A study on statistical process control (SPC) in pharmaceutical contract manufacturing : potential determinants of SPC implementation success : a thesis presented in partial fulfilment of the requirements for the degree of Master of Quality Systems at Massey University, Palmerston North, Manawatu, New Zealand
| dc.contributor.author | Cui, Lu | |
| dc.date.accessioned | 2020-11-24T02:14:16Z | |
| dc.date.available | 2020-11-24T02:14:16Z | |
| dc.date.issued | 2020 | |
| dc.description | Figures 2.8 (=Bou-Llusar et al., 2009 Fig 1) & 2.9 (=Jayamaha et al., 2009 Fig 1) have been removed for copyright reasons. | en_US |
| dc.description.abstract | Many organisations in New Zealand are still unfamiliar with Statistical Process Control (SPC) or how to implement it successfully, even though SPC has been widely used in other countries such as Japan, with great success. The potential of SPC has been underestimated in most cases, especially in the Pharmaceutical industry that share some common ground with SPC (e.g. measurement and analysis). It is not just control charts that make SPC successful. A control chart is just a tool (and a useful one at that) being used in the practice of SPC. There are some critical factors or enablers of successful SPC implementation. The context of this study is pharmaceutical contract manufacturing (PCM). The aims of this research are to identify a suitable SPC programme for PCM companies, identify enablers of successful SPC implementation, and to understand how these enablers cause quality improvement. A single case study was designed to verify the applicability of SPC. The research confirmed the suitability of a specific six-step SPC implementation approach mentioned in the literature. SPC was found to be a suitable technique for identifying and understanding process variation in PCM. The case study findings are useful to quality practitioners as well as PCM companies contemplating on implementing SPC. Regarding theoretical contributions, the researcher developed two theoretical models from extant literature and both models were empirically tested using survey data collected from 76 respondents using the state-of-the art in multivariate latent variable path modelling. The model test results showed that top management commitment has both a direct effect as well as an indirect effect on quality performance through other SPC/TQM enablers. The results also showed that soft factors of TQM/SPC are significantly more influential than hard factors of TQM/SPC in achieving quality performance. While this is nothing new, one thing that is novel in this research is the way researcher modelled hard and soft factors of TQM/SPC to estimate how much more important soft factors are than hard factors, in achieving quality performance. The limitations of the study and suggestions for future research have been provided at the end of this thesis (Chapter 6). | en_US |
| dc.identifier.uri | http://hdl.handle.net/10179/15822 | |
| dc.language.iso | en | en_US |
| dc.publisher | Massey University | en_US |
| dc.rights | The Author | en_US |
| dc.subject.anzsrc | 401409 Manufacturing safety and quality | en |
| dc.title | A study on statistical process control (SPC) in pharmaceutical contract manufacturing : potential determinants of SPC implementation success : a thesis presented in partial fulfilment of the requirements for the degree of Master of Quality Systems at Massey University, Palmerston North, Manawatu, New Zealand | en_US |
| dc.type | Thesis | en_US |
| massey.contributor.author | Cui, Lu | Lu |
| thesis.degree.discipline | Quality Systems | en_US |
| thesis.degree.grantor | Massey University | en_US |
| thesis.degree.level | Masters | en_US |
| thesis.degree.name | Master of Quality Systems (MQS) | en_US |