Improvement of Quality Defects and Wastage Control in The ATN Soap Industry Peshawar Through Six Sigma and Artificial Intelligence (AI)

Abstract

The ATN Soap Industry in Peshawar has faced significant challenges in controlling quality defects and minimizing wastage in its production  processes. To address these challenges, the integration of the Six Sigma methodology with Artificial Intelligence (AI) has been employed. Six Sigma is a well-known process improvement methodology that aims to reduce defects to achieve near-perfect quality, while AI offers advanced analytics and predictive capabilities that enhance Six Sigma's impact. This research aims to improve quality and reduce wastage using a hybrid approach of Six Sigma and AI, inspired by methodologies implemented in other sectors, such as textile manufacturing.The concept of Six Sigma, riginally developed by Motorola in the 1980s, is centered around reducing process variation and enhancing product quality (Antony, 2004). The methodology aims to achieve a process capability of 3.4 defects per million opportunities, making it a robust tool for quality improvement (Pyzdek & Keller, 2014). By integrating Six Sigma with AI, the ATN Soap Industry seeks to leverage predictive analytics to identify root causes of quality defects and optimize production processes. AI, particularly machine learning, can enhance Six Sigma by automating data analysis and providing deeper insights into complex production challenges (Perera, Nanayakkara, & Rodrigo, 2021).

Keywords- Quality Defects, Wastage Control,  ATN Soap, Six Sigma,  Artificial Intelligence (AI) & Peshawar.