In any manufacturing or production process, data collection is important to ensure proper and efficient process operation. For example, in a document production environment (such as a print shop), operators must monitor workflow information about each job that is being printed. The information is collected and analyzed to identify and address any issues that may have arisen during the production, as well as to identify areas for potential improvement.
Many production environments still use manual data collection methods for collecting workflow related information. Although many production environments have managed information systems that can automatically capture shop floor data, the data from these systems is not always accessible, it requires expensive monitoring equipment, and it does not allow for manual observations and judgments to be captured in an effective manner. As a result, manual recordkeeping is still a common form of data collection in a shop floor environment. Unfortunately, manual entries are often difficult to interpret, error prone, and require additional time to convert into a digital format for electronic storage. Often, the data is not viewed and analyzed until weeks after it has been collected and, therefore, entry and process errors are not identified in a timely manner.
This document describes methods and systems that are directed to solving at least some of the problems described above.