**2. Literature review**

#### **2.1. Review of maintenance approaches**

Different maintenance approaches (i.e. strategies and concepts, methodology or philosophy) have been developed in the last few decades.

The development of maintenance approaches are discussed by many authors [9–13]. Failurebased maintenance (FBM) prescribes activation of maintenance in the event of failure [10]. No action is taken to detect or to prevent failure [14]. Maintenance is carried out only after a breakdown. This approach is only appropriate in a case where customer demand exceeds supply and profit margins are large. However, increasing global competition, small profit margins, safety awareness and strict environmental regulations are changing the environment that most companies are facing today. In this regard, more emphasis is being placed on developing maintenance concepts [15]. However, it is always possible that a failure is allowed to occur. This depends on the existence of secondary damage, redundancy and the ease to repair. Waeyenbergh and Pintelon [13] suggest that one should determine the economic feasibility in order to evaluate the technical feasibility of FBM for a critical component or a non-critical component.

**1. Introduction**

The analytic hierarchy process (AHP) is widely used in multi-criteria decision-making tool for tackling multi-attribute decision-making problems in real situations [1]. It represents a powerful technique for solving complicated and unstructured problems that may have interactions and correlations among different objectives and goals [2]. The AHP helps the decision makers to organise the critical aspects of a problem into a hierarchical structure similar to a family tree [3]. It is based on experts' judgements through pairwise comparisons. Experts are interviewed and pairwise comparison judgements are applied to pairs of homogenous

AHP gained substantial attention as a possible solution to the decision-making problems in different organisational areas, for example, the selection of maintenance policy or factors of employee suggestion schemes which will be more deeply illustrated in the following section. However, this method can also be utilised in many other fields. For example, in the study [4], the fuzzy AHP was employed to prioritise and select a suitable organisational structure. The AHP method has been widely used in the decision-making problems that involve multiple criteria in multiple levels [5] as well. The method helps to decompose their decision problem into hierarchy of factors, each of which can be analysed independently and once the hierarchy is built, the decision makers systematically evaluate its various elements by comparing them one to another, two at a time, with respect to their impact on an element above them in the

Moreover, this technique allows for the search of relative importance placed on product attributes and attribute levels of the analysed complex goods [7]. To make the pairwise comparisons, we need a scale of numbers that indicate how many times a more important or dominant element over another element was, with respect to the criterion or property, with

In this chapter two case studies are presented: first, empirical case study will be utilised to evaluate and select the most appropriate maintenance approach; the second one, based on expert opinion will present a possibility to formalise the importance levels for the importance

Different maintenance approaches (i.e. strategies and concepts, methodology or philosophy)

The development of maintenance approaches are discussed by many authors [9–13]. Failurebased maintenance (FBM) prescribes activation of maintenance in the event of failure [10]. No action is taken to detect or to prevent failure [14]. Maintenance is carried out only after a

criteria, eventually generating the overall priorities for ranking the alternatives [1].

90 Applications and Theory of Analytic Hierarchy Process - Decision Making for Strategic Decisions

hierarchy [6]. AHP method is used to measure the importance of these factors.

respect to which they are, compared [8].

**2.1. Review of maintenance approaches**

have been developed in the last few decades.

**2. Literature review**

of factors of sustainability of employee suggestion schemes.

Preventive maintenance (PM) is comprised of maintenance activities that are undertaken after a specified period of time or amount of equipment used [16]. Therefore, traditional preventive maintenance models are using policies such as age replacement and block replacement [17]. One of the disadvantages of the PM is that PM is only suitable when the standard deviation of the failure population is small [18]. This means that if the distributions have a small standard deviation, they are usually a candidate for PM and in such cases PM is economical. Another shortcoming of PM is the lack of decision support systems and insufficient historical data [14, 19].

Condition-based maintenance (CBM) is a maintenance strategy that monitors the actual condition of the asset to decide what maintenance needs to be done [20]. CBM is defined as the preventive maintenance based on performance and/or parameter monitoring and the subsequent actions. Using a condition monitoring (CM) system, the machine condition is assessed by the current and historical measurements of one or more of relevant CM parameters [21]. Vibration-based maintenance (VBM) is the most frequently used technique under the CBM approach. By an efficient use of VBM policy, which means utilisation of the information provided by vibration monitoring system for planning and performing maintenance actions, the machine can be run until just before failure as defined by the monitored parameter reaching a predetermined unacceptable value [21]. Al-Najjar [22] indicated that the implementation of VBM policy provides possibilities for obtaining early indications of alterations of machinestate.

Al-Najjar [9] proposed a strategy called total quality maintenance (TQMain), which sustains not only machinery but also the essential elements constituting a manufacturing process, such as production/operation, environmental conditions, quality, personnel, and methods. TQMain was defined by Al-Najjar [23] as a means for monitoring and controlling deviations in a process, working conditions, product quality and production cost, and for detecting damage causes and their developing mechanisms and potential failures in order to interfere (when it is possible) to 'stop' or reduce machine deterioration rate before the production process and product characteristics are intolerably affected and to perform the required action to restore the machine/process or a particular part of it to as good as new. Further, Al-Najjar and Alsyouf [24] also presented what characterises TQMain and distinguish it from other maintenance concepts (e.g. reliability-centred maintenance (RCM), total productive maintenance (TPM)). They highlighted that TQMain supports the use of a common database, continuous improve‐ ment, implementation of CBM such as VBM, and it is based on intensive use of real-time data acquisition and analysis to detect reasons behind deviations in product quality and machine condition.

Reliability-centred maintenance was first introduced by the aircraft industry of the United States in 1978 [25]. There have also been several improvements to the traditional RCM methodology (e.g. RCM2). Moubray's book [11] is a key reference. RCM can, among other things, improve system availability and reliability, reduce the amount of preventive mainte‐ nance, unplanned corrective maintenance and increase safety. These are all important aspects for organisation in order to sustain in a competitive environment [26]. RCM aims to increase the asset's lifetime and create a more efficient and effective maintenance [27]. But, Al-Najjar [22] pointed out that RCM cannot completely exploit the use of condition monitoring (CM) techniques, and the progress of damage cannot be monitored until just before a failure. Further, Pintelon and Parodi [27] described that available statistical data used in RCM are insufficient or inaccurate, and that there is a lack of insight in the equipment degradation process (failure mechanisms) and the physical environment (e.g. corrosive or dusty environment) is over‐ looked. There have been already attempts to combine RCM and AHP in the maintenance domain—for example, development of a hybrid model for trunk road network maintenance prioritisation. The proposed hybrid model was used to establish failure diagnostic and multicriteria decision making, respectively [28].

Total productive maintenance (TPM) is a methodology originating from Japan to support its lean manufacturing system, since dependable and effective equipment are essential prereq‐ uisite for implementing lean manufacturing initiatives in any organisation [29]. To do so, the overall equipment effectiveness (OEE), which is defined as the product of availability, speed and quality performance, is used to assess the reached level [13]. Nakajima [30], a major contributor of TPM, has defined TPM as an innovative approach to maintenance that optimises equipment effectiveness, eliminates breakdowns and promotes autonomous maintenance by operators. The definition of TPM includes five major elements [31]:


Though the concept of TPM is simple and obvious, there are some reported limitations. First, TPM does not provide clear rules to decide which basic maintenance policy will be used, and second, calculation of the OEE is not really a complete analysis. Cost and profits are not taken into account, and therefore it is not a comprehensive measure [13]. Moreover, TPM also requires changing the organisational culture, what is not easily to accomplish. In this regard, Tsang and Chan [32] indicated that those organisations that will not change their culture will not be successful in implementing TPM. A study regarding application of AHP in the imple‐ mentation of TPM decision making in manufacturing organisations was performed by Ahuja and Singh [33].

#### **2.2. Review of employee suggestion system factors**

acquisition and analysis to detect reasons behind deviations in product quality and machine

92 Applications and Theory of Analytic Hierarchy Process - Decision Making for Strategic Decisions

Reliability-centred maintenance was first introduced by the aircraft industry of the United States in 1978 [25]. There have also been several improvements to the traditional RCM methodology (e.g. RCM2). Moubray's book [11] is a key reference. RCM can, among other things, improve system availability and reliability, reduce the amount of preventive mainte‐ nance, unplanned corrective maintenance and increase safety. These are all important aspects for organisation in order to sustain in a competitive environment [26]. RCM aims to increase the asset's lifetime and create a more efficient and effective maintenance [27]. But, Al-Najjar [22] pointed out that RCM cannot completely exploit the use of condition monitoring (CM) techniques, and the progress of damage cannot be monitored until just before a failure. Further, Pintelon and Parodi [27] described that available statistical data used in RCM are insufficient or inaccurate, and that there is a lack of insight in the equipment degradation process (failure mechanisms) and the physical environment (e.g. corrosive or dusty environment) is over‐ looked. There have been already attempts to combine RCM and AHP in the maintenance domain—for example, development of a hybrid model for trunk road network maintenance prioritisation. The proposed hybrid model was used to establish failure diagnostic and multi-

Total productive maintenance (TPM) is a methodology originating from Japan to support its lean manufacturing system, since dependable and effective equipment are essential prereq‐ uisite for implementing lean manufacturing initiatives in any organisation [29]. To do so, the overall equipment effectiveness (OEE), which is defined as the product of availability, speed and quality performance, is used to assess the reached level [13]. Nakajima [30], a major contributor of TPM, has defined TPM as an innovative approach to maintenance that optimises equipment effectiveness, eliminates breakdowns and promotes autonomous maintenance by

2. a thorough system of preventive maintenance for the equipment's whole life span;

3. implementation by various departments (engineering, production, maintenance, etc.); 4. total employee involvement from top management to the workers on the floor; and

Though the concept of TPM is simple and obvious, there are some reported limitations. First, TPM does not provide clear rules to decide which basic maintenance policy will be used, and second, calculation of the OEE is not really a complete analysis. Cost and profits are not taken into account, and therefore it is not a comprehensive measure [13]. Moreover, TPM also requires changing the organisational culture, what is not easily to accomplish. In this regard, Tsang and Chan [32] indicated that those organisations that will not change their culture will not be successful in implementing TPM. A study regarding application of AHP in the imple‐ mentation of TPM decision making in manufacturing organisations was performed by Ahuja

operators. The definition of TPM includes five major elements [31]:

5. motivation management through small group activities and teamwork.

condition.

criteria decision making, respectively [28].

1. overall equipment effectiveness maximisation;

and Singh [33].

The existing research aptly identifies the enablers to the employee suggestion schemes. Buech et al. [34] note that researchers trying to ascertain which factors affect employees to submit suggestions focus on three main streams of research. The first considers work environment, the second focuses on the features of the scheme, weighs the influence of feedback about suggestions against management support of the system as well as rewards for successful suggestions and the third deals with the characteristics of the individuals. Carrier [35] reports that the majority of researchers consider organisational creativity to be fostered through the personal characteristics and motivation of creative individuals while the other group of researchers turned their attention to context and organizational factors. Axtell et al. [36] argue that different sets of variables influence these two stages of employee suggestion system process, i.e. the creative and the implementation phases. So, it is evident that the drivers that trigger the suggestion scheme comprise individual, organisational and contextual variables. Moreover, the innovation process is a complex phenomenon and many variables have roles to play in determining its process [37]. Amabile et al. [38] also contend that the organisational context can impede or support the generation of ideas. Everyone has ideas all the time, not all are creative, nor do they all lead to innovation [39]. Therefore, creativity needs to be nurtured to turn into valuable suggestions. A list of variables emerging from the literature that hint as the indicators are: Top Management Support, Supervisor Encouragement, Coworker Support, Organisational Encouragement, Support for innovation, Communication Evaluation, Aware‐ ness, Resources, Rewards, Training, Effective System, Feedback, Implementation of Ideas, Empowerment, Job Factors, Expertise, Self-Efficacy and Individual Characteristics, Team‐ work, Employee Participation, Job Control, Organisational Impediments and the Competition, Employee Confidence, Sense of Security, Commitment and Accountability, Improvement in Process, Customer Satisfaction, Product Quality, New Revenue, Cost Saving, Employee Satisfaction.
