Artificial Intelligence for an Energy and Resource Efficient Manufacturing Chain Design and Operation
Artificial Intelligence for an Energy and Resource Efficient Manufacturing Chain Design and Operation
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人工智能实现能源和资源高效的制造链设计和运营
DOI：
10.1016/j.procir.2015.06.026
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发表时间：
2015
期刊：
影响因子：
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通讯作者：
Brinksmeier E.
中科院分区：
文献类型：
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作者：
Rentsch R;Heinzel C;Brinksmeier E.
消费和投资产品的能源和资源高效制造正成为一种竞争优势，企业对最佳制造链设计和流程操作越来越感兴趣。基于离散事件建模方法，将加热、热轧、锻造和车削的经验参数化过程模型组合为两个可选的副轴制造链。离散事件还考虑特定的NC代码（例如车削），并允许时间依赖的消耗轮廓计算。在所谓的系统实体结构中进一步定义和构造制造链及其所有过程的所有参数，为人工智能工具的数值优化提供了基础。采用遗传算法和适应度函数相结合的方法，有效地找到了制造轴时能耗和资源消耗最低的制造链设计和工艺参数集。
The energy and resource efficient manufacture of consumption and investment products is becoming a competitive advantage and companies are increasingly interested in optimal manufacturing chain design and process operation. Based on the discrete events modeling approach empirically parameterized process models for heating, hot-rolling, forging and turning are combined to two alternative manufacturing chains for the manufacture of countershafts. The discrete events also consider specific NC codes (e.g. for turning) and allow for time-depended consumption profile calculations. Further defining and structuring all parameters of the manufacturing chains with all their processes in so-called system entity structures provides the basis for a numerical optimization by artificial intelligence tools. A genetic algorithm in combination with a fitness function has been employed to find the manufacturing chain design and process parameter set with the lowest energy and resource consumption for the manufacture of the shafts in an effective way.
使用系统实体结构的基于模型的资源高效流程链规划
DOI：
10.1007/978-3-642-24491-9_36
发表时间：
2013
期刊：
影响因子：
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作者：
Larek R;Brinksmeier E;Pawletta T;Hagendorf O.
通讯作者：
Hagendorf O.
影响因子：
4.1
作者：
M. Helu;B. Behmann;H. Meier;D. Dornfeld;G. Lanza;V. Schulze
通讯作者：
V. Schulze
生产工程的未来趋势
DOI：
10.1007/978-3-642-24491-9
发表时间：
2013
期刊：
Procedia CIRP
影响因子：
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作者：
G. Schuh;R. Neugebauer;E. Uhlmann
通讯作者：
E. Uhlmann