Chemometrics Methods for Image-Based Monitoring and Control of Industrial Processes and Product Quality

基于图像的工业过程和产品质量监测和控制的化学计量学方法

• 批准号: 261188-2013
• 负责人: Duchesne, Carl
• 金额: $ 2.11万
• 依托单位: Université Laval
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=637824
• 关键词: Chemometrics; Methods; Image; Based; Monitoring

The long term goal of this research program consists of developing new chemometrics methods and systems engineering approaches for reducing variability, improving process operation and product quality in industrial areas that are important for the Canadian economy. Process chemometrics means using multivariate latent variable statistical methods for extracting relevant information from large process databases and multivariate images, and using the models for process monitoring, control and optimization. They help maintain international competitiveness, accelerate process development, and make a more efficient use of raw materials and energy. On the short term, the research will concentrate on developing tools for analyzing hyperspectral images of processes and products, and integrating these new sensors in engineering control systems in two areas: 1) production of complex polymer composites, and 2) culture systems for cell therapy development.To improve the performance/cost ratio and environmental signature of their products, the polymer processing industry is striving to replace the use of virgin resins as much as possible by incorporating low costs fillers and recycled resins. The viability of these new but more complex materials rely heavily on the ability to control the dispersion of the components within the finished products. This can hardly be assessed on a real-time basis using conventional destructive and time consuming lab testing. We will develop sensors and systems for real-time monitoring and quality control of these complex polymer composites.Large scale cell culture platforms are used for developing safer and better culture media for growing therapeutic stem cells and screening for molecules to stimulate growth and producing the desired type of cells more specifically. Monitoring growth, cell types and "health" for hundreds to thousands of cell cultures in parallel using the traditional manual approaches is time consuming. Automatic methods for non-intrusive monitoring of live cell cultures using long term large field phase contrast microscopy will be developed for accelerating media and cell therapy research.

该研究计划的长期目标包括开发新的化学计量学方法和系统工程方法，以减少对加拿大经济重要的工业领域的变异性、改进工艺操作和产品质量。过程化学计量学是指利用多元潜变量统计方法从大型过程数据库和多元图像中提取相关信息，并利用模型进行过程监测、控制和优化。它们有助于保持国际竞争力、加速工艺开发并更有效地利用原材料和能源。短期来看，该研究将集中于开发用于分析过程和产品的高光谱图像的工具，并将这些新型传感器集成到两个领域的工程控制系统中：1）复杂聚合物复合材料的生产，2）用于细胞疗法开发的培养系统。为了提高其产品的性能/成本比和环境特征，聚合物加工行业正在努力通过掺入低成本填料和回收材料来尽可能取代原始树脂的使用。 树脂。这些新的但更复杂的材料的可行性在很大程度上取决于控制成品中成分分散的能力。使用传统的破坏性且耗时的实验室测试很难实时评估这一点。我们将开发用于实时监测和质量控制这些复杂聚合物复合材料的传感器和系统。大规模细胞培养平台用于开发更安全、更好的培养基来生长治疗性干细胞，并筛选分子以刺激生长并更具体地产生所需类型的细胞。使用传统的手动方法并行监测数百到数千个细胞培养物的生长、细胞类型和“健康状况”非常耗时。将开发使用长期大视场相差显微镜对活细胞培养物进行非侵入式监测的自动方法，以加速培养基和细胞治疗研究。