Study of Demand Forecasting Using Time-Series Analysis (ARIMA)

Demand forecasting plays a pivotal role in the manufacturing industry, influencing inventory management, production planning, and operational efficiency. This research explores the application of time series analysis, specifically the Auto Regressive Integrated Moving Average (ARIMA) model, in forecasting demand within the manufacturing sector. The study aims to assess the effectiveness of the ARIMA model in predicting demand patterns, addressing the challenges posed by dynamic market conditions and fluctuating consumer preferences. By analyzing historical data and employing the ARIMA methodology, this research seeks to provide insights into the accuracy and reliability of demand forecasts in the manufacturing industry. The findings of this study contribute to enhancing decision-making processes, optimizing resource distribution, and improving supply chain management (scm) strategies in manufacturing enterprises.