罩式退火温度对高强IF钢组织及性能的影响

为研究不同退火温度下高强IF钢的组织性能及织构的变化规律,采用温箱式电阻炉加热模拟罩式退火工艺,研究了不同退火温度下高强IF钢210P1冷轧板力学性能;对不同退火温度钢板的r90进行了统计并对其进行显微组织观察;采用X射线衍射仪及热场发射扫描电镜对不同退火温度的罩式退火成品板进行了织构分析。结果表明,在高强IF钢210P1冷轧板的罩式退火过程中,提高退火温度将使晶粒明显长大。随着退火温度的升高,屈服强度及抗拉强度下降,伸长率升高,n值略有上升,板材横向r值增加较明显,有利织构{111}取向密度增加,不利织构{100}取向密度降低。     

复合氧漂活化体系在棉针织物冷轧堆中的应用

针对传统棉织物冷轧堆漂白法耗时长和耗碱高等问题,研究复合氧漂活化体系在棉针织布冷轧堆漂白中的应用。通过单因素试验法和正交试验法探讨各漂白因素对棉织物白度和断裂强力的影响。结果表明:在室温30℃,复合氧漂剂质量浓度4 g/L,H 2O 2质量浓度32.5 g/L,NaOH质量浓度5 g/L,堆置时间7 h时,该棉氧漂活化体系可获得与常规冷轧堆氧漂工艺相当的织物白度,并明显减少织物强力损伤,提高前处理效率,为实践生产提供参考。     

考虑设备劣化及返工的质量批量模型研究

为了得到最大质量批量，研究了返工成本边际效应下的期望利润值计算方法，将生产过程分为两个阶段：无需返工和需要返工的连续加工。给出了质量控制策略下批量计算公式以及考虑边际成本下的最大利润所对应的质量批量。采用蒙特卡洛仿真和Design Expert 8.0.6软件拟合，通过数字实验，对比了返工成本与未考虑返工成本情况下的期望利润值。研究显示，考虑返工成本边际效应下的质量批量大于一般的经济批量，所得到期望利润也最大。     

反应釜夹套多介质智能切换控制系统设计

为了解决反应釜夹套内多种介质切换时易因操作失误引起介质混乱的问题,提出了反应釜夹套多介质智能切换控制方案。在生产过程中进行升/降温操作时,程序通过介质标识位自动识别夹套内的当前介质,并通过压空操作时间标准判断夹套压空终点,可以自动完成介质压空及切换等操作。实际应用表明:该方案提高了夹套介质切换的可靠性。     

跨境电商保税仓库拣货策略研究

针对跨境电商客户订单的多品类且数量不稳定的特点，对跨境电商保税仓库拣货流程进行分析与优化。采用订单动态时间窗分拣策略，并在仓库拣货路径优化的基础上，建立了跨境电商保税仓库拣货模型。最后应用于某公司跨境电商保税仓库管理系统中，取得了较好的预期效果。     

Decomposition of first-order hybrid Petri nets for hierarchical control of manufacturing systems

Although hybrid Petri net (HPN) is a popular formalism in modelling hybrid production systems, the HPN model of large scale systems gets substantially complicated for analysis and control due to large dimensionality of such systems. To overcome this problem, a typical approach is to decompose the net into subnets and then control the plant through hierarchical or decentralized structures. Although this concept has been widely discussed in the literature for discrete PNs, there is a lack of research for HPNs. In this paper, a new method of decomposition of first-order hybrid Petri nets (FOHPNs) is proposed first and then the hierarchical control of the subnets through a coordinator is introduced. The advantage of using the proposed approach is validated by an existing example. A sugar milling case study is analysed by using a decomposed FOHPN model and the optimization results are compared against the results of the approaches presented in other papers. Simulation results show not only an improvement in production rate, but also show the ability to control the plant online. In addition, by using the hierarchical control structure for an FOHPN model, it is possible to reduce the cost of communication links, improve the reliability of the system, maintain the plant locally, and partially redesign the system.     

Development and monitoring of an integrated bioprocess for production of a potential malaria vaccine with Pichia pastoris

An engineered variant of the yeast Pichia pastoris was used to produce the potential malaria vaccine D1M1. This paper describes the implementation of an expanded bed adsorption chromatography step into a sequential cultivation process of the yeast in order to link protein expression, cell release, and product capture of the secreted protein in a fully automated plant. The process is operated with a semi-continuous strategy for an integrated production. Process improvements have been achieved using design of experiments. Resulting purities of product achieved up to 87% with recoveries of 51% in a single downstream operation. Furthermore, a multivariate analysis of historical batch data was used to develop a golden batch model for process monitoring.     

Optimal cost design of flow lines with reconfigurable machines for batch production

Modular reconfigurable machines offer the possibility to efficiently produce a family of different parts. This paper formalises a cost optimisation problem for flow lines equipped with reconfigurable machines which carry turrets, machining modules and single spindles. The proposed models take into account constraints related to: (i) design of machining modules, turrets, and machines, (ii) part locations, and (iii) precedence relations among operations. The goal is to minimise equipment cost while reaching a given output and satisfying all the constraints. A mixed integer programming model is developed for the considered optimisation problem. The approach is validated through an industrial case study and extensive numerical experiments.     

Multiphase batch process monitoring based on higher-order cumulant analysis

In this paper, a two-step phase partitioning strategy is proposed. Firstly, the number of phases is automatically determined according to the intra-class and inter-class similarity of feature space data, thus avoiding excessive manual intervention. Secondly, the phases are partitioned by step-wise adding the kernel entropy extended load matrix (KEELM), avoiding the wrong division of phases caused by unstable state of working condition conversion. A process monitoring model based on multiway kernel entropy independent component analysis (MKEICA) is constructed in each sub-phase to deal with complex batch processes with nonlinear and non-Gaussian properties. A new statistics index based on the idea of high order cumulant analysis (HCA) is constructed in each sub-phase for process monitoring. Compared with the traditional second-order statistics, it can obtain high-order statistical information. Finally, the proposed method is applied to the penicillin simulation platform process and compared with the traditional multiway kernel independent components analysis (MKICA) and HCA methods to verify the effectiveness of the method that is mentioned above.