Strategic Solutions to Performance Decline at PLTU Energi Nusantara

The Energi Nusantara Power Plant (PLTU Energi Nusantara) is facing a severe operational underperformance of lower generation, effectiveness of maintenance, and settled financial penalties from PLN on electricity supply toward PLN. These challenges have resulted in growing operational costs and falling revenues, undermining the sustainability of PLTU. Overcoming these challenges requires that a fundamental shift take place, and this paper focuses on the two main issues: the transition from a reactive maintenance culture towards predictive maintenance and the situation where decision- makers are between replacing a machine and taking major overhaul action when the machine’s condition has failed. Preventive maintenance is good maintenance that will increase the reliability of equipment, minimize downtime, and maximize electricity generation. These investment decisions have produced a trade-off between the replacement of obsolete equipment (with long-term benefits from technological progress) and carrying out big maintenance as a temporary cost-effective intervention. Employing Business Process Re-engineering (BPR), Total Productive Maintenance (TPM), and Life Cycle Cost Analysis (LCCA), it analyzes historical operational and financial data to suggest the best solutions. Physical evidence is that preventive maintenance increases plant effectiveness and decreases maintenance cost. Even where replacement of machinery requires higher initial capital investment, it will contribute to better operational and financial results over the long term than permanent repairs. This study offers direct guidelines for improving operating practices, establishing sustainable preservation strategies, and employing data-based capital investment decisions that help rehabilitate the plant’s performance and preserve its financial viability. The solutions enable PLTU to meet Indonesia’s increasing need for electricity and enhance its competitive landscape in the energy industry.

Introduction

The energy industry is the main sector in economic development, where the majority of power plants in Indonesia still use coal for energy generation. But, faced with growing operational issues and regulatory constraints, these same operators must produce power even more efficiently and sustainably. PLTU Energi Nusantara is running at very poor performance with low generation and inefficient maintenance, and PLN is applying fines for not delivering as per contractual contents. These problems have led to spiraling costs, falling income, and financial uncertainty, threatening the plant’s future.

The main operational challenges are long downtime due to aging equipment, a reactive maintenance approach, and unreliable coal feed. The financial effect of such inefficiencies could be seen; revenue decreased from IDR 54.3 thousand million in 2020 to 26.4 in 2023. Additionally, permanent sanctions from PLN make your financial difficulties worse. In the face of these challenges, it becomes essential to find efficient ways to recover operations and financial sustainability.

This work investigates two strategic scenarios: shifting from corrective to preventive maintenance to enhance the equipment reliability and to reduce downtimes, and investment decisions based on long-term planning for machinery replacement and major maintenance. The study adopts BPR to redesign inefficient processes, TPM as a philosophy towards developing an effective strategy, and LCCA as the technique in evaluating the financial viability of investment decisions over long periods.

The results in this study offer some clues to the best way of enhancing plant performance. Preventive maintenance is likely to improve equipment life and reduce operational downtime, and investment choices will determine if new equipment or the replacement of aged machinery makes more economic sense in the long term over heavy maintenance. Above all, the suggested solutions are designed to reestablish PLTU Energi Nusantara’s competitiveness and financial viability and give a helping hand to the fast-increasing demand for electricity in Indonesia.

Literature Study

This paper proposed an integrated solution to overcome the technical-operational and financial problems in PLTU Energi Nusantara by three major approaches: operational optimization using Business Process Reengineering (BPR), maintenance strategy using Total Productive Maintenance (TPM), and investment analysis using Life Cycle Cost Analysis (LCCA). These methods offer a disciplined method to streamline operations and improve maintenance practices and finances.

Operational Optimization using Business Process Reengineering (BPR)

Business Process Reengineering (BPR) is an intentional process for infusing innovation into organizations through the redesign of business processes to achieve dramatic improvements in critical, contemporary measures of performance such as cost, quality, service, and speed (Grover & Kettinger, 1998). BPR is about reimagining and reengineering processes, automating them, and making use of resources in an efficient way to bring about substantial positive change in cost, quality, and throughput (Srinivasan, 2011).

In the background of PLTU Energi Nusantara, BPR as a conceptual framework is utilized to create efficient operational processes by moving from reactive to preventive maintenance, better coordination among departments, and coal inventory management. Cause-and-effect process mapping analysis is one such method used to detect inefficiencies, and digital monitoring systems are being introduced to facilitate fast decision-making (Devani & Maidila, 2021). The company’s introduction of BPR should help cut downtime, raise electricity produced, and lift operations overall.

Maintenance Strategy using Total Productive Maintenance (TPM)

Total Productive Maintenance (TPM) is a maintenance system that leads to covering proactive and preventive ideas to achieve maximum equipment reliability and operational effectiveness (Agustiady & Cudney, 2016). The aim of TPM is to integrate maintenance into the daily operations and involve all employees, from operators to managers, in maintaining the condition of equipment (Borris, 2005).

The TPM model incorporates three main pillars: autonomous maintenance, under which operators are trained to conduct typical machine inspections and carry out simple repairs; planned maintenance, which indicates that planned maintenance activities are scheduled based on the history of failures; and predictive maintenance, which uses data analytics to predict potential failure (Agustiady & Cudney, 2016).

PLTU Energi Nusantara uses TPM to minimize equipment failures and to increase the reliability of the plant. Moving from responsive to predictive maintenance would allow the plant to minimize the incidence of non-scheduled downtime, reduce overall maintenance costs, and lessen the operating life of key assets. It is found from the studies that implementation of TPM in coal-fired power plants shows improvements in OEE, operation effectiveness of the system, and reduction in repair cost (Devani & Maidila, 2021).

Investment Analysis using Life Cycle Cost Analysis (LCCA)

Life Cycle Cost Analysis (LCCA) is a financial evaluation tool to scrutinize the overall cost of an asset over its lifetime, which includes asset acquisition, operation, maintenance, and disposal costs (Dhillon, 2009). It helps decision-making by allowing a comparison between the long-term cost implications of various investment options (Smartet al., 2019).

n PLTU Energi Nusantara, both investment options similar to the above (i.e., renewing old machines after they reach their economic life and new machine investment for second-life service) are analyzed. Through the evaluation of principal financial indexes, such as NPV, IRR, PBP, PI, and LCCA, the most economical investment direction is exposed. LCCA is a tool to minimize the capital investment and to make an economic balance sheet of the life cycle of the power plant so that the financial life cycle of the cycle power plant (Blank & Tarquin, 2020).

This integrated model involving BPR for operation optimization, TPM for maintenance enhancement, and LCCA for investment planning provides a systematic approach for reviving the performance of PLTU Energi Nusantara. BPR reduces bottlenecks, TPM improves machine reliability, and LCCA assists in cost-effective investment decisions. Collectively, these efforts are toward less downtime, lower maintenance costs, and long-term financial sustainability in power plant operations.

Methodology

A multimethod research methodology, combining both qualitative and quantitative analyses, is adopted to assess operational inefficiencies, the maintenance strategy, and the investment opportunity.

Operational Data Analysis (Using BPR)

Most of the existing approaches apply to creating solutions that rely on years of experienced operations or using the BPR.

The operational data analysis is used to assess and improve the current inefficiency of operations performed by PLTU of Energi Nusantara. Business Process Reengineering (BPR) is an approach that formally and structurally addresses the analysis and redesign of business processes at an entirely new level in order to attain dramatic improvements in overall simulation cost efficiency and performance.

BPR combines maintenance plans and investment alternatives in order to optimize the operational performance and the long-term viability. By tracing every process, it realizes gaps, which can be filled with preventive maintenance and suitable investments, which in turn will work together in an arrow-forward manner. Business Process Redesigning (BPR) is used to model the current process, detect bottlenecks, and propose prioritized processes.

Thus, BPR yields immediate and enduring benefits. In the immediate future, preventive maintenance underpinned by TPM will stabilize operations and enhance equipment effectiveness. For a long time, replacing machinery will improve performance, save energy, and be reliable. The PLTU Energi Nusantara integrated application presents a comprehensive paper on PLTU Energi Nusantara’s performance restoration and financial stabilization and supports the continuous development of sustainable energy production.

Maintenance Analysis (Using TPM)

The Maintenance Analysis evaluates the effectiveness of shifting from corrective maintenance to preventive maintenance using Total Productive Maintenance (TPM). The analysis measures equipment performance through Overall Equipment Effectiveness (OEE). OEE is calculated using the formula:

$$\begin{array}{rcl}& & OEE=(Availability)\times (Performance)\times (Quality)\end{array}$$

where:

$$\begin{array}{rcl}& & \text{Availability}=\frac{PlanProductionTime-Downtime}{PlanProductionTime}\\ & & \text{Performance}=\frac{ActualOutput}{TheoreticalOutput}\\ & & \text{Quality}=\frac{GoodUnitsProduced}{TotalUnitsProduced}\end{array}$$

The methodology is based on the computation of OEE for preventive and corrective maintenance policies for a quantitative comparison. Preventive maintenance is a desired outcome if it gives rise to a higher OEE, as it indicates the reliability, effectiveness, and cost-effectiveness.

This TPM-based analysis is used to not only determine the optimum maintenance policy but also to make investment decisions. This systematic method will mean maintenance policy and investment are made in line with the operation objective of PLTU Energi Nusantara, improving the productivity and sustainability for the long term to come.

Investment Data Analysis (Using LCCA)

The Investment Data Analysis assesses the financial feasibility of two options:

• Repairing existing machinery (major maintenance).

• Purchasing new equipment (capital investment).

Life Cycle Cost Analysis (LCCA) is applied to compare the long-term costs and benefits of each option, using Net Present Value (NPV), Internal Rate of Return (IRR), and Payback Period (PBP).

Net Present Value (NPV)

NPV is used to determine the profitability of each investment option by discounting future cash flows:

$$\begin{array}{r}NPV=\sum _{t=1}^n\frac{C_t}{{(1+r)}^t}-C_0\end{array}$$

NPV measures the difference between the present value of cash inflows and outflows. A positive NPV indicates that the investment will generate returns exceeding the cost of capital.

Internal Rate of Return (IRR)

$$\begin{array}{r}\sum _{t=1}^n\frac{C_t}{{(1+IRR)}^t}=C_0\end{array}$$

IRR represents the discount rate that makes the NPV of an investment equal to zero. A higher IRR compared to the WACC indicates a profitable investment.

Payback Period (PBP)

PBP measures how long it takes for an investment to recover its initial cost:

$$\begin{array}{r}PBP=\frac{InitialInvestmentCost}{AnnualNetCashInflow}\end{array}$$

Shorter payback periods are generally preferred as they reduce financial risk.

Profitability Index (PI)

$$\begin{array}{r}PI=\frac{PresentValueofFutureCashFlows}{InitialInvestmentCost}\end{array}$$

PI evaluates profitability/size to assess the feasibility of an investment.

Net Present Value (NPV), Internal Rate of Return (IRR), Payback Period (PBP), and Profitability Index (PI) are used to evaluate the potential return on investment, the time required to recover initial costs, and the relative profitability of different options. For instance, an option with a higher NPV and IRR, shorter PBP, and greater PI is considered more financially attractive.

To assess risk, Sensitivity & Scenario Analysis is performed by varying key financial parameters:

• ±20% changes in investment costs, maintenance costs, and electricity prices.

• Scenario Analysis evaluates three conditions:

– Best Case: Higher revenue, lower maintenance costs.

– Base Case: Expected operational conditions.

– Worst Case: Increased downtime and higher operational costs.

The sensitivity analysis is used to test the eligibility of the investment options and to confirm their financial viability under different economic and operating scenarios. “Best-case” and “worst-case” scenarios are used in the scenario analysis to estimate the likely range. Performance is compared to industry standards through benchmarking to determine the proposed strategies in relation to best available practices for coal-fired generation. These analyses guarantee that the investment decisions would be financially viable and market resilient.

An additional risk measure is provided using a Monte Carlo simulation. This simulation is repeated 10,000 times; input values (electricity prices, maintenance costs, fuel prices, etc.) are driven by a probability distribution of which we sample 10,000 times to generate the probable states of the world in terms of heterogeneity.

Key outputs analysed include:

• Probability of NPV > 0 (ensuring financial viability).

• Expected IRR Distribution (to assess investment return consistency).

• Break-even Probability (likelihood of cost recovery within the expected payback period).

Monte Carlo outcomes also provide guidance on the risk-adjusted viability of the investment and on financial levels required to be maintained for profitability.

By adopting BPR, TPM, and LCCA, three major objectives are set to be achieved through this research. The first is bringing in greater operating efficiency by recognizing and removing the process bottlenecks and by maximizing the coal process network. Secondly, it seeks enhanced maintenance efficiency in order to move from a reactive maintenance scheme to a preventive one. Production reliability may be a direct, significant, and observable benefit from prevention, while machine downtime may decrease as well. Finally, it hopes to facilitate cost-effective financial decision-making by informing investment in upgraded machinery or a maintenance strategy.

On the whole, this approach is comprehensive, data-driven, and applied to improve the performance of PLTU Energi Nusantara, acknowledging that this would result in operational excellence and financial sustainability in a sustainable solution.

Finding and Discussion

The purpose of this study is to propose practical alternative solutions based on applied theory framework and research methods, i.e., interview and survey. Through distilling the findings into tangible, actionable insights, this analysis strives to provide a rich overview of the problems and possible responses.

Operational data analysis of this study is used to identify the efficiency of PLTU Energi Nusantara’s business processes and to re-engineer the business processes of PLTU Energi Nusantara. Key operational constraints in coal handling, equipment utilization, and maintenance processes were isolated through process mapping and cause-effect analysis.

Based on this assessment, the BPR framework for PLTU Energi Nusantara is structured as follows:

According to Fig. 1, this model allows PLTU Energi Nusantara to transition from reactive maintenance into proactive and cost-effective operations. The facility can also lower plant downtime, optimize maintenance scheduling, and extend the life of equipment by incorporating total productive maintenance (TPM) and predictive maintenance.

Fig. 1. BPR framework.

BPR offers a methodical framework to reengineer these processes. The first step is to map the existing process to find inefficiencies and bottlenecks. Root cause analysis (RCA) is used to identify the fundamental causes impacting plant performance degradation. Table I will explain the process mapping and bottleneck from the PLTU business process as described in Table I.

Table I. Process Mapping PLTU Energi Nusantara

	PLTU operation process	Maintenance process
Input	Coal, water, air, and supporting fuel.	Machine performance data, maintenance schedules, and spare parts.
Process	– Coal Preparation: Coal is crushed and prepared for combustion.	– Monitoring: Periodic monitoring of machine conditions.
	– Combustion: Coal is burned in the boiler to generate steam.	– Problem Identification: Detecting potential issues through manual inspections.
	– Power Generation: Steam drives a turbine connected to a generator to produce electricity.	– Repairs: Performing corrective maintenance
		– Reporting: Documenting maintenance results for further evaluation.
	– Cooling: Steam is cooled back into water for reuse.
	– Electricity Distribution: Electricity is transmitted to the PLN network.
Output	Electricity ready for distribution.	Machines ready to operate with optimal efficiency.
	PLTU Operation Process	Maintenance Process
Problem	– Frequent boiler failures due to lack of preventive maintenance.	– Manual monitoring system that is not real-time, causing delayed issue detection.
	– Long processing time due to outdated equipment.	– Delayed spare parts procurement due to a slow purchasing process.
Impact	– Frequent downtimes, reducing electricity production capacity.	– Undetected machine failures, leading to higher repair costs.
	– Delays in combustion, reducing power generation efficiency.	– Extended downtimes, reducing PLTU productivity.

Process mapping and bottleneck identification that have been combined with Business Process Reengineering (BPR) have been minimally applied as the basis of the optimization of operation and maintenance processes at PLTU Energi Nusantara. With inefficient workflows redesigned and bottlenecks removed, the plant can shift from reactive maintenance practices to more organized, proactive strategies. Applying BPR retrieves some waste steps in coal preparation, boiler operation, and power generation, and the automation and intelligence monitoring programs are introduced to improve production efficiency.

The major findings revealed that the dependence on corrective maintenance is expensive and causes extensive operational downtime. In addition, investment decisions between buying new machines are faced with a choice of replacing or overhauling aging machinery.

Based on Fig. 2, to overcome those challenges, the BPR framework suggests the move to preventive maintenance from corrective maintenance. Preventative maintenance is known as scheduled maintenance designed to prevent the breakdown of equipment and increase the longevity of machines. This transition is further assisted by using this concept of TPM, which is a practice in an organization that involves the entire workforce in maintaining a planned level of equipment performance in the process.

Fig. 2. Workflow diagram.

This study will use the Total Productive Maintenance (TPM) model to compute the Overall Equipment Effectiveness (OEE) of two approaches. OEE is used as a performance indicator that combines these three fundamental aspects: availability, performance efficiency, and quality rate. By means of this calculation, we want to be able to evaluate the real consequences of the application of each one of these maintenance techniques, with a view to the best way to increase the operational reliability and the productivity of their machinery.

• Corrective Maintenance:

$$\begin{array}{rcl}& & \text{Availability}=\frac{17,520-8,330}{17,520}=52.45\mathrm{\%}\\ & & \text{Performance}=\frac{33,627,598}{88,000,000}=38.21\mathrm{\%}\\ & & \text{Quality}=\frac{33,627,598}{33,627,598}=100\mathrm{\%}\\ & & \text{OEE Formula}=OEE=52.45\mathrm{\%}\times 38.21\mathrm{\%}\times 100\mathrm{\%}\\ & & =20.04\mathrm{\%}\end{array}$$

• Preventive Maintenance:

$$\begin{array}{r}\text{Availability}=\frac{17,520-4,316}{17,520}=75.37\mathrm{\%}\end{array}$$

Average time is reduced in the transition from corrective to preventive maintenance = 50.51% (Devani & Maidila, 2021)

$$\begin{array}{rcl}& & \text{Performance}=\frac{53,301,078}{88,000,000}=60.57\mathrm{\%}\\ & & \text{Quality}=\frac{53,301,078}{53,301,078}=100\mathrm{\%}\\ & & \text{OEE Formula}=OEE=75.37\mathrm{\%}\times 60.57\mathrm{\%}\times 100\mathrm{\%}\\ & & =45.65\mathrm{\%}\end{array}$$

Preventive maintenance is clearly the superior strategy for PLTU Energi Nusantara, as it ensures greater equipment reliability, minimizes unplanned downtimes, and optimizes operational efficiency. By leveraging OEE as a standardized performance measure, this analysis will provide valuable insights into how each maintenance approach influences downtime, operational costs, and overall efficiency.

For investment decisions, tools like Life Cycle Cost Analysis (LCCA) are applied to evaluate options such as major maintenance or machinery replacement. Investment decision-making is a critical process in ensuring the long-term sustainability and efficiency of power generation facilities. This analysis will assess the Net Present Value (NPV), Internal Rate of Return (IRR), Payback Period (PBP), and Profitability Index (PI) to determine the most cost-effective solution.

Figs. 3 and 4 related to the investment calculation results for PLTU Energi Nusantara, several key highlights can be explained based on financial and investment analysis between the options of repairing the old machinery and purchasing new equipment.

Fig. 3. Investment analysis for repairing existing machinery.

Fig. 4. Investment analysis for purchasing new equipment.

Overall, purchasing new equipment is more profitable compared to repairing the old machinery, as indicated by the higher Net Present Value (NPV) of Rp 15,938 million for the new equipment option, compared to Rp 4772 million for repairs. This suggests that investing in new machinery will generate greater financial benefits in the long run.

Meanwhile, based on the Life Cycle Cost Analysis (LCCA) results, the total life cycle cost for purchasing new equipment is Rp 96,122 million, higher than Rp 60,290 million for repairs. However, this higher cost is offset by the greater revenue potential from investing in new equipment. This is further supported by the profitability ratio, where new equipment has a ratio of 1.97, higher than 1.74 for repairs. This confirms that purchasing new equipment will yield greater long-term profits compared to the repair option.

Based on these calculations, purchasing new equipment is the recommended choice as it offers higher financial benefits, faster investment returns, and better operational efficiency compared to simply repairing the old machinery.

Sensitivity analysis in Table II shows that the sensitivity impact of electricity price declines on the financial viability of the project is very high on NPV. If electricity prices drop, the project is no longer profitable, whereas if they increase, the value significantly improves. Initial investment also has a significant impact; that is, an increase in capital spending reduces the profitability, whereas reduced investment costs make the plan feasible. Conversely, although the operating costs have the least significant impact, it further illustrates the significance of stabilizing electricity prices and maximizing the investment costs to ensure long-term sustainability.

Table II. Calculation Sensitivity Variable

Variable	Unit	Current	+20% Swing	Base	−20% Swing	Current NPV	+20% Swing NPV	−20% Swing NPV	%+20% SWING	%−20% SWING	Absolute
Initial investment	Rp Mio	75,000	90,000	75,000	60,000	15,938	3,465	28,410	−78%	78%	156.5%
Operation costs	Rp/kWh	788.19	946	788	631	15,938	12,769	19,106	−20%	20%	39.8%
Electricity price	Rp/kWh	025	1230	1,025	820	15,938	34,766	(2,891)	118%	−118%	236.3%

In Table III, scenario analysis more closely examines financial viability by considering different market conditions: worst, base, and best-case scenarios. At the most unfavorable conditions, the project is at risk when the electricity price is too low and the investment amount is too high. But profitability increases in the down and best cases, the latter of which results in the highest financial returns. The findings of this research highlight the need for a systematic structuring of development projects that does a trade off between the cost of investment and the expected revenue to be generated under different economic conditions.

Table III. Scenario Analysis

Variable	Unit	Worst	Base	Best
Electricity price	$/ton	897	1025	1370
Costs ratio	$/ton	0.05	0.05	0.22
Initial investment	$ Mio	78,750	75,000	71,250
NPV	$ Mio	(8169)	15,938	50,777

Simulation analysis can include a probability distribution of NPV values, thus supporting more detailed risk analysis. The distribution follows a near-normal pattern with skewness and kurtosis almost zero, as revealed by the results depicted in Fig. 5. Most NPV observations are centered on the mean, suggesting a strong overall financial viability of the project. With an NPV that can be certain to be greater than zero, this project looks to be worthwhile given the realistic market conditions. These comparative studies together form a strong basis for financial risk decisions, pointing towards the requirement for proactive risk management to ensure long-run profitability and sustainability.

Fig. 5. Simulation analysis result.

Conclusion

PLTU Energi Nusantara suffers from substantial operational inefficiency and financial sustainability, indicating the comprehensive strategy to reengineer the workflow, to optimize maintenance, and to analyze the best investment model. Business Process Re-engineering (BPR) is a foundation to reorganize operations and embed preventive maintenance practices into daily routines. This leads to a switch from corrective maintenance to preventive maintenance, with the subsequent benefits of enhanced reliability, shorter downtime, and higher cost-effectiveness. The implementation of predictive monitoring, perfected spare parts handling, and employee training creates an organized, proactive maintenance culture that leads to better stability and productivity throughout the operation.

Preventative maintenance makes an even larger contribution to performance enhancement, as evident from the gain in OEE of 25.61% (going from 20.04% under corrective maintenance to 45.65% after introducing preventative maintenance practices). Scheduled maintenance, condition monitoring, and predictive analytics help maintain equipment uptime, minimize failures and increase productivity, extend asset life and lower maintenance costs, and provide a more predictable stability in power generation.

Following analysis with LCCA, it is found that even though major repairs are less expensive in the first cost stage, replacement is more cost-effective over the full life cycle. Although a new machine would cost more in its lifecycle (Rp 96,122 million vs. Rp 60,290 million for repair), the incremental generated profit is able to pay the differential. The new equipment produces a much higher NPV of Rp 15,938 million and an IRR of 12.42%, so it has outperformed the financial profitability of repairing the existing asset. A profit/cost ratio of 1.97 further confirms new machinery is more efficient, has less overhead, and increases production capacity for a greener and healthier power generator solution.

When BPR is combined with the traditional approaches like BPR for improvement in workflow, TPM for better equipment performance, and LCCA for investment of strategic resources, substantial operational and financial improvements are possible. These will result in a stable electricity supply, a reduction in contractual penalties, and improved competition in the context of the national energy of Indonesia, thus promoting sustainability and resilience.

Conflict of Interest

Conflict of Interest: The authors declare that they do not have any conflict of interest.