A maintenance method for a laboratory system comprising a first and second group of laboratory instruments for processing biological samples, data collection components connected to the groups of instruments, and a remote maintenance system connected to the data collection components is presented. The method comprises collecting operational data from the laboratory instruments by the data collection components, detecting an anomaly related to the laboratory instruments by a first data collection component, transmitting context data to the remote maintenance system upon detection of an anomaly, determining correlation(s) between the operational data and the anomaly(s), validating the correlation(s), determining at the remote maintenance system predictive rules corresponding to validated correlations, transmitting the predictive rule(s) to the data collection components, and predicting occurrence of an anomaly of laboratory instruments based on the one or more predictive rule(s) by the data collection components.

Discussed herein are systems, methods, and apparatuses for quality control monitoring of laboratory analyzers. A method can include receiving test results from laboratory analyzers, the test results corresponding to a same analyte, determining a standard deviation of differences (SDD) among pairs of the multiple test results, calibrating the laboratory analyzer based on the determined SDD.

A method for performing quality control on a diagnostic analyzer includes receiving control measurement values from each of a plurality of diagnostic analyzers. A quality control measurement value is received from a target diagnostic analyzer. The quality control measurement value is compared with statistical criteria associated with the plurality of quality control measurement values received from the plurality of diagnostic analyzers. A comparison result is communicated to a user interface associated with the target diagnostic analyzer.

A method for performing quality control on a diagnostic analyzer includes receiving control measurement values from each of a plurality of diagnostic analyzers. A quality control measurement value is received from a target diagnostic analyzer. The quality control measurement value is compared with statistical criteria associated with the plurality of quality control measurement values received from the plurality of diagnostic analyzers. A comparison result is communicated to a user interface associated with the target diagnostic analyzer.

Systems and methods for predicting a condition of an engine are described herein. A fluid sample having particles suspended therein is received from the engine. A plurality of particles are extracted from the fluid sample. A sample profile of the plurality of particles extracted from the fluid sample is obtained. A reference profile of particles of a reference fluid sample from a reference engine is obtained. The reference profile and the sample profile having particles identified based on size, aspect ratio and chemical composition. A correlation index between the sample profile and the reference profile is determined based on size and aspect ratio of the particles of the sample profile and the reference profile. A prediction that the engine has a known condition associated with the reference engine is generated from the correlation index. An output indicating the condition of the engine is generating based on the prediction.

Various embodiments include methods and apparatuses to reduce false-particle counts in a water-based condensation particle counter (CPC). In one embodiment, a cleanroom CPC has three parallel growth tube assemblies. A detector is coupled to an outlet of each of the three parallel growth tube assemblies, and is used to compare the particle concentrations measured from each of the three growth tube assemblies. An algorithm compares the counts from the three detectors and determines when the particles counted are real and when they are false counts. Any real particle event shows up in all three detectors, while false counts will only be detected by one detector. Statistics are used to determine at which particle count levels the measured counts are considered to be real versus false. Other methods and apparatuses are disclosed.

A kit and method for evaluation of the quality and the operating parameters of any types of fully automated open ELISA instruments are disclosed. The kit and method can be used to reliably assess quality control parameters including precision, volume removal accuracy, plate reader accuracy, plate reader linearity, plate washer quality, drift absence, and carryover absence. The evaluation can be completed in a timely and cost-effective manner and provide laboratories with the ability to readily validate the operation and performance of a fully automated ELISA instrument.

Various embodiments include methods and apparatuses to reduce false-particle counts in a water-based condensation particle counter (CPC). In one embodiment, a cleanroom CPC has three parallel growth tube assemblies. A detector is coupled to an outlet of each of the three parallel growth tube assemblies, and is used to compare the particle concentrations measured from each of the three growth tube assemblies with remaining ones of the three growth tube assemblies. An algorithm compares the counts from the three detectors and determines when the particles counted are real and when they are false counts. Any real particle event shows up in all three detectors, while false counts will only be detected by one detector. Statistics are used to determine at which particle count levels the measured counts are considered to be real versus false. Other methods and apparatuses are disclosed.

Various embodiments include methods and apparatuses to reduce false-particle counts in a water-based condensation particle counter (CPC). In one embodiment, a cleanroom CPC has three parallel growth tube assemblies. A detector is coupled to an outlet of each of the three parallel growth tube assemblies, and is used to compare the particle concentrations measured from each of the three growth tube assemblies. An algorithm compares the counts from the three detectors and determines when the particles counted are real and when they are false counts. Any real particle event shows up in all three detectors, while false counts will only be detected by one detector. Statistics are used to determine at which particle count levels the measured counts are considered to be real versus false. Other methods and apparatuses are disclosed.

Provided are a quality control method, a quality control system, a management apparatus, an analyzer, and a quality control abnormality determination method in which measurement results of both a quality control substance and a specimen are sufficiently utilized to improve the quality of quality control. The quality control method used in a management apparatus which is connected via a network to an analyzer installed in each of a plurality of facilities includes obtaining, from an analyzer in each facility via a network, first quality control information obtained by measuring an artificially generated quality control substance, and second quality control information obtained by measuring a plurality of specimens by the analyzer in each facility; and outputting information concerning quality control of an analyzer in at least one facility, based on the obtained first quality control information and second quality control information.