Systems and methods for automated image quality based diagnostics and remediation of document processing systems

Abstract

During the operation of a document processing system machine and job data are collected from a document processing system. Optionally, machine information, both for the specific machine and population based data are acquired from a database or server. Having accumulated the job data and machine data, the diagnostic inference engine performs an analysis to determine the initial diagnosis of the document processing system. After obtaining the initial diagnosis, the system determines the test patterns to be printed and the image quality tests to be performed. The system then prints test patterns, and scans the patterns to determine image quality parameters and/or to automatically identify image defects. Optionally, image defect information may also be provided by the customer or the service engineer via a user interface. Next, a diagnostic inference engine uses the results of the image quality analysis to refine the initial diagnosis. Then, the diagnostic results are output, stored, and optionally displayed to, for example a customer or a customer service engineer. Based on the diagnostic results, and if problems are found, the machine enters a repair sequence. In particular, the machine can request either a customer or a customer service engineer repair action, or, alternatively, enter an auto-correction or an auto-calibration mode to repair itself. Upon completion of one or more, or any combination, of these repair actions, the machine verifies its operation and again checks to ensure the repairs have been completed successfully.