An in vitro diagnostic instrument maintenance apparatus (100, 300), comprising: one or more monitoring devices (102A, 102B) configured to monitor condition-based parameters of one or more instrument components of one or more instruments (104A, 104B, 104C, 104N); a local data server (106, 306) coupled to the one or more monitoring devices (102A, 102B), the local data server including: a checking module configured to: test functionality of the one or more instrument components, and obtain the condition-based parameters of the one or more instrument components; a local database configured to contain a compilation of the condition-based parameters; and a remote server configured to communicate with the local data server and configured to receive and store the condition-based parameters in a condition-based maintenance parameter database, the remote server including a memory comprising: the CBM parameter database, a failure prediction engine module, a failure pattern library, a failure rules module, and a rules database, wherein the condition-based parameters comprise one or more of: a temperature of a component of the in vitro diagnostic instrument (104A, 104B, 104C, 104N); a pressure in a component of the in vitro diagnostic instrument (104A, 104B, 104C, 104N); a liquid level in a component of the in vitro diagnostic instrument (104A, 104B, 104C, 104N); a current drawn by a component of the in vitro diagnostic instrument (104A, 104B, 104C, 104N); a flow rate through a component of the in vitro diagnostic instrument (104A, 104B, 104C, 104N); and a backlash in a pump component of the in vitro diagnostic instrument (104A, 104B, 104C, 104N); the failure prediction engine module compares condition-based parameters stored in the CBM parameter database against failure patterns and/or normal patterns stored in the failure pattern library; and the failure rules module, based on a rule collected from the rules database, launches a suitable action if the condition-based parameters stored in the CBM parameter database are determined to be dissimilar enough from a normal pattern or similar enough compared to a failure pattern stored in the failure pattern library. one or more monitoring devices (102A, 102B) configured to monitor condition-based parameters of one or more instrument components of one or more instruments (104A, 104B, 104C, 104N); a local data server (106, 306) coupled to the one or more monitoring devices (102A, 102B), the local data server including: a checking module configured to: test functionality of the one or more instrument components, and obtain the condition-based parameters of the one or more instrument components; test functionality of the one or more instrument components, and obtain the condition-based parameters of the one or more instrument components; a local database configured to contain a compilation of the condition-based parameters; and a remote server configured to communicate with the local data server and configured to receive and store the condition-based parameters in a condition-based maintenance parameter database, the remote server including a memory comprising: the CBM parameter database, a failure prediction engine module, a failure pattern library, a failure rules module, and a rules database, the CBM parameter database, a failure prediction engine module, a failure pattern library, a failure rules module, and a rules database, wherein the condition-based parameters comprise one or more of: a temperature of a component of the in vitro diagnostic instrument (104A, 104B, 104C, 104N); a pressure in a component of the in vitro diagnostic instrument (104A, 104B, 104C, 104N); a liquid level in a component of the in vitro diagnostic instrument (104A, 104B, 104C, 104N); a current drawn by a component of the in vitro diagnostic instrument (104A, 104B, 104C, 104N); a flow rate through a component of the in vitro diagnostic instrument (104A, 104B, 104C, 104N); and a backlash in a pump component of the in vitro diagnostic instrument (104A, 104B, 104C, 104N); a temperature of a component of the in vitro diagnostic instrument (104A, 104B, 104C, 104N); a pressure in a component of the in vitro diagnostic instrument (104A, 104B, 104C, 104N); a liquid level in a component of the in vitro diagnostic instrument (104A, 104B, 104C, 104N); a current drawn by a component of the in vitro diagnostic instrument (104A, 104B, 104C, 104N); a flow rate through a component of the in vitro diagnostic instrument (104A, 104B, 104C, 104N); and a backlash in a pump component of the in vitro diagnostic instrument (104A, 104B, 104C, 104N); the failure prediction engine module compares condition-based parameters stored in the CBM parameter database against failure patterns and/or normal patterns stored in the failure pattern library; and the failure rules module, based on a rule collected from the rules database, launches a suitable action if the condition-based parameters stored in the CBM parameter database are determined to be dissimilar enough from a normal pattern or similar enough compared to a failure pattern stored in the failure pattern library.