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: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=753736
• 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，过程工业通常会收集越来越多的数据，需要对其进行分析以提取有用的信息以做出及时决策，随着人们对基于工业 4.0 技术的“智能工厂”概念的兴趣日益浓厚，这种趋势将持续下去。它促进从不同设备和来源（例如智能过程传感器和执行器、分析仪器、图像等）收集数据，并以结构化方式将它们互连，以提高过程性能。我的研究项目的长期目标包括开发新的数据驱动和系统工程方法，以减少可变性，改善流程操作和产品质量，并将其应用于对加拿大经济重要的工业领域。目的是帮助保持国际竞争力，加速工艺和产品开发，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我的团队最近设计的两种新的潜在变量方法，即顺序多块PLS回归（SMB-PLS）和未抽取小波变换 - 多元图像分析（UWT-MIA）将适用于解决原材料选择问题，并开发基于图像的传感器和工具用于过程和质量控制。还将开发用于设置原材料属性多元规格的通用框架，以应对工业中发现的大多数实际情况。还将提出多元工艺能力指标，以比较材料供应商满足客户规格的可能性。这些工具将有助于确保顺利进行。流程操作，实现该研究还旨在开发先进的过程分析技术（PAT），用于食品包装或气体分离应用中聚合物薄膜的在线质量控制。基于成像热成像的技术将被设计来改善薄膜的质量控制，这对于尽早发现产品缺陷、快速诊断原因并采取适当的补救措施以减少不合格的材料和生产成本非常重要。将提出活细胞成像工具来评估细胞他们将帮助研究人员和生物技术/生物制药行业利用其高通量筛选平台加速新细胞培养基、细胞疗法和药物的开发。该计划将在实践中转移方法和工具方面发挥领导作用，并帮助提高加拿大工业的竞争力。