Case of Preferential Selection of Attribute over Variable Control Charts in Trend Analysis of Microbiological Count in Water

Abstract

Monitoring the quality criteria in the healthcare industry and the pharmaceutical field specifically is a crucial mission activity to ensure the delivery of safe and effective treatment to patients with predictable and acceptable medicinal properties. One of the critical ingredients that are found in many activities is water. In the present study, the inspection characteristic trend was monitored by collecting results of the microbial count of Purified Water (PW) at two points in the water treatment station. The dataset was examined for pattern and distribution after processing and stratification and before conducting transformation using Microsoft Excel. Then, control charts were constructed using Statistical Process Control (SPC) software. The results showed that transformation improved data normalization for the Individual-Moving Range (I-MR) chart while the original pattern of the dataset was lost distorted. On the other hand, other advantages could be retained when using the Laney chart where no transformation was implemented on original raw data. The selection should be based on the nature of the process aim and condition.