Decreasing the moisture content variation of flakes in the drying process of Oriented Strand Board (OSB) manufacturing using multivariate time-series pattern discovery

使用多元时间序列模式发现来减少定向刨花板 (OSB) 制造干燥过程中薄片的含水量变化

• 批准号: 529533-2018
• 负责人: Wong, Andrew
• 金额: $ 1.82万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 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=668779
• 关键词: Decreasing; moisture; content; variation; flakes

Decreasing the variation in moisture content of flakes from the drying process is important for cutting the**manufacturing cost of Oriented Strand Board (OSB). A 1% reduction in the standard deviation of the moisture**worths more than $1 million manufacturing cost/year for a typical sized mill. The manufacturing process of**OSB involves cutting logs into flakes, drying the flakes, adding glue and wax, forming the flakes into a**uniform mat and then hot pressing the mat into panels approximately 4 foot by 8 feet. The drying process must**overcome challenges such as the highly variable moisture content of the raw logs, the mixing of flakes from**multiple dryers with different operating characteristics, the time delays of 10 minutes within the dryers and the**time delays of several hours between the dryers and the mat forming station where the moisture sensors are**located, etc. The mill maintains a large database with hundreds of operating variables recorded at high**frequency (every minute or less). Multivariate time-series pattern discovery thus has the potential to navigate**this large database and identify the optimum operating strategy and conditions that minimize the flake moisture**variability.

减少干燥过程中薄片含水量的变化对于降低定向刨花板（OSB）的制造成本非常重要。对于一个典型尺寸的磨机来说，水分标准偏差 ** 降低1%，每年的制造成本就超过100万美元。OSB的制造过程包括将原木切成薄片，干燥薄片，加入胶水和蜡，将薄片制成均匀的垫子，然后将垫子热压成大约4英尺乘8英尺的面板。干燥过程必须 ** 克服各种挑战，例如原木的水分含量变化很大，来自 ** 多个具有不同操作特性的干燥机的薄片的混合，干燥机内10分钟的时间延迟以及干燥机和湿度传感器 ** 所在的垫形成站之间的 ** 数小时的时间延迟，轧机维护着一个大型数据库，其中有数百个以高 ** 频率（每分钟或更少）记录的操作变量。因此，多元时间序列模式发现有可能导航 ** 这个大型数据库，并确定最佳的操作策略和条件，最大限度地减少薄片水分 ** 的变化。