Scalable Analytics for Extracting Control Insights from Historical Process Data: with Applications in the Pulp and Paper Industry

几十年来，林产品行业一直是加拿大经济的推动力。该部门的活动帮助创造了数以千计的就业机会、新的社区、一流的基础设施和世界上任何地方都无法超越的生活方式。该行业占加拿大制造业总出货量和国内生产总值的最大部分。近年来，该行业面临着许多新的挑战，包括来自国外生产的低成本材料的激烈竞争，以及旨在降低温室气体排放和改善环境可持续性的政府监管不断加强。因此，加拿大的木制品行业目前正经历其历史上最严重的经济衰退。在该行业的许多产品中，纸浆和纸张占了相当大的比例。纸浆和造纸业每年为经济贡献数十亿美元，直接雇用数万人。数以千计的人还受雇于支持纸浆和造纸业的第二企业。这一部门包括制造出口到世界各地的设备和系统的公司。鉴于纸浆和造纸工业对加拿大经济的重要性及其目前的经济困境，该行业的各种工艺必须以高效、自主和环境可持续的水平运行。考虑到这一目标，这项研究项目解决了模型识别和故障检测与诊断方面的重要挑战。三名来自过程控制、计算机科学和数学领域的UBC研究人员将带领一个包括两名博士生在内的团队改进当前的卡夫过程模型，并开发数据分析解决方案，将历史过程数据转化为知识和决策。学术界和产业界的合作伙伴将密切合作，以保持项目的重点和相关性。

The forest products industry has been a driving force in Canada's economy for decades. Activity in this sector has helped create thousands of jobs, new communities, excellent infrastructure and a lifestyle that is unsurpassed anywhere in the world. This industry accounts for the largest portion of Canada's total manufacturing shipments and gross domestic product. In recent years, this industry has faced a number of new challenges, including stiff competition from low cost materials produced abroad and increasing government regulations aimed at lowering green house gas emissions and improving environmental sustainability. As a result, Canada's wood products industry is currently undergoing the most severe economic downturn in its history.Among the industry's many products, pulp and paper make up a significant fraction. The pulp and paper industry contributes billions of dollars to the economy each year, and directly employs tens of thousands of people. Thousands of people are also employed by secondary businesses that support the pulp and paper industry. This sector includes companies that manufacture equipment and systems that are exported to all parts of the world. Given the importance of the pulp and paper industry to Canada's economy and its current economic troubles, it is imperative that the various processes in this industry are operated at levels that are highly efficient, autonomous, and environmentally sustainable. With this goal in mind, this research project addresses important challenges in model identification and fault detection and diagnosis.Three established UBC researchers, in process control, computer science, and mathematics, will lead a team including 2 Ph.D. students to refine current models of the kraft process and develop data analytics solutions to transform historical process data into knowledge and decisions. The academic and industrial partners will work together closely to keep the project focussed and relevant.