2022 Volume 35 Issue 5 Pages 310-314
The efficiency improvement of inputting information on paper manifest is an issue in the office work of industrial waste disposal companies. AI-OCR and RPA were introduced on a trial basis in order to verify the possibility and cost-effectiveness of efficiency improvement and automation of paper manifest input work by information technology. We confirmed the usage status of multiple forms of paper manifests, grasped the rate of correct reading of input information by AI-OCR, and measured the work time of transfer to the core business system by RPA.
The ratio of paper manifest forms that were used at five or more per day (defined as the ‘standard form rate’) was as high as approximately 90％, and the percentage of correct answers to all items read using AI-OCR was 87.0％ in average. AI-OCR has a function to learn the reading result in the past, so the reading accuracy may be improved, if the number of registration increases in future. Especially, it is necessary to unify full-width and half-width and address notation in order to raise the reading accuracy. In addition, as for the transcription work time by RPA, the data input time (including confirmation and correction) per 1 sheet was 50.2 seconds/sheet for a typical input pattern. In the case of the atypical input pattern, the automation was difficult, and the conventional manual input was necessary. Based on this, the suggestion that it is realistic to divide the automation work and the non-automation work first, and to raise the proportion of the former which applies RPA was obtained.
