New Latent Variable Methods for selection of raw materials, process monitoring and product quality control

用于原材料选择、过程监控和产品质量控制的新潜变量方法

• 批准号: RGPIN-2019-04800
• 负责人: Duchesne, Carl
• 金额: $ 3.35万
• 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: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=737867
• 关键词: New; Latent; Variable; Methods; selection

Nowadays, increasingly large amounts of data are routinely collected by process industries and need to be analyzed to extract useful information for making timely decisions. This trend will sustain in the future with the growing interest for the "smart factory" concept based on Industry 4.0 technologies. It promotes data collection from different devices and sources (e.g. smart process sensors and actuators, analytical instruments, images, etc.), and interconnecting them in a structured way in order to enhance process performance. Developing efficient methods to achieve this goal is the keystone of my research program. The long-term goal of my program consists of developing new data-driven and systems engineering approaches for reducing variability, improving process operation and product quality, and applying them in industrial areas that are important for the Canadian economy. The aim is to help maintain international competitiveness, accelerate process and product development, and make a more efficient use of raw materials and energy. On the short term, the research will concentrate on further developing two new latent variable methods recently devised in my group, namely the Sequential Multi-block PLS regression (SMB-PLS) and the Undecimated Wavelet Transform - Multivariate Image Analysis (UWT-MIA). These methods will be adapted and applied for solving raw materials selection problems, and developing image-based sensors and tools for process and quality control purposes. A generic framework for setting multivariate specifications for raw material properties to cope with most practical situations found in industry will be developed. Multivariate process capability metrics will also be proposed to compare the likeliness of suppliers of materials to meet customer's specifications. These tools will help ensure smooth process operation, achieve desired product quality, and reduce the amounts of off-specification materials and costs. This research also aims at developing advanced process analytical technologies (PAT) for on-line quality control of polymer films used for food packaging or gas separation applications. A new sensor based on imaging thermography will be devised to improve quality control of the films. This is important to enable early detection of product defects, rapid diagnosis of the causes, and taking appropriate remedial actions to reduce off-specs materials and production costs. In addition, live cell imaging tools will be proposed to assess cellular functionality in rapid and non-intrusive fashion. They will help researchers and the biotechnology/biopharmaceutical industry accelerate the development of new cell culture media, cell therapies, and medications using their high throughput screening platforms. Finally, the highly qualified personnel trained in this research program will take leadership roles in transferring the methods and tools in practice, and help increase the competitiveness of the Canadian industry.

如今，越来越多的数据是通过流程行业常规收集的，需要分析以提取有用的信息来做出及时的决策。这种趋势将在未来维持，因为基于行业4.0技术的“智能工厂”概念的兴趣日益增长。它从不同的设备和来源（例如智能过程传感器和执行器，分析仪器，图像等）促进数据收集，并以结构化的方式互连以提高过程性能。开发有效的方法以实现这一目标是我的研究计划的基石。我计划的长期目标是开发新的数据驱动和系统工程方法，以降低可变性，改善流程运营和产品质量以及在对加拿大经济重要的工业领域中应用它们。目的是帮助维持国际竞争力，加速过程和产品开发，并更有效地利用原材料和能源。在短期内，该研究将集中于进一步开发最近在我的小组中设计的两种新的潜在变量方法，即顺序多块PLS回归（SMB-PLS）和不可接受的小波变换 - 多元图像分析（UWT-MIA）。这些方法将被调整并应用于解决原材料选择问题，并为过程和质量控制目的开发基于图像的传感器和工具。将开发一个为原材料属性设置多元规格以应对行业中发现的最实际情况的通用框架。还将提出多元过程能力指标，以比较材料供应商的可能性以满足客户规格。这些工具将有助于确保流畅的过程操作，达到所需的产品质量，并减少规格外材料和成本的数量。这项研究还旨在开发高级工艺分析技术（PAT），以在用于食品包装或气体分离应用的聚合物膜的在线质量控制。将设计基于成像热摄影的新传感器，以改善膜的质量控制。这对于能够早期发现产品缺陷，快速诊断原因以及采取适当的补救措施来降低规格材料和生产成本很重要。此外，将提出实时细胞成像工具以快速和非侵入性的方式评估细胞功能。他们将帮助研究人员和生物技术/生物制药行业加快使用高通量筛选平台的新细胞培养基，细胞疗法和药物的发展。最后，在该研究计划中接受培训的高素质人员将在转移方法和工具中扮演领导角色，并帮助提高加拿大行业的竞争力。