Integrated Statistical and Engineering Process Control Based on Smooth Transition Autoregressive Model

Traditional studies on integrated statistical process control and engineering process control (SPC-EPC) are based on linear autoregressive integrated moving average (ARIMA) time series models to describe the dynamic noise of the system.However,linear models sometimes are unable to model complex nonlinear autocorrelation.To solve this problem,this paper presents an integrated SPC-EPC method based on smooth transition autoregressive (STAR) time series model,and builds a minimum mean squared error (MMSE) controller as well as an integrated SPC-EPC control system.The performance of this method for checking the trend and sustained shift is analyzed.The simulation results indicate that this integrated SPC-EPC control method based on STAR model is effective in controlling complex nonlinear systems.

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。

Multivariate Statistical Process Monitoring and Control: Recent Developments and Applications to Chemical Industry

Multivariate statistical process monitoring and control (MSPM&C) methods for chemical process monitoring with statistical projection techniques such as principal component analysis (PCA) and partial least squares (PLS) are surveyed in this paper. The four-step procedure of performing MSPM&C for chemical process, modeling of processes, detecting abnormal events or faults, identifying the variable(s) responsible for the faults and diagnosing the source cause for the abnormal behavior, is analyzed. Several main research directions of MSPM&C reported in the literature are discussed, such as multi-way principal component analysis (MPCA) for batch process, statistical monitoring and control for nonlinear process, dynamic PCA and dynamic PLS, and on-line quality control by inferential models. Industrial applications of MSPM&C to several typical chemical processes, such as chemical reactor, distillation column, polymerization process, petroleum refinery units, are summarized. Finally, some concluding remarks and future considerations are made.

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).

A novel Q-based online model updating strategy and its application in statistical process control for rubber mixing

To overcome the large time-delay in measuring the hardness of mixed rubber, rheological parameters were used to predict the hardness. A novel Q-based model updating strategy was proposed as a universal platform to track time-varying properties. Using a few selected support samples to update the model, the strategy could dramat- ically save the storage cost and overcome the adverse influence of low signal-to-noise ratio samples. Moreover, it could be applied to any statistical process monitoring system without drastic changes to them, which is practical for industrial practices. As examples, the Q-based strategy was integrated with three popular algorithms （partial least squares （PIE）, recursive PIE （RPLS）, and kernel PIE （KPIE）） to form novel regression ones, QPLS, QRPIE and QKPLS, respectively. The applications for predicting mixed rubber hardness on a large-scale tire plant in east China prove the theoretical considerations.

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.

Evaluation of Environmental Sound Pressure Level,Drawing of Noise-Isosonic Map Using Surfer V.19,and Prioritization of Engineering Noise Control Methods Using the Analytic Hierarchy Process(AHP):A Field Study in CGS Stations

Noise pollution is one of the most significant harmful physical factors in the industrial and occupational environments.Due to the high costs of exposure to excessive noise;continuous sound evaluation,propose and implement noise control plans in occupational environments is necessary.Thus,the present study aimed to review environmental sound measurements,drawing of noise maps,and prioritizing the engineering noise control methods using the Analytic Hierarchy Process(AHP).This study was a descriptive-analytical study that aimed to assess occupational noises and present a control plan in the City Gas Stations(CGSs)of Kerman,Iran in 2021.The present study was done in two phases.In the first phase,six CGSs were investigated to measure and evaluate the noise.In addition,the noise map of a CGS was drawn using the Surfer software.Finally,the AHP was used in the second phase of the research to prioritize the control measures.In this phase,four criteria and ten alternatives were identified.According to first phase results,the sound pressure level(SPL)of the stations varied from 76 to 98 dBA.Besides,the majority of the studied stations had a sound level higher than 85 dBA(danger zone).The second phase of the study showed that out of the four evaluated criteria,the executability criterion had the highest impact and the cost criterion had the lowest impact on the selection of control measures with a weight of 0.587 and 0.052,respectively.Based on the results of prioritization of the alternatives,using a silenced regulator(weight of 0.223)and increasing the thickness of the tube(weight of 0.023)had the highest and lowest priorities among the alternatives,respectively.The use of engineering noise control methods such as using silenced regulators was the best way to control the noises of CGSs.Additionally;it is noteworthy that AHP is a practical method for prioritizing alternatives to achieve the most accurate decision-making.The results of AHP can be of great help to health and safety experts and managers in choosing the sound engineering control measures more precisely.

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.

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.

Statistical Control and Investigation of Capability of Process and Machine in Wire Cut Edm Process of Gas Turbine Blade Airfoil Tip

Statistical process control (spc), as one of the quality devices, can be help manufacturers improve the quality of their products in today’s competitive world. This research examines the statistical method of wire-cut electric discharge machining (WEDM) process of the turbine blade airfoil tip for control and consistency of the process. For this purpose, the standard deviation control chart, S, and the average data, , which are applied for identifying the acquired factors, have been used. Next, regarding the plan features, the manufacturing process is assessed to determine whether the products meet quality and the customer requirements or not. Therefore, the coefficients Cpk is applied which indicate the capability of the manufacturing process. Then, in order to produce high quality blades within the tolerance range, the capability of WEDM machine is examined, using coefficients CM. Finally, it is shown that in order to produce the desired product, the process can be controlled and fixed by using the statistical process control devices and inspecting the standard deviation of data and investigation of capability of process and machine.

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.

Investment control in whole process of engineering construction project

in recent years, as the project of our country is increasing, investment growth, put forward new challenges to investment in construction projects. Research from the research status of investment in construction, the implementation process in accordance with the construction project, followed by analysis of the construction project investment the currently existing problems, and puts forward the implementation of the project the whole process as the main line, to scientific decision-making, rational design, bidding, construction control standard and completion of review strategies as the core.

Optimization study of station track utilization in high-speed railroad based on constraints of control in random origin and process

Purpose-The purpose of this paper is to eliminate the fluctuations in train arrival and departure times caused by skewed distributions in interval operation times.These fluctuations arise from random origin and process factors during interval operations and can accumulate over multiple intervals.The aim is to enhance the robustness of high-speed rail station arrival and departure track utilization schemes.Design/methodologylapproach-To achieve this objective,the paper simulates actual train operations,incorporating the fluctuations in interval operation times into the utilization of arrival and departure tracks at the station.The Monte Carlo simulation method is adopted to solve this problem.This approach transforms a nonlinear model,which includes constraints from probability distribution functions and is difficult to solve directly,into a linear programming model that is easier to handle.The method then linearly weights two objectives to optimize the solution.Findings-Through the application of Monte Carlo simulation,the study successfully converts the complex nonlinear model with probability distribution function constraints into a manageable linear programming model.By continuously adjusting the weighting coefficients of the linear objectives,the method is able to optimize the Pareto solution.Notably,this approach does not require extensive scene data to obtain a satisfactory Pareto solution set.Originality/value-The paper contributes to the field by introducing a novel method for optimizing high-speed rail station arrival and departure track utilization in the presence of fluctuations in interval operation times.The use of Monte Carlo simulation to transform the problem into a tractable linear programming model represents a significant advancement.Furthermore,the method's ability to produce satisfactory Pareto solutions without relying on extensive data sets adds to its practical value and applicability in real-world scenarios.

Study on the Interactivity of Controlled and Automatic Information Processing in L2 Reading

L2 reading is not only an important channel for people to obtain information and knowledge,but also the main way for people to learn a foreign language.Reading information processing can be divided into controlled processing and automatic processing.Controlled information processing is a conscious and resource-intensive processing model,while automatic information processing is an unconscious and automatic processing model.This study investigates the characteristics and interactivity of controlled and automatic information processing in L2 reading,and explores the roles of controlled and automatic information processing strategies in improving L2 reading ability.The findings are as follows:(a)controlled and automatic information processing is interactive in L2 reading;and(b)the uses of controlled and automatic information processing strategies are beneficial to the improvement of the reading ability of L2 learners.This study has important theoretical and practical value in improving the efficiency of L2 reading teaching and learning.

Application of single neuron adaptive PID controller during the process of timber drying

The paper presents a method of using single neuron adaptive PID control for adjusting system or servo system to implement timber drying process control, which combines the thought of parameter adaptive PID control and the character of neural network on exactly describing nonlinear and uncertainty dynamic process organically. The method implements functions of adaptive and self-learning by adjusting weighting parameters. Adaptive neural network can make some output trail given hoping value to decouple in static state. The simulation result indicates the validity, veracity and robustness of the method used in the timber drying process

Evaluation of Selected Control Programming Languages for Process Engineers by Means of Cognitive Effectiveness and Dimensions

Different programming languages can be used for discrete, abstract and process-oriented programming. Depending on the application, there exist additional requirements, which are not fulfilled by every programming language. Flexible programming and maintainability are especially important requirements for process engineers. In this paper, the programming languages Activity Diagram, State Chart Diagram and Sequential Function Chart are compared and evaluated with regard to these requirements. This evaluation is based on the principles of cognitive effectiveness and cognitive dimensions. The aim of this paper is to identify the programming language suited best for controlling sequential processes, e.g. thermomechanical or batch processes.

Study on Transient Flow Characteristics of Attitude Control Engine During Starting Process

Liquid bipropellant attitude control rocket engines are widely used in satellites,manned spaceships,deep space probes and other spacecraft.The performance of an attitude control engine is directly related to the lifetime,control precision and safety of a spacecraft.The study of flow characteristics of an engine transient process is important to improve its performance.In this paper,the transient flow test of a transparent test piece was carried out during the starting process of the attitude control engine.Then the transient process of the test piece was simulated and compared with the test results to verify the rationality of the simulation model.Transient flow simulation was carried out for the starting process of the real engine injector.The results show that the filling of the outer ring of the oxidant circuit is slower than that of the central collecting cavity,and the filling of the second layer of the outer ring is slower than that of the first layer.The filling process in the fuel path starts from the cooling hole near the inlet side and the fuel flows out in the circumferential direction.Installation direction has little influence on engine starting flow process in the ground state.The filling time of the engine in its vacuum state is longer than that in the ground state,the filling time of oxidizer is 31%longer than that in ground state,and the filling time of fuel is 57%longer than that in ground state.

Multivariable Decoupling Predictive Control with Input Constraints and Its Application on Chemical Process

A constrained decoupling (generalized predictive control) GPC algorithm is proposed for MIMO (malti-input multi-output) system. This algorithm takes account of all constraints of inputs and their increments. By solving matrix equations, the multi-step predictive decoupling controllers are realized. This algorithm need not solve Diophantine functions, and weakens the cross-coupling of the variables. At last the simulation results demon- strate the effectiveness of this proposed strategy.

Whole-Process Pollution Control for Cost-Effective and Cleaner Chemical Production A Case Study of the Tungsten Industry in China

In this research,a methodology named whole-process pollution control(WPPC)is demonstrated that improves the effectiveness of process optimization.This methodology considers waste/emission treatment as a step of the whole production process with respect to the minimization of cost and environmental impact for the whole process.The following procedures are introduced in a WPPC process optimization:①a material and energy flow investigation and optimization based on a systematic understanding of the distribution and physiochemical properties of potential pollutants;②a process optimization to increase the utilization efficiency of different elements and minimize pollutant emissions;and③an evaluation to reveal the effectiveness of the optimization strategies.The production of ammonium paratungstate was chosen for the case study.Two factors of the different optimization schemes-namely the cost-effectiveness factor and the environmental impact indicator-were evaluated and compared.This research demonstrates that by considering the nature of potential pollutants,technological innovations,economic viability,environmental impacts,and regulation requirements,WPPC can efficiently optimize a metal production process.