We now present the empirical findings from the research conducted within the Zambian mining industry, specifically in the Copperbelt and North-western provinces. Mining firms that participated in this study were FQM Trident Limited, Lumwana Mine, Kansanshi Mine, Lubambe Mine, Mopani Copper Mine, NFCA Southeast Orebody, Konkola Copper Mine, and CLM Luanshya Copper Mines. These entities represent a broad spectrum of the mining sector in Zambia and provide a comprehensive backdrop for the analysis of maintenance management practices

Identification of maintenance practices is critical to understanding the current maintenance landscape and establishes the foundation for subsequent evaluation and framework development. Through a thorough analysis of the responses from the surveyed professionals, we are able to ascertain the types of maintenance strategies that are in place, their scope, and their alignment with both the firms’ operational objectives and industry best practices.

Here, we examine the implementation of PM policies across the surveyed mining firms. These policies are central to the maintenance strategy and involve scheduling regular maintenance activities to prevent equipment failure before it occurs. Table 1 presents the PM scores and details for each mining firm, providing an overview of how each entity approaches maintenance management within their operations [12] . The scores reflect the firms’ adherence to their PM policies and the effectiveness of their implementation strategies.

PdM represents a shift from traditional maintenance strategies, focusing on real-time monitoring and analysis to predict equipment failure before it occurs [13] . This section assesses the presence and application of PdM programs within the mining firms involved in this study, as well as their impact on maintenance workflows and asset management. Table 2 presents the PdM scores and details for each mining firm, providing an overview of how each entity approaches maintenance management within their operations.

The scores indicate each firm’s engagement with PdM practices, with a score of 16 aligning with the best practice benchmark. The details provided show a varied approach to the application of PdM data, with some firms utilizing the insights gained to actively improve their maintenance strategies, while others have yet to capitalize on this data for enhancing asset performance and longevity. This reflects different stages of maturity in the adoption of PdM technologies and practices across the industry.

The utilization of CMMS is a critical component in modern maintenance management, offering an organized, digital approach to scheduling maintenance, tracking work orders, and managing inventory [14] . Table 3 presents the CMMS scores and details for each mining firm, providing an overview of how each entity approaches maintenance management within their operations. A score of 8 is indicative of the benchmark for best performance in CMMS usage. The scores presented demonstrate a varied level of CMMS utilization among the firms, with some achieving the benchmark and others recognizing the need for further development of their systems.

Reliability Engineering is an essential discipline in maintenance management, aimed at understanding and improving the reliability of systems and components within an organization [5] . Table 4 presents the Reliability Engineering scores and details for each mining firm, providing an overview of how each entity approaches maintenance management within its operations. This subsection delves into how the surveyed mining firms in Zambia adopt and implement reliability engineering practices, such as risk analysis, root cause analysis, and RCM, to enhance their maintenance programs.

We now provide a comprehensive evaluation of the maintenance practices currently in place across the surveyed mining firms in Zambia. The objective was to critically assess how these practices align with industry standards, their effectiveness in sustaining equipment operations, and their impact on overall production efficiency. This evaluation is crucial for identifying strengths, uncovering areas for improvement, and for benchmarking against best practices in the mining industry globally.

The assessment of the maintenance organization within the surveyed mining firms is a critical examination of how maintenance activities are structured and managed. This encompasses the organization’s approach to maintenance responsibilities, documentation clarity, training and competence of maintenance personnel, and the integration of continuous improvement processes. Table 5 presents the maintenance organization scores and details for each mining firm, providing an overview of how each entity approaches maintenance management within their operations.

The scores indicate the level of maturity in the organization and management of maintenance within each firm. The benchmark for best performance in maintenance organization is 16 points.

Analysing MWOs is crucial for understanding the efficiency and effectiveness of the maintenance function. MWOs are pivotal for planning, scheduling, executing, and recording maintenance tasks [15] . Table 6 presents the maintenance work order scores and details for each mining firm, providing an overview of how each entity approaches maintenance management within their operations. This subsection examines the surveyed mining firms’ processes for managing MWOs, their promptness in addressing them, and the systematic approach to maintaining historical data for future reference and continuous improvement.

The scores, with a benchmark of 20, reflect the degree to which each firm effectively handles maintenance work orders. These scores are derived from the percentage of work orders correctly attributed to assets, the thoroughness of work order coverage for maintenance activities, the quality of documentation for historical analysis, and the timeliness of maintenance task completion. Table 6 illustrates the relative performance of each firm in MWO management, identifying areas where they excel and where there are opportunities for improvement.

The effectiveness of maintenance planning and scheduling is a significant indicator of a maintenance organization’s efficiency and effectiveness [16] . Table 7 presents the maintenance planning and scheduling scores and details for each mining firm, providing an overview of how each entity approaches maintenance management within its operations.

The scores out of a possible best practice benchmark of 12 points reflect each firm’s capability in maintenance planning and scheduling. Higher scores indicate a more effective and efficient planning and scheduling process, with fewer delays and disruptions in maintenance operations. The details show that there is room for improvement in some firms, particularly in the areas of planning accuracy and the thoroughness of scheduling to prevent delays in maintenance activities.

Preventive maintenance is a foundational aspect of any robust maintenance management program, focusing on routine checks and services to avert unplanned breakdowns and failures [12] . This subsection evaluates the extent and regularity of preventive maintenance activities across the Zambian mining companies included in the study. Table 8 presents the Preventive Maintenance Coverage and Frequency scores. It reviews how comprehensively preventive maintenance programs cover critical equipment, the frequency of these maintenance activities, and their alignment with best practices

Operator maintenance initiatives represent an essential aspect of proactive maintenance strategies, where operations personnel play a direct role in the upkeep and basic maintenance tasks of equipment [17] . Table 9 presents the Operator maintenance initiatives score. This section evaluates the degree to which operators are involved in generating work order requests and their competence in carrying out minor maintenance tasks, which can significantly influence the overall maintenance workload and equipment uptime. The scores reflect the extent of operator engagement in maintenance initiatives, with a higher score indicating a greater level of involvement and training in maintenance-related tasks. The benchmark score for best performance in operator maintenance initiatives is 8 points. This benchmark represents an optimal level of operator involvement where they are highly proactive in generating maintenance work orders and are adept in performing a range of maintenance tasks such as inspections, lubrication, and minor repairs.

Mining firms offer educational programs to keep their maintenance staff up-to-date on the latest technologies and practices. These programs are essential for ensuring safe and sustainable operations. Table 10 details the scores assigned to each firm’s maintenance training programs, with a maximum achievable score of 12.

The management of maintenance inventory and purchasing is a key component that directly affects the ability of the maintenance department to perform its functions efficiently [18] . This subsection evaluates the practices related to inventory management and purchasing strategies within the mining firms, assessing how they manage their spare parts supply, control inventory levels, and ensure the availability of necessary items for maintenance tasks. Table 11 presents the management of maintenance inventory and purchasing score.

The scores out of a possible benchmark of 12 points provide insight into how well each firm is performing in terms of maintaining the necessary inventory for maintenance and managing the purchasing process efficiently. A higher score indicates a firm that has a solid system in place for inventory control and purchasing, ensuring that maintenance activities are not delayed due to the lack of necessary parts and materials.

Maintenance reporting is a systematic approach used to communicate the status, progress, and results of maintenance activities within an organization. Table 12 presents the Maintenance reporting score. This subsection examines how the mining firms in Zambia approach their maintenance reporting, which includes the generation of reports on equipment downtime, maintenance costs, and metrics such as Mean Time Between Failure (MTBF) and Mean Time To Repair (MTTR). A score of 4 represents the benchmark for best practice in maintenance reporting.

KPIs are vital in monitoring the effectiveness and efficiency of maintenance practices within an organization. They serve as a quantitative measure of maintenance performance and health, providing insight into areas that require improvement and those performing well [1] . In this subsection, we explore the implementation and impact of KPIs in the surveyed mining firms, evaluating how these metrics are used to guide maintenance strategies, resource allocation, and continuous improvement efforts.

Table 13 presents the KPI scores. The scores indicate how effectively each firm uses maintenance KPIs, with a higher score signifying a more sophisticated and integrated KPI system. The benchmark score for best performance in this area is 16 points.

Table 14 presents the financial planning and life cycle cost analysis score. Financial planning and life cycle cost analysis are pivotal for effective maintenance management, providing a framework for understanding the long-term costs associated with equipment ownership [7] . This subsection evaluates the degree to which the mining firms in Zambia incorporate life cycle costing in their financial planning, which is essential for making informed decisions on asset investments, maintenance strategies, and the overall allocation of financial resources.

The scores, with a benchmark of 12 points, reflect each firm’s engagement with financial planning practices that consider the full life cycle costs of their assets. A higher score indicates a more comprehensive approach to integrating life cycle cost analysis into financial planning, which can lead to more cost-effective maintenance management and investment decisions over the long term.

This subsection is dedicated to summarizing and understanding the range and commonality of maintenance practices used across different mining firms in Zambia. Table 15 presents the Descriptive Statistics of Maintenance Practices. Descriptive statistical analysis was performed to calculate means, medians, modes, and standard deviations for each maintenance practice category. Frequency distributions were also assessed as indicated in Table 16 .

To evaluate the maintenance practices within the Zambian mining industry, we conducted a comprehensive analysis using two key statistical methods: Correlation Analysis and Gap Analysis. These methods provide insights into the relationships between different maintenance practices and compare each firm’s performance against industry benchmarks.

Table 17 presents the Correlation Analysis Results. The purpose of the Correlation Analysis was to explore relationships between various maintenance practices. This involved calculating Pearson correlation coefficients for each pair of maintenance practices across different mining companies. The analysis helps in identifying practices that are closely related and may influence each other.

Table 18 shows the results from the Gap Analysis that was performed to compare each mining firm’s scores against the industry benchmarks (Best Firm scores). This analysis identifies specific areas where improvements are needed and where a firm is excelling.

The Gap Analysis provides a crucial insight into how each mining firm’s performance in various maintenance practices compares against the industry benchmarks, referred to as “Best Firm” scores. Interpretation of Gap Analysis results is as follows:

1) Maintenance Organisation: Almost all firms, except CNMC, KCM, and MOPANI, show a gap in their performance in this category. The negative values for KMP, TRIDENT, NFCA, LUBAMBE, and LUMWANA indicate areas for improvement.

2) Education Programs: This category reflects significant gaps for most firms, particularly for TRIDENT and LUBAMBE, indicating a need for enhanced focus on educational initiatives.

3) Maintenance Work Orders: Notable gaps are observed for TRIDENT, NFCA, and LUMWANA. This suggests that these firms may need to refine their work order management processes.

4) Maintenance Planning and Scheduling: While TRIDENT and LUMWANA align with the benchmark, other firms demonstrate gaps, indicating potential areas for improvement in planning and scheduling effectiveness.

5) Preventive Maintenance: The results show that most firms meet or are very close to the benchmark, with KCM performing above the benchmark.

6) Maintenance Inventory & Purchasing: Several firms, particularly MOPANI and NFCA, need to focus on improving their inventory management and purchasing strategies to meet industry standards.

7) CMMS Usage: There is room for improvement in CMMS implementation for most firms, as indicated by negative scores.

8) Operator Maintenance: A significant gap is observed in TRIDENT, NFCA, and LUBAMBE, suggesting a need for better engagement of operators in maintenance activities.

9) Maintenance Reporting: Most firms meet the benchmark, but KMP and LUBAMBE show gaps, indicating a need for more comprehensive maintenance reporting practices.

10) Predictive Maintenance: The performance of all firms aligns with or is close to the benchmark, indicating a strong focus in this area.

11) Reliability Engineering: CNMC, KCM, and LUMWANA are at the benchmark, but significant gaps exist in other firms, especially KMP and TRIDENT.

12) Maintenance KPI: Many firms are on par with the benchmark. However, TRIDENT shows a substantial gap, suggesting a need for improved performance tracking.

13) Finance Planning: Variability is observed in this practice, with NFCA at par with the benchmark, while TRIDENT, KMP, and LUMWANA show notable gaps.

Thus, the Gap Analysis highlights specific areas where each firm excels and where there are opportunities for improvement. By addressing these gaps, Zambian mining firms can enhance their overall maintenance management performance, aligning closer to industry best practices.

The Factor Analysis of maintenance practices within the Zambian mining industry has revealed several key dimensions that are crucial for understanding how these practices are interconnected and how they contribute to overall maintenance management.

The Regression Analysis aimed to explore the impact of various maintenance practices on the overall effectiveness of the maintenance program. The coefficients obtained provide valuable insights into the relative influence of each practice.

Table 19 shows the results from factor analysis of maintenance practices within the Zambian mining industry has revealed several key dimensions that are crucial for understanding how these practices are interconnected and how they contribute to overall maintenance management.

Factor 1 Interpretation: Factor 1 shows strong negative associations with practices like “Reliability Engineering”, “Education Programs”, “Maintenance KPI”, and “Preventive Maintenance”. This suggests that when Factor 1 is predominant, there is a reduced focus on long-term and strategic aspects of maintenance management. It indicates that firms scoring high on this factor might be prioritizing immediate operational needs over strategic, long-term planning.

Factor 2 Interpretation: This factor highlights a significant emphasis on “Predictive Maintenance” and “Education Programs”. The positive loadings here suggest that firms scoring high on this factor are likely to be more proactive in their maintenance approach, utilizing predictive techniques and investing in training and development. This aligns with modern maintenance practices that focus on preventing issues before they occur and ensuring the workforce is well-equipped with the necessary skills.

Factors 3 and 4 Interpretation: These factors show mixed loadings across various practices, indicating that they might represent more nuanced or specific aspects of maintenance management that don’t align neatly into broad categories like strategy or proactivity.

Table 20 shows results from the Regression Analysis that was aimed to explore the impact of various maintenance practices on the overall effectiveness of the maintenance program. The coefficients obtained provide valuable insights into the relative influence of each practice.

Positive Coefficients Across All Practices:

All the maintenance practices analysed have positive coefficients, indicating that they positively contribute to the overall effectiveness of maintenance management. This implies that improvements or investments in these areas are likely to enhance maintenance performance.

High-Impact Practices: Practices such as “Maintenance Work Orders”, “Maintenance Planning and Scheduling”, “Preventive Maintenance”, “Predictive Maintenance”, and “Maintenance KPI” show coefficients greater than 1. This suggests that these areas have a substantial impact on enhancing maintenance effectiveness. Specifically:

Maintenance Work Orders and Planning & Scheduling: These practices are critical for operational efficiency, indicating that well-managed work orders and effective planning significantly drive maintenance success.

Preventive and Predictive Maintenance: This reflects the growing importance of proactive maintenance strategies in minimizing downtime and extending equipment life.

Maintenance KPI: The high coefficient here highlights the importance of performance tracking and measurement in maintenance management.

Moderate Impact Practices: “Maintenance Organisation”, “Maintenance Inventory & Purchasing”, “CMMS”, “Operator Maintenance”, and “Maintenance Reporting” have coefficients less than 1 but are still positive. This suggests that while these areas are important, their impact might be more nuanced or indirect compared to other practices. For instance, effective CMMS usage and organized inventory & purchasing contribute to smoother maintenance operations, albeit less directly than more proactive strategies.

Education Programs and Finance Planning: These areas also show significant coefficients, emphasizing the importance of continuous learning and financial acumen in maintenance. It indicates that investing in staff education and sound financial planning are key drivers of maintenance excellence.

The analysis of maintenance practices within the Zambian mining industry highlights a diverse range of strategies employed across various firms. The practices identified range from preventive and predictive maintenance to the use of advanced CMMS and reliability engineering techniques. This diversity reflects the complexity and variability of maintenance needs within the industry.

The Regression Analysis findings were utilized to inform the development of the EMMF in several ways:

1) Prioritization of High-Impact Practices: The framework will prioritize areas that have shown the highest impact on maintenance effectiveness, such as proactive maintenance strategies (Preventive and Predictive Maintenance) and robust planning and scheduling.

2) Integration of Operational and Strategic Elements: While operational practices like work order management are crucial, the framework will also emphasize strategic aspects like KPI tracking and financial planning, as indicated by their significant coefficients.

3) Balanced Approach to Maintenance Management: The framework will advocate for a balanced approach that values both moderate and high-impact practices, ensuring a holistic maintenance strategy that covers operational efficiency, strategic planning, technological adoption, and workforce development. By combining these analytical insights, the EMMF will offer a comprehensive guide for mining firms to enhance their maintenance management practices, ultimately leading to improved reliability, efficiency, and cost-effectiveness in their operation.

The effectiveness of maintenance practices within the Zambian mining industry is a critical factor that significantly impacts equipment operations and overall production efficiency. The thorough evaluation of these practices reveals their alignment with industry standards and their pivotal role in ensuring operational continuity and efficiency.

The analysis of maintenance work orders is essential to understand the execution and planning of maintenance tasks. This efficiency is reflective of best practices in execution and data utilization. Effective work order management is a cornerstone of successful maintenance operations, as it ensures timely and efficient maintenance activities. It helps in reducing equipment downtime, which is a critical factor for maintaining operational productivity in the mining industry.

The effectiveness of maintenance planning and scheduling is a significant indicator of an organization’s maintenance efficiency. It plays a vital role in minimizing operational interruptions and ensuring that maintenance activities are performed in a cost-effective and timely manner.

The variation in scores among different firms indicates different levels of adherence to preventive maintenance protocols. A comprehensive approach to preventive maintenance can significantly improve equipment performance and longevity. These firms, with their high scores, demonstrate a proactive approach to maintenance, covering nearly all critical equipment and basing maintenance frequency on thorough condition monitoring.

The engagement of operators in maintenance tasks is an essential aspect of proactive maintenance strategies. These operators are not only involved in generating work order requests but are also trained in carrying out basic maintenance tasks. This involvement empowers operators to take an active role in the upkeep of the equipment they operate, fostering a culture of attention to detail and preventive care. Operator maintenance initiatives help in reducing the overall maintenance workload and improving equipment uptime.

The correlation analysis uncovered a range of relationships between different maintenance practices, revealing how interconnected these practices are. A notable finding is the strong positive correlation between maintenance organization and education programs. This relationship indicates that improvements in the organizational structure of maintenance departments are closely tied to the effectiveness of education programs.

Another significant correlation observed was between education programs and preventive maintenance. This implies that investment in education leads to more effective implementation of preventive maintenance strategies. It highlights the importance of continuous learning and development in the field of maintenance, enabling personnel to adopt and apply the best preventive practices effectively.

Interestingly, the analysis also revealed negative correlations, particularly between maintenance reporting and other practices such as maintenance organization and maintenance KPI. This suggests a potential disconnect between the reporting mechanisms and the broader organizational structure and goals. It raises questions about the efficiency and effectiveness of maintenance reporting in its current form and suggests that improvements in this area could have far-reaching benefits.

The development of the EMMF for the Zambian mining industry represents a significant step towards enhancing maintenance practices and ensuring operational excellence. The EMMF, informed by a comprehensive analysis of current maintenance operations, synthesizes various strategies into a cohesive and strategic approach. It is tailored to address the unique challenges and opportunities within the Zambian mining sector, thereby boosting the reliability and efficiency of mining equipment.

Table 21 encapsulates key insights and integrations of various components into the EMMF framework. Figure 7 indicates the hierarchy of the EMMF. This table serves as a concise overview, setting the stage for the comprehensive discussion that follows.

This is a critical element of the EMMF, focusing on forecasting potential equipment issues to prevent downtime [13] . In the context of the Zambian mining industry, where equipment reliability is paramount, the adoption of predictive maintenance can significantly reduce unplanned outages and maintenance costs. This shift not only improves equipment longevity but also enhances safety and reduces operational disruptions [1] .

In the Zambian mining context, where maintenance operations can be complex and resource-intensive, the integration of CMMS [14] can bring about increased efficiency and better resource allocation. By streamlining maintenance processes, CMMS helps ensure that maintenance tasks are performed promptly and accurately, thereby improving overall equipment performance [19] .

The mining industry is continually evolving with new technologies and practices, and the workforce must be equipped with the latest knowledge and skills. Training programs focused on advanced maintenance techniques, safety standards, and the use of sophisticated maintenance software are essential.

This is an integral component of the EMMF, focusing on improving the reliability of systems and components within the mining operations. This approach involves thorough risk analysis, root cause analysis, and the application of reliability-cantered maintenance (RCM) [5] methodologies. For Zambian mining firms, adopting reliability engineering practices means a more structured approach to maintenance planning, leading to fewer equipment failures and increased operational uptime.

Data analytics is highlighted in the EMMF as a crucial tool for informed maintenance decision-making [19] . In an industry where large volumes of operational data are generated, leveraging this data can provide significant insights into equipment performance, maintenance needs, and operational efficiencies. Data analytics enables mining firms to move towards data-driven maintenance strategies, optimizing maintenance schedules based on actual equipment conditions rather than predetermined schedules [20] .

Efficient inventory management is a key aspect of the EMMF. The availability of essential maintenance items and spare parts is critical to avoid delays in maintenance activities. Effective inventory management ensures that the right parts are available at the right time, minimizing equipment downtime and maintaining a smooth flow of operations.

The EMMF advocates for treating maintenance activities with the same rigor and structured approach as other critical business projects. This perspective ensures that maintenance tasks are not only aligned with broader business goals but are also managed effectively, delivered on time, and within budget.

Health and safety are paramount in the mining industry, and the EMMF places a strong emphasis on compliance with safety regulations. A safe work environment not only protects employees but also ensures that maintenance activities are carried out without accidents and interruptions. Implementing stringent health and safety standards as part of the maintenance process is crucial for the well-being of the workforce and the smooth operation of mining activities.

The EMMF aligns with the increasing importance of sustainability within industry practices. Eco-friendly maintenance processes, such as the use of environmentally friendly materials, recycling, and waste reduction, are encouraged. This approach not only addresses environmental concerns but also enhances the social and corporate responsibility of mining firms.