680m~3浮选机工业化应用过程中的动力学性能测试与分析

680m~3浮选机投入生产试运行已一年有余,表现出卓越的设备稳定性和分选性。本文从浮选流体动力学角度出发,对680m~3浮选机在带矿运行过程中的充气性能、矿浆循环悬浮性能和气泡大小及其负载性能进行了测试分析。结果表明,680m~3浮选机充气量可以达到1.1m~3/(m~2·min)以上,能够满足一般硫化矿大气量的生产需求,空气分散度在7以上,平均气含率约7%;不同深度浮选槽内矿浆浓度和粒级分布较为均匀,无明显分层现象。气泡表面积通量可达39.20s-1,随着气泡的上浮,气泡负载呈现上升趋势,最高可达3.37g/L。优越的浮选流体动力学特性充分地保障了680m3浮选机良好的分选效果。     

Design of delayed reconfigurable manufacturing system based on part family grouping and machine selection

To improve the convertibility of reconfigurable manufacturing system (RMS), the concept of delayed reconfigurable manufacturing system (D-RMS) was proposed. RMS and D-RMS are both constructed around part family. However, D-RMS may suffer from ultra-long system problem with unacceptable idle machines using generic RMS part families. Besides, considering the complex basic system structure of D-RMS, machine selection of D-RMS should be addressed, including dedicated machine, flexible machine, and reconfigurable machine. Therefore, a system design method for D-RMS based on part family grouping and machine selection is proposed. Firstly, a part family grouping method is proposed for D-RMS that groups the parts with more former common operations into the same part family. The concept of longest relative position common operation subsequence (LPCS) is proposed. The similarity coefficient among the parts is calculated based on LPCS. The reciprocal value of the operation position of LPCS is adopted as the characteristic value. The average linkage clustering (ALC) algorithm is used to cluster the parts. Secondly, a machine selection method is proposed to complete the system design of D-RMS, including machine selection rules and the dividing point decision model. Finally, a case study is given to implement and verify the proposed system design method for D-RMS. The results show that the proposed system design method is effective, which can group parts with more former common operations into the same part family and select appropriate machine types.     

Supply chain data analytics for predicting supplier disruptions: a case study in complex asset manufacturing

Although predictive machine learning for supply chain data analytics has recently been reported as a significant area of investigation due to the rising popularity of the AI paradigm in industry, there is a distinct lack of case studies that showcase its application from a practical point of view. In this paper, we discuss the application of data analytics in predicting first tier supply chain disruptions using historical data available to an Original Equipment Manufacturer (OEM). Our methodology includes three phases: First, an exploratory phase is conducted to select and engineer potential features that can act as useful predictors of disruptions. This is followed by the development of a performance metric in alignment with the specific goals of the case study to rate successful methods. Third, an experimental design is created to systematically analyse the success rate of different algorithms, algorithmic parameters, on the selected feature space. Our results indicate that adding engineered features in the data, namely agility, outperforms other experiments leading to the final algorithm that can predict late orders with 80% accuracy. An additional contribution is the novel application of machine learning in predicting supply disruptions. Through the discussion and the development of the case study we hope to shed light on the development and application of data analytics techniques in the analysis of supply chain data. We conclude by highlighting the importance of domain knowledge for successfully engineering features.     

Enriching Context Information for Entity Linking with Web Data

Journal of Computer Science and Technology - Entity linking (EL) is the task of determining the identity of textual entity mentions given a predefined knowledge base (KB). Plenty of existing...     

烧结机卸料装置耐磨性改善

烧结机导料箱、单辊破碎机和卸料漏斗承载着烧结热矿的导料、破碎与输送,是烧结生产的重要组成部分。高温、重载的工况环境决定着机尾卸料装置必须具有抗磨损、耐高温的特性。针对邯钢1^#435m^2烧结机机尾关键部件耐磨工作面寿命短,更换不方便等问题,分析磨损机理与失效原因,提出改进抗磨工作面结构,升级耐磨材料,优化焊接工艺等措施。通过技术方案的实施,使烧结机导料箱、单辊破碎机和卸料漏斗等卸料装置维持了较高的抗磨损性能,达到了预期的改造效果。     

COB LED自动在线点胶测试补粉机的研制

在COB(Chip On Board)LED光组件制造领域,点胶、测试和补粉关键工艺基本以手工或半自动为主。为了保证COB LED产品质量一致性、提高生产效率,研制了一种COB自动在线点胶测试及补粉一体机,实现点胶、测试、补粉生产工序的自动化生产。阐述了其工艺流程及设计总体方案,提出了荧光粉量修补方法,修正初次点胶量,实现动态调节,减少人工干预。经实验验证,该一体机可以提高点胶工艺的自动化程度,具有运行速度快、可靠性好、性能稳定等特点。     

基于SVM的煤与瓦斯突出预测模型及应用

为有效预测矿井内煤与瓦斯突出的危险程度,对其影响因素做了分析与探讨,分别构建了基于粒子群优化算法以及遗传算法支持向量机的煤与瓦斯突出预测模型,并且通过实例对两种模型预测的准确性进行了验证。分别利用单项以及综合指标、BP神经网络以及PSO-SVM模型、GA-SVM模型,对寺河煤矿二号井的突出区域进行预测比较。结果表明,PSO-SVM的预测模型不仅可以在小样本数据中预测出煤与瓦斯突出程度的大小,而且综合预测结果更加精确,其在解决矿井内煤与瓦斯突出的小样本数据中显示出更加强大、通用的性能。     

全电动注塑机研究进展及在汽配电子行业中的应用

介绍了全电动注塑机的特色，综述了国内外全电动注塑机在精密注塑、智能注塑、高效注塑和绿色注塑方面的研究进展，并对全电动注塑机在汽配电子行业中的应用作了简单介绍。对双电机同步控制技术的逐渐成熟为全电动注塑机实现大型化提供了助力，全电动注塑机高效、精密、智能、节能、环保的优势在汽配电子行业显示了很好的应用前景。     

Failure analysis of a machine support for fique fibre processing

Replacement cast steel supports for a machine consisting of bars that straighten out fique fibres have presented recurrent fracture, beyond 10⁶ cycles of service and their failure surfaces show features typical of fatigue under alternating bending conditions. Differences between original supports and replacement supports related to geometry roughness, hardness, chemical composition and microstructure were identified. To obtain a longer service life selected modifications of the geometry and use of different material were proposed based on load state analysis, finite element analysis, and fatigue strength calculations.