Exploring Unconventional Strategies for Enhancing Business Performance
Authors
Silva Ferreira, Israel
Issue Date
2024
Degree
Publisher
Dublin Business School
Rights holder
Rights
Abstract
The article delves into the significant role that real-time data plays in quality control, with a particular focus on the utilization of machine learning to enhance manufacturing outcomes. Through a thorough examination, it evaluates both the advantages and difficulties associated with harnessing real-time data, analyses the potential for machine learning to optimize Quality Control and Project Management procedures and the accuracy results of 5 different machine learning models. In doing so, it emphasises the value of real-time data in aiding Quality Managers and Project Managers in making well-informed decisions and increasing project success rates. Moreover, the article explores the integration of machine learning techniques to leverage current data and outlines the potential benefits and challenges that come with this approach. By providing insight into how project managers can effectively utilize machine learning, the article offers valuable guidance for enhancing project performance and achieving better overall results.