DSpace Repository

Welcome to the NWU Repository, the open access Institutional Repository of the North-West University (NWU-IR). This is a digital archive that collects, preserves and distributes research material created by members of NWU. The aim of the NWU-IR is to increase the visibility, availability and impact of the research output of the North-West University through Open Access, search engine indexing and harvesting by several initiatives.

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Recent Submissions

A multi-layered non-linear methodology to introduce alternative handheld drilling technology in tabular narrow reef mines
(North-West University, 2026) van Rooyen, Bertus; Vosloo, JC; van Laar, JH
Any mining operation that is unwilling or unable to adopt technological advancements will face profitability challenges throughout its lifespan. This statement is especially relevant to mature gold mines in South Africa that are air-reliant on compressed air rock drills. These operations were mainly sunk in the twentieth century, when compressed air drilling systems were the only effective method for drilling blastholes in narrow reefs. At that time, electricity was inexpensive and readily available, and the production blocks were close to the shafts. In the twenty-first century, the opposite is true, as compressed air drilling systems at certain mines are no longer techno-economically viable. Available literature indicates that alternative handheld drilling technologies exist but are rarely adopted due to insufficient implementation and change management methodologies. This study employed the case study research methodology to develop a unique pragmatic approach to implementing alternative handheld drilling technologies in mature, deep-level, tabular narrow reef gold mines. The agile method enables mine management to anticipate the urgency for alternative drilling technology before the need becomes a necessity. Past failures were analysed to identify hidden risks and opportunities that had been previously overlooked or underestimated. These failure drivers were used as strategic guidance to formulate the study specific method objectives. Kotter's change framework provided eight purposeful steps to introduce the alternative drilling system. A non-linear, multi-layered methodology is proposed, in which each step hosts an array of strategies methodically crafted to be practical, actionable, and useful. To verify the urgency of the change, the method initiates the change process by providing means to distinguish between correlation and causation. Once verified, a simple change vision is crafted to highlight the benefits to all stakeholders. The vision aims to establish trust in the change idea while aligning interests, ultimately promoting stakeholder buy-in. Responsibility structures ensure that every actionable task has an accountable person assigned. Critical upgrades to the water and electrical networks may be required to support the alternative drilling system. However, methodologies for assessing the mine's standard network support capability were not found in the literature. To fill this gap, this study developed a novel infrastructure evaluation methodology to identify the network's limitations and required upgrades. To implement the change, this study proposes a non-linear experimental approach that does not rely on a finite start and end state. In fact, the change idea is first tested on a small scale to validate its change benefits before committing to large-scale roll-outs. This allows for real-world feedback and prevents impulsive decision-making, which can lead to costly mistakes. By balancing ambition with caution, the method provides a strategy to prioritise crews during the roll-out phase based on their actual drilling performance. A continuous improvement strategy was integrated into the method to enable stakeholders to analyse the change results and formulate and implement improvement opportunities. The improvement strategy is based on the 80/20 principle and prioritises actionablem items by recognising that 20% of effort can yield 80% of the improvement. A mature gold mine was used as a case study to validate the proposed methodology. Hydropower was selected as a feasible alternative drilling technology, and the method was iteratively applied to convert all the stoping crews from pneumatic to hydro drilling. The continuous improvement loop enabled the project team to implement low-risk, viable adjustments to the change process, resulting in a projected 17% improvement in production. This improvement translates into an additional revenue stream generated of R760 million per annum. Ultimately, all the compressed air stoping crews were converted to localised and micro hydropower, making it the first mature South African gold mine originally designed to operate with compressed air stopes to achieve this outcome. This result validates the method's effectiveness in addressing the study's need for an implementation and change management methodology to introduce alternative drilling technology in narrow reef gold mines. The study concludes with an overview of the key lessons learned to achieve this outcome. The novel method proposed by this study is not simply based on theory; rather, it is supported by a firm foundation of real-world lessons learned and validated using a real-world case study to confirm its effectiveness.
Integrating industrial engineering and environmental sustainability for a sustainable competitive advantage in South Africa
(North-West University, 2026) Roopa, Meelan; Siriram, R
Environmental sustainability (ES) remains increasingly relevant to our world and more challenging for developing countries to achieve. At the same time, companies try to remain competitive and often turn to sustainable solutions for a competitive advantage. Concurrently, the field of Industrial Engineering (IE) has received growing interest in all parts of the world, in various sectors, since its inception during the first industrial revolution. The specialised discipline of IE has knowledge that yields productivity gains;yet no taxonomy model gives clear recognition or associations with environmental sustainability. The knowledge poolsof IE and ES currently lack a formalised, visible classification. This disparate leaves developing countries unable to successfully adopt environmental sustainability in order to ensure a sustainable competitive advantage. South Africa is no exception to this.This study strives to investigate IE knowledge to identify ways in which to enhance environmental sustainability in South Africa, using a sustainable competitive advantage. The core focus identifies various strategies, theories, and methods and practices (knowledge components) that are later linked with the strategic, tactical and operational business execution levels. It also investigates transdisciplinary knowledge creation, arguing that IE is capable of producing such knowledge. A staged Design Science Research (DSR) paradigm is followed and contextualised by the research onion using four distinct phases. The research design begins with a Systematic Literature Review and thematic analysis to explore IE knowledge and environmental sustainability as part of the rigour cycle of DSR. In the second phase, the relevance cycle involves interviewing South African industrial engineers and environmental sustainability managers to identify knowledge components for a sustainable competitive advantage, which are applied in industry and academia. The last two phases entail the design and validation of a Pyramid Water Fountain model that ensures a sustainable competitive advantage. The Abstract, Contextualise and Design (ACD) methodology is coined as a transdisciplinary design methodology used to create the artefact. The validation entailed a confirmatory focus group. These findings can thus be generalised to other developing countries by drawing on knowledge from the IE and environmental sustainability domains within transdisciplinary knowledge contexts. This research demonstrates transdisciplinarity and systemic environmental problem-solving, as well as sustainable competitive advantages that are inspired by the notions of integrating knowledge from IE and ES.
Supervised and transfer learning for industrial equipment remaining useful life prediction under limited data
(North-West University, 2026) Maré, T; Bührmann, JH
Remaining useful life (RUL) prediction is a key component of predictive maintenance (PdM) systems, where data-driven models are used to identify degradation patterns and predict impending equipment failure. Despite the advances of Industry 4.0 and the increased availability of sensor data, limited labelled degradation data remains a challenge in PdM. However, limited research has systematically assessed how different machine learning models perform as labelled target data become increasingly scarce. Moreover, when practitioners have access to only a limited amount of labelled target data, related source-domain datasets can be used. However, the domain shift between source and target datasets can affect model performance. This study therefore evaluates classical regression, tree based, and neural-network-based models under varying data-availability constraints. Feature selection and hybrid feature extraction architectures are also investigated to determine their effect on model performance (across the varying data availability constraints). In addition, three supervised fine-tuning strategies, namely full fine-tuning, layer freezing, and progressive unfreezing, are evaluated for scenarios where source-domain data are available. For the case where no labelled target data are available, adversarial domain adaptation is implemented using a domain adversarial neural network (DANN). The experiments are conducted using the Commercial Modular Aero-Propulsion System Simulation (C-MAPSS) datasets, with FD001 used as the target dataset and FD002 and FD003 used as source-domain datasets. The results show that, within the investigated C-MAPSS datasets and experimental design, no single modelling strategy performed best across all data-availability scenarios. Neural-network-based models generally performed best when sufficient labelled target data were available. Among the evaluated neural-network-based models, the Transformer showed the greatest robustness as target training data became scarce. Under extreme training-data scarcity, the evaluated linear and tree-based models became increasingly competitive and outperformed the neural-network-based models. Furthermore, feature selection was found to mainly improve computational efficiency, particularly reducing the recurrent models' training time by approximately 87% to 97%, although its effect on predictive accuracy varied across the evaluated models. The proposed AUC-RMSE metric further showed that conclusions based solely on aggregate RMSE can differ from those obtained when prediction performance is evaluated across different stages of the equipment lifecycle. For transfer learning, the supervised fine-tuning techniques were most advantageous in the lower-data scenarios, while negative transfer was observed under some higher-data conditions. The greatest benefits were observed for the more similar of the investigated source-target domains, where all three fine-tuning strategies achieved RMSE improvements of more than 50% over the supervised target-only baseline in the data-scarce scenarios. When labelled target data were unavailable, source-only transfer remained competitive in the smaller domain-shift setting, whereas DANN provided greater benefit in the larger of the investigated domain-shift settings. In this setting, DANN improved RMSE over the source-only baseline by more than 27% across all evaluated data ranges, with the highest improvement of 38% observed under extreme scarcity. Under very low and extreme labelled target-data settings, source-only and DANN-based transfer models also became competitive with, and in some cases outperformed, the supervised GRU baseline. These findings demonstrate predictive improvements within the investigated C-MAPSS benchmark scenarios. Future work should evaluate the investigated models on additional datasets to assess the generalisability of the findings. Moreover, the evaluation on real world industrial degradation data could further assess their practical applicability.
Designing a Lean and Green organisational sustainability model: A South African Ecotourism case study
(North-West University, 2026) Küsel, Mia; Coetzee, R; van der Merwe, P
It is widely recognised that the Covid-19 pandemic greatly affected the ecotourism industry, highlighting the need for improved or revised management strategies to address the changing circumstances post-pandemic. Additionally, the increased focus on achieving true sustainability in terms of the triple bottom line of organisational sustainability, social, environmental, and economic sustainability. This research examines the applicability of Lean-Green management to organisational sustainability. Thus, the problem identified focuses on organisational sustainability in nature-based ecotourism organisations in the post-pandemic climate. A case study method is identified as the basis for the research, with data collection through focus groups and a systematic literature review. The focus groups are conducted to record the different organisational elements of a specific nature-based ecotourism organisation in South Africa and to provide industry insight. Additionally, the systematic literature review examines the use of the Lean-Green framework in the context of tourism, specifically the ecotourism industry. This research presents a threedimensional matrix, developed using the Zwicky Box morphological analysis, that shows the balance between Lean and Green for organisational sustainability in the intricate ecotourism industry. This will not only reveal the specific use of Lean and Green within ecotourism but also highlight the inherent relationship between Lean and Green and long-term success through organisational sustainability. This research contributes to the UN Sustainable Development Goals and addresses organisational sustainability in the complex environment of ecotourism. This study can be used to achieve organisational sustainability in a personalised experience format for tourism organisations, as well as to inform the expansion of Lean-Green as a research field. Future work stemming from this research may include Lean-Green as a management approach for organisational sustainability in other sectors, as well as industrial engineering in the field of ecotourism.
Co-digestion of kitchen waste and pig manure for enhanced biogas production
(North-West University, 2026) Kanu-Uchenna, Ogochukwu Ruth; Waanders, FB; Olatunji, KO
Anaerobic co-digestion (ACoD) of kitchen waste (KW) and pig manure (PM) provides an effective means of treating organic waste and recovering biogas-based renewable energy. This study investigated the ACoD of KW and PM to enhance biogas production while recovering nutrients in a form suitable for agricultural reuse. Batch biochemical methane potential (BMP) tests were conducted at laboratory scale under mesophilic conditions (37 ± 2 °C) using six digesters configured with different KW:PM mixing ratios on a volatile solids (VS) basis: 100:0, 80:20, 60:40, 40:60, 20:80, and 0:100. All substrates were subjected to a combined mechanical (4-5 mm size reduction) and enzymatic pre-treatment to improve hydrolysis and substrate accessibility, while a well-adapted inoculum was employed to minimize lag phases and ensure process stability. Key process indicators, including daily and cumulative biomethane yields, pH, and ammonia levels, were monitored throughout a 28-day digestion period, and the final digestates were characterized for proximate composition, thermogravimetric behaviour, elemental profiles (ICPMS), and agronomic quality. The findings indicated that co-digestion improved methane production relative to mono-digestion of either substrate. Digesters with higher KW proportions (100:0, 80:20, and 60:40) exhibited short lag phases, pronounced early peaks in daily biomethane yield, and sustained methane generation during the exponential phase, leading to the highest cumulative biomethane yields, with the 100:0 and 80:20 reactors achieving final values of approximately 767 and 719 mL CH₄ g⁻¹ VS added, respectively. In contrast, mixtures dominated by PM (20:80 and 0:100) produced lower cumulative yields (around 459 and 299 mL CH₄ g⁻¹ VS), confirming that excessive manure content reduced substrate biodegradability and conversion efficiency. Nevertheless, all treatments maintained near neutral pH, high biomethane fractions, and no inhibitory symptoms, indicating that the KW-PM combinations, supported by the buffering capacity of manure and the applied pre-treatment, provided stable digestion conditions across the tested ratios. Digestate analyses revealed significant stabilization of organic matter, with thermogravimetric profiles indicating reduced volatile fractions relative to the feedstocks, and CHN data showing significant carbon depletion associated with methane formation. At the same time, total nitrogen in the digestate was conserved on a mass-percentage basis, with a high proportion present as ammonium-N, thereby enhancing the immediate plant-available nitrogen. Major plant nutrients (N, P, K) were present at agronomically relevant levels, while potentially toxic elements such as Pb, Cd, Cr, Ni, As, and Hg occurred at very low concentrations, below analytical detection limits, and well within international guideline values for materials intended for land application. These findings demonstrate that the co-digestion of KW and PM, particularly at KW-rich mixing ratios of 80:20 and 60:40, results in high methane recovery and the production of a nutrient-rich, lowcontaminant digestate suitable for use asan organic fertilizer. Although the 100:0 reactor achieved the highest cumulative methane yield, the 80:20 and 60:40 KW:PM ratios offered superior performance by combining high methane recovery with improved process stability, nutrient balance, buffering capacity, and potential relevance for small-scale systems. The study, therefore, informs the design of of small-scale KW-PM co-digestion system as a decentralized waste-toenergy and nutrient-recycling option for rural and peri urban communities in South Africa and similar contexts.