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 n...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.展开更多
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 impl...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.展开更多
This survey paper provides a review and perspective on intermediate and advanced reinforcement learning(RL)techniques in process industries. It offers a holistic approach by covering all levels of the process control ...This survey paper provides a review and perspective on intermediate and advanced reinforcement learning(RL)techniques in process industries. It offers a holistic approach by covering all levels of the process control hierarchy. The survey paper presents a comprehensive overview of RL algorithms,including fundamental concepts like Markov decision processes and different approaches to RL, such as value-based, policy-based, and actor-critic methods, while also discussing the relationship between classical control and RL. It further reviews the wide-ranging applications of RL in process industries, such as soft sensors, low-level control, high-level control, distributed process control, fault detection and fault tolerant control, optimization,planning, scheduling, and supply chain. The survey paper discusses the limitations and advantages, trends and new applications, and opportunities and future prospects for RL in process industries. Moreover, it highlights the need for a holistic approach in complex systems due to the growing importance of digitalization in the process industries.展开更多
The definitions, methodology, applications, and perspectives of process system engineering are discussed from a strategic point of view. The focal points in future development of process systems engineering are to bre...The definitions, methodology, applications, and perspectives of process system engineering are discussed from a strategic point of view. The focal points in future development of process systems engineering are to break through in methodology, to expand application fields, and to develop a new generation of process simulation systems.展开更多
基金Supported by National Natural Science Foundation of China (No. 70931004)
文摘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.
文摘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.
基金supported in part by the Natural Sciences Engineering Research Council of Canada (NSERC)。
文摘This survey paper provides a review and perspective on intermediate and advanced reinforcement learning(RL)techniques in process industries. It offers a holistic approach by covering all levels of the process control hierarchy. The survey paper presents a comprehensive overview of RL algorithms,including fundamental concepts like Markov decision processes and different approaches to RL, such as value-based, policy-based, and actor-critic methods, while also discussing the relationship between classical control and RL. It further reviews the wide-ranging applications of RL in process industries, such as soft sensors, low-level control, high-level control, distributed process control, fault detection and fault tolerant control, optimization,planning, scheduling, and supply chain. The survey paper discusses the limitations and advantages, trends and new applications, and opportunities and future prospects for RL in process industries. Moreover, it highlights the need for a holistic approach in complex systems due to the growing importance of digitalization in the process industries.
文摘The definitions, methodology, applications, and perspectives of process system engineering are discussed from a strategic point of view. The focal points in future development of process systems engineering are to break through in methodology, to expand application fields, and to develop a new generation of process simulation systems.
