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

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
负责人:
Gopaluni, Bhushan
金额:
$2.91万
依托单位国家:
加拿大
项目类别:
Collaborative Research and Development Grants
财政年份:
2019
资助国家:
加拿大
项目状态:
已结题
起止时间:
2019-01-01 至 2020-12-31

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中文摘要
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英文摘要
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.
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Scalable Analytics for Extracting Control Insights from Historical Process Data: with Applications in the Pulp and Paper Industry
  • 批准号:
    531114-2018
  • 项目类别:
    Collaborative Research and Development Grants
  • 资助金额:
    $1.17万
  • 财政年份:
    2021
  • 负责人:
    Gopaluni, Bhushan
  • 依托单位:
Towards Self Driving Processes: Leveraging the Data Revolution
  • 批准号:
    RGPIN-2017-05794
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $4.81万
  • 财政年份:
    2021
  • 负责人:
    Gopaluni, Bhushan
  • 依托单位:
Towards Self Driving Processes: Leveraging the Data Revolution
  • 批准号:
    RGPIN-2017-05794
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.4万
  • 财政年份:
    2020
  • 负责人:
    Gopaluni, Bhushan
  • 依托单位:
Scalable Analytics for Extracting Control Insights from Historical Process Data: with Applications in the Pulp and Paper Industry
  • 批准号:
    531114-2018
  • 项目类别:
    Collaborative Research and Development Grants
  • 资助金额:
    $2.91万
  • 财政年份:
    2020
  • 负责人:
    Gopaluni, Bhushan
  • 依托单位:
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