This paper studies that $sigma$ values(10, 20, 50) and $ ho$ values(-0.6, -0.3, 0.0, 0.3, 0.6) affect the total inventory cost of a supply chain and order fill rate when the market demand process follows a general auto-correlated AR(1) process without seasonality. $sigma$ indicates the degree of demand fluctuation and $ ho$ means the trend of demand. ANOVA tests using a 5% significance level are performed in SPSS to examine significant performance changes among various cases.