Continuous Quality Improvement by Statistical Process Control

Article deals with the application of selected tools of statistical process control, through which we can achieve continuous quality improvement. The advantage of these tools is that they can identify the effects of the processes that cause unnatural variability in processes that result of errors and poor quality. Tools like capability index, histogram, model DMAIC, control chart, etc. can reliably determine the anomalous variability in the process and thereby contribute to quality improvement. In the paper through histograms and Shewhart control charts action exposing the systemic implications of the processes and therefore unnatural variability in processes, which result in non-compliance. The results clearly show that through the DMAIC model can systematically improve quality. Histograms show the contribution of the normal distribution of frequencies monitored quality characteristics while Shewhart control charts show that the investigated processes are under statistical control. Use of DMAIC model as well as other statistical quality tools is a way to achieve continuous quality improvement. (C) 2016 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license.