Abstract:
Statistical quality control (SQC) methodology has been well recognized as a systematic approach for continuous quality improvement. Hence, SQC is adopted widely by both manufacturing and service industries as part of their operational strategy to improve quality performance. Holistically, SQC methodologies could be grouped into two categories, which are detection-based methodology, such as Sampling Inspection, Statistical Process Control (SPC); and prevention methodology for instance Process Capability study, Design for Manufacturability (DFM). Findings from the literature review suggested that the implementation of SQC methodology does improve organizational quality improvement. However, SQC methodology is generally viewed by prior researchers as a single entity without exploring the attribution or type of SQC methodologies that are driving quality performance. Hence, this research closes the literature gap by assessing the application level of each SQC methodology within Small and Medium Enterprises (SME) manufacturers in Johor Bahru (JB), and explore the relationship between the implementation level of SQC methodologies and quality performance. The study is quantitatively based via a survey questionnaire and responded by 110 SME manufacturing companies within JB. The implementation level of SQC methodologies and their relationship with quality performance are examined separately via descriptive analysis and Pearson correlation test. Finding from the study revealed that SME manufacturers in JB tend to adopt detection-based SQC methodologies (i.e. SPC and Sampling inspection) as their continuous quality improvement methodology. While prevention-based methodologies (Process capability and DFM) are still not the common practices. In addition, the result of this study also suggested that preventionbased methodologies are more likely to improve organizational quality performance. The finding and the SQC framework developed in this study has descriptive value in terms of studying, classifying, and defining the attributes of SQC and the relationships that govern continuous quality improvement in SMEs.
Page(s):
259-263
DOI:
DOI not available
Published:
Journal: Science International, Volume: 33, Issue: 3, Year: 2021
Keywords:
Statistical process control
,
Statistical Quality Control
,
Process Capabilliyt
,
Six Sigma
,
Sampling Inspection