direct impact

on the electricity supply situation in Malaysia (Energy Commission Report, Malaysia, 2015).

In fact, gas and coal remained as the command fuel for power generation at 49.4% and 42.6%

respectively, followed by hydroelectric at 4.8% and oil/distillate at 2.5%. Due to government

policy and the needy of the new market, most coal-fired power plants were operated at the

maximum level continuously since 2011 (Energy Commission Report, Malaysia, 2015). The

effect of such operation, coupled with lower quality coal and inadequate features in the boiler

design had taken a toll on most coal-fired power plants, where in 2013 the reliability of the

plants suffered heavily due to boiler tube failures which in turn contributed to significant

reduction of the availability of the coal plants. After a period of decision, Energy

Commission with the government support decided to maintain, sustain and develop steam

power plant to complete the energy demand. They compromise on developing of steam

power plant in maintaining the tariff cost and guided with high environment policy. By using

the gas and coal as types of fuel, the fuel cost on generation power will affected accordingly.

In facts, power plant life cycle is belonging to 25-year service and it’s the major asset to the

country (Energy Commission Report, Malaysia, 2015).

The coal power generations are composed with the boiler system, turbine system,

condensing and feed heating system, generator system and main transformer. The system of

the boiler purposely exchanges the coal combustion which is chemical energy into the

thermodynamic energy in the boiler through generating the steam from the boiler drum.

There are many boiler types such as a sub-critical boiler, boiler with reheater, single drum,

radiant and convectional of two-pass type superheaters, with controlled recirculation and

normal circulation. Wiser (2000) explained the Rankine cycle is the idealized cycle for steam

power plants, and could be describe as a heat engine process with a vapour power cycle. As

described by Kapooria, Kumar and Kasana (2008), the steam plant involves the process of

isentropic compression, isobaric heat supply, isentropic expansion and isobaric heat rejection.

The complexity of the process become the critical elements to the operators in ensuring the

equipment is operating in good condition. The equipment must operate with highly efficient

to produce high productivity and quality.

Realizing as main asset to the country, one of the IPPs located in Malaysia embarked

the TPM initiative. The organization start to embarked TPM initiative at the power station in

order to strategies the maintenance approach by maintaining the existing assets.

Consequently, TPM become a part of company strategy purposely to enhance strengthen the

power plant operation. The TPM steering community was initiated by the top management

purposely to drive the TPM program in station. Top management promptly promote the

TPM initiative to all levels of employees to ensure the TPM initiative deliver the objective

and goals. Since TPM launched in year 2010, the TPM program progressively implemented

among the operation staff which are responsible to operate the power plant. The TPM

program such as cleaning activities, identification of abnormalities, measuring the equipment

effectiveness, continuous improvement program, TPM competency and TPM assessment had

been done violently every year. After several years with multiple TPM program had been

instigated, the operation staff definitely adopt and practice the TPM initiative at the work

place. Furthermore, by looking at the positive impact to the organization, the researcher

believed there are restriction and critical issues facing by the origination during implement

the TPM initiative.

In order to ensure the initiative achieves the main goal, there are needs of measurable

element called Critical success factor (CSF). The CSFs described the factors that influence

the successful of the project, program, business, and activities with proper data analysis

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(Ahuja, & Khamba, 2008; Freund, 1988) . One of the pioneers in CSF research, Rockart

(1979), defined that CSF is a managerial and directional methods for managers to identify the

information needs to ensure the organization meet the main goal. CSFs could be used as

basics needs that are vital for a strategy to be successful and achievable. In steed focusing on

the relevant performance measures, Johnson, James and Michael Friesen (1995), also figured

out that CSFs involves with various factor with subject to the organization key performance

indicator. Therefore, there are needs on understanding the CFSs on the process of embarking

TPM initiative(Ahuja, & Khamba, 2008; Cigolini, & Turco, 1997). Literature on the CSFs

in TPM had been done by the previous scholar. Having says that, TPM CSFs must be

examining in order to identify the weakness and successful of the implementation. It’s part of

the implementation strategy. The restriction factor that contributed to the TPM CSFs clearly

identifies and positive action must be taken accordingly. As mentioned in the Table 2.1

below, the summary of TPM CSF by the scholar in various industry and research area.

Table 1: Summary of TPM CSFs implementation

Researcher Element and component of CSFs highlighted

Windle (1993)

Clear policy, target and effectiveness

Understanding of management plan and implementation

Employee involvement, management accountability and supervision

High quality and effective of training and education

Bamber et al. (1999) The existing organization and structure

Alignment to mission and goals

The involvement of people

An operation planning and implementation

Knowledge and beliefs of benefits

Time allocation for embark

Management commitment and obligation

Katila (2000) Education and training

Strengthen of maintenance system

Establish and perform education

Leadership and management involvement

Plan and promotional of activities

Preventive maintenance practice and policy

Managing and maintaining of data resources

Managing technology and strategy

Cua et al. (2001) Management commitment

Promotional and information

Employees motivation and inspiration

Education and training

Optimum organization function and roles

Hannson and

Backlund (2002)

Support from leadership

Strategic planning with vision and mission

Implementation of planning and program

Buying in and empowerment of people

Training and education

Communication and information

Monitoring and Evaluation

Seth and Tripathi

(2005)

Focus on customer satisfaction

Leadership for improvement

Strategic planning for improvement

Education and training

Information architecture

Performance measurement system

Material management and resources

Equipment and assets management

Process management and improvement

Financial resources and budgeting

Rodrigues and

Hatakeyama (2006) Implementation of 5S

Organizational operation and self-maintenance

Continuous education and training

Top management support and participant

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Siong and Ahmed

(2007)

Management support and assistance

Employee participation and contribution

Knowledge and skill of the employees

Training and education

Maintenance strategy and policy

Supplier support and sustaining

Ahuja and Khamba

(2008b)

Top management contribution and support

Cultural transformation from among staff

Employee involvement and participant

Traditional and Pro-Active maintenance policy

Training and education

Maintenance prevention and focused production system improvement

Badli Shah (2012) Top management commitment

Resource management and supply

Performance measurement system

Continuous improvement system

Education and training

Work culture and involvement

Therefore, by looking at all the CSFs mentioned by the scholars, there are essential

things to carry out the CSFs assessment. CSFs indicate the willingness of various factors

which contribute to the successful of TPM initiative (Ahuja, & Khamba, 2008; Dogra,

Sharma, Sachdeva, & Dureja, 2011; Maggard, & Rhyne, 1992). The proactive action must be

taken to cater the weakness during TPM program to ensure the objective is achievable.

However, the different organization will have the different difficulties and restriction and

subject to the types of industry (Ahuja, & Khamba, 2008;). Hence, the researcher interest to

find out and analyzed the fissure in implementing TPM between industries. The main gap is

the TPM initiative basically implements at manufacturing industry but not at the process

industry.

3. RESEARCH DESIGN AND METHODOLOGY

Realizing the criticality in implementing TPM initiative in industry, the researcher

attention to conduct this study to find the critical factors. According to Boynton, and Zmud

(1984), the critical factors is a management term for an element that is necessary for an

organization achieving their program objectives.

"Critical success factors are those few things that must go well to ensure success for a

manager or an organization, and, therefore, they represent those managerial or enterprise

area, that must be given special and continual attention to bring about high performance.

CSFs include issues vital to an organization's current operating activities and to its future

success."

Nevertheless, due to little research piloted in this area of power generation industry,

the researcher has been conducted the through questionnaire to determine the TPM CSFs in

power generation industry. Based on the previous literature, there are four critical factors

could influence the successful of TPM implementation which gives significant impact to the

business performance in the context of power generation industry. The research hypothesis

was developed purposely to explain the correlation stated in the research objective which

consist of concepts. The research hypotheses purposely develop to carry out the empirical

testing which is explaining below:

Research Hypothesis 1: The top management roles and responsibilities on the TPM

activities not affect to the business performance.

Research Hypothesis 2: The resource management contribution for the TPM activities

not gives the significant impact to the business performance.

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Research Hypothesis 3: The training and education of TPM to the employees not give

significant affects to the business performance.

Research Hypothesis 4: The TPM work culture not affect to the business performance

power generation industry.

From the hypothesis, the theoretical framework had been developing accordingly.

Figure 3.1 shows the relationship of the critical factors in implementing the TPM to the

business performance.

Figure 1: Theoretical framework for this study

Unit of analysis described as the single element or group of elements subject to

selection in the sample. Unit of analysis is definite as the level of aggregation of the data

collected during the subsequent data analysis stage. For this research, the unit of analysis is

from the power generation company which are embarking TPM initiative. In deep detailed

during this study was carried out, the employees from operation department only carried out

the TPM initiative. Therefore, the questionnaire was distributed to the employees who are

attached at the operation department. The target population for this study is 50 percent of the

total staff attached at operation department.

The Statistical Package for the Social Science (SPSS) software was applied to

perform required statistical analysis of the data from the distributed questionnaire. Before the

statistical analysis was conducted it was necessary to first evaluate the reliability and validity

of the instruments to ensure that the finding would be reliable and valid. The management of

the company, the TPM facilitator, TPM expert, and TPM community was validate the

questionnaire before distributed to the respondent.

4. Results and Discussion

From the survey exercise, 100 respondents out of 150 employees in operation

department response to the survey questionnaire. This response rate is 66.7% and it is mainly

being completed by the employees involves in the TPM activities at the workplace.

According to Sekaran (2003) respondents to the survey questionnaire is enough if the sample

size is from 30 to 500 respondents and is sufficient to review and depends on the population

of the selective research area.

In the beginning, the normality test was carried out for this study purposely to ensure

there are no extreme scores on an individual variable, or on a set of variables, that they will

distort the overall results. In addition, the normality test deliberately to examine the data

distribution and to identify the likely data pattern distribution. Therefore, the researcher

carries out normality test descriptive analysis for each dimension. Before analysis the

dimension, the researcher came out with summary analysis for the normality test presented in

Top management

Resource management

Work Culture

Training and education

Business

Performance

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Table 4.1. which is intentionally to ensure there are no missing data and the data validity is

high for each of the dimension in the normality test. After carried out the summary of

normality test, the researcher continues proceed the normality analysis by looking at each of

dimension as presented in Table 4.1 also.

Table 2: Construct normality statistical results

Construct Normality, N

(Valid)

Mean Standard

error

Skewness Kurtosis

Top Management 100 3.6600 0.8854 -1.164 2.176

Continuous Improvement 100 3.6580 0.7896 -1.357 2.818

Resources Management 100 3.6245 0.7440 -1.118 2.310

Training and Awareness 100 3.5783 0.7402 -1.037 2.190

Work Culture 100 3.5833 0.8546 -0.846 1.276

General Question 100 3.6960 0.7931 -1.453 3.589

The mean for management result is 3.66 which indicate that normality of mean with

the standard error is 0.8554. The probability distribution skewness is -1.164 and it means the

distribution is skewed to the left. Besides that, it can be explained the mean of the construct is

less than mode. Kurtosis value for management is 2.176 and it means the distribution

produces fewer and less extreme outliers than does the normal distribution. For continuous

improvement construct, the skweness value is -1.357 which means the distribution curve is

skewed to the left. Due to that, the mean is usually less than the median and the few low

scores tend to shift the mean to the left. The mean for continuous improvement is 3.658 and

the kurtosis value is 2.817. The kurtosis value is close to 3 which is normal distribution for

univariate. The skewness for training is -1.037 which is at negative value and its mean the

distribution skewed to the left with the standard error value is 0.241. The kurtosis value is

2.817 and close to 3 which is normal distribution for univariate. The skewness for resource

management is -1.118 negative and its mean the distribution skewed to the left with the

standard error value is 0.241. The kurtosis value is 2.310 and close to 3 which is normal

distribution for univariate. The mean for work culture normality test is 3.5833 and the

skewness for work culture is -0.846 negative and its mean the distribution skewed to the left

with the standard error value is 0.241. The skewness value is less than -1.0 and can

acceptable because it close to 0. Its means the respondent realized that the culture could be

one of the factor influence the TPM activities. The kurtosis value is 1.276 which is quit far

from the normal distribution which is at 3.0 values. Besides, the descriptive normality test for

general question asked to the respondent also presented in the normality test. The kurtosis

value is 3.589 and the skewness value is -1.453 where the distribution is skewed to negative

distribution. The kurtosis reading is closed to 3.0 which is normal distribution peak.

The researcher carried out the KMO and Bartlett’s Test of Sphericity in order to

measure of sampling adequacy which indicates the variable ratio for the analysis being

conducted. In most academic and business studies, KMO & Bartlett’s test plays an important

role for accepting the sample adequacy. Table 4.2 shows the KMO and Bartlett’s Test for this

research. For this research, the KMO of Sampling Adequacy is 0.919 and within the

acceptable range. Besides, the Bartlett’s test of sphericity results is 0 which mean the result is

more than 0.005. Its mean the data significantly meaningful to carried out the further analysis

for this research.

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Table 3: KMO and Bartlett’s Test

Nevertheless, the researcher carried out Cronbach's alpha analysis. Cronbach's alpha

is a measure of internal consistency, that is, how closely related a set of items are as a group.

It is considered to be a measure of scale reliability. A "high" value for alpha does not imply

that the measure is unidimensional. If, in addition to measuring internal consistency, you

wish to provide evidence that the scale in question is unidimensional, additional analyses can

be performed. Due to that reason, the reliability test, the researcher carried out Cronbach

Alpha test for all the constructive. Table 3 showed the analytical result test for Cronbach

alpha α for all dimensions.

Table 4: Cronbach Alpha results

Dimension Cronbach Alpha No of item

Top Management 0.945 7

Resource Management 0.961 11

Training and education 0.924 6

Work Culture 0.934 6

Continuous Improvement 0.959 10

The result for Hypothesis 1 Top management shows Cronbach alpha α is more than

0.9 with the value is 0.945 at the excellent value. The high value for Cronbach alpha

represents the reliability of the scores. The Hypothesis 2 on the resource management

presents Cronbach alpha α value is more than 0.9 at 0.961 at the excellent value. The high

value for Cronbach alpha represents the reliability of the scores. Hypothesis 3 regarding the

training shows Cronbach alpha α is more than 0.9 with the value is 0.924 at the excellent

range. The high value for Cronbach alpha represents the reliability of the scores. For the

construct, work culture which is the Hypothesis 4 shows Cronbach Alpha α is more than 0.9

with the value is 0.934 at the excellent range also. In addition, the high value for Cronbach

alpha represents the reliability of the scores for the dimension. In addition, the researcher

carries out the Cronbach Alpha test for independence variables. Result shows the Cronbach

alpha α is more than 0.9 with the value is 0.959 at the excellent range which mean high

reliability and high consistency of the measurements.

In intention to evaluate the significant of the independent variables and dependent

variables, the multiple regression applied for this study. The multiple regressions used for

prediction and for this case the DV is explain by 4IVs. Table 4.4 below represents the

descriptive statistics for each of the dimension by calculating the mean and standard

deviation.

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Table 5: Descriptive analysis for multiple regressions

The researcher found that the proposed model is a good descriptor of the relationship

between the dependent and predictor variables. This is because given the R-square value of

0.823 implies that the four predictor variables explain about 82.3% of the variance in the

CSFs. Therefore, it is a quite good and respectable result. Table 4.5 show the model summary

for multiple regressions which is represents the R-square and df.

Table 6: Model summary for multiple regressions

The ANOVA table below shows that the F value is 110. The ANOVA Table 6 shows

p is 0.00, df is 4 and F value is 110.264. Due to that, the decision is to reject the null

hypothesis and support the alternate hypothesis. The researcher develops the model from the

multiple regressions then.

Table 7: ANOVA for multiple regression

Based on the coefficients results showed in Table 8, the intercept constant value for

the multiple regression model is 0.272, constant value for management is 0.527, constant

value for training is 0.417, constant value for work culture is -0.016 and constant value for

resources is 0.018.

Table 8: Multiple regression coefficient

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Table 9 represent the multiple regression residual statisic with the continous

improvement as dependent variables. The analysis also shown the mean for the predicted

value and the R-suqare for the mulitple regression. Besides that, the mahal distance means is

3.96 and cook distance means is 0.074. The mahalanobis is represent the distance between a

point mean to the regression line.

Table 9: Multiple regression residual statisic

The researcher comes out with distribution plot thru the equation and prediction from

the model. As presented below, the dependent variable is continuous improvement as

constant variables. The prediction is coming from the 4 IVs which consist with management,

training, work culture and resources.

During the data analysis, the study also carried out the T-test to find the significant

different between 2 groups which are executive and non-executive. The t-test tells us if the

variation between two groups is significant between executive and non-executive. In deep,

purposely the comparison is involving the different level of job descriptions, task and level of

educations. The table 10 shows the group statistic between executive and non-executive.

Table 10: Group statistic for Independent test

Ratio between both groups is 90:10 which are presented 90% of the respondent from

non-executive and 10% of the respondent is coming from executive. In general, the results

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show in the Table 10 shows significant values are more 0.05 for all dimensions between

which mean there are no significant between 2 groups.

In detail show at Table 11, by looking at management dimension on t-test analysis,

give the F value is 3.309, the corresponding p-value (p=0.072), which is above the alpha

value of 0.05. As such, the researcher failed to reject the null hypothesis of equal variance

and therefore report the equal variances assumed t-value. In the test equality for means

column, the p value is 0.774 which is bigger than alpha value 0.05. Therefore, the researcher

accepts the null hypothesis and rejects the alternate hypothesis (H1: There is a different in the

level of management for executive and non-executive).

Table 11: Independent sample test

In total by looking at the Levene,s test for equality of variances, the p value for all

dimensions is bigger than alpha value 0.05 except foe management dimension. Therefore, the

researcher accepts the null hypothesis and rejects the alternate hypothesis. It can have

concluded that there is no significant level of dimension for, continuous improvement,

training, resources, and work culture for executive and non-executive. Besides, by looking at

the t-test equality for means column, the p value for all dimensions is bigger than alpha value

0.05. Therefore, the researcher accepts the null hypothesis and rejects the alternate

hypothesis. It can be concluded that there is no significant level of dimension for

management, continuous improvement, training, resources, and work culture for executive

and non-executive.

5. CONCLUSION

This study deliberated the theory development on the critical success factors on

implementing TPM in power generation industry in order to increase the business

performance. There is much research that highlighted that the need of Top Management

commitment in ensuring successful of TPM implementation in various industries. Therefore,

the researcher believed the Top Management is the key factors on driving and organizing the

TPM initiative. Besides that, the researcher interest to examine the Top Management

capabilities on energizing the new initiative. In fact, there is important on realizing the top

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management roles and responsibilities which contribute to the business performance. The

resource management which is consists of production resource, material resource, human

resource, financial resource, technology resource and information resource. Resource

management is the essential factor which is supporting the organization towards the business

performance. The resource management is an important mechanism organizing the material,

human resource and budgeting in order to ensure the successful of implementing the TPM

initiative. In technical perspective, this activity also involves in supporting the equipment

performance, reliability and engineering of the machine. By looking at the power plant

business orientation, there is different business operation compared with the manufacturing

industry. Therefore, it is important to understanding and examines the resource management

factors contribute to the TPM activities in power generation industry on improving the

business performance. The TPM philosophy could easily be understood by employees and an

organization should be innovative to copy the TPM practices and procedures from other

industries. However, the organization need to carry out training in order to ensure employee

full awareness of the TPM initiative. Due to that, there is important to investigate the need of

training and education to the employees during implementing TPM in ensuring the benefits to

the business performance for the power generation industry. The researcher believes training

mechanism is the tools on delivering the message to the employees. During the initiating of

the TPM initiative, employee’s involvement towards the work culture change is the most

important on supporting the organization maintenance approach. The employee willingness

on changing the work culture environment to the TPM implementation will show the support

to the top management. Thus, there is need to investigate the impacts on the employee’s

involvement during TPM implementation for enhancing the power generation business

performance. After making some modification on the TPM practices, the power generation

industry in Malaysia slowly adopts and adapts the TPM initiative. However, there are

difficulties experiences in enhancing the TPM initiative at the power generation industry in

Malaysia. Supported by Cooke (2000), most of the organization failed to completion the

TPM process because the TPM process is too complex. Due to that, the researcher

recommends the Critical Success Factors (CSFs) for the TPM implementation which could

impact to the power generation business performance. Thus, the researcher proposes the top

management, resource management, training and work culture is the main CSFs in embarking

the TPM in the organization.

REFERENCES

Abdullah, F. (2003). Lean manufacturing tools and techniques in the process industry with a focus on

steel (Doctoral dissertation, University of Pittsburgh)

Abdullah, F., & Rajgopal, J. (2003, January). Lean manufacturing in the process industry. In IIE

Annual Conference. Proceedings (p. 1). Institute of Industrial Engineers-Publisher.

Abdulmalek, F. A., Rajgopal, J., & Needy, K. L. (2006). A classification scheme for the process

industry to guide the implementation of lean. Engineering Management Journal, 18(2), 15-25.

Ahuja, I. P. S. (2009). Total productive maintenance. In Handbook of Maintenance Management and

Engineering (pp. 417-459). Springer London.

Ahuja, I. P. S., & Khamba, J. S. (2008a). Assessment of contributions of successful TPM initiatives

towards competitive manufacturing. Journal of Quality in Maintenance Engineering, 14(4),

356-374.

ISSN: 2289-4519 Page 66

Ahuja, I. P. S., & Khamba, J. S. (2008b). Total productive maintenance: literature review and

directions. International Journal of Quality & Reliability Management, 25(7), 709-756.

Ahuja, I.P.S. and Khamba, J.S., (2008c). Strategies and success factors for overcoming challenges in

TPM implementation in Indian manufacturing industry. Journal of Quality in Maintenance

Engineering, 14(2), pp.123-147.

Ahuja, I. S., Khamba, J. S., & Choudhary, R. (2006), January). Improved organizational behavior

through strategic total productive maintenance implementation. In ASME 2006 International

Mechanical Engineering Congress and Exposition (pp. 91-98). American Society of

Mechanical Engineers.

Annamalai, V. E. (2011). Managing knowledge in a process industry: some experiences and a

framework. International Journal of Business Information Systems, 7(3), 269-285.

Belassi, W. and Tukel, O.I., 1996. A new framework for determining critical success/failure factors in

projects. International journal of project management, 14(3), pp.141-151.

Becker, J. E. (2001). Implementing 5S: To promote safety & housekeeping. Professional Safety,

46(8), 29.

Brah, S. A., & Chong, W. K. (2004). Relationship between total productive maintenance and

performance. International Journal of Production Research,42(12), 2383-2401.

Chan, F. T. S., Lau, H. C. W., Ip, R. W. L., Chan, H. K., & Kong, S. (2005). Implementation of total

productive maintenance: A case study. International Journal of Production Economics, 95(1),

71-94.

Chen, T. L. (2009). Real-time turbine maintenance system. Expert Systems with Applications, 36(4),

8676-8681.

Cigolini, R., & Turco, F. (1997). Total productive maintenance practices: a survey in Italy. Journal of

Quality in Maintenance Engineering, 3(4), 259-272.

Dogra, M., Sharma, V. S., Sachdeva, A., & Dureja, J. S. (2011). TPM–a key strategy for productivity

improvement in process industry. Journal of Engineering Science and Technology, 6(1), 1-16.

Energy Commission Report, Malaysia (2015)

Freund, Y.P., 1988. Critical success factors. Planning Review, 16(4), pp.20-23.

Graisa, M., & Al-Habaibeh, A. (2011). An investigation into current production challenges facing the

Libyan cement industry and the need for innovative total productive maintenance (TPM)

strategy. Journal of Manufacturing Technology Management, 22(4), 541-558.

Kumar, P., Varambally, K. V. M., & Rodrigues, L. L. (2012). A Methodology for Implementing Total

Productive Maintenance in Manufacturing Industries–A Case Study. International Journal of

Engineering Research and Development, 5(2), 32-39.

Mad Lazim, H., & Ramayah, T. (2010). Maintenance strategy in Malaysian manufacturing

companies: a total productive maintenance (TPM) approach.Business Strategy Series, 11(6),

387-396.

Maggard, B. N., & Rhyne, D. M. (1992). Total productive maintenance: a timely integration of

production and maintenance. Production and Inventory Management Journal, 33(4), 6.

McKone, K. E., & Weiss, E. N. (1998). TPM: planned and autonomous maintenance: bridging the gap

between practice and research. Production and Operations Management, 7(4), 335-351.

ISSN: 2289-4519 Page 67

McKone, K. E., Schroeder, R. G., & Cua, K. O. (2001). The impact of total productive maintenance

practices on manufacturing performance. Journal of operations management, 19(1), 39-58.

Mobley, R. K. (2002). An introduction to predictive maintenance. Butterworth-Heinemann.

MY, B.S., 2012. Total productive maintenance: a study of Malaysian automotive SMEs.

In Proceedings of the World Congress on Engineering (Vol. 3).

Patterson, J. W., Fredendall, L. D., Kennedy, W. J., & McGee, A. (1996). Adapting total productive

maintenance to Asten, Inc. Production and Inventory Management Journal, 37(4), 32.

Patterson, J. W., Kennedy, W. J., & Fredendall, L. D. (1995). Total productive maintenance is not for

this company. Production and Inventory Management Journal, 36(2), 61.

Pool, A., Wijngaard, J., & Van der Zee, D. J. (2011). Lean planning in the semi-process industry, a

case study. International Journal of Production Economics, 131(1), 194-203.

Schuman, C. A., & Brent, A. C. (2005). Asset life cycle management: towards improving physical

asset performance in the process industry. International Journal of Operations & Production

Management, 25(6), 566-579.

Seng, O. Y., Jantan, M., & Ramayah, T. (2005). Implementing total productive maintenance (TPM) in

Malaysian manufacturing organization: an operational strategy study. The ICFAI Journal of

Operations Management,4(2), 53-62.

Shulver, M. Total Productive Maintenance. Wiley Encyclopedia of Management.

Söderholm, P., Holmgren, M., & Klefsjö, B. (2007). A process view of maintenance and its

stakeholders. Journal of Quality in Maintenance Engineering, 13(1), 19-32.

Starr, A., & Ball, A. (2000). Systems integration in maintenance engineering. Proceedings of the

Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering,

214(2), 79-85.

Suzuki, T. (1994). TPM in process industries. Productivity Press.

Swanson, L. (1997). An empirical study of the relationship between production technology and

maintenance management. International Journal of Production Economics, 53(2), 191-207.

Turbide, D. A. (1995). Japan's new advantage: total productive maintenance.Quality Progress, 28(3),

121.

Venkatesh, J. (2007). An introduction to total productive maintenance (TPM).The plant maintenance

resource center, 3-20.

Waeyenbergh, G., & Pintelon, L. (2002). A framework for maintenance concept development.

International journal of production economics, 77(3), 299-313.

Willmott, P., & McCarthy, D. (2000). TPM-A Route to World Class Performance: A Route to World

Class Performance. Newnes.

Wireman, T. (2004). Total productive maintenance. Industrial Press.

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