- Title
- A model for smart factories in the pharmaceutical manufacturing sector
- Creator
- Mugwagwa, Basil
- Subject
- Internet of things
- Subject
- Manufacturing processes -- Automation Drug factories Pharmaceutical technology
- Date Issued
- 2019
- Date
- 2019
- Type
- Thesis
- Type
- Masters
- Type
- MBA
- Identifier
- http://hdl.handle.net/10948/41897
- Identifier
- vital:36607
- Description
- Since the turn of the century, the manufacturing industry has metamorphosed from manually driven systems to digitalisation. Product life cycles have shortened and customer demands have become more intense. Globalisation has brought about challenges that drive the need for smart manufacturing. Industry 4.0 has emerged as a response to these demands. The integration of various processes, facilities and systems throughout the value chain and digitalisation of physical systems is promoted in Industry 4.0. Due to increased competitive pressures, organisations are strategically looking at automation to deliver competitive advantage in delivering products at the right cost, quality, time and volumes to the customers. Organisations are therefore looking for manufacturing solutions that are technology driven, 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. The smart factory, a component of Industry 4.0, is a self-organised, modular, highly flexible and reconfigurable factory that enables the production of customised products at low cost, therefore maximising profitability. Smart manufacturing can bring about competitive advantages for an organisation. Labour concerns have been raised against automation and smart manufacturing, citing potential job losses, workforce redundancy and potential employee lay-offs. This unease, in turn, influences the employees’ attitude towards technology, which could lead either to its acceptance or refusal. The purpose of this research is to enhance the understanding of smart factories in the pharmaceutical 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 a 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 pharmaceutical manufacturers 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 attitudes towards the acceptance of technology, within the pharmaceutical manufacturing company. Descriptive statistics were used to summarise the data into a more condensed form, which could simplify the identification of patterns in the data. Inferential statistics were used to validate if the conclusions made from the sample data could be inferred to a larger population. Various factors influence perceptions about ease of use and usefulness, which then, in turn, influence attitudes 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, supported by Exploratory Factor Analysis, Correlations and ANOVA Testing identified the following factors as having an influence on the Attitude towards the Positive Impact of Smart Factories, within the pharmaceutical manufacturing company: Training and Development, Individual Characteristics, Trust, Organisational Culture, Resources and Costs and Job Security. The importance of each factor was identified to understand its function how to improve the implementation of smart factories. The research results indicated that the perception of management and employees is different on factors like such as Training, Individual Characteristics, Trust, Resources and Costs, Automation and Support and Parent Company in relation to technology acceptance. There was however no difference in perception between managers and employees on Security, Government Laws and Regulations, Organisational Culture, Peer Support and Organisational Support in relation to technology acceptance. The research study contributed to the identification and understanding of the factors influencing the implementation of smart factories in the pharmaceutical industry.
- Format
- xvi, 172 leaves
- Format
- Publisher
- Nelson Mandela University
- Publisher
- Faculty of Business and Economic Sciences
- Language
- English
- Rights
- Nelson Mandela University
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