Keywords

1 Introduction

Maintenance is an important task to keep equipment reliability to ensure that all production activities run smoothly according to the set schedule and target [1]. The high occurrences of machine breakdown is a problem that many companies face with today. This condition certainly results in the production process in the company becoming unproductive and inefficient [2]. Mining activities are the first series of work activities at Semen Padang Co. The activities are mining limestone and silica stone as the main ingredients for making cement. Unit of mining in Semen Padang Co. also faces with a high breakdown of equipment operating conditions that have exceeding the set target. The problem of high breakdown will be explained by the Reliability Centered Maintenance (RCM) approach [3]. The application of RCM can help to decide what the different maintenance strategies required to ensure a high reliability of equipment with a reasonable cost [1, 4].

2 Reliability Centered Maintenance

RCM is the optimal mix of reactive, time-based, interval-based, condition-based, and proactive maintenance [1, 5]. RCM is used to determine what failure management strategies must be implemented to ensure that the system reaches the desired level of safety, reliability, environmental health and operational readiness in the most cost-effective way. Often, the purpose of maintenance is to prevent all possible failures, and produce an over-maintenance program and maintenance activities to be ineffective [6]. The application of RCM will produce a treatment program that is truly applicable and effective [3, 7].

RCM recognizes the value of your personnel and takes advantage of their extensive experience running the equipment [1, 8]. Run to Failure (RTF) works on the assumption that it is most cost effective to let equipment run unattended until it fails. This type of maintenance is used for the lowest priority equipment. Preventive Maintenance (PM) comprises maintenance tasks on a piece of equipment at regular intervals regardless whether the equipment needs it or not. When well implemented, PM may produce savings in excess of 25 percent [1, 9]. Even though PM is an improvement over RTF, abrupt failures that cause unscheduled downtime still occur. Predictive Maintenance (PDM) is maintenance based on real-time data collected on a piece of equipment. The data show the “health” of the equipment. Proactive Maintenance (PAM) determines the root causes of failure and implements “fixes” (e.g., redesign the equipment so that it does not break down as frequently).

3 Case Study

The case study herein was carried out in Semen Padang Co. mine conveyor belt system. The conveyors transport crushed lime stone or silica stone to storages in the plant. This study takes operating and repairs data from 2015 to 2017. The operation of the conveyor system must be able to maintain the availability of limestone and silica in each plant’s storage capacity at least 50%. Totally, annual requirement for limestone is 9,850,000 tons and 750,000 tons of silica stone for all plant. Processing and transport activities of material must be carried out safely by taking into account the safety of the operator and maintenance crew and not causing pollution to the environment. In the conveying system of Semen Padang Co. mine there are 42 conveyor items. RCM applications are implemented in the most critical machines. The critical value of the machine is determined by weighing several aspects of the scale of assessment in accordance with the operational requirements of the equipment.

The weighing scale is made with low, medium and high values (with values 1, 2, 3) and the equation used is:

$$ MC \, = \, 0.2*L \, + \, 0.2*Q \, + \, 0.1*M \, + \, 0.2*B \, + \, 0.3*E $$
(1)

Where machine criticality (MC), conveyor length (L), storage load volume (Q), material transported (M), machine breakdown (B) and environment impact (E). As a result, we get the most critical belt conveyor as A1J12A, with a value of 3 criticality (see Table 1).

Table 1. Criticality of conveyor belt in Semen Padang. Co. Mining (partial)
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The next step is to create a Fault Tree Analysis (FTA) that aims to identify each failure and find the root cause of the failure that can be generated from each machine component. Examples of FTA on conveyor A1J12A can be seen in the Fig. 1.

Fig. 1.
figure 1

Partial fault tree analysis of conveyor belt

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Reliability data is needed to decide whether an item is critical. This data describes the failure process and optimizes the scheduling of preventive maintenance time. Examples of such data are those at average time between failures (MTTF), average repair time (MTTR) and failure rate function. Furthermore, an analysis of Failure Mode and Effect Analysis (FMEA) was developed which consisted of tabulation failure modes obtained from FTA and machine reliability data.

Then, an assessment is carried out so that the risk priority index (RPN) will be obtained from each failure mode. The value of RPN is the multiplication of the values of severity, occurrence and detection. Each of these parameters is made in 10 rating scales.

3.1 Selection of Maintenance Strategy

The next step is selection the maintenance strategy in each failure mode in the FMEA tabulation. Determination of maintenance strategies by using the RCM Logic Tree Diagram (LTA). The maintenance type determination that will be carried out is processed by answering each step of the question that is in the LTA of RCM (Fig. 2).

Fig. 2.
figure 2

RCM logic tree diagram

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Next is to determine the maintenance interval from the results of the LTA. Maintenance Scheduling is performed on failure modes that have high risk as shown in Table 2.

Table 2. Risk ranking categories
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4 Result and Discussion

Base on the result of FMEA (Table 3), we can see that there are four modes of failure that belong to a “High” criticality group. In accordance with the Table 2, these four failure modes must be mitigated. The failure modes are bearing of return idler worn out or broken, rubber belt splicing peel off, belt torn (leaked out) and bearing of carrying idler worn out or broken. Based on the calculation of MTTR and MTTF using the failure mode distribution approach that occurs, the reduction in downtime is obtained by 629.8–368.8 = 261 h or 41.44% of the down-time generated by the four components that have a “high” criticality, see Table 4.

Table 3. Failure mode and effect analysis for conveyor A1J12A (partial)
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Table 4. Reduction of downtime by proposed maintenance
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5 Conclusion and Further Research

The application of the RCM approach illustrated in the case study shows an improvement in the maintenance strategy applied to maintenance of the conveyor belt at Semen Padang Co. mine. Furthermore, the critical level of failure mode with FMEA is analyzed and the MTTF, MTTR and reliability calculations are carried out by looking at the distribution of failures that occur. From these results, improvements were made which resulted in a decrease in hours of downtime by 41.44% from the current hour of downtime.

Finally, this case study to be continued on other mining equipment at Semen Padang Co. for obtaining an optimal maintenance strategy in terms of scheduling equipment maintenance and maintenance costs.