《【精编】电池生产计划的制定概述》由会员分享，可在线阅读，更多相关《【精编】电池生产计划的制定概述（46页珍藏版）》请在金锄头文库上搜索。
1、武汉理工生产计划课程设计飞轮电池生产计划的制定 市场需求预测-4 实际产品的生产工艺路线分析-10 生产方式的经济分析和比较-11 制定综合生产计划-13 生产能力的粗平衡-14 制定主生产计划-14 制定MRP,CRP-14 生产能力的精平衡-39 零件工序卡编制-39 产品装配工序卡编制-411.市场需求预测（Market forecast）实验数据month1month2month3month4month5month6month7month8month9month10month11month12year91824211020272311222926quarter？根据给出的数据，选择一种
2、模型来预测下一年的市场需求量，属于长期预。从给出的数据分析可以得出，每年的同一月份市场需求量比较接近，而同一年份的不同月份之间存在较大的差异，市场需求量与时间季节因素有关。方案一：Seasonalized Time Seiries Regression的模型来进行市场预测。预测结果如下： Sales CONFIDENCE INTERVAL ( 90%) * SEASONALIZED TIME SERIES REGRESSION FORECASTING *-PROBLEM NAME: Untitled- FORECAST Sales - ABSOLUTE YEAR MONTHACTUAL REG
3、RESSION SEASONALIZED ERROR 1 1 9.000 17.533 8.766 0.234 1 2 18.000 17.982 17.982 0.018 1 3 24.000 18.430 24.573 0.573 1 4 21.000 18.879 22.025 1.025 1 5 10.000 19.327 9.664 0.336 1 6 20.000 19.776 19.776 0.224 1 7 27.000 20.224 26.966 0.034 1 8 23.000 20.673 24.118 1.118 1 9 11.000 21.121 10.561 0.4
4、39 1 10 22.000 21.570 21.570 0.430 1 11 29.000 22.018 29.358 0.358 1 12 26.000 22.467 26.212 0.212- Sales CONFIDENCE INTERVAL ( 90%) YEAR MONTH FORECAST LOWER BOUND UPPER BOUND 2 1 11.458 10.910 12.006 2 2 23.364 22.268 24.460 2 3 31.750 30.289 33.212 2 4 28.305 27.026 29.584REGRESSION EQUATION: Y =
5、 a + bX WHERE: Y = Sales X = TIME PERIOD a = 17.0844 b = 0.4486FORECAST = Y * SEASONAL INDEX (i)R = 0.942R-SQUARE = 0.8872MEAN ABSOLUTE DEVIATION (MAD) FOR THE LAST 3 PERIODS = 0.333MEAN SQUARED ERROR (MSE) FOR ALL PAST PERIODS = 0.283MEAN ERROR (bias) FOR ALL PAST PERIODS = -0.131STANDARD ERROR (si
6、gmasubyx) IS = 0.605SEASONAL INDEX (1) = 0.500SEASONAL INDEX (2) = 1.000SEASONAL INDEX (3) = 1.333SEASONAL INDEX (4) = 1.167由决定系数R=0.942和相关系数R2=0.8872，预测结果准确性很高。预测的误差在合理的范围内，预测结果如下：month1month2month3month4year212243228方案二：TIME SERIES REGRESSION 模型进行预测预测结果如下： Sales CONFIDENCE INTERVAL ( 90%)* TIME SE
7、RIES REGRESSION FORECASTING *-PROBLEM NAME: Untitled- Sales Sales ABSOLUTE PERIOD ACTUAL FORECAST ERROR 1 9.000 14.846 5.846 2 18.000 15.783 2.217 3 24.000 16.720 7.280 4 21.000 17.657 3.343 5 10.000 18.594 8.594 6 20.000 19.531 0.469 7 27.000 20.469 6.531 8 23.000 21.406 1.594 9 11.000 22.343 11.34
8、3 10 22.000 23.280 1.280 11 29.000 24.217 4.783 12 26.000 25.154 0.846- Sales CONFIDENCE INTERVAL ( 90%) PERIOD FORECAST LOWER BOUND UPPER BOUND 13 26.091 14.974 37.208 14 27.028 15.911 38.145 15 27.965 16.848 39.082 16 28.902 17.785 40.019REGRESSION EQUATION: Y = a + bX WHERE: Y = Sales X = TIME PERIOD a = 13.9091 b = 0.9371R = 0.500R-SQUARE = 0.2501MEAN ABSOLUTE DEVIATION (MAD) FOR THE LAST 3 P
