<![CDATA[In the dynamic landscape of the apparel manufacturing industry, timely and accurate decision-making is critical to operational success. However, the absence of a real-time monitoring system on the production floor has led to dependency on manual reporting, resulting in data delays, inconsistencies, and even manipulation. These challenges severely limit transparency, responsiveness, and overall efficiency. This thesis addresses this business-critical issue by proposing the implementation of a Manufacturing Execution System (MES) to digitally transform production monitoring and reporting processes. Utilizing the Soft Systems Methodology (SSM), this study explores multiple stakeholder perspectives including production teams, supervisors, and management to define root causes and identify feasible solutions. The research incorporates qualitative insights through interviews and surveys, coupled with best practice analysis to design a context-specific MES framework. The outcome aims to enhance real-time data visibility, streamline workflows, and support data-driven decision-making, ultimately contributing to increased productivity and trust across operational levels.]]>
Copyrights © 2025
