Abstract: Risk based lifecycle management systems are presented herein. A system determines a process ontology of a process including process steps of the process and objects including attributes corresponding to performances of the process steps; associates a process step with respective objects using a tracing matrix; detects an event corresponding to a performance of the process step; and associates the event with the process step and the respective objects using the tracing matrix. In response to determining, utilizing a machine learning model, that the event corresponds to a defined risk profile including defined failure modes, the system selects a group of defined failure modes as candidates of causality of the event representing potential multi-variant causes of the event, and sends the candidates of causality of the event directed to a user identity to facilitate mitigation of effects of the potential multi-variant causes of the event on the process.

Abstract: Residual limit determination for a cleaning agent corresponding to a validation of an equipment cleaning process is presented herein. A system determines a cleaning agent for cleaning a group of equipment to be used to manufacture a product; and determines a sum of surface areas of respective surfaces of respective groups of parts of the group of the equipment that have been determined to be contacted by the product and the cleaning agent. Based on the sum of surface areas of the respective surfaces that have been determined to be contacted by the product and the cleaning agent, the system determines a cleaning agent residue limit representing a threshold maximum allowable residue of the cleaning agent to be present after the cleaning process has been performed on the group of equipment, and facilitates a cleaning validation of the cleaning process according to the cleaning agent residue limit.

Abstract: Automated test case validation execution is presented herein. A system obtains image data representing a test result of a test step of a validation process; extracts the test result from the image data; derives an expected result from an expected result sentence that has been obtained from a first cell of a row of a table of a document, in which the row corresponds to the test step; based on the test result and the expected result, determines a test status of the test step; generates a result sentence comprising the test result and a portion of the expected result sentence; generates a javascript object notation (JSON) data structure comprising the result sentence and the test status; and populates, using the JSON data structure, a second cell of the row with the result sentence and a third cell of the row with the test status.

Abstract: Risk based lifecycle management systems are presented herein. A system determines a process ontology of a process including process steps of the process and objects including attributes corresponding to performances of the process steps; associates a process step with respective objects using a tracing matrix; detects an event corresponding to a performance of the process step; and associates the event with the process step and the respective objects using the tracing matrix. In response to determining, utilizing a machine learning model, that the event corresponds to a defined risk profile including defined failure modes, the system selects a group of defined failure modes as candidates of causality of the event representing potential multi-variant causes of the event, and sends the candidates of causality of the event directed to a user identity to facilitate mitigation of effects of the potential multi-variant causes of the event on the process.

Abstract: Residual limit determination for a cleaning agent corresponding to a validation of an equipment cleaning process is presented herein. A system determines a cleaning agent for cleaning a group of equipment to be used to manufacture a product; and determines a sum of surface areas of respective surfaces of respective groups of parts of the group of the equipment that have been determined to be contacted by the product and the cleaning agent. Based on the sum of surface areas of the respective surfaces that have been determined to be contacted by the product and the cleaning agent, the system determines a cleaning agent residue limit representing a threshold maximum allowable residue of the cleaning agent to be present after the cleaning process has been performed on the group of equipment, and facilitates a cleaning validation of the cleaning process according to the cleaning agent residue limit.

Abstract: Validating and maintaining respective validated status of software applications and manufacturing systems and processes is presented herein. A validation system can comprise a mapping component configured to extract, from a set of requirement specification documents, individual requirement specifications; and extract, from a set of test function documents, test steps. Further, the validation system can comprise a tracing component configured to generate a trace matrix associating the individual requirement specifications with respective test steps of the test functions or respective documents of the set of requirement specification documents. In an aspect, the validation system can enforce, via respective object linking and embedding control extensions, respective roles of authors, reviewers, and approvers of the set of requirement specification documents. In another aspect, the validation system can electronically receive and insert test results in the set of test function documents.