摘要
国内煤机行业市场竞争需求和供给侧改革要求我国煤机制造企业积极开展质量提升行动。质量提升方案需要科学实用的质量投入产出预测模型辅助决策。非等间隔序列GM(1,1)模型可以适用煤机质量成本数据少、信息贫乏、非等间隔的特点,与指数模型相比,对质量成本随质量水平的变动趋势拟合度好,预测精度高,可以降低预测偏差,提高质量提升方案质量;与传统GM(1,1)模型相比,数据要求更低,具有更强的实用性,为企业质量提升提供了更加准确实用的决策工具。
The market competition demand and supply side reform of the domestic coal machine industry required that the coal machine manufacturing enterprises need to actively carry out the quality promotion action.Quality promotion programs required scientific and practical quality input-output prediction model to assist decision-making.The non-equidistant GM（1,1）model can be applied to with the characteristics of low coal machines quality cost data,poor information and non-equal intervals.Compared with the exponential model,the quality cost was fitted with the change trend of quality level and had high prediction accuracy,which can reduce the prediction error and improve the solution quality.Compared with the traditional GM（1,1）model,the data requirements were lower and more practical,which provided more accurate and practical solution for enterprise quality improvement decision-making tools.
作者
安景文
吴竹南
王刚
An Jingwen, Wu Zhunan, Wang Gang(School of Management, China University of Mining and Technology, Beijing, Haidian, Beijing 100083, Chin)
出处
《中国煤炭》
2018年第5期19-23,共5页
China Coal
关键词
煤机制造企业
质量成本
灰色系统理论
coal machine manufacturing enterprise, quality cost, grey system theory
