Masters Degrees (Industrial Engineering)
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Browsing Masters Degrees (Industrial Engineering) by browse.metadata.type "Thesis"
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- ItemA data and modelling framework for strategic supply chain decision-making in the petro-chemical industry.(Stellenbosch : Stellenbosch University, 2006-12) Van Schalkwyk, Willem Tobias; Bekker, James; Stellenbosch University. Faculty of Engineering. Dept. of Industrial Engineering.ENGLISH ABSTRACT: The research was initiated by an opportunity within the petro-chemical company Sasol to explore, improve and integrate various analytical techniques used in the modelling, design and optimisation of supply chains. Although there is already a strong focus on the use of analytical applications in this environment, the lack of both modelling integration and analytical data availability has led to less than optimal results. This document presents an exploration into the supply chain planning landscape, and in particular strategic planning in the petro-chemical environment. Various modelling methodologies and techniques that support strategic supply chain decision-making are identified, followed by an in-depth analysis of the data requirements for effectively constructing each of these models. Perhaps the biggest hurdle in the continual use of modelling techniques that support strategic supply chain decision-making, remains the extent of the data gathering phase in any such project. Supply chain models are usually developed on an ad hoc project basis, each time requiring extensive data gathering and analysis from transactional data systems. The reason for this is twofold: 1) transactional data are not configured to meet the analytical data requirements of supply chain models, and 2) projects are often done in isolation, resulting in supply chain data that end up in spreadsheets and point solutions. This research proposes an integrated data and modelling framework, that aspires to the sustainable use of supply chain data, and continual use of modelling techniques to support strategic supply chain decision-making. The intent of the framework is twofold: 1) to enable the design of new supply chains, and 2) to ensure a structured approach for capturing historical supply chain activities for continued review and optimisation. At the heart of the framework is the supply chain analytical data repository (SCADR), a database that maintains supply chain structural and managerial information in a controlled data model. The motivation behind developing a database structure for storing supply chain data is that a standard encoding method encourages data sharing among different modelling applications and analysts. In the globalised environment of the 21•t century, companies can no longer ensure its market position solely by its own functional excellence ... in the new economy, whole business ecosystems compete against each other for global survival (Moore, 1996). This motivates the ever-increasing importance of supply chain management, which necessitates the use of advanced analytical tools to assist business leaders in making ever more complex supply chain decisions. It is believed that the integration of information requirements for multiple optimisation/ modelling initiatives in a structured framework (as presented in this research) will enable sustainability and improved strategic decision-making for the petro-chemical supply chain.
- ItemAn activity-based workload modelling approach for determining diagnostic radiographer staffing requirements within a diagnostic radiology practice.(Stellenbosch : Stellenbosch University, 2021-03) Cloete, Cosmo; Bam, Louzanne; De Kock, Imke; Stellenbosch University. Faculty of Engineering. Dept. of Industrial Engineering.ENGLISH ABSTRACT: Radiology is a medical speciality that uses imaging technologies to obtain and interpret medical images. Radiology forms a crucial part in the diagnosis and treatment of diseases, thus the quality of the reports and images, together with the quick turnaround time of the results, is paramount. The radiology team consists of radiologists, who are medical specialists that interpret images to appropriately advise on treatment, while radiographers operate the imaging equipment and ensure correct patient positioning The efficiency of a radiology department is influenced by effective integration of workflow and imaging technologies as well as by appropriately aligned staffing,amongst other factors. Furthermore, diagnostic radiographers are responsible for producing the medical images that form the basis for accurate diagnosis hence, ensuring that a diagnostic radiology practice is staffed by a sufficient number of diagnostic radiographers is a vital aspect in enabling effective service delivery. However, a review of existing radiology-specific staffing approaches reveals that radiology workload models focus mainly on diagnostic radiologists within tertiary hospital environments, while research into radiographers’ workload and staffing only considers the radiation therapy practice field. This research develops a framework that can be used to accurately determine diagnostic radiographer staffing requirements. The proposed framework is developed based on requirement specifications. These requirement specifications are formulated based on a body of literature that includes both general healthcare-and radiology-specific staffing approaches. A complete evaluation approach (verification and validation) is applied to the requirement specifications and the proposed framework. A self-verification of the requirement specifications to the proposed framework is done followed by a theoretical verification of both the underlying bodies of literature and the framework that involves subject matter experts. The validation process includes a case study application of the framework to a private diagnostic radiology practice. The results of the case study are validated with subject matter experts to confirm the framework’s applicability and practicability. Insights from the case application confirm that the diagnostic radiographer staffing framework can be applied to both public and private diagnostic radiology environments.
- ItemAdding multi-objective optimisation capability to an electricity utility energy flow simulator(Stellenbosch : Stellenbosch University, 2016-03) Brits, Ryno Ockert; Bekker, James; Stellenbosch University. Faculty of Engineering. Dept. of Industrial Engineering.ENGLISH ABSTRACT: The energy flow simulator (EFS) is a strategic decision support tool that was developed for the South African national electricity utility Eskom. The advanced set of algorithms incorporated into the EFS enables various departments within Eskom to simulate and analyse the Eskom value chain from primary energy to end-use over a certain study horizon. The research in this thesis is aimed at determining whether multi-objective optimisation (MOO) capability can be added to the EFS. The study forms part of a series of research projects. This project builds on the work of Hatton (2015) in which the focus was on single-objective optimisation capability for the EFS. Inventory management at Eskom's coal- red power stations was identified as the most suitable area for the formulation of an MOO model. It was also identified that certain modifications to the existing EFS architecture can possibly improve its potential as an optimisation tool. The architecture of the EFS is studied and modifications to it are proposed. A multi-objective inventory model is then formulated for Eskom's network of coal- red power stations using the simulation outputs of the EFS. The model is based on the movement of coal between the various power stations in an attempt to maintain an optimal inventory level at each station as far as possible. To solve the model, a suitable MOO algorithm is selected and integrated with the simulation component of the EFS. Several experiments are conducted to validate the MOO model and test the e effectiveness of the algorithm in solving the optimisation problem.
- ItemAdditive manufacturing costing parameter sensitivity(Stellenbosch : Stellenbosch University, 2019-12) Van der Merwe, Hendrik Lodewyk; De Beer, D. J.; Van der Merwe, A. F.; Stellenbosch University. Faculty of Engineering. Dept. of Industrial Engineering.ENGLISH ABSTRACT: Additive manufacturing (AM) offers a perfect solution for the development and manufacturing of many products, but the burning issue is to determine which products should be manufactured in such a way? Also, of extreme importance, is to understand the economy of scale for the use of AM competitively. The latter requires knowledge-based decision-making systems based on product geometry, complexity, size, tolerance, material requirements, and mechanical properties, parallel with AM machine or process capabilities. Although directly involved in the material research and platform development from the onset, the Massachusetts Institute of Technology (MIT) classified AM as only one of ten breakthrough technologies in 2013. Forbes depicts AM as the technology that will equip manufacturers with the ability to turn product development into their competitive advantage. With the advancement in computer and software capabilities, it will rapidly dominate 40% of the market share (Gartner 2015). Capability alone will not suffice, however. To increase market share, focus should be placed on the analysis of AM costing. The thesis aims to determine if a more simplistic but accurate cost determination method can be developed to augment online costing opportunities that are fully integrated with the Enterprise Resource Planning (ERP) system. Costing is one of the critical business functions of any advanced manufacturing operation. This critical business function is also known as enterprise resource planning application components. Examples of these are aspects that allow an AM unit to use a system of integrated applications to manage the business and automate various back-office functions related to technology. It also allows for services and human resources to develop the data capturing, manipulations, calculation, and validation for a unique enterprise resource-planning model that is founded in a fail-safe quality management system (QMS).
- ItemAdditive manufacturing enabled drug delivery features for titanium-based total hip replacement cementless femoral stems(Stellenbosch : Stellenbosch University, 2015-03) Bezuidenhout, Martin Botha; Dimitrov, D. M.; Dicks, Leon Milner Theodore; Van der Merwe, A. F.; Stellenbosch University. Faculty of Engineering. Dept. of Industrial Engineering.ENGLISH ABSTRACT: Bacterial colonisation and biofilm formation onto total hip replacement femoral stems remain a serious complication detrimental to the success of total hip arthroplasty. Current treatment procedures are accompanied by a heavy financial burden and morbidity for the patient while failing to guarantee a successful outcome with no reinfection. In fact, infection rates after revision surgeries are typically higher than those for primary hip arthroplasties. This study investigates conceptual drug delivery channels to be incorporated within cementless femoral stems by applying additive manufacturing as enabler technology. Drug delivery from these features is aimed at both prophylaxis and treatment of infection, with the latter emphasising the concept of creating a reinforceable antimicrobial depot inside the implant. The novelty lies in facilitating the administration of multiple drug dosages from within the implant instead of the once-off implant-based release strategies currently employed. Samples containing internal channels were designed based on analogies to drug delivery studies reporting on the commercial antibiotic loaded bone cement, Palacos R+G loaded with gentamicin. These samples were manufactured by LaserCUSING® from Ti-6Al-4V ELI powder. For prophylactic proof of concept, testing the channels were filled with Palacos R+G and challenged with two clinical isolates of Staphylococcus aureus in a bacterial growth inhibition study. Gentamicin-susceptible S.aureus Xen 36 was prevented from colonising for a minimum of 72 hours, whereas gentamicin resistant S.aureus Xen 31 reached the material within 24 h, signifying the importance of drug selection according to pathogen. Hence, a solution of vancomycin in phosphate buffered saline pH 7.4 was used during in vitro reservoir release testing. Three dosage injections were made into each of six samples during a cumulative incubation period of 100 h. A biocompatible 5,000 Da molecular weight cut off polyethersulfone nanoporous membrane was employed as release rate-controlling device. Released vancomycin was quantified with reversed phase high performance liquid chromatography. The resulting release profile was characterised by means of the Korsmeyer-and-Peppas model for diffusion based drug delivery. Constraint diffusion was identified as the mechanism controlling release, implying interplay between Fickian diffusion and polymer relaxation for effecting vancomycin release from within the reservoir. The concept created in this study provides a basis towards the development of full scale intelligent implants with multiple dose in situ drug delivery capabilities. Implants incorporating this concept could aid in the perpetual struggle against infection by providing a new strategy for delivery of high level antibiotics directly to the site of infection.
- ItemAdditive manufacturing for the spare part management of classic cars(Stellenbosch : Stellenbosch University, 2022-04) Paskert, Lukas; Sacks, Natasha; Stellenbosch University. Faculty of Engineering. Dept. of Industrial Engineering.ENGLISH ABSTRACT: The maintenance of older vehicles can be challenging since the supply of spare parts by the original equipment manufacturer is not guaranteed throughout the lifespan of a vehicle. Thus, there is a need to improve the current spare part supply chain for the automotive industry specifically for outdated products like classic cars. Within the automotive industry additive manufacturing (AM) technology is already being implemented in the production cycle of new cars. The need to improve the supply of spare parts for classic cars and the increased use of the AM technology raised the question whether additive manufacturing can have an impact on the spare part management of classic cars. In order to answer this question, this research study started with the review of literature. Three critical scoping literature reviews were undertaken to analyse the current performance of the spare part management of classic cars and to identify spare part attributes for the ranking of spare parts according to their potential for additive manufacturing. To fully understand the spare part management of classic cars, a first literature study on the classic car market was conducted. A second literature review on spare part management within the automotive industry utilized a performance measurement model to measure the impact of adopting additive manufacturing. Based on this, the applicability of additive manufacturing was the subject of the third literature review. Results show that a potential for additive manufacturing exists, and it can be measured with spare part attributes. Based on these results, it was decided to follow an exploratory research design approach. A survey was conducted with classic car owners to identify sourcing problems of spare parts and to assess their willingness to adopt additive manufacturing. The data from the survey was analysed using a ranking methodology from science which was modified toward the application of additive manufacturing on the spare part management of classic cars. The outcome of the ranking highlighted that small parts (e.g. switches) and batches are best suitable for additive manufacturing. A Delphi survey with subject-matter experts validated the ranking method. A case study was carried out in which a speedometer gear was reverse-engineered, additive manufactured and tested under realistic conditions. The case study highlighted that additive manufacturing is feasible to produce spare parts on demand and on a decentralized implementation strategy. Overall, this research has shown that additive manufacturing has a high potential to impact the spare part management of classic cars. The research result showed that unsatisfied customer demand is recognised. Additive manufacturing is a technologically feasible solution to produce many spare parts and has the high potential to increase the supply chain performance of classic car spare parts.
- ItemAgeing estimation models for lightly loaded distribution power transformers(Stellenbosch : Stellenbosch University, 2018-03) Mukuddem, Mohamed Ziyaad; Jooste, J. L.; Stellenbosch University. Faculty of Engineering. Dept. of Industrial Engineering.ENGLISH ABSTRACT: Power transformers form an integral part of present day electricity networks. They allow for power to efficiently be transported over vast distances. They are however one of the most expensive assets within the distribution network. In order to maximise return on investment for these assets, transformer owners need to ensure that they operate for as long as possible. The ageing of a transformer is based primarily on the condition of the solid insulation inside the transformer. There are various ageing models which attempt to predict the ageing of a transformer based on parameters such as hot-spot temperature, oxygen and moisture content. Typical distribution networks are designed with transformer redundancy. In these networks, the full load of a substation is typically shared across two or more transformers. This results in individual transformers being lightly loaded (<50%). This study investigates the accuracy of the ageing models presented on a fleet of twenty distribution power transformers. The study compiles an algorithm which carries out two main functions. The first is to determine the hot-spot temperature based on loading. The second is to predict the loss-of-life based on the various ageing models identified. This predicted loss-of-life value is compared to measured loss-of-life values in order to determine which model produces the most accurate results. Using these results, the study goes further to modify these ageing models in an attempt to improve the accuracy thereof. These modified model’s accuracy rates are compared to each other as well as the initial ageing models to identify if any improvement in accuracy is produced. A modified output model is produced which increases the accuracy of the loss-of-life prediction for lightly loaded transformers. The modified model utilises the historic average hot-spot operating temperature in order to determine the ageing rate. This can be utilised by asset managers of power transformers in distribution networks.
- ItemAn agent-based approach to customer crowd-shipping(Stellenbosch : Stellenbosch University, 2022-04) Malan, Phillip Christian; Searle, Christa; Jan H, Van Vuuren; Stellenbosch University. Faculty of Engineering. Dept. of Industrial Engineering.ENGLISH SUMMARY: The challenge of effective last-mile deliveries is progressively becoming more important with the acceleration in the e-commerce industry that is accompanied by a growing number of doorstep deliveries. Crowd logistics provides innovative solutions whereby ordinary people become in- volved in the execution of logistics operations. A particular crowd logistics initiative, referred to as customer crowd-shipping, recently gained interest from researchers after initial implemen- tations thereof had been performed by companies such as Walmart and Amazon. The approach involves the use of a retailer’s in-store customers, in addition to regular delivery vehicles, for delivering orders to online customers. Such in-store customers, referred to as occasional drivers, are offered incentives to deliver orders on their way home after visiting the retailer. In this thesis, an agent-based simulation model is proposed for studying the highly dynamic working of the customer crowd-shipping initiative. The model encompasses a traditional last- mile delivery system, complemented by the ability to utilise autonomous occasional drivers. The modelled traditional last-mile delivery system consists of a dedicated fleet of delivery vehicles serving online customers from a single depot. The execution of deliveries is formulated as a vehicle routing problem and subsequently solved by means of well-known vehicle routing heuristics. In addition, the occasional drivers are modelled as autonomous agents who have the ability to act outside of the control of the retailer. Rather than being assigned to particular orders, occasional drivers are presented with potential orders from which they may select an order suitable for them to deliver. Their decision to participate is modelled based on self- interest, where an occasional driver agent aims to maximise the difference between the incentive offered and his or her perceived value of the additional time required to deliver the order. An integrated approach to customer crowd-shipping is developed in order to consider the benefits for both the retailer and occasional drivers. This includes an incentive scheme and a method for identifying online customers as candidates for crowd-shipping. The latter involves the dynamic calculation of the company’s cost to serve an individual customer, which is determined for all online customers. Finally, user-friendly access to the agent-based simulation model is facilitated by a graphical user interface. The proposed model is subjected to systematic verification, ensuring the correct functioning and integration of its subcomponents. Moreover, the model is evaluated under various operating conditions to gain a deeper understanding of the crowd-shipping initiative, while simultaneously validating the model as adequate. In particular, parameter variation, sensitivity analyses, and scenario analyses are conducted, followed by face validation by subject matter experts. The results of the various analyses indicate that customer crowd-shipping may successfully function as an extension to an existing last-mile delivery system, with the potential of reducing both the total delivery cost and customer waiting time. These benefits are, however, shown to be influenced by the incentive scheme and the strategy by which online customers are se- lected as crowd-shipping candidates. Finally, it is deduced that the maturity of the customer crowd-shipping system and the occasional population’s perceived value of time influence the performance of the customer crowd-shipping model.
- ItemAgriculture sector implications of a green economy transition in the Western Cape Province of South Africa : a system dynamics modelling approach to food crop production(Stellenbosch : Stellenbosch University, 2015-12) Van Niekerk, Jacobus Bosman Smit; Brent, Alan C.; Musango, J. K.; Stellenbosch University. Faculty of Engineering. Dept. of Industrial Engineering.ENGLISH ABSTRACT: The Western Cape Province of South Africa has introduced a green economy plan called "Green is Smart". This initiative has the envisaged possibility of providing the Province with a sustainable economy. The transition towards a green economy will, however, have implications on the food crop production in the Province. Agriculture is a vital part of the Province's economy and a "systems thinking" approach is required to better understand how this transition will influence food crop production. The aim of this study is then to better understand systems thinking, identify different system modelling approaches, and to better understand how the Western Cape's agriculture acts as a complex system. By achieving this, the green economy transition can be better managed within the Province's food crop production. After reviewing the literature, system dynamics modelling was identified as the preferred modelling technique to better understand the implications of a green economy transition of the Western Cape's food crop production. The model simulates the production for ten different food crops from 2001 until 2040. Food crops are produced with a combination of different framing practices, namely conventional, organic and conservation farming. There are three different green economy scenarios (pessimistic, realistic and optimistic), and one scenario where current practices are continued (business as usual). The model results indicate that all three green economy scenarios will require significant financial investment. The results also indicate that only the optimistic green scenario might be worth the financial investment when considering the potential benefits. The study further provides recommendations for stakeholders in order to help this transition to a green economy within the Western Cape food crop sector. The study highlights the usefulness of using system dynamics to model and better comprehend complex systems. The limitations of system dynamics modelling are also discussed in this study. Difficulties with obtaining historical data and modelling sporadic events are the two most noteworthy limitations.
- ItemAlgorithm selector for dynamic AGV scheduling in a smart manufacturing environment using machine learning(Stellenbosch : Stellenbosch University, 2022-11) Schweitzer, Felicia Cathrin; Louw, Louis; Bitsch, Günter; Stellenbosch University. Faculty of Engineering. Dept. of Industrial Engineering.ENGLISH ABSTRACT: Artificial intelligence is considered as significant technology for driving the future evolution of smart manufacturing environments forward. At the same time, automated guided vehicles (AGVs) play an essential role in manufacturing systems because they have such great potential when it comes to improving internal logistics by increasing production flexibility. Consequently, the productivity of the entire system relies on the quality of the schedule, which is capable of achieving massive cost savings by minimizing delay and the total makespan. However, traditional scheduling algorithms often have difficulties in adapting to changing environment conditions, and the performance of a selected algorithm depends on the individual scheduling problem. That is why the analysis of scheduling problem classes can help to identify the most suitable algorithm depending on a given problem. Currently, the focus in the literature lies on individual algorithm approaches for specific AGV scheduling scenarios, but the influence of framework conditions to the algorithm performance lacks attention. More research is necessary in terms of the dynamic and independent reaction for optimizing the AGV scheduling procedure without human surveillance in case of failures. To develop an algorithm selection approach for AGV scheduling scenarios, this research answered the question of how machine learning approaches must be implemented so that the allocation of tasks in the context of dynamic AGV scheduling can be improved to increase performance. This study followed Design Science Research, particularly the cognition process based on Osterle et al. (2011) that builds on an analysis, design, evaluation, and diffusion phase. During the design phase, laboratory experiments unveiled the successful implementation of two constraint programming solvers for solving scheduling problems based on the Job Shop Scheduling Problem (JSSP) and Flexible Job Shop Scheduling Problem (FJSSP). OR-Tools developed by Google and CP Optimizer of IBM solved large instances in reasonable time, and the performance of the solver strongly depended on the given scheduling problem class and problem instance. Consequently, it is beneficial to make use of an algorithm selection, as the overall production performance increased by selecting the most suitable algorithm for a given instance. The field experiment within the learning factory of Reutlingen University enabled the implementation of the approach within a dynamic environment, that can react to disruptions like machine break-downs or AGV failures. As a limitation, the research considered a simplification of the AGV scheduling problem based on the JSSP and FJSSP. As such, the parameters are limited to transport orders, transport durations, sequences and AGVs. Furthermore, the training of the selector was with a limited amount of 544 benchmark instances. Nevertheless, this research showed an exemplary extension of existing scheduling approaches to develop an algorithm selection model which can be built upon in the future. This research places the focus on constraint programming solutions for scheduling problems and emphasizes the benefits of applying machine learning for algorithm selection on a per-instance base. In this way, scheduling systems can be computationally faster and more efficient in the future and help to achieve the desired overall performance of smart manufacturing systems.
- ItemAlpha case removal from titanium alloys by machining with tungsten carbide cutting tools(Stellenbosch -- Stellenbosch University, 2016-03) Conradie, Francois Willem; Oosthuizen, Gert Adriaan; Sacks, Natasha; Stellenbosch University. Faculty of Engineering. Dept. of Industrial Engineering.ENGLISH ABSTRACT: The use of titanium is rising steadily. This surge is due to the metal’s favourable biocompatibility, corrosion resistance and high specific strength. Despite the increasing demand, titanium production is currently limited by outdated manufacturing processes. New processing techniques are therefore under investigation so that raw material may be produced at lower cost. One of the manufacturing processes under review, is the use of chemical milling for the removal of the hard and brittle oxide layer (alpha case) which forms at production temperatures above T = 600°C. Chemical milling facilities currently used in alpha case removal demand high workplace and environmental safety standards which would incur high capital cost if constructed in South Africa. Alternatively, the already established South African machining industry can be expanded to economically remove alpha case using existing infrastructure (milling machines). No machining guidelines are available and such a process is currently deemed uneconomical due to tooling cost. This study therefore investigated the performance of tungsten carbide indexable cutters in the removal of alpha case through machining, and developed guidelines for the economical removal of alpha case. Background experiments determined the hardness-depth profile, composition and grain structure, which were used to aid in the experimental setup and design of primary experiments. The primary objective investigated the feasibility of replacing the acidic solutions of chemical milling, with tungsten carbide cutting tools in machining. The wear of the tungsten carbide cutters and the effect of alpha case on their performance were documented and used to measure the feasibility of machining. At high cutting speeds the carbide cutting tools experienced excessive chipping and notching, which resulted in short tool life and low material removal. Alpha case removal was, however, readily achieved at low cutting speeds where traditional flank wear was experienced. At low cutting speeds, tool life also more closely resembled that which is observed with traditional titanium machining. Furthermore, feed rate had a negligible effect on tool wear and tool life at low cutting speeds. The most effective cutting strategy for alpha case removal with tungsten carbide indexable cutters, therefore involves the employment of low cutting speeds in combination with high feed rates. This will ensure long tool life while still realising reasonable material removal rates. The secondary objective investigated is the scope of feasibility of alpha case machining removal in the context of the South African manufacturing industry. The already established machining industry in South Africa would profit from the expanded titanium machining industry, which could in turn hold further downstream manufacturing benefits. It is hypothesised that at low annual production volume, the tungsten carbide cutting tools used in machining removal of alpha case are the more economical option. Owing to the high cost of constructing new chemical milling facilities, only at high production volume would chemical milling become a viable option for long term manufacturing.
- ItemAlternative technologies for the production of high carbon ferromanganese: A techno-economic Evaluation(Stellenbosch : Stellenbosch University, 2020-12) Sithole, Ntokozo Aphelele; Bam, Wouter; Steenkamp, Joalet Dalene; Stellenbosch University. Faculty of Engineering. Dept. of Industrial Engineering.ENGLISH ABSTRACT: The manganese resource (land-based) in South Africa is currently the largest, accounting for 75% of the global resource. Ore exporting has increased from 50% of the total sales in 1997 to around 85% in 2016 and the trend seems to be increasing (Directorate Mineral Economics, 2017). Furthermore, manganese smelters have either reduced capacity or shut down completely due to operational costs. Van Zyl (2017) explored the various aspects that limit growth in the mineral value chain (Van Zyl, 2017). One of the barriers that were identified in the beneficiation of manganese is the high cost of electricity required for ore smelting. Ferromanganese in South Africa is produced using Submerged-arc furnace (SAF) technology which relies heavily on electricity during production. The current study aimed to identify and compare alternative furnace technologies that can or could produce HCFeMn. The main criterion is to substantially reduce the reliance on electricity during production. The objective of the study was to make use of a literature review in the ferromanganese industry and the ironmaking industry to identify suitable alternative furnace technologies. Alternative technologies will then be compared using a techno-economic evaluation to assess the financial performance of each furnace when compared to the current technology the SAF. The evaluation consisted of mass and energy balances of the HCFeMn process and economic models. Furthermore, the sensitivity of the economic model results in response to deviations in CAPEX and OPEX estimates was investigated. The SAF was compared to the BF that was identified in the ferromanganese industry and the COREX® that was identified in the ironmaking industry. Both technologies commercially produce FeMn and/or pig iron. The BF relies on coke and the COREX® relies on coal. Mass and energy balance model results indicate that SAF recovers the least amount of manganese at 82.8% and the COREX®recovers the most at 84.1%. Fixed capital costs make the SAF the most attractive, the COREX® and BF cost 35% and 37% more, respectively. Annual production costs per ton of alloy for the COREX® on average over the project life are over 26% lower than both furnaces. The COREX® had the highest NPV (R 11 430.46) and IRR (33.11%) with the lowest discounted payback period of 7 years. The SAF NPV was 33% lower, IRR 5.04% lower, and DPBP 1 year longer than the COREX®. The BF performed the worst financially. In all three scenarios, the COREX® yielded a positive NPV, meaning the probability of a 15% return is 1. Furthermore, manganese recoveries as low as 79.7% still yield an NPV 38% higher than the SAF base case. Sourcing of technical and economic data was a challenge, the BF model had outdated HCFeMn process data available. The COREX® has no data published for the HCFeMn process, data can be obtained from thermochemical modelling, laboratory or pilot plant scale tests. Process data specific for the COREX® could improve the quality of the model outcomes of the. Collaborations with Mintek and industry partners are recommended to obtain better quality technical and economic data.
- ItemAnalysing product development best practices and improvement of associated activities with an application to a South African company(Stellenbosch : Stellenbosch University, 2002-12) Hall, Georgina; Van Wijck, W.; Stellenbosch University. Faculty of Engineering. Dept. of Industrial Engineering.ENGLISH ABSTRACT: The dynamic and highly competitive environment that most product development organisations find themselves in demands a method to constantly assess the maturity of the organisations' product development processes and systems. Many of these organisations are in the product development business and for this reason a need was identified for a method that can be used by managers to identify areas in need of improvement on a continual basis. . This thesis included a literature study of product development best practices and organisational measurement techniques, as well as the application and evaluation of a tool that enables the business managers to assess the state of these product development activities against the benchmark of these said best practices. The theoretical approach taken in this thesis, was to define the scope of the organisations and products to be included in the thesis, to investigate the current best practices within both the academic and industry arenas and identify the needs of product development organisations in terms of measuring their product development process maturity and then an evaluation of the tool that enables the identification of shortcomings in the organisations' development systems. Included in the literature study were a variety of Business and Quality Philosophies, existing standards and measurement tools, as well as a brief look at Organisational culture and how it affects Product Development Activities. The results of this literature were then used to substantiate the tool that was used for the actual evaluation and case study. The literature provided a good basis of evaluation, particularly in the way that the tool employs measurements and scoring techniques to assess an organisation's position in terms of product development best practices. The case study then took an existing tool that is currently used by DRM Associates (USA) in assessing the state of an organisation's Product Development Best Practices and used it to assess a Business Unit within a South African company. The results were analysed and the tool thus evaluated in terms of accuracy, user-friendliness and value for the South African market. It was found that the tool is very accurate in terms of identifying areas of weakness both with respect to the strategic performance of the organisation as well as the individual best practices. It is easy to understand, but the scoring system utilised is not that easily employed. It was felt that the scoring systems needed to be more generic as those of ISO 9004 and the South African Excellence Model The idea is that managers do the assessment once in conjunction with a group of consultants and then again as part of a continuous improvement drive, on their own. Managers with limited knowledge of product development best practices and philosophies would find the assessment difficult to do on their own due to the ambiguous scoring criteria. It was felt that a generic system would be easier to use by non-technical people. Once the assessment had been completed and the tool itself evaluated, the value of such a tool for South African product development organisations was also evaluated. In this evaluation it was found that the tool could be more valuable as a guide for future education (an educational roadmap) than as a benchmarking and assessment tool.
- ItemAn analysis of possible effects of developmental pricing: A simulation study of the polypropylene industry in South Africa(Stellenbosch : Stellenbosch University, 2017-03) Gova, Webster; Bam, Wouter; Schutte, Cornelius Stephanus Lodewyk ; Stellenbosch University. Faculty of Engineering. Dept. of Industrial Engineering.ENGLISH ABSTRACT: Beneficiation of locally extracted minerals to produce fully processed, highvalue utility products is currently limited in South Africa. However, in the polypropylene value chain, locally mined coal is fully beneficiated to produce petroleum equivalent fuels and chemicals. The polypropylene value chain contributes fully processed, high utility products for use in various sectors of the economy, including the plastics industry. The Departments of Mineral Resources (DMR), Trade and Industry (DTI), have respectively identified the petroleum and plastics industries as some of the priority industries for intervention in the beneficiation strategy. The polypropylene upstream industry is currently dominated by China, with capacity representing 19% of global supply, while South Africa only accounts for 1%. However, the current capacity in South Africa represents 53% of polypropylene supply on the African continent. The current study investigated possible effects of a cost-plus developmental pricing policy as a beneficiation strategy in the polypropylene upstream industry. The study focussed on evaluating possible effects of cost- plus pricing on the future attractiveness for investment in capital projects to expand polypropylene production capacity in South Africa. The study demonstrated a systematic approach combining simulation and decision models to account for unavailability of full information and high uncertainties in estimates for quantitative appraisals during industrial policy analysis. The study combined value chain analysis using the global value chain (GVC) framework and Monte Carlo (MC) stochastic simulation methodologies to evaluate the possible impact of developmental pricing. The GVC framework was used to analyse the polypropylene upstream value chain with respect to governance and input/output structure. The MC simulation was applied to a discounted cash- flow (DCF) model on net present value (NPV). The approach presented in this research accounts for limited or asymmetric information, high competition and uncertainty in the local polypropylene industry. In addition, this systematic approach to industrial policy analysis appears to be useful in achieving beneficiation strategy objectives in highly competitive, highly regulated globalised industries. This can enable policy-makers to identify measurable impacts in formulating policies for beneficiation strategies. In South Africa, beneficiation strategies for the polypropylene and plastics industry can focus on identifying other raw materials to compete with existing value chains in order to stimulate more upstream competition. This can allow local production of more internationally competitive upstream products and offer better prices to the downstream industries.
- ItemAnalysis of the behaviour of flexibility parameters in intralogistics systems(2021-03) Reinhart, Marvin Markus; Von Leipzig, Konrad; Palm, Daniel; Stellenbosch University. Faculty of Engineering. Dept. of Industrial engineering.ENGLISH ABSTRACT: Today's logistics systems are characterised by uncertainty and constantly changing requirements. Rising demand for customised products, short product lifecycles, and a large number of variants enormously increase the complexity of these systems. In particular, intralogistics material flow systems must be able to adapt to changing conditions at short notice, with little effort and at low cost. To fulfil these requirements, the material flow system must be flexible in three important dimensions, namely layout, throughput, and product. Whilst the scope of the flexibility parameters is described in literature, the respective effects on an intralogistics material flow system and the influencing factors are mostly unknown. In this context, this thesis aims to analyse the behaviour of the flexibility parameters with the help of a multimethod simulation. Therefore, the definitions of the parameters found in the literature are first analysed and specified with regard to their influencing factors. Subsequently, hypotheses regarding the characteristics of the flexibility parameters on the logistical throughput, the production output, and the degree of utilisation of the means of transport are formulated. To confirm the hypotheses, a simulation model based on the logistics learning factory Werk150 of the ESB Business School on the campus of Reutlingen University is developed. The intralogistics system consists of various flexible means of transport which have a defined source-sink relationship. Within the scope of the simulation, these static structures are incrementally transformed into more flexible ones and examined with regard to their behaviour. The model as well as the obtained results are ultimately verified and validated using common techniques in production and logistics systems simulation. The work shows that with an increasing flexibilization of the intralogistics material flow system, the performance can significantly increase. Furthermore, the analysis provides information on where the system-specific potentials of flexibility as well as the limits to changeability lie.
- ItemAn analysis of the upstream supply chain for second-line drugs for multidrug-resistant tuberculosis(Stellenbosch : Stellenbosch University, 2017-03) Lingervelder, Deon; Bam, Louzanne; Stellenbosch University. Faculty of Engineering. Dept. of Industrial Engineering.ENGLISH ABSTRACT: Systematic problems in the supply chain of second-line anti-TB drugs (SLDs) for multidrug- resistant tuberculosis (MDR-TB) are well documented and contribute significantly to the comprehension of the difficulties preventing successful control of the disease. Though literature contains a wealth of proposed changes to global SLD supply chain policies, there is a significant research gap related to quantitative modelling of the SLD supply chain to accurately predict the expected impact of these proposed changes on the availability of SLDs. The global SLD supply chain consists of two components: (i) the ‘upstream’ component which includes all activities from the manufacturing of the active pharmaceutical ingredient through to the warehousing of drugs prior to shipment; and (ii) the ‘downstream’ component which includes in-country warehousing and delivery of drugs to various healthcare facilities. A prominent problem in the supply chain, is the erratic demand patterns, since these prohibit accurate forecasting and effective planning. Consequently, manufacturers are forced to produce drugs in inefficient batch sizes, causing higher prices and longer, inconsistent lead times. A possible solution to address this problem, is the implementation of a large buffer stockpile directed at (i) preventing stock-outs and treatment interruptions, and (ii) combining and timing orders to permit current manufacturers to produce medicines more efficiently. The aim of this study is to model a part of the upstream supply chain of MDR-TB SLDs and to evaluate the impact of implementing such a buffer stockpile. The supply chain is modelled using system dynamics and the model is used to evaluate the likely impact of a range of alternative inventory management policies on the supply chain performance. Three different SLD formulations are included in the model to ensure that the recommendations based on this research are robust. These formulations, namely capreomycin, kanamycin and cycloserine, account for approximately 58% of the total procurement costs of the current supply chain. The modelling results indicate that the inventory policies that will most likely lead to the most significant improvement in the supply chain performance, are the policies that implement a reorder quantity based on an exponential smoothing forecast of previous demand, specifically when a smoothing factor of either 0.1 or 0.5 and a high reorder point are implemented. This research contributes to the current academic literature by increasing the understanding of the upstream SLD supply chain, by providing a quantitative evaluation of the expected impact of suggested changes to the supply chain, and by presenting an example of an application of the system dynamics modelling approach that is not common in literature.
- ItemThe application of 3D Printing in reconstructive surgery(Stellenbosch : University of Stellenbosch, 2010-03) Honiball, John Robert; Dimitrov, D. M.; University of Stellenbosch. Faculty of Engineering. Dept. of Industrial Engineering.ENGLISH ABSTRACT: As part of a growing trend in the medical industry of patient specific solutions, a need arises for means and methods that could grant surgeons the ability to improve their pre-operative planning, and help streamline their intra-operative proceedings relative to each individual patient. A suitable solution has emerged in the form of Additive Fabrication. Most of the traditional layer manufacturing technologies have been considered to be too expensive for medical application, and could not always be justified. However, more cost effective technologies, such as 3D Printing, have recently come to the scene and definitely require a fresh re-consideration for medical applications. In this report the research results are presented that look at the applications of 3D Printing in various fields of reconstructive surgery. Based on a variety of case studies the outcome strongly suggests that 3D Printing might become part of standard protocol in medical practice in the near future.
- ItemApplication of clustering techniques for improved energy benchmarking on deep-level mines(Stellenbosch : Stellenbosch University, 2024-03) Caromba, Claudio Mauricio; Schutte, Cornelius Stephanus Lodewyk ; Van Laar, Jean Herman ; Stellenbosch University. Faculty of Engineering. Dept. of Industrial Engineering.ENGLISH ABSTRACT: The South African mining industry relies on coal-based energy to run operations, with the sector utilising 29.6 Terawatt-hours of electricity in 2018. However, constraints on energy availability and rising electricity prices pressure the industry to manage energy usage better and remain one of the main contributors to the South African economy. Energy benchmarking is a popular and effective energy management method in the mining sector. Current methods use the average energy usage of various mining shafts over different intervals to develop benchmarks. These benchmarks may lead to skewed performance evaluation if the mining shafts have vastly different modes of operation or when anomalous energy usage is present within the interval. Clustering-based benchmarking techniques have been applied successfully in other industries, to group similar energy users and identify energy savings opportunities, but remains unstudied in the mining sector. This study developed and applied a clustering-based benchmarking method to evaluate the performance of a single high-energy usage system (internal benchmarking) and different mining shafts (external benchmarking) at a deep level gold mine in South Africa. A combination of the quantitative research approach and a case study research design was employed to derive steps for each application of the method. In both cases the relevant datasets were collected and processed, before selecting the number of clusters and best suited clustering algorithm using a combination of popular clustering metrics. The clusters were used to identify benchmarks to compare with traditional methods from the industry. The K-means unsupervised learning clustering algorithm was used to group energy usage patterns and generate five typical load profiles representing common pumping energy usage on a mine shaft. These profiles were used as benchmarks to identify outlier energy usage and potential energy-saving opportunities on the mining shaft using cluster quartile and average pumping-energy intensity benchmarks. The K-means clustering algorithm was applied to four production shafts at the mining complex to identify different energy usage groups. The ordinary least squares benchmarking method was leveraged to develop expected energy usage benchmarks within each cluster to determine the scope for improvement and compare energy performance. Compared to traditional methods, the benefit of clustered energy usage benchmarks on deep-level mines is shown by successfully identifying groups that better describe the energy usage type. The five typical load profiles were 14 % better at explaining the energy usage than the day-of-week grouping, and the four cluster-based expected energy benchmarks were twice as good at energy prediction than the current method of a single equation for all the energy users. These improvements in energy benchmark development allow for a fair and accurate evaluation of energy performance and do not over- or underestimate the severity of the wastage and the opportunity for energy savings. This facilitates focused and measurable energy management that may assist mines in continuing their valuable contribution to the South African economy.
- ItemApplication of lean principles in the South African construction industry(Stellenbosch : Stellenbosch University, 2021-03) Maradzano, Isabellah; Matope, Stephen; Stellenbosch University. Faculty of Engineering. Dept. of Industrial Engineering.ENGLISH ABSTRACT: South Africa is a developing country that invests billions of rands annually in the construction industry. This industry consumes resources, and inevitably, waste is generated during the process. Although numerous approaches have been developed to improve quality, efficiency, and effectiveness in this industry, lean principles offer the ability to minimise and eliminate non-value adding work thus increasing value for the client. The research was carried out in three stages which are literature review, lean construction framework development and lean construction framework validation and verification through case studies. In the literature review section the thesis discussed concepts of lean, lean thinking principles, lean production methods to reduce waste, lean construction, benefits of lean construction, lean construction tools currently used worldwide, barriers to lean construction, drivers of lean construction practice in the South African construction industry, waste classification in this industry and controllable waste in construction. The research study then used the systematic literature review methodology to systematically analyze applications of lean principles in the construction industry, and identified tools that will be used to be implement lean construction in the South African construction industry (electrical and mechanical engineering services). The results of the systematic literature were used to develop a lean construction implementation framework. The framework was then implemented and refined using two local case studies focusing on electrical and mechanical engineering services in the South African construction industry. The refined lean implementation framework is made out of four segments which are focusing on culture and behaviour, implementing lean construction practices, lean construction drivers, and using lean project management strategies.
- ItemApplication of lean tools in rolling stock procurement supply chain management(Stellenbosch : Stellenbosch University, 2018-03) Ekene, Nicholas Umeh; Fourie, Cornelius J.; Matope, Stephen; Stellenbosch University. Faculty of Engineering. Dept. of Industrial Engineering.ENGLISH ABSTRACT: The main aim of this research study was an investigation of applicable lean tools in rolling stock procurement supply chain management (SCM). Lean principles resonate from the manufacturing environment while rolling stock procurement SCM is a typical example of the non-manufacturing environment. Hence a variance in applicable tools is apparent. The case study of the research was studied and analysed. The procedure adopted for measurement and analysis of the case study (rolling stock procurement SCM) began with mapping the process areas. This was performed through a type of lean tool known as value stream mapping. After the SCM mapping, the lean waste in the SCM was identified through waste analysis. During analysis, it was discovered that the bidding process holds the highest area of waste. Following this finding, the bidding process was evaluated, upon which lean tools for waste reduction are prescribed. From the findings obtained in the measurement and analysis step, mapping of the future state was carried out. Based on the mapping of the future state of the supply chain, relevant performance metrics are recommended for a periodic check. Limitations, as well as assumptions encountered during the research study, are also discussed. The study conclusion is presented in the form of answers to the research questions. Some of the major waste discovered in the bidding process includes poor communication between bidding team and end user and difficulty in sourcing for potential suppliers. The recommendations put forward in this research project are to strategically reform the bidding process by making required changes to tender documents, standardising the procurement SCM process and improving the communication culture between suppliers and SCM.