Stopping Time Detection of Wood Panel Compression: A Functional Time-Series Approach

Author:

Shang Han Lin1234,Cao Jiguo56,Sang Peijun78

Affiliation:

1. Department of Actuarial Studies and Business Analytics , Sydney , New SouthWales , Australia

2. Macquarie University , Sydney , New SouthWales , Australia

3. Department of Actuarial Studies and Business Analytics , Sydney , , New South Wales , Australia

4. Macquarie University , Sydney , , New South Wales , Australia

5. Department of Statistics and Actuarial Science , Burnaby , , British Columbia , Canada

6. Simon Fraser University , Burnaby , , British Columbia , Canada

7. Department of Statistics and Actuarial Science , Waterloo , , Ontario , Canada

8. University of Waterloo , Waterloo , , Ontario , Canada

Abstract

Abstract We consider determining the optimal stopping time for the glue curing of wood panels in an automatic process environment. Using the near-infrared spectroscopy technology to monitor the manufacturing process ensures substantial savings in energy and time. We collect a time-series of curves from a near-infrared spectrum probe consisting of 72 spectra and aim to detect an optimal stopping time. We propose an estimation procedure to determine the optimal stopping time of wood panel compression and the estimation uncertainty associated with the estimated stopping time. Our method first divides the entire data set into a training sample and a testing sample, then iteratively computes integrated squared forecast errors based on the testing sample. We then apply a structural break detection method with one breakpoint to determine an estimated optimal stopping time from a univariate time-series of the integrated squared forecast errors. We also investigate the finite sample performance of the proposed method via a series of simulation studies.

Publisher

Oxford University Press (OUP)

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

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