Faculty of Engineering and the Built Environment (ETDs)

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Back analysis of previously stooped Panels to improve the safety and productivity of future stooping operations at new Denmark colliery
(University of the Witwatersrand, Johannesburg, 2024) Gonsalves, Ricardo
New Denmark Colliery (NDC) is a Seriti-owned underground coal mine in the Mpumalanga Province. It started stooping operations towards the end of 2018 and has since stooped 50 panels safely across all three of its shafts. NDC selected the NEVID method, which is known for its safety and success in neighbouring mines. Initially stooping panels in the 1100 block, NDC encountered challenges due to narrow panel spans, leading to limited goafing and heightened abutment stresses on surrounding pillars and infrastructure. This necessitated additional support for strategic pillars to ensure long-term stability. To address these challenges, comprehensive research was conducted, which included back-analysis of stooped panels and numerical modelling. Findings revealed that goafing was influenced more by horizontal stress concentrators, such as geological structures than panel spans. Goafing at NDC has primarily been defined by low-angle shear failures, which only extend a couple of metres into the immediate sandstone roof. This is known as partial goafing, which typically results in high abutment stresses. Since complete goafing is unlikely due to the depth below surface and the competent roof material, the high abutment stresses needed to be managed by increasing the width of the barrier pillars between panels and leaving a sufficient number of stopper pillars at the end of a stooped panel. Numerical modelling was used to validate NDC's current design strategy of stooping panels and to determine the width of new barrier pillars. The derived strategy includes an increase in barrier pillar width and stand-off distances, to ensure the long-term stability of main developments. iv The current stooping strategy which was informed by comprehensive research and modelling, has proven effective in both safety and stability.
Improving grade estimation using machine learning: a comparative study of ordinary kriging against machine learning algorithms
(University of the Witwatersrand, Johannesburg, 2024) Akpabio, Aniekan
This study investigated the efficiency of machine learning (ML) methods in the accurate prediction of ore grades, placing them in direct comparison with the established Ordinary Kriging (OK) methodology, a mainstay in geostatistical analysis. Utilising a dataset from a complex platinum group elements (PGE) deposit, the research assessed a suite of ML algorithms—namely, Random Forest (RF), Decision Trees (DT), Support Vector Regression (SVR), and particularly 𝑘- Nearest Neighbours (𝑘NN). The latter is highlighted for its adeptness in assimilating spatial data correlations intrinsically, echoing the insights from Nwalia's analytical explorations. The research engages with detailed swath plot analyses, comparative metric evaluations, and a nuanced understanding of spatial continuity, to illustrate the distinct advantages and operational competencies of the models. 𝑘NN, with its reliance on local data proximities and non-parametric nature, alongside RF, with its ensemble-based approach, emerged as capable in point estimate predictions. These models adeptly delineated local grade variations, demonstrating a high degree of reliability to the observed data and outperforming the OK model in both precision and accuracy. Further, the study examined block estimate predictions, a cornerstone in practical mining and resource estimation, where both 𝑘NN and RF demonstrated a commendable ability to generalise predictions over larger spatial extents. This translates into significant potential for enhancing mineral resource estimation processes, tailoring them to the granular specifics of a given ore body, and refining block model accuracy to inform more strategic mining operations. While the results endorse the ML methodologies as robust alternatives to traditional geostatistical techniques, the research also highlights the nuanced nature of these predictions. Factors such as the ore body's heterogeneity, the appropriateness of the variogram model, and the interplay between prediction scale and algorithmic performance are examined, offering a critical lens through which the suitability of each method is assessed. iv The research suggests that while some models like LR and SVR are bounded by linear assumptions and hyperparameter sensitivities, non-linear models such as DT and RF can innately navigate the complex, multifaceted layers of geological data. The comprehensive evaluation extends to propose a novel set of performance metrics designed to capture the intricacies of grade prediction, thereby aligning closely with the operational demands and decision-making processes in the mining industry.
Supply Chain Risk Management in Manufacturing Small and Medium Enterprises: A Systematic Literature Review
(University of the Witwatersrand, Johannesburg, 2024) Pungula, Vusumuzi; Sunjka, B.
Background: Small and Medium Enterprises (SMEs) are becoming major actors in the manufacturing sector due to the rising complexity of global supply chains. However, they still face enormous risks from supply chain disruptions and market dynamics, which can have costly effects. SMEs sometimes lack the means and expertise to execute comprehensive risk management plans intended for larger businesses, despite their significance. Research on Supply Chain Risk Management (SCRM) specifically for small and medium-sized enterprises (SMEs) is noticeably lacking, especially in the manufacturing sector. Purpose: The aim of the study was to systematically review how SCRM has been developing in manufacturing SMEs globally over the past two decades, and provide insights for policymakers, industry associations, and SMEs themselves. Method: A Systematic Literature Review (SLR) was conducted by utilizing a qualitative research approach. Seven key phrases were formulated to guide the search for relevant articles published between 2000 and 2023. A thorough screening process was employed to select 38 articles that met inclusion criteria, and data analysis was performed using NVivo software on these articles. Following this, thematic analysis and textual narrative synthesis methods were employed for data analysis and synthesis. The discussion of the identified themes provides comprehensive insights to policymakers, industry associations, and SMEs into the current status of SCRM research in manufacturing SMEs globally. It highlights the importance of effectively addressing risk variables, developing tailored SCRM approaches, and striking a balance between risk reduction efforts and strategic opportunities within supply chains to enhance resilience and ensure operational continuity. Results: The review revealed a significant increase in SCRM research pertaining to manufacturing SMEs over the past decade. Trends analysis indicated a growing emphasis on SCRM in various disciplines, highlighting its increasing significance. Thematic analysis identified eight key themes, including the current status of SCRM research and factors influencing SCRM strategies in manufacturing SMEs. Conclusion: Based on the comprehensive review of literature, several key conclusions can be drawn. There is prevalent recognition of the importance of SCRM within SMEs, emphasizing the need for proactive risk mitigation strategies tailored to the SME context. While formal risk management approaches are increasingly adopted, the context-specific nature of risk management practices highlights the importance of tailored approaches. Technological advancements play a significant role in enhancing SCRM strategies, alongside the integration of green supply chain management practices.
The improvement of the on-time delivery for “company x” e-commerce orders during the golden quarter
(University of the Witwatersrand, Johannesburg, 2024) Sukazi, Thobile Nomalungelo; Sunjka, Bernadette
E-commerce has revolutionized global business and consumer interactions, offering convenience and accessibility across various domains like Business-to-Business (B2B), Business-to-Consumer (B2C), and Consumer-to-Consumer (C2C). The COVID-19 pandemic has accelerated digital transformation, with South Africa's e-commerce market showing robust growth projections, fuelled by factors such as improved internet penetration and shifting consumer behaviours. The Omni-channel strategy has become standard, with leading players leveraging digital capabilities to maintain market share. Notably, the "Golden Quarter" of retail, encompassing events like Black Friday and Singles Day, presents a pivotal opportunity for retailers to boost profits through strategic promotional efforts. As the market matures, focus shifts to optimizing the final mile of delivery, aiming to improve efficiency and reduce costs. This project seeks to explore tailored strategies for final mile optimization in Company X, aligning with the broader goal of enhancing efficiency and customer experiences in South Africa's growing e-commerce sector. Despite being the second-largest wholesale food distributor in South Africa, Company X experienced significant on-time delivery performance declines, particularly in its discount retailer brand, Banner 3. The analysis identified logistical bottlenecks in the final mile as the primary contributor to these challenges, resulting in an average delay of 4.3 days in the order fulfilment process. Additionally, the study highlighted the importance of addressing these challenges to maintain customer satisfaction, loyalty, and competitiveness in the rapidly evolving South African e-commerce landscape. This study employs a comprehensive framework and systematic approach to investigate the research questions and objectives. A qualitative research design involves one-on-one interviews conducted digitally via Microsoft Teams. Ethics clearance (MIAEC 099/23) was obtained, ensuring transparency and participant understanding. The sampling strategy prioritizes quality over quantity, with six diverse participants selected to provide rich qualitative data. Data analysis follows Braun and Clarke's thematic analysis approach, incorporating triangulation methods and emphasizing thorough documentation to ensure validity and reliability. This research has thoroughly investigated Company X's final mile delivery challenges during the Golden Quarter, providing comprehensive insights and recommendations for enhancement. Key findings underscore the significance of accurate forecasts, planning collaboration, proximity to customers, fleet and technology utilization, customer service levels, and delivery types in optimizing delivery performance. Recommendations encompass advanced forecasting models, collaborative planning efforts, tailored customer promises, technological enhancements, and automation to address identified challenges and capitalize on opportunities for improvement. The proposed strategies offer a strategic roadmap for Company X to enhance efficiency, customer satisfaction, and competitiveness in the e-commerce landscape, aligning with the study's objectives and concluding the project successfully. The tailored recommendations contribute valuable strategies for improving efficiency, customer satisfaction, and competitiveness. Future research could focus on evaluating the implementation of these strategies and exploring emerging technologies to further optimize the delivery process and adapt to evolving market dynamics.
Development of an enterprise engineering strategy execution framework
(University of the Witwatersrand, Johannesburg, 2024) Mudavanhu, Thabani B.; Emwanu, Bruno
Even with a myriad of implementation models from consulting firms and academia – the success rate of Strategy Execution (SE) remains low. Extant literature in strategy execution exposes inadequacies of theoretical foundations for the assertions outlined in current SE models. In addition to this, where there is some explanation, the theory is inconsistent, and discipline biased which limits development of general application theory. Further to this ‘enterprises’ as the housing (the system of interest) from which a strategy is launched rarely receive the level of attention and rigor that technical systems do. Against this background, this study sought to understand how the success rate of SE can be improved through the application of Enterprise Engineering (EE) principles and practices. The premise being that the challenges in implementing strategies in any organisation are too an extent related to the design of the enterprise. Consequently, the common challenges attributed to the failure in SE can be linked to the enterprise design and as such organisations can, to an extent be designed to influence SE. Considering the complexity / greyness of the study area and limited literature in the relatively new discipline of EE, specifically enterprise ontology theory (the theoretical lens of this study), a structured literature review was used as the basis for a Delphi study. A two (2) round Delphi study was conducted with experts in the field to determine and validate the critical dimensions in Strategy Execution. Thirty-one (31) and twenty (25) experts participated in Delphi Round 1 and 2 respectively. The experts came from four regions of the world and were largely academics, board members and executive leaders and practitioners many of them tasked with either overseeing or leading strategy execution. The study revealed that there is a significant relationship between the design of an enterprise at the deepest level (the ontological layer) and the seven (7) aggregated themes that were synthesised in this study and are linked to constraining successful SE – (a) the strategy itself, (b) leadership, (c) people (the team); (d) effective communication; (e) organisational capabilities (f) organisational enablers and (g) organisational culture. The study proposed a generic enterprise engineering-based strategy execution (EEbSE) framework anchored in the deepest layer of an organisation, the ontological layer - the level where companies transact (cooperate and enter into agreements). Consequently, the study confirmed the proposition that ‘organisations can, to some degree, be designed or re-engineered for strategy execution’. This study demonstrates how EE can be useful in aiding Successful SE. An example of a key take-away include the need to check for execution readiness at the ontological layer and v eliminating any construction flaws (errors) that will later reflect as ‘common’ challenges. For example, lack of commitment [people issues] and lack of an implementation [culture issues] are flaws associated with SE that can be traced and re-engineered at the ontological level. This study adds to on-going work to confront the SE challenge and demonstrates the relevancy and pervasiveness of the application of EE.
Bodies of cunicularity in supersonic flow
(University of the Witwatersrand, Johannesburg, 2024) Myburgh, Sabrina Gabrielle; Law , Craig
Prior studies outlined the success of using randomised High Porosity Cellular Material cyl- inders both numerically and experimentally, however showed limited applicability to real-life aerodynamics applications. The primary effect of supersonic flow over porous media is to attenuate the bow wave by reducing the angle of incidence and redistributing the flow field, significantly reducing wave drag. The aim of this work was to investigate the drag-reduction effect of organised porosity within conic bodies of revolution on the supersonic flow field. Various organised porous cone-cylinders were developed to investigate the effect of the porous structure on the flow field, including shock waves, momentum changes and flow structures in and around the por- ous body. Several conic profiles were investigated. A numerical and experimental investigation was carried out in steady, supersonic flow at Mach 3.5 (Re = 3.9 × 10−5). The conic models had a porosity of ≈ 60%. The blow down supersonic wind tunnel facility at the University of the Witwatersrand was used for the exper- imentation, where schlieren photographs were captured along with drag force measurements of the solid and porous baseline cones. Numerical CFD simulations were carried out for a wider range of porous configurations using ANSYS Fluent R22.2. The numerical, experi- mental and literature Cd and flow visualisation were used to validate the numerical method, showing good agreement across data sets. Certain cunicular arrangements effectively reduced the drag in some shapes, while others worsened the drag. The greatest drag reduction of 40% was achieved in the cunicular BS4 Ellipsoid. The change in drag was associated with three sources, namely wave drag, jet v interaction, and momentum addition by the jet. These changes resulted from the flow inter- actions occurring within the inlet, internal and venting structures. Changes in drag depended on several factors, including vent geometry, expansion ratio, exit angle, inlet geometry and the crossflow condition, to name a few. Wave drag reduction was dependent on shock at- tenuation and reducing the wave angle, which was generally ensured by the conic surface pores absorbing energy from the bow wave. The jet interaction and momentum recovery were dependent on vent expansion ratio, exit angle and crossflow condition. The jet interaction had the greatest increase on the drag of the system, however, the effects of this were mitigated by using low vent angles with correct expansion ratios to maximise momentum recovery from the jet. The effect of the combined system was specific to the particular case, where the solid cone shape greatly influenced the overall performance. The effect on drag reduction was cumulative, sensitive and highly dependent on the individual case. The cunicular system is a viable drag reduction mechanism in conic bodies, however careful balancing of the porous inflow, outflow, bow wave and venting conditions is required in order to achieve significant drag reduction.
Characterisation, Modelling, Finite element analysis, and optimisation of hyperelastic materials for Non-Pneumatic Wheels
(University of the Witwatersrand, Johannesburg, 2024) Bhartu, Saahil; Pietra, Francesco
This abstract concludes the exploration of hyperelasticity within the context of mechanical engineering. Through this section, we have delved into the substantial elastic deformations characteristic of hyperelastic materials, their capacity for energy conservation during deformation, and their inherently non-linear behaviour. The calibration of non-linear material models has been informed by a rigorously designed experimental regimen, where preferred methodologies and necessary precautions were identified to ensure the integrity of the data obtained. Theoretical foundations for the development of constitutive models have been established, with a discussion of prevalent models frequently employed in engineering applications. Practical modelling applications introduced have provided a tangible context for the utilization of hyperelastic material models. While our focus was predominantly on nearly or fully incompressible materials, foundational concepts for compressible behaviour were also addressed, setting the stage for further investigative pursuits. Polyurethane (PU) materials exemplify hyperelastic behaviour. Through computational simulation, we assessed the deformation in a structured wheel to be 4.6mm, utilizing a 9;5 and 2 parameter Mooney-Rivlin model for the PU material. Experimental testing was conducted measuring deformation to be 4.1mm From the results, the deformation patterns, stress distributions, and contact pressures were analysed, indicating the wheel’s ability to endure a contact pressure of 7.36MPa, deformation of 4.6mm, Von-Mises stress of 3.9MPa. This investigation not only corroborates the distinctive properties of hyperelastic materials but also illustrates how analysis results can inform and optimize design iterations. It demonstrates the practical applications of hyperelastic material models in design engineering, providing a comprehensive understanding that is indispensable for the modelling and analysis of hyperelastic components.
The assessment of exploration processes in the Upstream Industry to increase exploration efficiency and promote accelerated drilling decisions.
(University of the Witwatersrand, Johannesburg, 2024) Tshikovhi, Rilwele Mikovhe Muditambi; Botha, A.
During petroleum exploration, petroleum companies (operators) require efficient hydrocarbon detection and delineation methods to locate petroleum prospects and promote drilling (Selley, 1998). The two pre-drill surveys under investigation in this study are seismic surveys and controlled source electro-magnetic (CSEM) surveys which are used to study the subsurface during offshore petroleum exploration. Drilling dry holes is inevitable, however, a proper and thorough prospect evaluation can significantly increase the chance of success of a prospect (Milkov & Samis, 2020). The purpose of the research is to evaluate seismic and CSEM surveys as secondary hydrocarbon detection tools used to recommend drilling, and to also determine if any of these methods can encourage accelerated drilling decisions and significantly reduce exploration risk. A total of 49 seismic-based samples and 41 CSEM-based samples were used in the study. Survey anomalies were assessed against drilling results to determine the predictive strength of each survey. The Chi-test confirmed that there is a significant association between survey anomalies and attributes such as well results, predictive strength, fluid type and trap style. The researcher analysed the two datasets to determine the probability of an anomaly in each survey and the chance of success if each well is drill based on these surveys. The presence of an anomaly was defined as a positive anomaly (PA) and the absence of an anomaly was defined as a negative anomaly (NA). Fluid type and trap style were used to analyse the predictive ability of the survey anomalies. Seismic and CSEM surveys have indicated a high probability of discovering charged reservoirs in a structural trap as compared to stratigraphic traps, however, CSEM is slightly better than seismic surveys in defining these reservoirs. Both surveys have a low probability of predicting a charged stratigraphic reservoir, although seismic surveys have indicated higher chance of success as compared to CSEM. Positive anomalies observed in both surveys proved to be good indicators of gas-bearing reservoirs as compared to other hydrocarbon fluid. CSEM has a slightly higher chance of predicting oil than seismic surveys. A simplified process mapping for the current offshore exploration processes was conducted. A decision tree was used to analyse seismic and CSEM surveys as secondary tools with emphasis given to their hydrocarbon detection capabilities. Bayesian Theorem was used to calculate the posterior probabilities given that a well is drilled on a positive iii anomaly. The same was applied for wells drilled on negative anomalies. The results have indicated that CSEM has a higher probability of detecting hydrocarbon accumulations as compared to seismic surveys.
Investigating the impact of Railway Signalling Performance on Railway Operations & Performance in South Africa
(University of the Witwatersrand, Johannesburg, 2024) Naidoo, Pranell; Sunjka, Bernadette
The South African railway was once an attractive and thriving industry, serving as a catalyst for socio-economic growth and opportunities (George, Mokoena and Rust, 2018). However, in the past decade, the South African freight rail service has become uncompetitive, unreliable, and ineffectively integrated to other modes of freight transportation (The World Bank, 2023). Railway signalling systems are a vital component of the rail network as it ensures that trains travel safely and the rail network is operating at optimal capacity (Zhang et al., 2021). This research focuses on investigating the critical factors contributing to poor railway signalling performance in South Africa, and the impact that these risk factors have on the performance of railway operations, safety and the organization. A critical literature review revealed a gap in the knowledge and understanding of the systemic factors contributing to poor signalling performance. In the effort to close this literature gap, a holistic approach was adopted to develop a conceptual framework which presented factors identified from literature which affects the performance of railway signalling systems. This research adopted a qualitative research approach to achieve the objectives of this research. Semi-structured interviews were conducted with railway signalling and operations professionals. Thematic analysis was used to identify emergent themes from the collected data. The findings identified several factors contributing to poor signalling performance, some of the major identified factors were theft and vandalism, loss of critical skills, lack of investment and budget, managerial issues, ageing infrastructure, inadequate maintenance, human factors, etc. The research findings concluded by outlining the recommendations for future research to address theft and vandalism through collaborative strategies and initiatives, obtaining investments through public-private partnerships, addressing the skills shortage through effective skills retention programs, upgrading the freight rail signalling systems, optimizing the maintenance philosophy, and expanding the research into the passenger rail network to improve railway signalling systems in South Africa.
An analysis of factors leading to the production of defective wagons in Transnet Engineering
(University of the Witwatersrand, Johannesburg, 2024) Nemakhavhani, Pfananani Thelma; Dewa, Mncedisi Trinity
Rail manufacturing industries play a crucial role in many countries by developing cost-effective transportation solutions to move freight more efficiently. To date, the industry has seen the implementation of traditional quality management practices that are critical in driving efficiencies and better-managed operations to improve the quality of their freight wagons. Despite the conventional quality management techniques, the rail industry continues to manufacture defective rolling stock due to design changes, errors and omissions, and inadequate skills. Over the past few decades, industry and academia have identified various factors contributing to rolling stock manufacturing defects. Nevertheless, which factors were predominantly responsible for the defective wagon production at the Transnet Engineering (TE) Bloemfontein factory remained unclear. Identifying the most prevalent causes of defects is essential in addressing the organisation's quality issues. The primary purpose of this study was to gain insights into the root causes of the defects and recommend strategies to minimise them. The study used an interpretive methodology to identify the root cause of defective wagons produced at TE. Data was collected using purposive sampling. Ten experienced TE employees actively engaged in freight wagon manufacturing were selected for face-to-face interviews. During the research study, the interviews were conducted with the employees using a semi-structured format that allowed for open-ended questions. Investigative techniques, such as cause-and-effect diagrams and the Five "Whys" root cause analysis tool, were used to investigate defects' root causes on the customer complaints register. Additionally, thematic analysis was applied to thoroughly analyse the interviews conducted with the employees, which allowed for a deeper understanding of the issues at hand. The findings showed that inadequate skills, human errors and omissions, a lack of quality culture, time constraints, management's failure to enforce accountability, and poor workshop maintenance/machinery all contribute to defective wagon production. The research provided recommendations, including adopting innovative technology and skills transfer programs to enhance the company's quality management practices.

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