- Title
- A model for smart factories in the automotive sector
- Creator
- Leo, Jo-Anne Ronell
- Subject
- Internet of things
- Subject
- Manufacturing processes -- Automation Labor supply -- Effect of technological innovations on Cloud computing
- Date Issued
- 2018
- Date
- 2018
- Type
- Thesis
- Type
- Masters
- Type
- MBA
- Identifier
- http://hdl.handle.net/10948/22531
- Identifier
- vital:29997
- Description
- The manufacturing industry is on the brink of transformation, with smart factories and digitalisation at the forefront. New challenges such as globalisation, cost pressure and consumer demands are imminent in the current environment. In order to overcome these challenges, the Fourth Industrial Revolution, also known as Industry 4.0 has emerged. Industry 4.0 promotes the computerisation of manufacturing facilities and emphasises an end-to-end digitalisation of physical resources and integration of processes through the entire value chain. The smart factory, a component of Industry 4.0, is a self-organised, modular, highly flexible and reconfigurable factory that enables production of customised products at low cost, therefore maximising profitability. Manufacturing processes are driven by technologies such as cyber-physical systems, big data, collaborative robots and the Internet of Things. This allows autonomous communication throughout the value chain between machine-to-machine and human-to-machine. Organisations consider automation and technology as strategic business tools which are used to increase short and long term profits and realise operating objectives. In contrast, the implementation of automation and technology in the workplace raises labour concerns, fear of layoffs and redundancies among the workforce. This unease, in turn, influences the employees’ attitude towards technology which could lead either to its acceptance or refusal thereof. The purpose of this research is to enhance the understanding of smart factories in the automotive industry by conducting a systematic analysis of the factors which influence the attitude of those involved towards a smart factory implementation. This study focuses on the perceptions among employees and management. The research is an quantitative study consisting of a literature review of the key concepts related to Industry 4.0, smart factories and technology-acceptance theories. The empirical study consisted of surveys completed by management and employees of one of the automotive Original Equipment Manufacturers (OEM), in South Africa. The questionnaire used in this research consists of questions regarding demographic data and questions regarding the perception of change and factors influencing the attitudes towards the acceptance of technology within the OEM. To summarise the data into a more condensed form which could simplify the identification of patterns in the data, descriptive statistics were used. Inferential statistics were used to validate if the conclusions made from the sample data could be inferred to a larger population. Various factors influence the perception about ease of use and usefulness, which then in turn influences the attitude and the intention to use technology. These factors have been examined by numerous authors in the technology acceptance literature. Recommended factors based on the statistical analysis of the questionnaire results were identified. A model identified the following factors as having an influence on the Attitude towards the Positive Impact of Smart Factories within the OEM: Skills and Training, Individual Characteristics, Trust, Organisational Culture, Resources and Costs and Job Security. The importance of each factor was identified to understand its function in how to improve the implementation of smart factories. This research suggested improvements for the automotive OEM based on the statistical analysis of the survey results. Inconclusive results were indicated on three variables and these should be improved, namely, Organisational Culture, Job Security and Security and International / National Standards. Two sub-groups were defined by different job levels and different perceptions were found concerning the factors that were measured. People at different job levels in the OEM perceived medium to large significant differences in all the factors comprising the proposed model of the Attitude towards a Smart Factory. The smart factory model developed in this study specified the factors which influence the Attitude towards a Smart Factory within the automotive sector and the effect these factors have on technology acceptance.
- Format
- xiv, 172 leaves
- Format
- Publisher
- Nelson Mandela University
- Publisher
- Faculty of Business and Economics Sciences
- Language
- English
- Rights
- Nelson Mandela University
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