PRODUCTION LOG DATA ANALYSIS FOR REJECT RATE PREDICTION AND WORKLOAD ESTIMATION

Authors: 
Pfeiffer, András & Gyulai, Dávid & Szaller, Ádám & Monostori, Laszlo
Year: 
2018 (published)
DOI: 
10.1109/WSC.2018.8632482
Open access: 
Yes
Abstract: 
The main focus of the research presented in this paper is to propose new methods for filtering and cleaning large-scale production log data by applying statistical learning models. Successful application of the methods in consideration of a production optimization and a simulation-based prediction framework for decision support is presented through an industrial case study. Key parameters analysed in the computational experiments are fluctuating reject rates that make capacity estimations on a shift basis difficult to cope with. The most relevant features of simulation-based workload estimation are extracted from the products’ final test log, which process has the greatest impact on the variance of workload parameters.
SCI: 
No
Kiemelt: 
No
Pdf: 
No
Place of publication: 
https://www.informs-sim.org/wsc18papers/includes/files/298.pdf