This paper discusses how gamma irradiation plants are putting the latest advances in computer and information technology to use for better process control, cost savings, and strategic advantages.
Some irradiator operations are gaining significant benefits by integrating computer technology and robotics with real-time information processing, multi-user databases, and communication networks. The paper reports on several irradiation facilities that are making good use of client/server LANs, user-friendly graphics interfaces, supervisory control and data acquisition (SCADA) systems, distributed I/O with real-time sensor devices, trending analysis, real-time product tracking, dynamic product scheduling, and automated dosimetry reading. These plants are lowering costs by fast and reliable reconciliation of dosimetry data, easier validation to GMP requirements, optimizing production flow, and faster release of sterilized products to market.
There is a trend in the manufacturing sector towards total automation using “predictive process control”. Real-time verification of process parameters “on-the-run” allows control parameters to be adjusted appropriately, before the process strays out of limits. Applying this technology to the gamma radiation process, control will be based on monitoring the key parameters such as time, and making adjustments during the process to optimize quality and throughput. Dosimetry results will be used as a quality control measurement rather than as a final monitor for the release of the product. Results are correlated with the irradiation process data to quickly and confidently reconcile variations. Ultimately, a parametric process control system utilizing responsive control, feedback and verification will not only increase productivity and process efficiency, but can also result in operating within tighter dose control set points. 相似文献
Emanation thermal analysis was used to characterize the thermal behaviour of alumina coatings as deposited on EUROFER 97 steel
surface by filtered vacuum arc technique. Temperature ranges of the healing of cracks and structure irregularities observed
by SEM were determined from the ETA results. Transport properties of the alumina coatings were assessed from the ETA results
by the evaluation of radon diffusion parameters in the temperature range from 50 to 300°C. Healing microstructure irregularities
of the alumina coatings can be expected in the range 300–700°C as indicated by the decrease of the radon release rate. From
the ETA results it followed that the onset of healing the cracks observed by the SEM on the surface of one alumina coating
sample can be expected at 430°C.
Dedicated to Dr. K. Habersberger, Past-Chairman of the thermal analysis working group of the Czech Chemcial Society, at the
occasion of his 75th birthday 相似文献
The release of the FDA’s guidance on Process Analytical Technology has motivated and supported the pharmaceutical industry to deliver consistent quality medicine by acquiring a deeper understanding of the product performance and process interplay. The technical opportunities to reach this high-level control have considerably evolved since 2004 due to the development of advanced analytical sensors and chemometric tools. However, their transfer to the highly regulated pharmaceutical sector has been limited. To this respect, data fusion strategies have been extensively applied in different sectors, such as food or chemical, to provide a more robust performance of the analytical platforms. This survey evaluates the challenges and opportunities of implementing data fusion within the PAT concept by identifying transfer opportunities from other sectors. Special attention is given to the data types available from pharmaceutical manufacturing and their compatibility with data fusion strategies. Furthermore, the integration into Pharma 4.0 is discussed. 相似文献
In quantitative on-line/in-line monitoring of chemical and bio-chemical processes using spectroscopic instruments, multivariate calibration models are indispensable for the extraction of chemical information from complex spectroscopic measurements. The development of reliable multivariate calibration models is generally time-consuming and costly. Therefore, once a reliable multivariate calibration model is established, it is expected to be used for an extended period. However, any change in the instrumental response or variations in the measurement conditions can render a multivariate calibration model invalid. In this contribution, a new method, spectral space transformation (SST), has been developed to maintain the predictive abilities of multivariate calibration models when the spectrometer or measurement conditions are altered. SST tries to eliminate the spectral differences induced by the changes in instruments or measurement conditions through the transformation between two spectral spaces spanned by the corresponding spectra of a subset of standardization samples measured on two instruments or under two sets of experimental conditions. The performance of the method has been tested on two data sets comprising NIR and MIR spectra. The experimental results show that SST can achieve satisfactory analyte predictions from spectroscopic measurements subject to spectrometer/probe alteration, when only a few standardization samples are used. Compared with the existing popular methods designed for the same purpose, i.e. global PLS, univariate slope and bias correction (SBC) and piecewise direct standardization (PDS), SST has the advantages of implementation simplicity, wider applicability and better performance in terms of predictive accuracy. 相似文献
