This study proposed a new real-time manufacturing process monitoring method to monitor and detect process shifts in manufacturing operations.Since real-time production process monitoring is critical in today’s smart ...This study proposed a new real-time manufacturing process monitoring method to monitor and detect process shifts in manufacturing operations.Since real-time production process monitoring is critical in today’s smart manufacturing.The more robust the monitoring model,the more reliable a process is to be under control.In the past,many researchers have developed real-time monitoring methods to detect process shifts early.However,thesemethods have limitations in detecting process shifts as quickly as possible and handling various data volumes and varieties.In this paper,a robust monitoring model combining Gated Recurrent Unit(GRU)and Random Forest(RF)with Real-Time Contrast(RTC)called GRU-RF-RTC was proposed to detect process shifts rapidly.The effectiveness of the proposed GRU-RF-RTC model is first evaluated using multivariate normal and nonnormal distribution datasets.Then,to prove the applicability of the proposed model in a realmanufacturing setting,the model was evaluated using real-world normal and non-normal problems.The results demonstrate that the proposed GRU-RF-RTC outperforms other methods in detecting process shifts quickly with the lowest average out-of-control run length(ARL1)in all synthesis and real-world problems under normal and non-normal cases.The experiment results on real-world problems highlight the significance of the proposed GRU-RF-RTC model in modern manufacturing process monitoring applications.The result reveals that the proposed method improves the shift detection capability by 42.14%in normal and 43.64%in gamma distribution problems.展开更多
After giving a short review of the methods used for detecting and monitoring in general systems, this paper describes the way of communication between computer and Computer Numerical Control (CNC) Machining Center (MC...After giving a short review of the methods used for detecting and monitoring in general systems, this paper describes the way of communication between computer and Computer Numerical Control (CNC) Machining Center (MC). Based on these, the paper addresses the means of performing in cycle measurement for manufacturing quality, provides an approach of improving the state of manufacturing process by achieving the real time change of control parameters according to the level of manufacturing process, and discusses the technique of implementing in process dimensional errors compensation corresponding to the in cycle measurement. The results of the experiments show that the frame design is successful and the operation is reliable. The system is taking shape nowadays.展开更多
From a regulatory perspective,drug quality consistency evaluation must concern different processes used for the same drug.In this study,an assessment strategy based on quality by design(QbD)was developed for populatio...From a regulatory perspective,drug quality consistency evaluation must concern different processes used for the same drug.In this study,an assessment strategy based on quality by design(QbD)was developed for population pharmaceutical quality evaluation.A descriptive analysis method based on QbD concept was first established to characterize the process by critical evaluation attributes(CEAs).Then quantitative analysis method based on an improved statistical process control(SPC)method was established to investigate the process indicators(PIs)in the process population,such as mean distribution,batch-to-batch difference and abnormal quality probability.After that rules for risk assessment were established based on the SPC limitations and parameters.Both the SPC parameters of the CEAs and the risk of PIs were visualized according to the interaction test results to obtain a better understanding of the population pharmaceutical quality.Finally,an assessment strategy was built and applied to generic drug consistency assessment,process risk assessment and quality trend tracking.The strategy demonstrated in this study could help reveal quality consistency from the perspective of process control and process risk,and further show the recent development status of domestic pharmaceutical production processes.In addition,a process risk assessment and population quality trend tracking provide databased information for approval.Not only can this information serve as a further basis for decisionmaking by the regulatory authority regarding early warnings,but it can also reduce some avoidable adverse reactions.With continuous addition of data,dynamic population pharmaceutical quality is meaningful for emergencies and decision-making regarding drug regulation.展开更多
基金support from the National Science and Technology Council of Taiwan(Contract Nos.111-2221 E-011081 and 111-2622-E-011019)the support from Intelligent Manufacturing Innovation Center(IMIC),National Taiwan University of Science and Technology(NTUST),Taipei,Taiwan,which is a Featured Areas Research Center in Higher Education Sprout Project of Ministry of Education(MOE),Taiwan(since 2023)was appreciatedWe also thank Wang Jhan Yang Charitable Trust Fund(Contract No.WJY 2020-HR-01)for its financial support.
文摘This study proposed a new real-time manufacturing process monitoring method to monitor and detect process shifts in manufacturing operations.Since real-time production process monitoring is critical in today’s smart manufacturing.The more robust the monitoring model,the more reliable a process is to be under control.In the past,many researchers have developed real-time monitoring methods to detect process shifts early.However,thesemethods have limitations in detecting process shifts as quickly as possible and handling various data volumes and varieties.In this paper,a robust monitoring model combining Gated Recurrent Unit(GRU)and Random Forest(RF)with Real-Time Contrast(RTC)called GRU-RF-RTC was proposed to detect process shifts rapidly.The effectiveness of the proposed GRU-RF-RTC model is first evaluated using multivariate normal and nonnormal distribution datasets.Then,to prove the applicability of the proposed model in a realmanufacturing setting,the model was evaluated using real-world normal and non-normal problems.The results demonstrate that the proposed GRU-RF-RTC outperforms other methods in detecting process shifts quickly with the lowest average out-of-control run length(ARL1)in all synthesis and real-world problems under normal and non-normal cases.The experiment results on real-world problems highlight the significance of the proposed GRU-RF-RTC model in modern manufacturing process monitoring applications.The result reveals that the proposed method improves the shift detection capability by 42.14%in normal and 43.64%in gamma distribution problems.
文摘After giving a short review of the methods used for detecting and monitoring in general systems, this paper describes the way of communication between computer and Computer Numerical Control (CNC) Machining Center (MC). Based on these, the paper addresses the means of performing in cycle measurement for manufacturing quality, provides an approach of improving the state of manufacturing process by achieving the real time change of control parameters according to the level of manufacturing process, and discusses the technique of implementing in process dimensional errors compensation corresponding to the in cycle measurement. The results of the experiments show that the frame design is successful and the operation is reliable. The system is taking shape nowadays.
基金The National Major Scientific and Technological Special Project for‘Significant New Drugs Development’(Grant No.:2017ZX0901001-007)provides support for this study.
文摘From a regulatory perspective,drug quality consistency evaluation must concern different processes used for the same drug.In this study,an assessment strategy based on quality by design(QbD)was developed for population pharmaceutical quality evaluation.A descriptive analysis method based on QbD concept was first established to characterize the process by critical evaluation attributes(CEAs).Then quantitative analysis method based on an improved statistical process control(SPC)method was established to investigate the process indicators(PIs)in the process population,such as mean distribution,batch-to-batch difference and abnormal quality probability.After that rules for risk assessment were established based on the SPC limitations and parameters.Both the SPC parameters of the CEAs and the risk of PIs were visualized according to the interaction test results to obtain a better understanding of the population pharmaceutical quality.Finally,an assessment strategy was built and applied to generic drug consistency assessment,process risk assessment and quality trend tracking.The strategy demonstrated in this study could help reveal quality consistency from the perspective of process control and process risk,and further show the recent development status of domestic pharmaceutical production processes.In addition,a process risk assessment and population quality trend tracking provide databased information for approval.Not only can this information serve as a further basis for decisionmaking by the regulatory authority regarding early warnings,but it can also reduce some avoidable adverse reactions.With continuous addition of data,dynamic population pharmaceutical quality is meaningful for emergencies and decision-making regarding drug regulation.
