Factors influencing the automation of procurement processes at Higher Education Institutions in South Africa
- Authors: Kock, Yolandi
- Date: 2021-04
- Subjects: Automation , Business logistics , Industrial procurement
- Language: English
- Type: Master's theses , text
- Identifier: http://hdl.handle.net/10948/51732 , vital:43367
- Description: The main objective of this research was to evaluate the factors that influence the automation of procurement processes at Higher Education Institutions in South Africa. This was appropriate due to the important role that procurement plays in the day to day activities in the higher education environment and the need to fully automate procurement systems to assist in cost saving efforts and process efficiency. The study employed the survey method in the collection of data and questionnaires were the main data collection instrument. Seventy (70) respondents, who all form part of the Purchasing Consortium of Southern Africa (PURCO SA) were targeted to participate in the empirical study. Initial review of the topic revealed limited research into automated procurement systems at higher education institutions in South Africa, but indicated that universities in countries like Ghana, Italy, Kenya and Zimbabwe were more advanced in terms of automation. The study achieved its purpose by reaching both the main and the secondary research objectives successfully, highlighting the factors that influence the automation of procurement processes. The analysis further revealed time and cost savings as well as process efficiencies when using automated procurement systems. The study concludes with recommendations for Procurement Managers and recommendations on future research. , Thesis (MBA) -- Faculty of Business and Economic Sciences , Business Administration, 2021
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- Date Issued: 2021-04
Impact of automation technologies on employment
- Authors: Dukashe, Loyiso
- Date: 2021-04
- Subjects: Automation , Automation -- Economic aspects , Employees -- Technological innovations
- Language: English
- Type: Master's theses , text
- Identifier: http://hdl.handle.net/10948/51335 , vital:43265
- Description: Throughout history, the introduction of automated technologies has an impact on on human labour. The current wave of technological advancement has expanded the scope of automation raising a concern about the future relevance of human labour. Hence, this study investigated possible futures on the effect of automation technologies on employment. The study adopted a desktop research approach using secondary sources employing future studies methodologies. The study identified a need to transform employment, educational systems and social policy to proactively respond to future effects of automation technologies towards employment. , Thesis (MBA) -- Faculty of Business and Economic Sciences, Business Administration, 2021
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- Date Issued: 2021-04
Perceptions regarding shared value within the South African mining industry
- Authors: Khubana, Talifhani
- Date: 2021-04
- Subjects: Automation , Business planning , Gold mines and mining -- South Africa
- Language: English
- Type: Doctoral theses , text
- Identifier: http://hdl.handle.net/10948/51710 , vital:43365
- Description: Mining has been a key driver of socioeconomic change, economic growth and environmental impact for decades. However, the industry’s volatility and its negative social and environmental effects are sources of concern. In this context, the study investigated the stakeholders’ perceptions of Shared Value (SV) within the mining industry of South Africa. This included establishing antecedents and outcomes of SV within the South African mining industry. The study also aimed to fill the research gap and contribute to the existing body of knowledge regarding the mining industry and SV in South Africa. The comprehensive literature review in this study included discussion on the overview of the South African mining industry, theories related to SV, theoretical perspectives on SV, and the experiential studies supporting the study’s hypothetical model. The empirical investigation conducted by means of a survey was undertaken under the unprecedented conditions of COVID-19 pandemic. The primary data was statistically examined in six phases: exploratory factor analysis (EFA); Cronbach’s alpha; descriptive statistics; Pearson’s product correlation; and regression analysis. The ANOVA was also conducted to determine the influence of demographic factors on SV perceptions. The empirical results confirmed that automation and innovation (through three pillars, namely, innovation for value chain inclusivity, automation and business model innovation, infrastructure development) and employment conditions are the antecedents of SV. The study illustrated three approaches of SV: reconceiving the product/service and markets, reimagining value chain productivity and development of the enabling environment. Furthermore, the study revealed competitive advantage and sustainability performance as the outcomes of SV. This study makes a notable contribution throughout management and strategy practices as it provides insightful guidelines for stakeholders to understand how to adapt and enforce SV strategies, while empirical results could also be utilised by the government as a guide to formulate policies and strategies relating to the mining industry. , Thesis (DPhil) -- Faculty of Business and Economic Sciences, Business Management, 2021
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- Date Issued: 2021-04
Software robot process automation at the South African Revenue Service (SARS)
- Authors: Ferreira, Cheryl-Ann
- Date: 2021-04
- Subjects: Automation , Automation -- Economic aspects , South African Revenue Service
- Language: English
- Type: Master's theses , text
- Identifier: http://hdl.handle.net/10948/51383 , vital:43270
- Description: Technology is everywhere and what was inconceivable five years ago, such as selfdriving vehicles, drones and virtual assistants are now changing the way we perceive professions in the future. The latest software is utilised to discover new drugs, translate languages and even invest large sums of money. The Fourth Industrial Revolution (4IR), also referred to as Industry 4.0, is disrupting almost every industry worldwide and changing entire production systems and the management thereof and governance Artificial intelligence (AI) is not new and due to recent developments in information and technology, the impact thereof will be more significant in the near future. This research has tried to gain insight into the perceptions of employees and management regarding the factors that influence the attitude towards Robotic Process Automation (RPA) are beneficial for both the organisation and the employees. The aim of this treatise was to develop a greater knowledge and understanding of RPA, to identify the factors that are significant for a conceptual model and gain an understanding of the alignment of the views of employees and management pertaining to the factors that influence the attitude towards RPA. The information gained from this treatise could assist SARS leadership to better understand the perceptions of employees and management pertaining to RPA. The research furthermore endeavoured to discover the factors that affect the attitude towards RPA, to identify back office processes for RPA and to ascertain the benefits to SARS of utilising RPA. , Thesis (MBA) -- Faculty of Business and Economic Sciences, Business Administration, 2021
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- Date Issued: 2021-04
A genetic algorithm to obtain optimum parameters for a halcon vision system
- Authors: Fulton, Dale Meares
- Date: 2017
- Subjects: Genetic algorithms , Artificial intelligence , Automation , User interfaces (Computer systems)
- Language: English
- Type: Thesis , Masters , MEng
- Identifier: http://hdl.handle.net/10948/29751 , vital:30774
- Description: This report discusses the optimisation of a HALCON vision system using artificial intelligence, specifically a genetic algorithm. Within industrial applications, vision systems are often used for automated part inspection and quality control. A number of vision system parameters are to be selected when setting up a vision system. Since each vision system application differs, there is no specific set of optimal parameters. Parameters are selected during installation using a trial and error method. As a result, there is a need for an automated process for obtaining suitable vision system parameters. Within this report, research was conducted on both vision systems, genetic algorithms and integration of the two. A physical vision system was designed and developed utilising HALCON vision software. A genetic algorithm was then developed and integrated with the vision system. After integration, experimental testing was performed on the genetic algorithm in order to determine the ideal genetic algorithm control parameters which yield ideal genetic algorithm performance. Once the ideal genetic algorithm was obtained, the genetic algorithm was applied to the vision system in order to obtain optimal vision system parameters. Results showed that applying the genetic algorithm to the vision system optimised the vision system performance well.
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- Date Issued: 2017
An Internet of things model for field service automation
- Authors: Kapeso, Mando Mulabita
- Date: 2017
- Subjects: Internet of things Manufacturing processes -- Automation , Automation
- Language: English
- Type: Thesis , Masters , MCom
- Identifier: http://hdl.handle.net/10948/18641 , vital:28698
- Description: Due to the competitive nature of the global economy, organisations are continuously seeking ways of cutting costs and increasing efficiency to gain a competitive advantage. Field service organisations that offer after sales support seek to gain a competitive advantage through downtime minimisation. Downtime is the time between service requests made by a customer or triggered by equipment failure and the completion of the service to rectify the problem by the field service team. Researchers have identified downtime as one of the key performance indicators for field service organisations. The lack of real-time access to information and inaccuracy of information are factors which contribute to the poor management of downtime. Various technology advancements have been adopted to address some of the challenges faced by field service organisations through automation. The emergence of an Internet of Things (IoT), has brought new enhancement possibilities to various industries, for instance, the manufacturing industry. The main research question that this study aims to address is “How can an Internet of Things be used to optimise field service automation?” The main research objective was to develop and evaluate a model for the optimisation of field services using an IoT’s features and technologies. The model aims at addressing challenges associated with the inaccuracy or/and lack of real-time access to information during downtime. The model developed is the theoretical artefact of the research methodology used in this study which is the Design Science Research Methodology (DSRM). The DSRM activities were adopted to fulfil the research objectives of this research. A literature review in the field services domain was conducted to establish the problems faced by field service organisations. Several interviews were held to verify the problems of FSM identified in literature and some potential solutions. During the design and development activity of the DSRM methodology, an IoT model for FSA was designed. The model consists of:The Four Layered Architecture; The Three Phase Data Flow Process; and Definition and descriptions of IoT-based elements and functions. The model was then used to drive the design, development, and evaluation of “proof of concept” prototype, the KapCha prototype. KapCha enables the optimisation of FSA using IoT techniques and features. The implementation of a sub-component of the KapCha system, in fulfilment of the research. The implementation of KapCha was applied to the context of a smart lighting environment in the case study. A two-phase evaluation was conducted to review both the theoretical model and the KapCha prototype. The model and KapCha prototype were evaluated using the Technical and Risk efficacy evaluation strategy from the Framework for Evaluation of Design Science (FEDS). The Technical Risk and Efficacy strategy made use of formative, artificial-summative and summative-naturalistic methods of evaluation. An artificial-summative evaluation was used to evaluate the design of the model. Iterative formative evaluations were conducted during the development of the KapCha. KapCha was then placed in a real-environment conditions and a summative-naturalistic evaluation was conducted. The summative-naturalistic evaluation was used to determine the performance of KapCha under real-world conditions to evaluate the extent it addresses FSA problems identified such as real-time communication and automated fault detection.
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- Date Issued: 2017
Factors which affect the levels of automation in an automotive final assembly plant
- Authors: Pillay, Prabshan
- Date: 2012
- Subjects: Process control -- Automation , Automation , Automobile industry and trade
- Language: English
- Type: Thesis , Masters , MBA
- Identifier: vital:8833 , http://hdl.handle.net/10948/d1019800
- Description: In the global automotive industry there is a drive toward integration of autonomous and human operated equipment. Monfared and Yang (2006:546) suggest that this dynamic requirement could be met with elements to be investigated in a research paper. Current investigations show a gap in management not having a guideline which can be used to help decide between automation versus human capital in the planning of new production facilities in the automotive assembly plant. (Skjerve and Skraaning, 2004:3). The purpose of this research is to determine what factors affect this decision-making process. In order to carry out this research, an in-depth literature review was conducted using various sources. The sources included, but were not limited to, interviews at assembly plants, the Nelson Mandela Metro University library, various e-journals and the internet. The literature review led to the finding of the factors which affect Levels of Automation (LOA) and to the development of the research instrument which was used to measure the impact of those factors. The results of fifty-two (52) respondents were then analysed and used as evidence to support the three hypotheses proposed. As a result of completing the above procedure the following hypotheses were supported. The greater the level of technology and the lower the skills of employees the greater the level of automation in an automotive assembly plant to be used. The greater the complexity of the assembly processes the lower the level of automation in an automotive assembly plant to be used. The higher the flexibility the greater the level of automation in an automotive assembly plant to be used. This means that managers and supervisors of assembly plants should consider the level of technology and skills of employees, flexibility and complexity during the design stages of an automotive assembly line as these factors will affect profitability by reducing waste, improve quality as well as allow for flexibility in customer demand in terms of volumes and product variance.
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- Date Issued: 2012