用户名: 密码: 验证码:
中药制药过程控制及集成化生产若干关键问题研究
详细信息    本馆镜像全文|  推荐本文 |  |   获取CNKI官网全文
摘要
中药制药工业化生产一般分为中药前处理、中药浸膏生产、中药制剂与包装三个阶段,其中中药浸膏生产阶段包含提取、浓缩、干燥等工段,是中药工业化生产的核心过程。随着新工艺新方法的不断出现,以及GMP规范在中药制药过程生产管理中的实施,传统的控制方法和中药制药企业落后的基础自动化网络已不能满足中药制药工业发展的需求。
     本文以中药浸膏生产过程为主要研究对象,在深入分析生产工艺及控制需求的基础上,针对当前生产管理中存在的一系列问题,系统研究了中药浓缩浓度软测量、中药温浸动态提取温度控制、中药制药过程控制系统的设计与构建、中药制药信息化集成技术和中药制药CIPS等一系列理论与应用问题。论文的主要工作归纳如下:
     (1)针对中药浓缩过程中药液浓度难以在线测量的问题,提出了基于支持向量回归的浓度软测量方法。该方法利用支持向量机适用于小样本学习,具有学习速度快、全局最优和泛化性好的优点,采用基于数据驱动建模的思想,充分利用中药浓缩工段历史数据,选取六个辅助变量,用支持向量回归的方法建立软测量模型,并利用过程数据进行参数寻优和校验。利用优化后的模型对中药浓缩过程浓度进行了预测,验证了模型的学习性能和泛化性能。结果表明本文建立的软测量模型实现了对中药浓度较为精确的预测,有效解决了中药浓缩过程中难以实现的中药浓度在线测量问题,具有较高的实用价值。
     (2)针对中药温浸动态提取工段温度的精确控制问题,本文以某制药厂中药提取系统为研究对象,分析了中药提取工段的工艺设备和传热过程,建立了简化模型。针对提取工段温度控制非线性、时变性、纯滞后的特点,设计了自适应模糊PID控制器,并进行了仿真研究。仿真结果表明采用参数自整定模糊PID控制,系统调节时间短,响应速度快、温度控制精度高、具有较好的鲁棒性。
     (3)对中药提取、浓缩、干燥等工段的自动化需求和测控要点进行了分析,研究了中药制药设备集成方案。设计了基于Profibus-DP的现场总线控制网络,介绍了控制系统的硬件配置、系统组态、软件体系。利用Profibus和工业以太网的结合,实现对中药制药各工段的集中监控、分散控制,为实现更进一步的MES和ERP应用构建了平台。
     (4)对中药制药信息集成化技术进行了研究,在分析了中药制药企业业务流程和信息特征的基础上,提出了中药制药信息集成方案。运用OPC技术和XML设备描述方法,采用OPC DA和OPC XML-DA两种标准进行系统集成。在此基础上,建立完善可靠的生产过程实时数据库系统和管理生产过程的关系数据库,通过基于WebServices的制药企业集成化平台实现企业的分布式和远程管理控制。本文对实现信息集成的关键化技术进行了详细论述。
     (5)为实现中药制药全过程的优化控制,提出了中药制药过程集成过程控制系统(CIPS)的总体设计思想与设计原则,分析了各部分模块的功能,论述了关键技术。对MES和ERP系统的实施和功能模块进行了详细论述。
     目前中药制药先进过程控制和集成化生产技术的研究刚刚起步,由于中药制药装备的标准化和中药质量控制体系还不完善,为在中药企业实施集成化过程控制系统带来了巨大困难。本文对在现阶段装备水平和技术水平下的中药制药企业过程控制和集成化生产技术的若干问题进行了研究,取得了一定成果,具有广阔的应用前景。自动化和信息化是实现我国中药制药现代化的必游之路,随着中药制药装备标准化和中药质量控制体系的逐步完善,本文的一些思想和方法对在更高基础和标准上实施中药制药集成化生产技术也具有一定的参考价值。
Industrialized production of Chinese pharmaceutical manufacturing is generally divided into Chinese medicine pretreatment, extracting, preparation and packaging three stages, and the stage of Chinese medicine extracting is the core process of the medicine industrialized production, which includes extraction, concentration, drying, etc. With the new craft new method continue to emerge and the implementation of GMP standard in production management of Chinese pharmaceutical manufacturing, conventional control method and the backward basic automation net in the enterprises have not meet the demand of the Chinese medicine industry's development.
     On the basis of deep analysis in extracting craft and control need, the paper mainly did research on the production process of extracting. For a range of problems in current production, these were systematically investigated, that include Chinese medicine concentration soft-sensor, temperature control of Chinese medicine warm immersion dynamic extraction, design and construction of control system in Chinese pharmaceutical manufacturing process, information integrated technique of Chinese pharmaceutical manufacturing, CIPS of Chinese pharmaceutical manufacturing and a series of theoretical and applied problems. All the main work of the paper is sum-up as follows:
     (1) For the problem of on line measuring Chinese medicine consistency was difficult in the process of concentration, the method of consistency soft-sensor based on Support Vector Regression was presented. The method has the advantage of fast learning speed, global optimum and well generalization performance, because Support Vector Regression has the ability of small sample learning. Applying the idea of data-driven modeling and making full use of Chinese medicine concentration's historical data, six auxiliary variables were selected. A soft-sensor model was established by Support Vector Regression, and the parameters were optimized and checked making use of the process-data. It made prediction on consistency during Chinese medicine concentration by using the optimized model, and the model's ability of learning and generalization were verified. The results show that the soft-sensor model could not only achieve the accurate prediction of Chinese medicine consistency, but also effectively resolve the problem of on line measuring Chinese medicine consistency in the process of concentration. Therefore, it has practical value.
     (2) Aimed at temperature accurate control of Chinese medicine warm immersion dynamic extraction, the paper focused on Chinese medicine extraction system in a pharmaceutical enterprise. Processing facilities and heat-transfer process of Chinese medicine extraction were analyzed, and the simplified model was established. Adapting to the characteristics of nonlinearity, time-varying and pure time-delay in temperature control in Chinese medicine extraction, a fuzzy self-tuning PID control system was designed and simulations were performed. The simulation results indicate that the system put up synthetic performance, such as less modulation time, quicker responses, high temperature control accuracy and good robustness stability.
     (3) The paper analyzed the automation requirement and measurement &control points in extraction, concentration, and drying, and researched Chinese pharmaceutical manufacturing's equipment integration. A monitoring control network was designed based on PROFIBUS-DP, and its hardware, system configuration, software system were introduced. Making use of the union of PROFIBUS and industrial Ethernet, the centralized monitor and decentralize control, which in every section of Chinese pharmaceutical manufacturing process, were realized, and the platform was built, which for widely applications in MES and ERP.
     (4) Based on the analysis of business process and information characteristics of pharmaceutical enterprise, the paper studied information integration technology of Chinese pharmaceutical manufacturing, and information integration plan of Chinese pharmaceutical manufacturing was presented. Using OPC technology and XML device description method, two standards of OPC DA and OPC XML-DA were employed for system integration. On this basis, these were established that include complete and reliable real-time database in the production process and relation database in the management process. Distributed control and remote administration control of the enterprises were achieved, through the integration platform of pharmaceutical enterprise that based on Web Services. The key technologies of realizing information integration were discussed in detail.
     (5) The main design and principle of the process of Chinese pharmaceutical manufacturing's computer integrated process system (CIPS) were presented, so as to achieve the optimum control in the whole process of Chinese pharmaceutical manufacturing. It analyzed the function of each part of the module, and discussed the key technologies. The implementation of MES and ERP system and functional module were discussed in detail, and the solution was proposed which satisfied advanced control and real-time optimization.
     At present, advanced process control and integrated manufacturing technology of Chinese pharmaceutical manufacturing research has just started. Because the standard of Chinese pharmaceutical manufacturing equipment and Chinese medicine quality control system were not be still perfect, that had brought enormous difficulties to the implement of integrated process control in pharmaceutical enterprises. The paper researched several problems existing in process control and integrated technology in pharmaceutical enterprise, under equipment and technology level at this stage, and the research got some achievements, moreover, it has a broad application prospect. Automation and information is the only way that realizes Chinese medicine modernization. With equipment standard of Chinese pharmaceutical manufacturing and quality control system of Chinese medicine gradually improving, some ideas and methods in the paper have some referenced value of the implement of integrated technology of Chinese pharmaceutical manufacturing based on higher basis and standard.
引文
[1]元英进,刘明言,董岸杰.中药现代化生产关键技术.化学工业出版社,2001.
    [2]王玉华,袁久荣.中药质量与质量控制方法概述.中成药.2003,25(3):234-236.
    [3]科技部,卫生部,等.中药现代化发展纲要(2002-2010).2002.10.
    [4]瞿海斌,程翼宇,等.论加速建立现代化中药制造工业的若干制药工程技术问题.中国中药杂志.2003,28(10):904-906.
    [5]汤继亮.我国中药自动化工程项目在规划、设计和实施中的有关问题.中国医药工业杂志.2008,39(4):308-312.
    [6]曹光明,俞子行.论中药工业中的中试放大验证.世界科学技术.2002,4(6):19-23.
    [7]邓修.中药制药工程与技术.华东理工大学出版社,2008.
    [8]汪涛,孙亮,等.中药超微粉碎的研究进展与应用前景.中国粉体技术.2008,14(4):31-36.
    [9]李焕杰.中药提取分离技术的进展.中国药房.2007,18(1):1429-1432.
    [10]肖观秀,吕惠生,张敏华.超临界萃取生物碱研究进展.中草药.2004,35(12):1421-1423.
    [11]邬方宁.超声提取技术在现代中药中的应用.中草药.2007,38(2):315-316.
    [12]陈勇,李页瑞,等.中药醇沉工艺及装备研究进展与思考.世界科学技术.2007,9(5):16-19.
    [13]邱志芳,陈勇,等.中药浸膏干燥技术研究进展.世界科学技术.2008,10(2):122-126.
    [14]范骁辉,叶正良,程翼宇.基于信息融合的中药多元色谱指纹图谱相似性计算方法.高等学校化学学报.2006,27(1):26-29.
    [15]胡楚楚,李云飞,程翼宇.一种基于指纹图谱分析技术的中药生产工艺稳定性评价方法.中国中药杂志.2006,31(14):1151-1154.
    [16]翟海斌,欧丹林,程翼宇.中药提取物质量控制的一种新方法探讨.中国药学杂志.2006,41(1):57-60.
    [17]张立国,朱静,倪力军.中药提取和浓缩过程的理论模型及控制策略.天津大学学报.2007,40(12):1490-1494.
    [18]曹光明.中药制药工程学.化学工业出版社,2004.
    [19]龙丽姮,罗安,等.基于SQP的中药双效浓缩过程优化.化工自动化及仪表.2006,33(6):19-22.
    [20]黄挚雄,罗安,黎群辉.迭代学习控制算法在中药生产过程提取工段的应用.仪器仪表学报.2007,28(8):1434-1439.
    [21]黄挚雄.中药生产过程优化控制策略的研究.中南大学博士学位论文,2006.
    [22]韦文祥,沈洪远,罗安.神经元网络软测量模型在中药浓缩工段的应用.化工自动化及仪表.2007,34(5):57-61.
    [23]汤继亮.中药提取过程计算机控制系统的设计与应用应用.医药工业设计杂志.2002,23(6):39-44.
    [24]George Cheng, Johnny Wang, Steve Smialkowski. Model-free Adaptive Control of Evaporators. Vancouver:IEEE "Dynamic Modeling Control Applications for Industry" Conference, April 30 to Mayl,1998.
    [25]Raja Kumar More, Vijaya Kumar Bulasara, etc. Optimization of crude distillation system using aspen plus:Effect of binary feed selection on grass-root design. Chemical Engineering Research and Designm.2010,88(2):121-134.
    [26]Mehrdokht B. Nikoo, Nader Mahinpey. Simulation of biomass gasification in fluidized bed reactor using ASPEN Plus. Biomass and Bioenergy.2008,32(12): 1245-134.
    [27]俞秀丽,田耀华.对制药设备CIP与SIP相关问题的讨论.2008,17(4):36-39.
    [28]田耀华.浅析制药装备的若干问题.2007,29(2):14-20.
    [29]李晓光.混合建模方法研究及其在化工过程中的应用.北京化工大学博士学位论文,2008.
    [30]韩曾晋.自适应控制.清华大学出版社,1995.
    [31]慕春棣,梅生伟,申铁龙.非线性系统鲁棒控制理论的一些进展.控制理论与应用.2001,18(1):1-6.
    [32]Richalet J. Model Predictive Heuristic Control:Application to Industrial Process. Automatica,1978,17(5):413-428.
    [33]席裕庚.预测控制.国防工业出版社,1993.
    [34]Mahmoodi. Sanaz, Poshtan.Javed., etc. Nonlinear model predictive control of a PH neutralization process based on Wiener-Laguerre model. Chemical Engineering Journal.2009,146(3):328-337.
    [35]Yang Jianfeng, Zhao Jun., etc. Adaptive nonlinear model predictive control for a class of multivariable chemical process. Journal of Chemical Industry and Engineering (China).2008,59 (4):934-940.
    [36]Lee. JungHeon, Lim.Henry C., Hong Juan. Application of nonsingular transformation to on-line optimal control of poly-β-hydroxybutyrate fermentation. Journal of Biotechnology.1997,55 (3):135-150.
    [36]Lee. JungHeon, Lim.Henry C., Hong Juan. Application of nonsingular transformation to on-line optimal control of poly-β-hydroxybutyrate fermentation. Journal of
    Biotechnology.1997,55(3):135-150.
    [37]Upreti. Simant R.,Sundaram.Baranitharan S., Lohi.Ali. Optimal control determination of MMA polymerization in non-isothermal batch reactor using bifunctional initiator. European Polymer Journal.2005,41 (12):2893-2908.
    [38]孙增圻.智能控制理论与技术.清华大学出版社,2003.
    [39]蔡自兴.智能控制.电子工业出版社,2004.
    [40]E.H. Mamdani. Applications of fuzzy algorithms for control of simple dynamic plant. Proc.IEEE.1974,121:1585-1588.
    [41]Hong Che-Wun. Fuzzy control strategy design for an autopilot on automobile chassis dynamometer test stands. Mechatronics.1996,6(5):537-555.
    [42]Hanakuma Y, Irizuki Y, etc. Design of a selftuning fuzzy control system and the application to a distillation column. International chemical engineering.1994,34(1): 91-96.
    [43]Brosilow C B, Joseph B. Inferential Control of Process. AIChE J,1978,24(3):485-509.
    [44]孙优贤,褚健.工业过程控制技术(方法篇).化学工业出版社,2005.
    [45]McAvoy T.J.. Contemplative stance for chemical process control-an IFAC report, Automatica,1992,28(2):441-442.
    [46]M.T.Musavi, C.Domnisoru,etc. A neuro-fuzzy system for prediction of pulp digester k-number. IEEE,1999:4253-4258
    [47]Helena,Cristina,etc. Neural Network and Hybrid Model:A Discussion about Different Modeling Techniques to Predict Pulping Degree with Industrial Date. Chemical Engineering Science,2001,56:565-569
    [48]颜学峰.基于径基函数—加权偏最小二乘回归的干点软测量.自动化学报.2007,33(2):193-196.
    [49]Persson.Ulf, Ledung Lars, etc. On-line optimization of pulp & paper production. TAPPI Fall Technical Conference:Engineering, Pulping and PCE and I, October 26 to October30,2003.
    [50]Kaushik Basak, K.S.Abhilash, etc. On-line optimization of a crude distillation unit with constraints on product properities. Industrial and Engineering Chemistry Research,2002,41(6):1557-1568.
    [51]Chen, Z., C.Xu. Batch processes optimization and advanced control-a survey. Control and Instruments in Chemical Industry,2003,30(3):1-6.
    [52]陈治纲,许超,邵惠鹤.间歇过程优化与先进控制综述.化工自动化及仪表.2003,30(3):1-6.
    [53]Xiong Z, Zhang J. Product quality trajectory tracking in batch processes using iterative learning conrrol based on time-varying perturbation models. Industrial & Engineering Chemistry Research,2003,42(26):6802-6814
    [54]Flores-Cerrillo J, MacGregor J F. Within-batch and batch-to-batch inferential-adaptive control of semibatch reactor:A partial least squares approach. Industrial & Engineering Chemistry Research,2003,42(14):3334-3335
    [55]Bruce M R. Back to the future:MES from 1999-2000. Boston, Mass., USA:AMR Inc.,1995.
    [56]Williams T J. The Purdue enterprise reference architecture. Computers in Industry, 1994,22(2/3):141-158.
    [57]柴天佑,金以慧,等.基于三层结构的流程工业现代集成制造系统.控制工程.2002,9(3):1-6.
    [58]Vernadat F B. Enterprise modeling and integration(EMI):current status and research perspectives. Annual Reviews in Control,2002,26(1):15-25.
    [59]阳宪惠.现场总线技术与应用.清华大学出版社,1999.
    [60]缪学勤.工业通信网络技术最新进展.可编程控制器与工厂自动化.2008,12:36-42.
    [61]华镕.两种新技术把现场总线推向新时代.中国仪器仪表.2008,12:30-33.
    [62]包伟华,张浩,许大庆.现场总线设备描述技术的研究.华东电力.2006,34(6):454-458.
    [63]Hubschle.Klaus, Making FDT development more efficient. IEE Computing and Control Engineering,2004,15(3):44-46.
    [64]Mahnke.W. OPC unified architecture:The future standard for communication and information modeling in automation. ABB Review,2009,ABB Rev(3):56-61.
    [65]Shieipen.M. OPC UA supporting the automated engineer of production monitoring and control systems. Proceedings of the 13th IEEE International Conference on Emerging Technologies and Factory Automation,2008:640-647.
    [66]李海青,黄志尧.软测量技术原理及应用.化学工业出版社,2000.
    [67]王珏,周志华,周傲英.机器学习及其应用.清华大学出版社,2008.
    [68]Wang X, Luo R, Shao H.Designing a Soft Sensor for Distillation Column with the Fuzzy Distributed Radial Basis Function Neural Networks. Proceedings of the 35th IEEE Conference on Decision and Control,1996,2:1714-1719.
    [69]Devogelaere D., Rifckaert M.,Leon O.G. Application of feedforward neural networks for soft sensors in the sugar industry. IEEE Proceedings of the Ⅶ Brazilian Symposium on Neural Networks(SBRN'02),11-14 Nov.2002:2-6.
    [70]Vapnik V N. The Nature of Statistical Learning Theory. New York:Springer-Verlag,
    [71]常玉清,王福利,等.基于支持向量机的软测量方法及其在生化过程中的应用.仪器仪表学报,2006,27(3):241-244.
    [72]T.Mitchell. Machine Learning. McGraw-Hill,1997.
    [73]王华忠,俞金寿.统计学习理论与支持向量机在过程控制中的应用.化工自动化及仪表.2004,31(5):1-6.
    [74]Vapnik V. N., Levin E, Le Cun Y. Measuring the VC-dimension of a learning machine. Neural Computation,1994,6:851-876.
    [75]Cortes C, Vapnik V. Support-vector net works. Machine Learning,1995,20:273-297
    [76]Burges C J C. A Tutorial on Support Vector Machines for Pattern Recognition. Data Mining and Knowledge Discovery,1998,2(2):121-167.
    [77]Cristianini N, Shawe Taylor J. An Introduction to Support Vector Machine. Cambridge University Press,2000.
    [78]Suykens J A K. Nonlinear Modeling and Support Vector Machine. IEEE Instrumentation and Measurement Technology Conference Budapest. Hungary, 2001.21-23.
    [79]O.L. Mangasarian. Generalized support vector machines. Technical Report Mathematical
    [80]张学工.关于统计学习理论与支持向量机.自动化学报,2000,26(1):32-42
    [81]Nello Cristianini, John Shawe-Taylor,李国正,王猛,曾华军译.支持向量机导论.电子工业出版社,2004.
    [82]邓乃扬,田英杰.数据挖掘中的新方法—支持向量机.科学出版社,2004.
    [83]Steve R Gunn. Support Vector Machines for Classification and Regression. University of Southampton,1998
    [84]Smola A, Scholkopf B. A tutorial on support vector regression. Technical Report NC2-TR-1998-030. London:Royal Holloway, University of London,1998.2-58.
    [85]刘明言,余根.中药提取液浓缩新工艺和新技术进展.中国中药杂志.2006,31(3):184-187.
    [86]张素萍.中药制药工艺与设备.化学工业出版社,2005.
    [87]Chih-Jen Lin. Formulations of Support Vector Machines:A Note from an Optimization Point of View. Neural Computation,2001,13(2):307-317.
    [88]陈建龙,王焕魁.中药提取过程中亟待解决的工程技术问题.中药研究与信息.2002,4(9):14-16.
    [89]刘晓堂,史泳,等.中药提取工艺研究进展.中国医学研究与临床.2006,4(5):48-51.
    [90]陶永华.新型PID控制及应用.机械工业出版社,2002.
    [91]刘金琨.先进PID控制Matlab仿真.电子工业出版社,2004.
    [92]诸静.模糊控制原理与应用.机械工业出版社,2005.
    [93]吴晓莉,林哲辉.MATLAB辅助模糊系统设计.西安电子科技大学出版社,2002.
    [94]姜文佳,姜永健,等.模糊PID控制算法改进及其在温控系统中的应用.控制工程.2006,13(4):338-340.
    [95]Wu ZQ, Mizumoto M. PID type fuzzy controller and parameters adaptive method. Fuzzy Sets and Systems,1996,78(1):23-26.
    [96]Zhi-Wei Woo, Huang-Yuan Chung,Jin-Jye Lin. A PID type fuzzy controller with self-tuning scaling factors. Fuzzy sets and systems,2000,115(2000):321-326.
    [97]Huang Y, Yasunobu S. A general practical design method for fuzzy PID control from conventional PID control. San Antonio, Texas:The Ninth IEEE International Conference,2000.2:699-972
    [98]李敏远,都延丽.智能自整定PID在药剂温度控制系统中的应用.控制理论与应用.2003,20(5):805-810.
    [99]Ziegler J G, Nichorls N B. Optimum setting for automatic controller. ASME Transactions,1942,64:759-768.
    [100]白羽.中药提取生产过程的自动化控制.自动化与仪表.2007,3:69-72.
    [101]卢佩,詹金良.中药提取过程控制系统的设计与应用.微计算机信息.2007,23(5-1):69-71.
    [102]许小球.中药提取生产过程与自动化控制.中国制药装备.2009,11(11):414-416.
    [103]石建平,刘庆阁,魏静薇.全自动双效浓缩器控制技术.热能动力工程.2003,18(5):69-72.
    [104]徐扬.中药生产浓缩工段控制系统的研制.中南大学硕士学位论文,2006.
    [105]刘庆阁,王建忠,等.中药生产自动化.中国医药工业杂志.2003,34(8):414-416.
    [106]赵陆军,徐思康,张保献.中药水提取液常用精制方法概述.中国中医药信息杂质.2000,7(11):47-48.
    [107]刘苗,于筛成,等.中药醇沉工艺及设备解析.中成药.2007,29(8):1202-1204.
    [108]蔡业彬,曾亚森,等.喷雾干燥技术研究现状及其在中药制药中的应用.化工装备技术.2006,27(2):5-10.
    [109]刘彤军,王宽全.大型喷雾干燥塔控制策略的研究.工业控制计算机.2005,18(5):19-22.
    [110]N.A.Correa. Self-tuning control of egg drying in spouted bed using the GPC algorithm. Dying Technology,2002,20(4):820-825.
    [111]朱宏吉,张明贤.制药设备与工程设计.化学工业出版社,2004.
    [112]方晓柯,王建辉,顾树生.多总线集成方案的改进.石油化工高等学校学报.2007,20(3):54-56.
    [113]冯丽辉.DCS、FCS、CIPS的集成与应用.工业仪表与自动化装置.2002,9(3):1-6.
    [114]Profibus Specification Normative Parts of Profibus-FMS,-DP,-PA according to the European Standard EN 50 170 Volume 2. SIEMENS.1998.
    [115]Profibus International. Profibus Specification(Edition 1.0),1998.
    [116]Josef Weigmann,Gerhard Kilian,闫志强(译).西门子PROFIBUS工业通信指南.人民邮电出版社,2007.
    [117]孙鹤旭,梁涛,云利军.Profibus现场总线控制系统的设计与开发.国防工业出版社,2007.
    [118]崔坚.西门子S7可编程控制器—STEP7编程指南.机械工业出版社,2007.
    [119]西门子(中国)有限公司自动化与驱动集团.深入浅出西门子WinCC V6.北京航空航天大学出版社,2004.
    [120]高复先.信息资源规划—信息化建设基础工程.清华大学出版社,2002.
    [121]Natanya Pitts(著),徐晓梅(译).XML技术内幕.机械工业出版社,2002.
    [122]Mark Birbect(著),裴剑锋,等(译).XML高级编程.机械工业出版社,2002.
    [123]OPC Foundation. OLE for process control data access customer interface standard version 2.05A.2002.6.
    [124]OPC Foundation. OPC Data Exchange 1.00 Specification.Oct,1998.
    [125]OPC Foundation. OPC DA 3.00 Specification.Mar,2003.
    [126]OPC Foundation. OPC AE 1.00 Specification.Mar,2003.
    [127]OPC Foundation. OPC HDA1.10 Specification.Jan,2002.
    [128]OPC Foundation. OPC Security 1.00 Specification.Oct,2000.
    [129]OPC Foundation. OPC Batch 2.00 Specification.July,2001.
    [130]OPC Foundation. OPC XML-DA 1.01 Specification.Oct,2004.
    [131]陈在平.现场总线及工业控制网络技术.电子工业出版社,2008.
    [132]刘卫昌,马增良.企业综合自动化系统中实时数据库系统设计.计算机应用研究.2005,8:146-149.
    [133]鲁明休,罗安.化工过程控制系统.化学工业出版社,2006.
    [134]高巍,赵海,徐久强.信息融合中实时数据库关键技术.科技经济市场.2007,02:15-16.
    [135]王成光.流程工业大型实时数据库理论、技术与应用.浙江大学博士学位论文,2003.
    [136]郑颖.基于MES的实时数据库系统的设计与实现.北京交通大学专业硕士学位论文,2008.
    [137]元利兴,姚鸿燕.用于CIPS的实时数据库系统.河北工业大学学报.2000,29(3):18-21.
    [138]叶建位,苏宏业.实时数据库系统关键技术及实现.计算机应用研究.2004,3(1):45-47.
    [139]钱笑宇,张彦武.工业实时数据库的研究和设计.计算机工程.2005,31(1):98-99.
    [140]Ceramie. Web Services essentials. Cal., USA:O'Reilly Media Inc.,2002.
    [141]Seely Scott, Sharkey Kent. SOAP:Cross Platform Web Services Development Using XML. Indiana:Prentice Hall PTR,2002.
    [142]龙文,吴义生,等.中药制药企业生产计划管理研究.计算机与应用化学.2005,22(8):667-670.
    [143]张桂平,郁鼎文,吴志军.基于Web的中药业ERP采购管理和营销管理研究.中国制造业信息化.2004,33(1):71-73.
    [144]刘建胜.离散型制造业MES若干关键技术及其应用研究.南昌大学博士学位论文,2008.
    [145]王志新,金寿松.制造执行系统MES及应用.中国电力出版社,2006.
    [146]孙彦广,陈靖屏.流程工业制造执行系统.化学工业出版社,2006.
    [147]Hillard M.S, Larson D.L, Rosenberg M.J. LIMS:A Suite of Database Tools for Laboratory Organization. Computer-Based Medical Systems. CBMS 2001. Proceeding.14th IEEE symposium,2001,158-162.
    [148]郭超,金晓明,荣冈.数据校正技术在流程工业企业物料平衡中的应用.2005,32(3):39-41.
    [149]高学金,王普,等.面向制药行业MES的研究.自动化博览.2005,6:61-63.
    [150]孙旨义.制药行业自动化信息技术最新应用及展望.自动化博览,2008,10:22-26.
    [151]罗鸿.ERP原理设计实施.电子工业出版社,2002.
    [152]王虎,赵敏.基于GMP中校制药企业ERP生产管理系统设计.计算机系统应用,2002,12:5-8.
    [153]张翠丽,张申生,李磊.制药行业BOM的数据库设计及算法研究.计算机工程.2006,32(1):270-272.
    [154]杨彪,李勇,等.药业企业MRP Ⅱ/ERP物料清单重构研究.昆明理工大学学报(理:工版).2005,30(2):37-40.
    [155]王琦.结合智能决策支持的ERP生产控制系统研究与实现.四川大学硕士学位论文,2005.
    [156]国家药品监督管理局.药品生产质量管理规范,1998
    [157]汤继亮.关于RFID电子标签技术在药品生产质量监控和GMP管理应用方面的一些问题.中国医药工业杂志,2006,37(12):5-8.
    [158]韩祯祥,张琦,文福拴.粗糙集理论及其应用.信息与控制,1998,27(1):37-45.

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700