Scalable Analytics for Extracting Control Insights from Historical Process Data: with Applications in the Pulp and Paper Industry
用于从历史过程数据中提取控制见解的可扩展分析:在纸浆和造纸行业中的应用
基本信息
- 批准号:531114-2018
- 负责人:
- 金额:$ 2.91万
- 依托单位:
- 依托单位国家:加拿大
- 项目类别:Collaborative Research and Development Grants
- 财政年份:2020
- 资助国家:加拿大
- 起止时间:2020-01-01 至 2021-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
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.
几十年来,森林产品工业一直是加拿大经济的推动力。这一领域的活动帮助创造了数千个就业机会、新社区、优良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,以及旨在降低绿色气体排放和改善环境可持续性的政府法规的增加。因此,加拿大的木制品行业目前正在经历其历史上最严重的经济衰退。
在该行业的许多产品中,纸浆和纸张占很大比例。纸浆和造纸工业每年为经济贡献数十亿美元,并直接雇用数万人。数以千计的人还受雇于支持纸浆和造纸工业的二级企业。该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,本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。
三个建立UBC的研究人员,在过程控制,计算机科学和数学,将领导一个团队,包括2博士。学生们可以改进牛皮纸工艺的当前模型并开发数据分析解决方案,将历史工艺数据转化为知识和决策。学术和工业合作伙伴将密切合作,以保持项目的重点和相关性。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Gopaluni, Bhushan其他文献
A Novel Approach to Alarm Causality Analysis Using Active Dynamic Transfer Entropy
- DOI:
10.1021/acs.iecr.9b06262 - 发表时间:
2020-05-06 - 期刊:
- 影响因子:4.2
- 作者:
Luo, Yi;Gopaluni, Bhushan;Zhu, Qun-Xiong - 通讯作者:
Zhu, Qun-Xiong
Targeted deep learning classification and feature extraction for clinical diagnosis.
- DOI:
10.1016/j.isci.2023.108006 - 发表时间:
2023-11-17 - 期刊:
- 影响因子:5.8
- 作者:
Tsai, Yiting;Nanthakumar, Vikash;Mohammadi, Saeed;Baldwin, Susan A.;Gopaluni, Bhushan;Geng, Fei - 通讯作者:
Geng, Fei
Gopaluni, Bhushan的其他文献
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{{ truncateString('Gopaluni, Bhushan', 18)}}的其他基金
Scalable Analytics for Extracting Control Insights from Historical Process Data: with Applications in the Pulp and Paper Industry
用于从历史过程数据中提取控制见解的可扩展分析:在纸浆和造纸行业中的应用
- 批准号:
531114-2018 - 财政年份:2021
- 资助金额:
$ 2.91万 - 项目类别:
Collaborative Research and Development Grants
Towards Self Driving Processes: Leveraging the Data Revolution
迈向自动驾驶流程:利用数据革命
- 批准号:
RGPIN-2017-05794 - 财政年份:2021
- 资助金额:
$ 2.91万 - 项目类别:
Discovery Grants Program - Individual
Towards Self Driving Processes: Leveraging the Data Revolution
迈向自动驾驶流程:利用数据革命
- 批准号:
RGPIN-2017-05794 - 财政年份:2020
- 资助金额:
$ 2.91万 - 项目类别:
Discovery Grants Program - Individual
Deep Learning Enabled Maintenance Free Control
深度学习支持免维护控制
- 批准号:
536418-2018 - 财政年份:2020
- 资助金额:
$ 2.91万 - 项目类别:
Collaborative Research and Development Grants
Scalable Analytics for Extracting Control Insights from Historical Process Data: with Applications in the Pulp and Paper Industry
用于从历史过程数据中提取控制见解的可扩展分析:在纸浆和造纸行业中的应用
- 批准号:
531114-2018 - 财政年份:2019
- 资助金额:
$ 2.91万 - 项目类别:
Collaborative Research and Development Grants
Deep Learning Enabled Maintenance Free Control
深度学习支持免维护控制
- 批准号:
536418-2018 - 财政年份:2019
- 资助金额:
$ 2.91万 - 项目类别:
Collaborative Research and Development Grants
Towards Self Driving Processes: Leveraging the Data Revolution
迈向自动驾驶流程:利用数据革命
- 批准号:
RGPIN-2017-05794 - 财政年份:2019
- 资助金额:
$ 2.91万 - 项目类别:
Discovery Grants Program - Individual
Process analytics to predict arc loss in an electric arc furnace**
预测电弧炉电弧损耗的过程分析**
- 批准号:
536692-2018 - 财政年份:2018
- 资助金额:
$ 2.91万 - 项目类别:
Engage Grants Program
Towards Self Driving Processes: Leveraging the Data Revolution
迈向自动驾驶流程:利用数据革命
- 批准号:
RGPIN-2017-05794 - 财政年份:2018
- 资助金额:
$ 2.91万 - 项目类别:
Discovery Grants Program - Individual
Towards Self Driving Processes: Leveraging the Data Revolution
迈向自动驾驶流程:利用数据革命
- 批准号:
RGPIN-2017-05794 - 财政年份:2017
- 资助金额:
$ 2.91万 - 项目类别:
Discovery Grants Program - Individual
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