Statistical Process Control (SPC) Implementation in Manufacturing Industry to Improve Quality Performance: A Prisma Systematic Literature Review and Meta Analysi

Industrial Engineering Department, BINUS Graduate Program - Master of Industrial Engineering, 11480 Bina Nusantara University, Jakarta, Indonesia

^* Corresponding author: hadiyanto001@binus.ac.id

Abstract

The fundamental need for quality in manufacturing is the production process must be able to generate the product with an acceptable variance from the stated quality index. Statistical process control (SPC) is frequently used to monitor standards, take measurements, and take corrective action. Preferred Reporting Items for Systematics Reviews and Meta-Analyses (PRISMA) methods were used to better inform reviewers and readers about the authors’ actions and findings, speed up the review process, and improve the quality of the reporting. Publish or perish, VOS viewer, and Mendeley Desktop were also used to search related articles and analyze the bibliometric. The conclusion notes that integrating other quality approaches has increased the use of SPC in the manufacturing sector. This was applied within other quality improvement programs such as Six Sigma and TQM. Even though SPC is a statistically based technique, challenge, and limitation factors showed that implementing SPC in the manufacturing industry will be successful if other crucial factors like management, education/training, culture, and the availability of human resources are well-prepared. In conclusion, the authors hope that this review will highlight the value of SPC as a potential tool for quality control and enhancement in the manufacturing sector.