Impactsofcomputerized maintenancemanagementsystem andrelevantsupportive organizationalfactorsontotal productivemaintenance

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Impacts of computerized
maintenance management system
and relevant supportive
organizational factors on total
productive maintenance
Hadi Balouei Jamkhaneh
Department of Management, University of Mazandaran, Sari, Iran
Javad Khazaei Pool
Department of Management, University of Isfahan, Isfahan, Iran
Seyed Mohammad Sadegh Khaksar
La Trobe Business School, Department of Management, Sport and Tourism,
La Trobe University, Bendigo, Australia
S. Mohammad Arabzad
Najafabad Branch, Islamic Azad University, Isfahan, Iran, and
Reza Verij Kazemi
Department of Management, Islamic Azad University, Chalus Branch,
Chalus, Iran
Abstract
Purpose – The application of automated systems is rapidly increasing in different industries and
organizations. In this regard, computerized maintenance management systems (CMMS) using information
technology play an important role in the automating production systems. The purpose of this paper is to
investigate the impacts of CMMSs and relevant supportive organizational factors on the effectiveness of total
productive maintenance.
Design/methodology/approach – This study is classified as a quantitative survey-based research using
structural equation modeling. The scope of the study includes manufacturing companies in Iran. A total of
125 questionnaires from 60 companies were collected from January to March 2014 to help validate the
conceptual model and test the hypotheses.
Findings – The results support the concept CMMSs positively relates to relevant supportive organizational
factors (resource allocation, decision-making structure, senior management support, employees’ involvement
and effective instruction) on the effectiveness of total productive maintenance. The relevant supportive
organizational factors can also be seen as the predictors of CMMSs.
Originality/value – This study integrates the CMMSs and relevant supportive organizational factors in a
robust model to examine the effectiveness of total productive maintenance. This study also examines the
impacts of CMMSs and relevant supportive organizational factors on total productive maintenance which
seems to not be done previously.
Keywords Computerized maintenance management system (CMMS),
Relevant supportive organizational factors, Total productive maintenance (TPM)
Paper type Research paper
1. Introduction
Nowadays, one of the essential foundations in the manufacturing industry is undoubtedly
industrial machineries and systems. The growing trends in productivity and efficiency of
production as well as achieving international standards, particularly in the domestic and
global competitive environments may not be imaginable without time management in
Benchmarking: An International
Journal
Vol. 25 No. 7, 2018
pp. 2230-2247
© Emerald Publishing Limited
1463-5771
DOI 10.1108/BIJ-05-2016-0072
Received 26 May 2016
Revised 25 June 2017
Accepted 7 August 2017
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/1463-5771.htm
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application and operation of industrial machineries and production systems, and cost
management in reducing maintenance expenditures and downtimes (Rostamiyan, 2006).
Due to the advancement of technology in recent years, operation, maintenance and repair
of machineries and systems, particularly in terms of technical protection and optimization of
physical assets have gradually changed. Organizations are now more aware of the efficiency
of technology in system failure prevention, because these failures can be a warning of
production stop, loss of customers and reduction of market share, personnel unemployment,
etc. According to Tavakkoli-Moghaddam et al. (2009), organizations are required to improve
their understanding of an appropriate maintenance program and implement the program to
remain competitive in the market. The literature shows organizations must consider that
damages and downtimes of machineries and industrial installations are not an issue that can
completely be prevented. However, less attention has been paid to developing
planning techniques that can assure reliability across the value chain (Fraser et al., 2015).
It is important because the lack of reliability in systems imposes pressure to organizations to
improve overall business performance. For this reason, the relevant literature on maintenance
emphasizes the utility of systems such as computerized maintenance management system
(CMMS), reliability centered maintenance (RCM) and Total Productive Maintenance (TPM)
may increase reliability (Fernandz et al., 2003).
New trend of Maintenance activities is moving to a very complex environment known as
repair engineering which requires organizations to look at the systems from a broader
perspective. The main features of this trend is likely to be rapid expansion of outsourcing
and requesting a broader cooperation from exploitation personnel, as discussed in the
maintenance methods, TPM and implementation criteria. As discussed in the literature, it is
projected that in near future, CMMS would undertake a greater role in the management of
maintenance and repair activities in more effective and efficient ways (Garg and Deshmukh,
2006; Uysal and Tosun, 2012). In fact, the CMMS plays a fundamental role in solving the
problem of huge amounts of data accumulated in the organization, although, due to
the difficulties inherent in their structures, the use of this data is not always possible
(Litprot and Palarchio, 2000).
Homsi (1995) determined that a prerequisite for successful implementation of TPM is a
CMMS to be utilized for managing maintenance information and implementing procedures
of CMMS. Bohoris et al. (1995) discussed how Land-Rover as one of the leading companies in
the UK utilizes TPM by implementing a CMMS. They found the implementation steps of
TPM, the difficulties encountered, and the usefulness and necessity of a CMMS for the
successful implementation of TPM in Land-Rover (Bohoris et al., 1995). Labib (2004)
investigated the characteristics of CMMSs to identify their demands and current deficiencies
in manufacturing industry. An implication was to identify the need for information to aid
maintenance, followed by justifications for current deficiencies in existing off-the‐shelf
CMMSs. Similarly, Ahuja and Khamba (2008) examined factors influencing the
implementation of TPM practices in the Indian manufacturing industry, and to devise an
overall maintenance strategy for overcoming obstacles to successful TPM implementation.
Ying (2008) analyzed TPM and RCM synergic relationship using their benefits and
barriers in a system and constructed the CMMS. An integrated system can combine the RCM
analysis process, the situation of implementing TPM and the plant assets information
together to attain the purpose of changing the maintenance strategy dynamically based on the
plant’s operation condition. Rahim et al. (2014) examined the TPM as a significant technique to
improve the maintenance management of production equipment. Also, they dealt with the
relationship between TPM and existing techniques in maintenance management such as
CMMS. Lopes et al. (2016) presented an ongoing project aiming to develop a CMMS for a
manufacturing company and reviewed the requirements specification of a CMMS using a case
study research. Further, they described the crucial phases of a project, including the
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identification of requirements and the specifications of the system, to show how the CMMS
applied and reflected its effectiveness and efficiency (Lopes et al., 2016). The application of
information technology certainly provides the possibility of optimizing preventive repair
activities. Often, only after complementation of installation, users may understand that their
new system does not fully meet their requirements. In fact, prospective users must be
prepared to express what they expect from the CMMS, although they are not commonly able
to evaluate an objectivejudgment and choose suitable software.
This study attempts to fill this gap by proposing a conceptual model as how CMMS and
relevant supportive organizational factors can affect the TPM. This study contributes to
expand knowledge on the mentioned issue, as it has been neglected in previous research.
More specifically, this study helps further research to look thoroughly at the implementation
of CMMS in different contexts by identifying uncertain aspects of the CMMS and
relevant supportive organizational factors and evaluating its relationship to the TPM. It is
important because investigations on relationships among these three variables (CMMS,
relevant supportive organizational factors and TPM) may reveal how an organization would
rely on systematic and rigorous implementation of maintenance strategies to advance its
organizational objectives and ensure competitiveness over the long term.
2. Theoretical framework
2.1 Computerized maintenance management system (CMMS)
CMMS are using increasingly in control and maintenance management for machineries in
servicing and producing in different industries. The principals of CMMS were used for the
first time in the hospital maintenance systems in which machinery malfunction may have
serious impacts of human life (Saharkhiz et al., 2012). Currently, companies consider the
importance of maintenance management systems as a tool for enhancing the total
performance in their systems (Enciso-Medina et al., 2011; Tätilä et al., 2014; Hooi and Leong,
2017). The emergence of smart devices in past few years has caused the popularity of these
systems in different industries such as healthcare, automobile and aircraft (Shahin and
Ghazifard, 2013; Tripathi and Tripathi, 2013; Irizarry et al., 2014).
A CMMS is a software program designed to assist planning, management and
administrative functions required for effective maintenance and repairs. Bagadia (2006)
categorized these functions in production, planning and reporting work orders, developing
record tracking and recording parts of transactions. According to Tretten and Karim (2014),
a CMMS is not only a control tool of maintenance, but also, it is to ensure high quality of
outputs by utilizing appropriate maintenance activities over time. Seemingly, one of the
most significant benefits that a CMMS can provide for manufacturing industries is that it
helps the organization to focus and investigate good repair experiences. Generally, the
current CMMSs have been presented as modular configuration to ensure greater flexibility
and good compatibility in various fields of production (Mather, 2003; Braglia et al., 2006).
As the technical skills of maintenance and repair employees became better over time, the
respect to such systems as an interesting option becomes more important. That is,
investments on CMMSs in large and advanced organizations are increasingly growing.
Technically, these systems are designed in a manner that provides significant support for
documentations control through ISO 9001:2008 (Sivaram et al., 2012; Kedaria and
Deshpande, 2014; Tretten and Karim, 2014). Many of the existing CMMSs have the same
efficiency, and common components which are provided by many CMMS software
applications (Saharkhiz et al., 2012).
The application of a CMMS can create many advantages for an organization. One of the
greatest benefits is to remove manual paper works and to monitor system activities
leading to improved productivity (Ramachandra et al., 2012; Shahin and Ghazifard, 2013).
It is noteworthy that the functionality of a CMMS is the ability to collect and store
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customized information in the required form, as requested by the user (Uysal and
Tosun, 2012). A CMMS does not assist for maintenance decisions, rather provides
customized information for managers of operations systems to effectively influence service
delivery and efficiently remain the system long-lasting. Generally, the advantages of the
implementation of a CMMS can be seen as follows (Bagadia, 2006):
• maintaining optimum device performance by reducing downtimes and resulting in a
longer-lasting machinery;
• diagnose the imminent problems rather than detecting the errors while happening,
whereby resulting in less failures and customer complaints;
• achieve a higher level of planned maintenance activities that allow more efficient use
of personal resources;
• influence enablers that better anticipate inventory management and purchase of
spare parts for removing the deficiency and minimizing existing stocks; and
• maintain optimum performance of the device by reducing downtimes and resulting in
a longer lifetime of the device.
2.2 Relevant supportive organizational factors
A critical review of previous studies on factors affecting the success of maintenance, repair
and computerized systems shows five effective supportive organizational factors (Ang et al.,
2001; Rouibah et al., 2009; Aref et al., 2013). These five factors include resource allocation,
decision-making structure, senior management support, employees’ involvement and
effective training. Each of these factors is briefly described below.
2.2.1 Resource allocation. One of the factors affecting the success of information systems
is allocating sufficient resources. Ein-Dor and Segev (1978) suggested that resources such as
money, qualified manpower and time are required for success in projects. Allocating
adequate resources to information systems activities leads to an increase in organizational
commitment and overwhelming organizational barriers (Beath, 1991).
2.2.2 Decision-making structure. Decision-making structure indicates the degree of
control or authority to decide in the organization and the participation of employees in
decision-making relating to the information systems (Hage and Aiken, 1969).
A decentralized decision-making structure is one of the factors facilitating the
implementation of IT systems in large and complex organizations (Boynton et al., 1994).
Since the organizational structure establishes organizational processes and
decision frameworks, a highly centralized organizational structure is likely to be
more successful in the application of information systems (King and Sabherwal, 1992).
Such justifications prove that the decision-making structure is a factor that affects the
success of information systems.
2.2.3 Senior management support. Senior management support describes organization’s
top-level managers’ participation in the information systems activities ( Jarvenpa and Ives,
1991). King and Teo (1996) acknowledged that senior management support facilitates the
successful development of strategic information systems applications, while a lack of
support prevents the strategic application of information systems. Similarly, Cho (2007)
investigated the effect of leadership on the success of information systems and indicated
that the leadership supports improved information systems in organizations through
creating favorable circumstances and encouraging employees to use them at work.
2.2.4 Employees’ involvement. Organizations seek flexibility in response to a growing
trend of the application of advanced technology at workplace. It is clear that organizations
must consider employees’ involvement in decision-making processes as an essential way to
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acquire a broader knowledge at work to better identify and understand organizational
requirements in information systems. Latham et al. (1994) claim that employees’
involvement has a motivational effect on their employees’ satisfaction and commitment,
leading to an increase in their responsibility toward maintenance of the machineries that
they work with and eventually resulting in continuous success of TPM in organizations.
Similarly, a research by Ahuja and Khamba (2008) revealed that an increasing in employees’
involvement often leads to lower costs of procurement, maintenance and production and
optimized layers of different business sectors of anorganization.
2.2.5 Effective instruction. There is no doubt that the effectiveness of instruction can
improve the quality of information systems, but it requires complex situations for the
organizations to meet significant changes rationally in accordance with adopting
information systems to facilitate organizational achievements. However, organizations are
required to consider the way that the applied instruction is needed to be prepared,
implemented, analyzed and assessed, to increase its effectiveness and efficiency.
Thiagarajan and Zairi (1997) contended that instruction is the second most important
factor (after commitment) for the successful implementation of TPM in an organizational
context. So, employees must be essentially trained for understanding the effective
implementation of TPM.
2.3 Total productive management
As a pioneer of total productive management in 1940s and 1950s, Japan strived to
practically take advantage of theories and assumptions of preventive maintenance (PM) to
optimize equipment maintenance systems through establishing Japanese culture with
elements of teamwork, cooperation and responsibility, which was later known as the TPM
approach (Ramesh et al., 2008). This innovative approach was rapidly globalized and
consequently supported by industry owners (Sharma and Singh, 2015) to reduce costs of
maintenance and increase functionality of systems (Figure 1).
TPM is a program with focus on innovative methods of machinery maintenance and
repair in the entire process. This program is developed to improve production, reduce
production time and increase employee satisfaction (Fraser, 2014; Upadhye et al., 2009;
Ramesh et al., 2008). Successful implementation of TPM in organizations is not only a
subject to outlining the procedures and techniques required to implement it, but also it
should also benefit from the intangible effects of TPM’s foundational philosophy
such as good impression to customers about the company, its products’ quality and
reliability (Ahmed et al., 2005). Kumar et al. (2014) examined the relationship between TPM
program and manufacturing performance in the Indian manufacturing industries to:
determine the benefits obtained from the TPM implementation; identify common
indicators; and explore the common expectations of the system while implementing
TPM program. This relationship is presented in coordination with management and
employees’ involvement (see Figure 2). Solving software and employee problems is more
difficult than applying TPM techniques, as human subjects in most cases require
much time and more effort to be familiarized with and adopt the systems (Shirose, 1992;
Tajiri and Gotoh, 1992).
Run to
failure
PM
developed
TPM
developed
in Japan
TPM
brought
to the USA
TPM
19801970–19801960–19701950–19601940
Figure 1.
Chronology of TPM
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3. Hypotheses development and conceptual model
3.1 CMMS and TPM
In contemporary highly challenging environment, CMMS plays a major role in the
management information systems for competitiveness as it stores a large amount of data,
information, previous maintenance cases and best practices including machinery track
numbers, failure modes, diagnosis methods and maintenance solutions (Tajadod et al., 2016;
Wan et al., 2017). Thus, achieving business productivity in maintenance systems must be
treated as a strategic asset for industries to create world-class-manufacturers (Brah and
Chong, 2004; Ahuja and Khamba, 2008; Ahuja, 2011).
An organization’s performance in terms of TPM is significantly impacted by using
appropriate information technology such as enterprise resource planning, manufacturing
execution system, content management systems and CMMS ( Jonsson, 2000; Lai and Yik, 2012;
Aboelmaged, 2014; Wan et al., 2017). In academic research, CMMSs have been investigated to
manage information systems and knowledge and maintenance productivity (Stephens, 2010;
Lopes et al., 2016; Fraser et al., 2015). For example, Rastegari andMobin (2016) indicated that a
CMMS can support maintenance productivity by tracking the movement of spare parts,
allowing operators to report faults faster; improve communication between operations and
maintenance personnel more reliable; develop PM schedules on time; provide maintenance
managers with information to have better control over their departments; and offer
accountants information on machineries to enable capital expenditure decisions to be made.
Investigating on a number of 558 companies that applied CMMSs, a research by
Campbell et al. (2010) revealed that the studied companies, could improve their maintenance
productivity up to 28.3 percent, reduce their equipment downtimes by 20.1 percent, save up to
19.4 percent of resources costs and reduce inventory maintenance and repair by 17.8 percent,
in an average payback period of 14.5 months. The results of the study by Campbell et al.
(2010), therefore, show the importance of the implementation of a CMMS in a maintenance
productivity context. According to Fernandz et al. (2003), if a maintenance strategy is to be
productive, it must be supported with CMMSs as a powerful tool necessary for obtaining
information from raw data and supporting the decision-making process. Similarly, Bohoris
et al. (1995) demonstrated the use of a CMMS can be an important contributor enabling a
better organized TPM implementation by providing prompt and accurate information.
Based on the relevant literature, hence, the following hypothesis is proposed:
H1. A CMMS positively relates to the effectiveness of TPM.
3.2 Organizational factors and TPM
Considering the literature discussed above, organizational factors, if applying appropriately,
can provide many benefits for the TPM program (Mckone et al., 1999; Ahuja and Khamba,
2008; Abdallah, 2013). For example, Wang (2006) showed that organizational capabilities
1. System
T
P
M
2. Measurement
3. Autonomous Maintenance
5. Continuous Improvement
6. Culture
7. Training
8. Plant Design4. Housekeeping
Defined
Objectives
Source: Carannante et al. (1996)
Figure 2.
Eight strategic steps
towards TPM
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can facilitate TPM practices across a variety of dimensions (total effectiveness, total
maintenance system and total participation of all employees). It is thus understandable why
many companies must develop organizational strategies as a source to facilitate obtaining
and using TPM so that they can remain competitive (Singh and Ahuja, 2012; Méndez and
Rodriguez, 2017). The existence of flexible decision-making structure along with the top
management support, employees’ involvement, training and integrated maintenance
strategies with total quality management, TPM practices can has a positive impact on the
competitive position of companies and operational performance (Simões et al., 2011; Muchiri
et al., 2014; Piechnicki et al., 2015; Modgil and Sharma, 2016). According to Poduval et al.
(2015), TPM implementation will successful if employees stay motivated and committed.
Based on a case study in plants in Germany, likewise, Konecny and Thun (2011) found that
organizational supportive level has a positive impact on TPM. Based on these findings in
the literature, hence the following hypothesis is proposed:
H2. Related supportive organizational factors positively relate to the effectiveness
of TPM.
3.3 Organizational factors and CMMSs
A review of the previous studies shows that there exists a consensus that organizational
factors are critical to the success of CMMSs (Marquez and Gupta, 2006; Aboelmaged, 2014;
Lopes et al., 2016). Regarding the need for information to aid maintenance management,
organization factors including resource allocation, decision-making structure, senior
management support, employees’ involvement and effective training build up a link with
CMMSs to offer simplified data collection and formalized modules for the analysis of
maintenance data management (Labib, 2004; Rouibah et al., 2009; Aref et al., 2013).
Organizationalfactors are a highly relevant issue in a production environment where the
way how to manage a large number of machineries is so much critical and hence the need
for achieving a CMMS is very significant (Marquez and Gupta, 2006).
Empirical evidence relating to the maintenance systems supports that organizational
framework is associated with CMMS in manufacturing organizations ( Jantunen et al., 2010;
Uysal and Tosun, 2012). Testing the technological-organizational-environmental model,
Aboelmaged (2014) concluded that e-maintenance technology readiness in manufacturing
organizations are mainly influenced by technological and organizational determinants. With
respects to the maintenance systems, Sacco (2014) emphasized the utilizing an appropriate
organizational structure and implementing an effective training program may lead to a
significant increase in sharing information across the organization and improving the
overall CMMS performance. Therefore, the following hypothesis is proposed:
H3. Related supportive organizational factors positively relate to CMMSs.
Considering the aforementioned points and the factors affecting the TPM, we seek in this
research to investigate the impact of these factors on TPM through developing a conceptual
model (Figure 1), since the awareness of their impacts (organizational factors and CMMS)
may contribute to better planning in order to improve the effectiveness of TPM in
manufacturing systems (Figure 3).
4. Methodology
4.1 Sample and participants
The data were collected from a sample of professional and skilled employees working in
different manufacturing companies in Iran through distributing questionnaire through
verbal, mail, fax and internet during January to March 2014. Approximately 206 of those
working in manufacturing plants (60 companies) were invited to participate in the study.
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Of the 206 distributed questionnaires, 133 questionnaires were returned. From them,
125 questionnaires were considered suitable and valid for data analysis. Also, confirmatory
factor analysis (CFA) was used to confirm the construct validity of the questionnaire and
results verified the validity of the questionnaire. Cronbach’s α was used to determine the
reliability of the questionnaire. Table I shows the questionnaire’s variables, factor loadings
and Cronbach’s α.
TPMCMMS
H
3
H2
H1
OF
Notes: TPM: total productive maintenance; OF:
organizational factors; CMMS: computerized
maintenance management system
Figure 3.
Conceptual model
Variable Item Factor loading α
CMMS CMMS1 0.61 0.82
CMMS2 0.73
CMMS3 0.75
CMMS4 0.78
CMMS5 0.55
CMMS6 0.83
OF OF1 0.76 0.75
OF2 0.70
OF3 0.85
OF4 0.70
OF5 0.66
TPM TPM1 0.92 0.91
TPM2 0.65
TPM3 0.82
TPM4 0.80
TPM5 0.69
TPM6 0.73
TPM7 0.61
TPM8 0.56
TPM9 0.94
TPM10 0.78
TPM11 0.87
TPM12 0.71
TPM13 0.56
TPM14 0.64
TPM15 0.85
TPM16 0.91
Table I.
Reliability and
validity analysis
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4.2 Measures
Data collection was done through a survey questionnaire with five-point Likert scales
(Table AI). The items were identified by reviewing the relevant literature (Raouf et al., 1993;
Rouibah et al., 2009; Cheng, 2011; Cuaa et al., 2001; Konecny and Thun, 2011; Amzat and
Idris, 2012; Hazen et al., 2014), previously conducted empirical research and interviews with
experts. A questionnaire was developed based on a review of theoretical foundations.
The procedure of developing and implementing questions is at first based on customizing
the items related to each variable. Considering the role of experts in management sciences,
organizational behavior, industrial psychology and marketing, some items were also
formulated in accordance with the atmosphere of Iran’s manufacturing companies. In doing
so, a primary copy of the questionnaire was distributed among a sample of 30 production
experts and necessary modifications were made based on their comments. Figure 4
illustrates the research methodology used in this study.
Finally, after distributing and collecting the questionnaires, the obtained data were
analyzed using SPSS18 and Amos20 software. Structural equation modeling (SEM) was
used to validate the conceptual model and test the hypotheses. In SEM, the adaptation
of the research data and the conceptual model is investigated to see if the fit is good and,
on the other hand, to test the significance of the relationships in the fitted model.
Identifying Variables from Reviewing Literature
Conducting a Questionnaire Consulting Experts
Validating the Questionnaire
Distributing the Questionnaire among Industrial Experts
Modifying the Questionnaire by Experts’ Opinions
Finalizing the Questionnaire
Developing Hypothesis
Figure 4.
Research methodology
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5. Findings
Following the two-step approach recommended by Anderson and Gerbing (1988), we first
examined the measurement model to test reliability and validity. Then we examined the
structural model to test research hypotheses and model fitness. First, we conducted a CFA
to examine the convergent validity and discriminant validity.
To determine the extent to which the indices are acceptable for measurement models, all
measurement models must be separately analyzed at first. In doing so, three measurement
models which were related to the variables are separately tested. The total fit indices of
measurement models are presented in Table II.
According to Table II, it can be concluded that the measurement models are totally fit. In
other words, general indices verify that the data clearly supports the models. After
reviewing and confirming the measurement models in the first step, the fit of the research
conceptual model was tested in the second step. Total fitness indices of the conceptual
model are presented in Table III.
As shown in Table III, all indices were consistent with the acceptable fit level. So, it can
be concluded that this model fits well with the data, and hence, the conceptual model can be
considered for hypotheses analysis (see Figure 5).
Indices name
Variable Cmin/df GFI AGFI CFI RMSEA
CMMS 2.16 0.95 0.93 0.96 0.035
OF 2.11 0.97 0.95 0.98 0.019
TPM 1.82 0.98 0.97 0.959 0.004
Recommended value 3W W0.90 W0.90 W0.90 0.10W
Notes: CFA, confirmatory factor analyses; GFI, goodness-of-fit index; AGFI, adjusted goodness-of-fit index;
RMSEA, root mean square error of approximation
Table II.
Total fit indices of
measurement models
TPMCMMS 0.66
0.520.
54
OF Figure 5.
Structural model
Indices name
Variable Cmin/df GFI AGFI CFI RMSEA
Final model 2.25 0.97 0.95 0.98 0.032
Recommended value 3W W0.90 W0.90 W0.90 0.10W
Table III.
Total fitness indices
of the survey
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After reviewing and approving the model, the two partial indices of critical ratio (CR) and
p were used to test the significance of the hypotheses. CR is a value which is obtained by
dividing the “estimation of regression weight” by “standard error.” According to a
significant level of 0.95, the CR must be out of (−1.96, +1.96). If a CR is inside this interval,
the parameter of the model is not considered as a significant ratio. The hypotheses
with regression coefficients and the values of partial indices of each hypothesis are
presented in Table IV.
As seen in Table IV, with respect to the absolute value of the critical ratios which are
greater than 1.96 and the p-values which are less than 0.01, the regression coefficients
are impressive and support the research hypotheses. Of the three hypotheses, all have
positive impacts.
The results obtained from AMOS20 software showed that the structural model of the
research has a good fit and the overall fit of the model is acceptable (CMIN/df¼ 2.25,
RMSEA¼ 0.032, GFI¼ 0.97, AGFI¼ 0.95 and CFI¼ 0.98). All measured path coefficients
have significant values (po0.001). Reviewing the literature and previously conducted
studies confirmed the results to be expectable, with positive and significant relationships
between organizational factors and direct CMMSand TPM.
As indicated in Table IV, the relationship between CMMS and TPM is significant
( β¼ 0.66, CR¼ 5.41). This finding supports H1. CMMS is a computerized maintenance
management tool. This tool is used to enter, approve and plan the information about the
maintenance and repair activities and the related costs and times. In fact, the main task of a
CMMS is provision and this system is a tool for managing and improving maintenance and
repair activities for equipment, facilities and machines in organizations. As a result,
methods and criteria should be defined to evaluate the personnel’s skills and their
participation in different branches of TPM so as to encourage those with higher levels of
skill and participation.
Additionally, the effects of organizational factors on TPM is positive and significant
( β¼ 0.52, CR¼ 4.73). These finding indicates that H2 is supported. Thus, an environment
should be provided in which the personnel are courageous to participate in maintenance
activities and needed supports are done by maintenance groups. The personnel should have
the ability to identify partial defects and remove them, and the organization should let them
comment on defects identification and analysis.
Finally, the path coefficient from organizational factors to CMMS is positive and
significant (β¼ 0.54, CR¼ 5.06). According to these finding, H3 is supported. In this
regard, company’s managers help reduce costs through supporting the CMMS which
finally increases the company’s ability to compete with its rivals. Also, implementing a
CMMS in a company collects the produced knowledge effectively and helps increase
human resource efficiency which in turn indirectly reinforces the company’s competing
power against other competitors.
6. Discussion and conclusion
This study aimed at developing and validating a conceptual model on relationships
among CMMSs and relevant supportive organizational factors and TPM. More specifically,
Hypothesis Path β CR Result
H1 CMMS → TPM 0.66*** 5.41 Supported
H2 OF → TPM 0.52*** 4.73 Supported
H3 OF → CMMS 0.54*** 5.06 Supported
Note: ***po0.001
Table IV.
Regression coefficients
and results of
hypotheses test
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result of H1 indicated that the principle of CMMSs can positively relate to the effectiveness
of TPM. This result is in line with research by Rastegari and Mobin (2016) and Campbell
et al. (2010). Similar to the research of Rastegari and Mobin (2016), our finding in H1 showed
that assist planning, management and administrative functions can develop PM schedules
and offer real time PM schedules to better identify malfunctions across the systems.
H2 indicating the relationship between supportive organizational factors and the
effectiveness of TPM was also supported. Consistent with research by Poduval et al.
(2015) and Konecny and Thun (2011), our finding for H2 illustrated that organizations must
utilize a flexible decision-making framework through participation of both top management
and employees to ensure integration across the system and identify potential risks prior to
happening. These risks are important as they may increase the system costs over time.
Similarly, H3 was supported in which its finding showed that supportive organizational
factors are related to CMMSs. In line with research by Aboelmaged (2014), Jantunen et al.
(2010) and Uysal and Tosun (2012) that highlighted technological factors applied across the
organization can facilitate implementing the integrated maintenance strategies and allow
both management and employees to establish an appropriate decision-making process for
the purpose of the analysis of maintenance data management, our finding also showed that
this relationship can help simplify data collection, application and sharing across the
systems to ensure system reliability in data analysis.
While the application of CMMS and TPM has been considered as an important
management principle that can provide strategic and operational benefits, adoption of these
techniques has yet to be seen as a considerable rate in manufacturing companies. Thus, it is
necessary to find out about the effectiveness of applying CMMS and related supportive
organizational factors on the effectiveness of TPM so as to create a positive attitude toward
these principles in operational performance of an organization. Building upon this
theoretical objective, this study has enhanced and developed a research model to test the
impact of related supportive organizational factors on CMMS and TPM in manufacturing
companies in Iran. The current study’s framework provides a good starting point for
analyzing and investigating appropriate factors that may affect the performance of
manufacturing industry thereby, in comparison with previous research, this study
developed a unified integrated model that evaluate the relationships between CMMSs,
related supportive organizational factors and the effectiveness of TPM. Many organizations
receive services from domestic and external environment producing software applications
for automation of their business processes which may dissatisfy them from these services in
majority of cases. The main reason for this dissatisfaction is because of a lack of appropriate
evaluation and analysis regarding the related processes and investigation of requirements
for the automation, as well as, a lack of software evaluation in order to find out the way in
which they can fulfill the identified requirements. In fact, the effectiveness of these software
applications is supported by organizational factors including allocating the resources, senior
management support and the organizational culture and structure.
6.1 Managerial implications
This study offers several managerial implications. First, the use of principle of CMMSs in
manufacturing organizations may reduce maintenance costs. Top management is
therefore, required to ensure all resources such as human capital, social capital and
financial capital are considered prior to establishing a CMMS. Managers must consider the
role of employees in achieving a CMMS. In this case, organizational trainings and
interventions may help better prepare employees to adopt the principle of a CMMS.
This in turn needs financial support in which all machineries should be evaluated for
maintenance and possible repair in both short and long term. Second, managers are
required to immediately look forward to seeing how to increase the organizational
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productivity as the application of a CMMS requests so much financial support over time.
As a result of this, third, management would be able to improve the industrial average
savings resulting from the initiation of a functional predictive maintenance program:
reduced the number of errors, reduced downtime, increased service life and availability of
components, preventive remedies, reduced expenditures of the parts and workforces,
integrated technical diagnostics in maintenance management, improved product quality,
improved safety of workforces and working environment, increased employee self-esteem
in decision making, increased energy savings. The present study may help the
maintenance managers or line managers on shop floor to understand the various aspects
of organizational factors, CMMS and, consequently, how do they affect the TPM practices.
Effective CMMS and TPM help to make an eye on the day to day operations processes and
its maintenance requirements for business excellence.
6.2 Limitations and research directions
Since the objectives of the present study have been accomplished, it is required to state its
limitations. First, the study has mostly focused on medium- and high-tech industries. So, the
results cannot be generalized for low-tech industries, because challenges and effective
factors in low-tech businesses are different. Second, the study has only considered
manufacturing companies in Iran. Therefore, it is necessary to study multinational
companies and expand the research scopeto include more international partners. Third, the
information required for the study has been collected during the growth step of applying
CMMS and TPM. As these principles are accepted more extensively, following the effect of
their applications on the effectiveness of the organization will be more rational. In addition,
all the data have been collected cross-sectional, thus the variables and their results may be
limited to a specific period.
Future research may follow the progress of consequences of applying CMMS and related
supportive organizational factors from the growth to maturation. We recommend further
research to investigate the effects of applying the RFID technology on the effectiveness of
TPM and performance in manufacturing sectors, as we believe that technological
innovations can facilitate the adoption of CMMS and TPM in an organizational context.
Despite the methodological perspective in this study consists of a quantitative approach, we
would expect a significant tendency toward applying qualitative research methods in this
field, as the role of human resources and/or social capital may be sooner or later seen as an
enabler of TPM.
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Smith, N., Mitton, C., Bryan, S., Davidson, A., Urquhart, B., Gibson, J.L., Peacock, S. and Donaldson, C.
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Appendix
Corresponding author
Javad Khazaei Pool can be contacted at: khazaei110@gmail.com
Related supportive organizational factors
1 Resource allocation is closely aligned with other key processes, e.g., strategic planning, budgeting
2 Management decision style helps me to be productive and do the job in time
3 My professional ability is sufficient to develop my work
4 Top management tries to take part in deciding in what order the TPM should be implemented
5 The organization has established a program for employees about TPM
Computerized maintenance management systems (CMMS)
1 The system will schedule preventive maintenance by calendar date
2 The system can produce management reports on demand
3 The system is user friendly
4 The system has security password or code protection
5 The system has an ongoing support program
6 The system keeps the quality records
Total productive maintenance (TPM)
1 We dedicate a portion of every day solely to maintenance
2 We emphasize good maintenance as a strategy for achieving quality and schedule compliance
3 We have a separate shift, or part of a shift, reserved each day for maintenance activities
4 Our maintenance department focuses on assisting machine operators perform their own
preventive maintenance
5 Our plant stays on the leading edge of new technology in our industry
6 We are constantly thinking of the next generation of technology
7 We are a leader in the effective use of new process technology
8 We search for continuing learning and improvement after installation of the equipment
9 We actively develop proprietary equipment
10 We rely on vendors for most of our equipment
11 We have equipment which is protected by the firm’s patents
12 Proprietary equipment helps us gain a competitive advantage
13 Operators understand the cause and effect of equipment deterioration
14 Groups are formed to solve current equipment problems
15 Customer standards are always met by our plant
16 We strive to establish long-term relationships with suppliers
Table AI.
Measurement items
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	Appendix