|Ade Supriatna||Industrial Engineering, Universitas Darma Persada|
|Moses Laksono Singgih||Industrial Engineering, Institut Teknologi Sepuluh November|
|Erwin Widodo||- Industrial Engineering, Institut Teknologi Sepuluh November, Surabaya, East Java, Indonesia
|Nani Kurniati||Industrial Engineering, Institut Teknologi Sepuluh November|
Equipment performance is very important in the production process. Equipment performance can be determined by overall equipment effectiveness performance (OEE) and maintenance strategies. This study encourages the use of OEE, in addition to the estimated total maintenance costs, of rental equipment as a consideration in determining optimal maintenance strategies. Meanwhile, the proposed maintenance strategies are corrective maintenance (CM) and a combination of CM with preventive maintenance (PM). The aim of this study was to obtain a maintenance strategy that would minimize the estimated total maintenance costs and increase OEE. Mathematical models of estimated total maintenance costs are developed based on maintenance strategies generated by each maintenance combination. The results of this study showed that when a rental period increases by two years, a combination of CM and PM strategies will cause maintenance costs to increase by 37.54%. Meanwhile, if the lessor only does CM, the increase will be greater (i.e., 55.12%). Comparison of the two strategies revealed that the combination of PM with CM is more efficient than CM alone. Further, OEE experienced an average decline of 3.7% despite the maintenance strategy.
Maintenance; OEE; Overall equipment effectiveness; Rent equipment
At present, the manufacturing industry is facing rapid technological developments. Technology is generally expensive and requires special skills in both operating and maintaining it. This has resulted in a change in the industry paradigm. Generally, companies have their own equipment, so that production processes and maintenance activities can be carried out by the maintenance department within each company. However, companies with limited capital often choose to rent with maintenance of production equipment. Thus, companies can focus on their core business matters and improve efficiency by converting fixed costs to variable costs (Singgih et al., 2018). A company may rent out equipment (lessee) to other companies (lessors) with the cooperation stated in a contract agreement detailing the obligations of the lessor and the lessee. The lessor is generally obliged to maintain equipment performance, while the tenant is obliged to pay for the rented equipment. Thus, the lessor must devise maintenance strategies that can minimize total maintenance costs and optimize equipment performance so as not to exceed the budget based on lessee payments.
Some researchers have previously discussed rental equipment issues (Jaturonnatee, 2006; Pongpech and Murthy, 2006; Yeh and Chang, 2007; Yeh et al., 2009; Chang and Lo, 2011; Yeh and Kao, 2011; Schutz and Rezg, 2013; Zhou et al., 2015; Hajej et al., 2015; Mabrouk et al., 2016; Su and Wang, 2016; Hamidi et al., 2016; Zhou et al., 2016; Hung et al., 2017; Wang et al., 2018). Wang et al. (2018) and Hajej et al. (2015) focused on guarantees in the area of ??rental equipment. Other studies have addressed the issue of maintenance strategies by considering penalty factors in equipment rental transactions (Jaturonnatee, 2006; Pongpech and Murthy, 2006; Yeh and Chang, 2007; Yeh et al., 2009; Yeh and Kao, 2011; Yeh et al., 2011; Hung et al., 2017). They used equipment failure thresholds to determine the schedule and number of preventive maintenance (PM) imperfections that can minimize total maintenance costs. In addition to imperfect PMs, they used minimum CM to repair equipment failures. Generally, they consider penalties when equipment failures occur. However, penalties are not often considered for the duration of equipment repair. In fact, this often happens.
In contrast with Jaturonnatee et al. (2006), Pongpech and Murthy (2006) used a periodical PM scheme in which PM actions were implemented periodically with various levels of maintenance. Pongpech and Murthy (2006) extended a mathematical model to determine the ideal PM period and reduce the failure rate, resulting in a minimum estimated total maintenance charge. This research method was more practical, but the resulting performance was lower than that produced by Jaturonnatee et al. (2006). Yeh et al. (2009) expanded a mathematical model and algorithm to determine the total performed PM schedules, the time interval between PM actions, and the best efficiency level alongside the estimated total maintenance charge criteria. Yeh et al. (2009) considered decreases in the secure failure rate of each PM event during a rental period. However, Yeh et al. (2009) assumed that the time of each equipment repair would exceed the time specified in the contract agreement, and this does not always occur. Consequently, the lessor will be in an unfavorable condition.
In contrast with previous studies, Schutz and Rezg (2013) and Zhou et al. (2007, 2015) established a reliability threshold for determining PM schedules and discussed guarantees of rental equipment performance. Meanwhile, Mabrouk et al. (2016) used downtime as a barrier to determine when PM. Mabrouk et al. (2016) combined PM with imperfect CM as a maintenance strategy to determine future rental periods. Xiang et al. (2017) developed a multi-unit maintenance rental equipment scheme in which the effectiveness of the PM is determined to reduce the failure rate. One method used to determine PM effectiveness is the method of reducing the failure rate (FRRM) (Jaturonnatee, 2006; Pongpech and Murthy, 2006; Yeh and Chang, 2007). The FRRM reduces the equipment failure rate by a safe amount or a safe amount equal to the failure rates that exist after PM actions (Finkelstein, 2008). Another method for determining PM effectiveness is the age reduction method (ARM) (Zhou et al., 2007; Schutz and Rezg, 2013; Zhou et al., 2015; Hajej et al., 2015; Hamidi et al., 2016; Hung et al., 2017). The ARM is the age of the equipment returned earlier than today with a safe amount after PM actions (Finkelstein, 2008).
Out of the aforementioned research, only Zhou et al. (2015) and Schutz and Rezg (2013) discussed equipment performance as a result of maintenance activities. However, they did not discuss variable costs, such as penalties, in the context of optimization determination. According to his research, maintenance not only affects equipment performance but also affects the performance of maintenance activities; overall equipment effectiveness (OEE) can do both. OEE provides an overview of engine conditions determined by availability ratios, performance ratios, and quality ratios. These three ratios are important because they indicate the suitability of the equipment to be used in the production process (Pariaman et al., 2017; Rahman et al., 2018).
For this reason, the present research integrated both of them into rental equipment. In the present study, OEE was used as a measure of equipment performance. Meanwhile, the proposed maintenance strategies include minimal corrective maintenance (CM) and a combination of minimal CM with imperfect PM. ARM was also used in this study to determine the effectiveness of imperfect PM. The purpose of this study was to obtain a maintenance strategy that could minimize estimated total maintenance costs and increase OEE. Mathematical models of estimated total maintenance costs were developed based on maintenance strategies generated by each maintenance combination, and the failure rate was assumed to follow the Weibull distribution.
This article was arranged systematically as follows. Segment 2 illustrates the mathematical model developed in the present study. The characteristics of an optimal maintenance strategy are explored in Segment 3. Segment 4 presents the characteristics of the model through numerical analysis. Finally, Section 5 presents conclusions drawn from the previous exposure.
In this study, we recall various notations:
Table 1 Notations of the present model
The use of OEE for the purpose of renting equipment has been carried out successfully. The results of the OEE model characterization differed between different renting period conditions. OEE has a different value because it is influenced by many factors, such as renting period, number of PM, failure, repair time, and maintenance level. Using a rent period of two to six years and forming a shape parameter of 1.5 to 2, a scale parameter of 0.5 to 1, and a repair time from one to two hours results in an OEE of 69.3% to 95.0%. The use of PM and CM as a maintenance strategy yields differences in the estimated total maintenance charge by increasing scale parameters, shape parameters, rental periods, and the duration of repairs. Compared to the CM alone, the combination of PM and CM can improve efficiency from 30.893% to 78.897%. Thus, the results of this study can be considered by lessors to aid in devising maintenance strategies to maintain efficient equipment performance. The results of this study are promising for the future development of rented equipment studies using OEE. For the purposes of future research, OEE is now proven to measure equipment performance not only in the manufacturing industry but also in equipment rental. OEE is useful as a threshold to determine when PM should be executed. Future research may consider the duration of PM actions by generalizing various statistical distributions to devise maintenance strategies that can minimize total estimated maintenance charges.
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