An overview of time-based and condition-based maintenance in industrial application☆
Highlights
► Presents an overview of TBM and CBM techniques. ► We discuss how the TBM and CBM techniques work toward maintenance decision making. ► The challenges of implementing each technique are compared. ► Each of techniques is found to have unique concepts, procedures and challenges.
Introduction
Over the last few decades, maintenance functions have drastically evolved with the growth of technology. Maintenance is defined as a set of activities or tasks used to restore an item to a state in which it can perform its designated functions (Dhillon, 2002, Duffuaa et al., 1999). Maintenance strategies can be broadly classified into Corrective Maintenance (CM) and Preventive Maintenance (PM) strategies (Duffuaa, Ben-Daya, Al-Sultan, & Andijani, 2001).
Corrective maintenance, also known as run-to-failure or reactive maintenance, is a strategy that is used to restore (repair or replace) some equipment to its required function after it has failed (Blanchard, Verm, & Peterson, 1995). This strategy leads to high levels of machine downtime (production loss) and maintenance (repair or replacement) costs due to sudden failure (Tsang, 1995). An alternative to the CM strategy is the PM strategy. The concept of PM involves the performance of maintenance activities prior to the failure of equipment (Gertsbakh, 1977, Lofsten, 1999). One of the main objectives of PM is to reduce the failure rate or failure frequency of the equipment. This strategy contributes to minimising failure costs and machine downtime (production loss), and increasing product quality (Usher, Kamal, & Syed, 1998).
In the industry, application of the PM strategy can be generally performed through either experience or original equipment manufacturer (OEM) recommendations, and is based on a scientific approach. The application of PM through experience is a conventional PM practice. In most cases, it is performed at regular time intervals, T (Canfield, 1986, Nakagawa, 1984, Sheu et al., 1995). Through experience, no standard procedures are followed, thus knowledge from technicians and engineers for maintenance purposes is a valuable asset to the company. Technicians and engineers in this setting learn from previous mistakes and, based on their experience, are able to detect the abnormal conditions of a machine by sense. They can then decide the appropriate PM actions to apply in order to avoid machine breakdown. The main drawback of PM through experience, however, is that the company may face difficulties when the experienced person leaves the company. Moreover, such persons may be not present in production lines round-the-clock to solve maintenance problems.
Through OEM recommendations, PM is carried out at a fixed time, for example every 1000 h or every 10 days, based on recommendations. However, this PM practice is not usually applicable when attempting to minimise operation costs and maximise machine performance. Labib (2004) listed three reasons for this: First, each machine works in a different environment and would, therefore, need different PM schedules. Second, machine designers often do not experience machine failures and have less knowledge of their prevention compared to those who operate and maintain such machines. Finally, OEM companies may have hidden agendas, that is, maximising spare parts replacement through frequent PMs. This is supported by Tam, Chan, and Price (2006), who stated that PM intervals based on OEM recommendations may not be optimal because actual operating conditions may be very different from those considered by the OEM. As such, actual outcomes may not satisfy company requirements.
The area of operational research introduced the application of PM based on a scientific approach in 1950. The scientific approach involves specific processes and principles that employ various analytical techniques, such as statistics, mathematical programming, artificial intelligence, etc. The main advantage of PM practice based on the scientific approach is that decision making is based on facts acquired through real data analysis. In the literature, PM based on the scientific approach can be classified into two techniques: comprehensive-based and specific-based techniques. The comprehensive-based technique also known as maintenance concept development, which can be defined as a set of various maintenance interventions (experience-based, time-based, condition-based, etc.) and the general structure in which these interventions are foreseen (Pintelon & Waeyenbergh, 1999). According to Waeyenbergh and Pintelon (2002), maintenance concept development forms the framework from which installation-specific maintenance techniques are developed and is the embodiment of the way a company thinks about the role of maintenance as an operational function. Some examples of maintenance concepts are reliability-centred maintenance (RCM), business-centred maintenance, risk-based maintenance, total-productive maintenance (TPM), and the centre for industrial management maintenance concept development framework. The specific-based technique, as its name implies, is a specific maintenance technique that has unique principles for solving maintenance problems. Examples of specific-based technique are time-based maintenance (TBM) and condition-based maintenance (CBM).
This paper presents an overview of the application of TBM and CBM, both of which have been widely reported in the literature. Although some papers that discuss TBM and CBM (e.g., Mann, Saxena, & Knapp, 1995) are available, an overview of their application and comparison from a practical perspective remains lacking. Thus, this paper has two main objectives. The first objective is to explore how each of these maintenance techniques works toward maintenance decision making. The second objective is to discuss their effectiveness from a practical point of view. The paper is presented as follows: Brief reviews of the concepts, general processes toward maintenance decision making, and recent applications of TBM and CBM are described in Sections 2 Time-based maintenance (TBM), 3 Condition-based maintenance (CBM), respectively. A comparison of the maintenance techniques from a practical point of view is presented in Section 4. Finally, conclusions are made in Section 5.
Section snippets
Time-based maintenance (TBM)
Time-based maintenance, also known as periodic-based maintenance (Yam et al., 2001a, Yam et al., 2001b) is a traditional maintenance technique. In TBM, maintenance decisions (e.g., preventive repair times/intervals) are determined based on failure time analyses. In other words, the aging (expected lifetime), T, of some equipment is estimated based on failure time data or used-based data (Lee, Ni, Djurdjanovic, Qiu, & Liao, 2006). TBM assumes that the failure behaviour (characteristic) of the
Condition-based maintenance (CBM)
Condition-based maintenance, also known as predictive maintenance is the most modern and popular maintenance technique discussed in the literature (Dieulle et al., 2001, Han and Song, 2003, Moya, 2004). CBM was introduced in 1975 in order to maximise the effectiveness of PM decision making. According to Jardine, Lin, and Banjevic (2006), CBM is a maintenance program that recommends maintenance actions (decisions) based on the information collected through condition monitoring process. In CBM,
Comparison of TBM and CBM
The previous sections presented an overview of TBM and CBM with respect to their principles, general processes toward maintenance decision making, and their recent application reported in the literature. In this section, the challenges of implementing the TBM and CBM techniques from a practical perspective that covers the issues of data required and collection, data analysis/modelling, and decision process are compared and discussed. A summary of these issues is given in Table 1.
Future challenge and consideration of CBM
Previous section reveals that although the application of CBM is more beneficial compared to TBM from a practical point of view, further research on CBM is still necessary. This section discusses some of the challenges and considerations the future of CBM research.
The application of CBM for complex and sensitive equipment/system such as electrics, electronics and mechatronics products become one of the challenge in future CBM research. This challenge relay on the application of advanced
Conclusions
This paper presented an overview of the TBM and CBM techniques with emphasis on how these techniques work toward maintenance decision making. A recent application of each technique was reviewed, followed by a comparison of the challenges faced in implementing each technique from a practical point of view. In general, it can be concluded that each of the techniques has its own unique concept/principle, processes, and challenges toward real industrial practise.
From the concept/principle point of
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