OPENZDM solutions for AI quality assessment and decision support aim for data driven defect prediction and estimation of machine components degradation through drifts in data distribution. The main goal is to predict defects such as broken paper, dust or glued paper so that changes in machinery/parameters can be performed and the defect avoided and also to estimate degradation based on slight and smooth changes in the process start occurring due to component wear-out / degradation and, if data is representative enough, it may be different data distributions in time.
Comment:
OPENZDM solutions for AI quality assessment and decision support aim for data driven defect prediction and estimation of machine components degradation through drifts in data distribution. The main goal is to predict defects such as broken paper, dust or glued paper so that changes in machinery/parameters can be performed and the defect avoided and also to estimate degradation based on slight and smooth changes in the process start occurring due to component wear-out / degradation and, if data is representative enough, it may be different data distributions in time.