A method of providing dynamic analysis for troubleshooting in vitro diagnostics instrument issues, the method comprising: receiving, at a second computing device in communication with a plurality of instruments, identification of an issue associated with a portion of an instrument of the plurality of instruments, the identification received from a first computing device in communication with the instrument; accessing, by a central computing device, data from one or more databases; determining, by the central computing device, an ordering of one or more corrective actions for resolving the issue by applying the data to a probabilistic model based on patterns from the plurality of instruments and operator input; and providing, by the central computing device, the one or more corrective actions in the determined order to the first computing device to be displayed via a user interface at the instrument, wherein the second computing device is the central computing device, and wherein the method employs an intelligent service assistant expert system comprising - a case-based reasoner, - a rules-based reasoner and - a troubleshooting reference model, wherein the one or more databases store rules, wherein said rules link issues to corrective actions based on the reported success/failure patterns across the fleet of instruments, and wherein the troubleshooting reference model employs a graph structure, wherein known cases are attached in the leaves of the graph structure wherein the intelligent service assistant expert system semi-automatically identifies said issue patterns across the plurality of instruments and creates additional rules, and wherein - the intelligent service assistant case-based reasoner reuses similar cases to understand a problem and suggests a solution based on prior documented experience; and - the intelligent service assistant rules-based reasoner is used to derive new rules for the intelligent service assistant knowledge base with the goal to connect an explicit issue to specific corrective actions to achieve an event-code driven intelligent service assistant behavior; and - the intelligent service assistant troubleshooting reference model provides a representation of troubleshooting body of knowledge in the form of a standard model which can be used to derive general rules from. receiving, at a second computing device in communication with a plurality of instruments, identification of an issue associated with a portion of an instrument of the plurality of instruments, the identification received from a first computing device in communication with the instrument; accessing, by a central computing device, data from one or more databases; determining, by the central computing device, an ordering of one or more corrective actions for resolving the issue by applying the data to a probabilistic model based on patterns from the plurality of instruments and operator input; and providing, by the central computing device, the one or more corrective actions in the determined order to the first computing device to be displayed via a user interface at the instrument, wherein the second computing device is the central computing device, and wherein the method employs an intelligent service assistant expert system comprising - a case-based reasoner, - a rules-based reasoner and - a troubleshooting reference model, - a case-based reasoner, - a rules-based reasoner and - a troubleshooting reference model, wherein the one or more databases store rules, wherein said rules link issues to corrective actions based on the reported success/failure patterns across the fleet of instruments, and wherein the troubleshooting reference model employs a graph structure, wherein known cases are attached in the leaves of the graph structure wherein the intelligent service assistant expert system semi-automatically identifies said issue patterns across the plurality of instruments and creates additional rules, and wherein - the intelligent service assistant case-based reasoner reuses similar cases to understand a problem and suggests a solution based on prior documented experience; and - the intelligent service assistant rules-based reasoner is used to derive new rules for the intelligent service assistant knowledge base with the goal to connect an explicit issue to specific corrective actions to achieve an event-code driven intelligent service assistant behavior; and - the intelligent service assistant troubleshooting reference model provides a representation of troubleshooting body of knowledge in the form of a standard model which can be used to derive general rules from. - the intelligent service assistant case-based reasoner reuses similar cases to understand a problem and suggests a solution based on prior documented experience; and - the intelligent service assistant rules-based reasoner is used to derive new rules for the intelligent service assistant knowledge base with the goal to connect an explicit issue to specific corrective actions to achieve an event-code driven intelligent service assistant behavior; and - the intelligent service assistant troubleshooting reference model provides a representation of troubleshooting body of knowledge in the form of a standard model which can be used to derive general rules from.