Fulfilment process is important for operational efficiency in semiconductor manufacturing, particularly for Company A, a leader in wafer processing equipment for thin-film deposition. This study investigates methods to enhance Company A's fulfilment process through the integration of a lot-sizing simulation into their existing ERP system, focusing on optimizing order quantities amid fluctuating demand. The research addresses three primary objectives: identifying inaccuracies in the current simulation, exploring ERP system integration methods, and evaluating fulfilment process improvements through enhanced demand forecasting and data accuracy.
A mixed-method approach was adopted, incorporating qualitative insights from surveys with Company A’s stakeholders and quantitative data analysis for pain point identification. A SWOT analysis, along with an Fishbone Diagram and Monte Carlo simulations, supported the identification of key areas for improvement and the validation of proposed solutions. External market research enabled better insights to potential integration efforts and functions. Additionally, the study employed a Non-Linear Programming (NLP) model to evaluate multiple lot-sizing scenarios based on metrics such as cost efficiency, safety stock, demand accuracy capacity utilization, and service level.
The findings indicate significant potential for reducing inaccuracies and optimizing fulfilment through ERP integration, improving both forecast precision and process adaptability. While the proposed integration shows clear benefits in operational efficiency and cost savings, challenges around real-time data synchronization and user training. This research highlights the value of ERP-integrated lot-sizing for achieving resilience and efficiency in semiconductor manufacturing supply chains.