Hybrid Neural Network Model for RH Vacuum Refining Process Control

A hybrid neural network model,in which RH process(theoretical)model is combined organically with neural network(NN)and case-base reasoning(CBR),was established.The CBR method was used to select the operation mode and the RH operational guide parameters for different steel grades according to the initial conditions of molten steel,and a three-layer BP neural network was adopted to deal with nonlinear factors for improving and compensating the limitations of technological model for RH process control and end-point prediction.It was verified that the hybrid neural network is effective for improving the precision and calculation efficiency of the model.

ADVANCED QUALITY CONCEPTS AND COMPOSITE RELIABILITY THROUGH STATISTICALPROCESS CONTROL

The physical properties of thermosetting resins and resin based composites may be influenced by changes in any one of the mang formulating or process related variables involved in their manufacture. When resins and composite materials are required to perform in aggressive environments, reliable and predicable performance is essential and therefore these materials must be prepared and tested in accorkance with a strictquality plan. This paper outlines the elements of statistical process control (S.P.C.)as it may be applied to non-metallic materials and discusses the concept of Capability Index (Cp).

Compared Insights on Machine-Learning Anomaly Detection for Process Control Feature

Anomaly detection is becoming increasingly significant in industrial cyber security,and different machine-learning algorithms have been generally acknowledged as various effective intrusion detection engines to successfully identify cyber attacks.However,different machine-learning algorithms may exhibit their own detection effects even if they analyze the same feature samples.As a sequence,after developing one feature generation approach,the most effective and applicable detection engines should be desperately selected by comparing distinct properties of each machine-learning algorithm.Based on process control features generated by directed function transition diagrams,this paper introduces five different machine-learning algorithms as alternative detection engines to discuss their matching abilities.Furthermore,this paper not only describes some qualitative properties to compare their advantages and disadvantages,but also gives an in-depth and meticulous research on their detection accuracies and consuming time.In the verified experiments,two attack models and four different attack intensities are defined to facilitate all quantitative comparisons,and the impacts of detection accuracy caused by the feature parameter are also comparatively analyzed.All experimental results can clearly explain that SVM(Support Vector Machine)and WNN(Wavelet Neural Network)are suggested as two applicable detection engines under differing cases.

Risk Management of Clinical Reference Dosimetry of a Large Hospital Network Using Statistical Process Control

Managing TG-51 reference dosimetry in a large hospital network can be a challenging task. The objectives of this study are to investigate the effectiveness of using Statistical Process Control (SPC) to manage TG-51 workflow in such a network. All the sites in the network performed the annual reference dosimetry in water according to TG-51. These data were used to cross-calibrate the same ion chambers in plastic phantoms for monthly QA output measurements. An energy-specific dimensionless beam quality cross-calibration factor, , was derived to monitor the process across multiple sites. The SPC analysis was then performed to obtain the mean, , standard deviation, σk, the Upper Control Limit (UCL) and Lower Control Limit (LCL) in each beam. This process was first applied to 15 years of historical data at the main campus to assess the effectiveness of the process. A two-year prospective study including all 30 linear accelerators spread over the main campus and seven satellites in the network followed. The ranges of the control limits (±3σ) were found to be in the range of 1.7% - 2.6% and 3.3% - 4.2% for the main campus and the satellite sites respectively. The wider range in the satellite sites was attributed to variations in the workflow. Standardization of workflow was also found to be effective in narrowing the control limits. The SPC is effective in identifying variations in the workflow and was shown to be an effective tool in managing large network reference dosimetry.

Problems and Strategies in Applications of Advanced Process Control in China

Advanced Process Control （APC） is necessary for oil refining and chemical process in China, but some problems have emerged in the application of APC techniques in this field. This paper discusses the conditions of APC application concerning process design, distributed control system （DCS） choice and regular control. It analyzes the problems and strategies in APC application. Some suggestions are proposed for the enterprise to benefit from APC application.

Collaborative Simulation Method with Spatiotemporal Synchronization Process Control

When designing a complex mechatronics system, such as high speed trains, it is relatively difficult to effectively simulate the entire system＇s dynamic behaviors because it involves multi-disciplinary subsystems. Currently, a most practical approach for multi-disciplinary simulation is interface based coupling simulation method, but it faces a twofold challenge： spatial and time unsynchronizations among multi-directional coupling simulation of subsystems. A new collaborative simulation method with spatiotemporal synchronization process control is proposed for coupling simulating a given complex mechatronics system across multiple subsystems on different platforms. The method consists of 1） a coupler-based coupling mechanisms to define the interfacing and interaction mechanisms among subsystems, and 2） a simulation process control algorithm to realize the coupling simulation in a spatiotemporal synchronized manner. The test results from a case study show that the proposed method 1） can certainly be used to simulate the sub-systems interactions under different simulation conditions in an engineering system, and 2） effectively supports multi-directional coupling simulation among multi-disciplinary subsystems. This method has been successfully applied in China high speed train design and development processes, demonstrating that it can be applied in a wide range of engineering systems design and simulation with improved efficiency and effectiveness.

Influence of process control agents on the performance of Ni_3Al by mechanical alloying

The influence of process control agents （PCAs） on the mechanical properties of Ni3AI intermetallic compounds by mechanical alloying was investigated in order to develop oxide deposition reinforced intermetallics. The PCAs in mechanical alloying were pure ligroin, 75 vol.% ligroin ＋ 25 vol.% alcohol, 50 vol.% ligroin ＋ 50 vol.% alcohol, 25 vol.% ligroin ＋ 75 vol.% alcohol, and pure alcohol. The normal composition is Ni-22.9at.%Al-0.5at.%B, the ball-to-powder weight ratio is 10：1, and the milling time is 30 min. Then, the powders were sintered by spark plasma sintering under 40 MPa for 5 min at 1000℃. The results show that a higher bending strength and a higher hardness were obtained when the PCAs were 75% ligroin ＋ 25% alcohol in mechanical alloying. The bending strength is about 2700 MPa and the hardness （HV） is more than 6 GPa.

Reduction Process of Blue Tungsten Oxide and its Microcomputer Process Control

Grain size control of tungsten powder is essential for high quality tungsten products. Based on studies on the hydrogen reduction process of tungsten oxide, a microcomputer system is described for reduction process control. The system, now running in Zhuzhou Tungsten and Molybdenum Materials Plant, controls the temperature of the reduction furnace and hydrogen pressure. It also controls a mechanical pusher which pushs the boats charged with blue tungsten oxide into the furnace tubes. Some of the technical problems in the process are analysed.

Formal Reduction of Interfaces to Large-scale Process Control Systems

A formal methodology is proposed to reduce the amount of information displayed to remote human operators at interfaces to large-scale process control plants of a certain type. The reduction proceeds in two stages. In the first stage, minimal reduced subsets of components, which give full information about the state of the whole system, are generated by determining functional dependencies between components. This is achieved by using a temporal logic proof obligation to check whether the state of all components can be inferred from the state of components in a subset in specified situations that the human operator needs to detect, with respect to a finite state machine model of the system and other human operator behavior. Generation of reduced subsets is automated with the help of a temporal logic model checker. The second stage determines the interconnections between components to be displayed in the reduced system so that the natural overall graphical structure of the system is maintained. A formal definition of an aesthetic for the required subgraph of a graph representation of the full system, containing the reduced subset of components, is given for this purpose. The methodology is demonstrated by a case study.

Advances in Process Control for Refractory Production

This paper reviews main problems of domestic refractories, in terms of the structure, principle, performance and new theory of automatic control, such as modern control, fuzzy control, artificial neural network, and expert system. Advanced equipment used in Rill Dalian Plant is introduced, as well as quality control and guarantee in Europe. Some topics to upgrade Chinese refractory industry are discussed.

基于Statistical Process Control风险等级判定及神经网络模型构建珠海市传染病指数

目的建立珠海市传染病指数预报模型,为传染病风险预测预报提供思路。方法利用统计过程控制(SPC)的控制下限、中线和控制上限划分全市2014—2017年以周次为时间计量单位的流感样病例比例、手足口病及其他感染性腹泻发病率的风险等级(布雷图指数采用5、10、20判定)。运用长短时记忆神经网络模型(LSTM)和自回归移动平均模型(ARIMA)对2018年15~19周数据进行预测。计算传染病指数并将预测值与实际值对比进而评估预测一致性。结果珠海市手足口病发病率LSTM模型中,测试集MSE为9.0441,RMSE为3.0073,训练集MSE为1.1812,RMSE为1.0868。其余模型在训练集和测试集均表现良好,没有出现过拟合现象。风险指数等级预测与实际值对比,预测一致率为96.0%。结论利用SPC划分风险等级,运用LSTM等构建传染病指数预测模型可行。

Study on Quality and Safety Trust Early Warning of Dairy Products Based on Statistical Process Control

In order to solve such problems as lack of dynamic evaluation system in evaluation of quality and safety trust of dairy products,and weak awareness of prevention,it is necessary to introduce the statistical process control into the quality and safety trust evaluation system of dairy products,and establish quality and safety trust early warning model for dairy products,so as to determine the control limit of control chart and carry out early warning according to eight criteria. According to the empirical results,the statistical process control is helpful for finding the hidden process risks and providing the necessary basis for enterprises taking positive measures to raise the confidence of consumers.

Tufting Carpet Machine Information Model Based on Object Linking and Embedding for Process Control Unified Architecture

In view of the lack of research on the information model of tufting carpet machine in China,an information modeling method based on Object Linking and Embedding for Process Control Unified Architecture(OPC UA)framework was proposed to solve the problem of“information island”caused by the differentiated data interface between heterogeneous equipment and system in tufting carpet machine workshop.This paper established an information model of tufting carpet machine based on analyzing the system architecture,workshop equipment composition and information flow of the workshop,combined with the OPC UA information modeling specification.Subsequently,the OPC UA protocol is used to instantiate and map the information model,and the OPC UA server is developed.Finally,the practicability of tufting carpet machine information model under the OPC UA framework and the feasibility of realizing the information interconnection of heterogeneous devices in the tufting carpet machine digital workshop are verified.On this basis,the cloud and remote access to the underlying device data are realized.The application of this information model and information integration scheme in actual production explores and practices the application of OPC UA technology in the digital workshop of tufting carpet machine.

Application of Statistical Process Control for Setting Action Thresholds as Quality Assurance of Dose Verifications in External Beam Radiotherapy

Purpose: To test the concept of Statistical Process Control (SPC) as a Quality Assurance (QA) procedure for dose verifications in external beam radiation therapy in conventional and 3D Conformal Radiotherapy (3D-CRT) treatment of cervical cancer. Materials and Methods: A study of QA verification of target doses of 198 cervical cancer patients undergoing External Beam Radiotherapy (EBRT) treatments at two different cancer treatment centers in Kenya was conducted. The target doses were determined from measured entrance doses by the diode in vivo dosimetry. Process Behavior Charts (PBC) developed by SPC were applied for setting Action Thresholds (AT) on the target doses. The AT set was then proposed as QA limits for acceptance or rejection of verified target doses overtime of the EBRT process. Result and Discussion: Target doses for the 198 patients were calculated and SPC applied to test whether the action limits set by the Process Behavior Charts could be applied as QA for verified doses in EBRT. Results for the two sub-groups of n = 3 and n = 4 that were tested produced action thresholds which are within clinical dose specifications for both conventional AP/PA and 3D-CRT EBRT treatment techniques for cervical cancer. Conclusion: Action thresholds set by SPC were within the clinical dose specification of ±5% uncertainty for both conventional AP/PA and 3D-CRT EBRT treatment techniques for cervical cancer. So the concept of SPC could be applied in setting QA action limits for dose verifications in EBRT.

Assessing the Awareness and Usage of Quality Control Tools with Emphasis to Statistical Process Control (SPC) in Ethiopian Manufacturing Industries

Introduction: The present work was devoted to assess the awareness and usage of quality control tools with the emphasis on statistical process control in Ethiopian manufacturing industries. Semi structured questionnaire has been employed to executive and technical managers of manufacturing industries of various size and specialism across the country. Stratified random sample method by region was used to select sample industries for the study. The samples used for this study are industries mainly from Oromiya, Addis Ababa, Tigray, Amara, SNNP and Diredawa regions proportional to their size of the available industries. Methods: Exploratory method and descriptive statistics was used for data analysis. Available documents and reports related to quality control policy of the selected companies were investigated. Results and Discussions: The number of manufacturing industries involved in this study was 44. Of the sampled manufacturing industries about 60% are from Oromiya and Addis Ababa regions. It has been reported that 100% of the respondents said that the importance of quality control tools is very important to their organizations’ productivity and quality improvement (Figure 3). Quality control professionals were also asked the extent to which quality control system is working in their industry and majority of the respondents (45%) have indicated that quality control system is working to some extent in their respective industries (Figure 18). Conclusions and Recommendations: Most of the quality department of the industries did not fully recognize the importance of statistical process control as quality control tools. This is mainly due to lack of awareness and motivation of the top managements, shortage of man power in the area, and others together would make it difficult to apply quality control tools in their organization. In general, the industries in Ethiopia are deficient in vigor and found to be stagnant hence less exposed to a highly competitive market and don’t adopt the latest quality control techniques in order to gain knowledge about systems to improve quality and operational performance. We conclude that quality management system has to be established as an independent entity with a real power and hence the quality control department which is responsible for quality can make an irreversible decision with respect to quality of any given product. Moreover, the concerned bodies (government and ministry of industries) should give attention and work together with universities to ensure how these statistical process control techniques could be incorporated in a curriculum of the universities at higher levels in degree and masters programs. Furthermore, different trainings which could improve quality and efficiency of their respective management system should be given as short and long term to the employees including top and middle managers found in various industries relevant to their process.

Process Control for Dissolving Pulp by SuperBatch Cooking

The process of producing dissolving pulp with SuperBatch cooking was introduced. The factors that affected the quality of the dissolving pulp and the corresponding operations were investigated.

An Integrated Approach for Process Control Valves Diagnosis Using Fuzzy Logic

Control valves are widely used in industry to control fluid flow in several applications. In nuclear power systems they are crucial for the safe operation of plants. Therefore, the necessity of improvements in monitoring and diagnosis methods started to be of extreme relevance, establishing as main goal of the reliability and readiness of the system components. The main focus of this work is to study the development of a model of non-intrusive monitoring and diagnosis applied to process control valves using artificial intelligence by fuzzy logic technique, contributing to the development of predictive methodologies identifying faults in incipient state. Specially in nuclear power plants, the predictive maintenance contributes to the security factor in order to diagnose in advance the occurrence of a possible failure, preventing severs situations. The control valve analyzed belongs to a steam plant which simulates the secondary circuit of a PWR—Pressurized Water Reactor. The maintenance programs are being implemented based on the ability to diagnose modes of degradation and to take measures to prevent incipient failures, improving plant reliability and reducing maintenance costs. The approach described in this paper represents an alternative departure from the conventional qualitative techniques of system analysis. The methodology used in this project is based on signatures analysis, considering the pressure (psi) in the actuator and the stem displacement (mm) of the valve. Once the measurements baseline of the control valve is taken, it is possible to detect long-term deviations during valve lifetime, detecting in advance valve failures. This study makes use of MATLAB language through the “fuzzy logic toolbox” which uses the method of inference “Mamdani”, acting by fuzzy conjunction, through Triangular Norms (t-norm) and Triangular Conorms (t-conorm). The main goal is to obtain more detailed information contained in the measured data, correlating them to failure situations in the incipient stage.

Process Control and Optimization for Heterologous Protein Production by Methylotrophic Pichia pastoris

The methylotrophic yeast Pichia pastoris is a highly successful system for production of a variety of heterologous proteins due to its unique features/abilities for effective protein expression, and tremendous efforts have been made to increase heterologous protein productivity by P. pastoris in recent years. When new engineered yeast strains are constructed and are ready to use for industrial protein production, process control and optimization techniques should be applied to improve the fermentation performance in the following aspects: (1) increase recombinant cell concentrations in fermentor to high density during growth phase; (2) effectively induce heterologous proteins by enhancing/stabilizing titers or concentrations of the proteins during induction phase; (3) decrease operation costs by relieving the working loads of heat-exchange and oxygen supply. This article reviews and discusses the key and commonly used techniques in heterologous protein production by P. pastoris, with the focus on optimizations of fermentation media and basic operation conditions, development of optimal glycerol feeding strategies for achieving high density cultivation of P. pastoris and effective heterologous protein induction methods by regulating specific growth rate, methanol concentration, temperatures, mixture ratio of multi-carbon substrates, etc. Metabolic analysis for recombinant protein production by P. pastoris is also introduced to interpret the mechanism of sub-optimal heterologous protein production and to explore further optimal expression methods.

Integrated Product and Process Control for Sustainable Semiconductor Manufacturing

半导体制造是有几百复杂单位操作和它的一个生产序列被策略开发总是为保证没有缺点的产品的收益质问。在这份报纸，通过集成产品和过程控制的先进控制策略被建立。建议多尺度的计划为协调设备控制，进程控制和产品质量控制包含三层。在上面的层，联机控制表演评价被使用减少优秀变化并且最大化全面产品表演(OPP ) 。它用作监督控制在中间的层更新进程控制器的配方。过程控制器作为指数地加权的移动一般水准(EWMA ) 被设计拒绝骚乱的 run-to-run 控制器那例如用坏的过程移动，飘移和工具，被施加到操作。在这个过程的设备个别地被控制维持它的最佳的运作的地位并且最大化全面设备有效性(OEE ) ，基于过程控制器给的集合点。建议综合控制计划的功效通过案例研究被表明，在的地方两 OPP (为产品) 并且 OEE (为设备) 被提高。