Information Technology Infrastructure for Augmented Problem Solving in Process Systems

用于增强过程系统问题解决的信息技术基础设施

• 批准号: RGPIN-2018-04549
• 负责人: Chan, Christine
• 金额: $ 2.48万
• 依托单位: University of Regina
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=647110
• 关键词: Information; Technology; Infrastructure; Augmented; Problem

***Intelligent decision support systems (DSSs) and applications of artificial intelligence (AI) play a key role in improving productivity of Canadian industries. The Information Technology Association of Canada (ITAC) advocated that Canada expands her development and adoption of information and communications technology (ICT) so as to drive stronger productivity across all sectors of the economy. It is estimated that the Canadian market for the "internet of things" solutions would grow from $5 billion in 2013 to $21.1 billion in 2018 [ITAC report, Feb 16, 2015]. Speaking to CNN (F. Zakaria) at the World Economic Forum at Davos Switzerland in 2017, Ginni Rometty, current IBM CEO, described AI's role in the partnership between humans and machines as “augmented cognition”. In other words, AI not only supports but augments human cognition so that humans can be more efficient and “do a better job” (http://machinelearning.ai/artificial-intelligence/davos-2017-ibm-ceo-ginni-rometty-on-artificial-intelligence/, retrieved on July 23, 2017). In building intelligent DSSs that support human problem solving, a fundamental and most difficult step is knowledge acquisition, mainly due to the implicit nature of knowledge [Breuker, 2013]. ******The objective of the proposed research is to build an information technology infrastructure for knowledge acquisition (KA), which will support building intelligent DSSs that augment the problem solving abilities of human operators when they encounter operational problems in engineering process systems. The rule extraction approach will be adopted because it can generate interpretable rules from a well-trained artificial neural network (ANN) model. The explicit knowledge will be integrated with human expertise for building intelligent DSSs. This approach can effectively make use of the vast amount of data generated by the Canadian process industries while also overcoming the KA bottleneck. The KA infrastructure will be applied to the carbon dioxide capture process system and the cyclic solvent injection process for heavy oil recovery. The former is a key technology for cutting harmful carbon dioxide emissions from coal-fired power generation, and the latter system is a recovery method of heavy oil, a key resource important for sustaining the Canadian economy for many decades to come. The research results of the KA method, algorithms, and DSSs will benefit industrial engineers and operators. The insights and lessons learned in the research project would enable them to better understand the complex engineering process systems, and the DSSs would support them in solving operational problems in a timely manner and avoid downtime. The research results and HQP trained will contribute to information technology advancement of industrial operations related to energy production and greenhouse gas reduction in the Canadian economy.********************************************

***智能决策支持系统（DSS）和人工智能（AI）的应用在提高加拿大行业的生产率方面起着关键作用。加拿大信息技术协会（ITAC）主张加拿大扩大了她的信息和通信技术（ICT）的发展和采用，以提高经济各个部门的强大生产力。据估计，“物联网”解决方案的加拿大市场将从2013年的50亿加元增长到2018年的211亿加元[ITAC报告，2015年2月16日]。现任IBM首席执行官Ginni Rometty在2017年在达沃斯瑞士世界经济论坛上与CNN（F. Zakaria）进行了交谈，将AI在人类和机器之间的伙伴关系中的作用描述为“增强认知”。换句话说，AI不仅支持人类的认知，因此人类可以更有效并“做得更好”（http://machinelearning.ai/artaver-cover-intelligence/davos-2017-ibm-ceo-ceo-ceo-ceo-ceo-ceo-ginni-rometty-rometty-rometty-noty-on- and- arndercover-intelligence/，2017年7月23日，2017年7月回溯。在构建支持人类问题解决的智能DSS时，一个基本和最困难的步骤是知识获取，这主要是由于知识的隐含性[Breuker，2013年]。 *****拟议的研究的目的是建立一个知识获取（KA）的信息技术基础架构，该基础架构将支持构建智能DSSS，以增强人类操作员在工程过程中遇到操作问题时解决问题的能力。将采用规则提取方法，因为它可以从训练有素的人工神经元网络（ANN）模型中生成可解释的规则。明确的知识将与人类的专业知识集成，以构建智能DSSS。这种方法可以有效地利用疫苗加拿大流程行业产生的数据量，同时也克服了KA瓶颈。 KA基础设施将应用于二氧化碳捕获过程系统和循环溶液注入过程，以进行重油回收。前者是从燃煤发电中削减有害二氧化碳排放的关键技术，后来的系统是一种重油的恢复方法，这对于维持加拿大经济的未来几十年很重要。 KA方法，算法和DSSS的研究结果将使工业工程师和运营商受益。研究项目中所学的见解和教训将使他们能够更好地了解复杂的工程过程系统，而DSSS将支持他们及时解决运营问题并避免停机时间。研究结果和经过HQP训练的HQP将有助于信息技术的进步与加拿大经济中的能源生产和减少温室气体有关的工业运营。****