Computer Configuration Comparison for Maintenance Diagnostics
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Diagnosing and troubleshooting malfunctioning computers remains a time-consuming and challenging task due to the difficulty in comparing configurations and performance of individual machines with properly functioning peers, especially when finding comparably configured models is hard.
Innovation Solution
A system and method that utilize a cluster database and tracker database to compare configuration information values of individual computers with typical cluster members, indicating how closely the computer's configuration conforms to peer group standards, aiding in maintenance and servicing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If service personnel manually diagnose and troubleshoot malfunctioning computers by guessing possible causes and trying various fixes, then they can eventually resolve the problem, but the process becomes time-consuming and requires considerable experience and ingenuity
Solution Approach 1:
The system performs preliminary actions by automatically gathering configuration information from the malfunctioning computer and comparing it with configuration data from a database of properly functioning peer computers before service personnel begin their diagnosis. This preliminary automated comparison identifies configuration differences that may be causing the problem, providing service personnel with targeted leads rather than requiring them to start from scratch with manual guessing and testing.
2Reliability
If service personnel manually diagnose and troubleshoot malfunctioning computers by guessing possible causes and trying various fixes, then they can eventually resolve the problem, but it may involve replacing hardware components or re-installing software components that were not actually needed, wasting both time and materials
Solution Approach 1:
The system performs preliminary automated configuration comparison before service personnel begin their troubleshooting, identifying specific configuration differences between the malfunctioning computer and properly functioning peers. This preliminary analysis provides targeted guidance on what configuration changes to test, preventing service personnel from unnecessarily replacing hardware components or re-installing software that is already correctly configured.
3Reliability
If computers are clustered into groups for automated backup and monitoring, then critical services can be kept fully operative even when some computers are placed out of service, but the task of diagnosing problems in malfunctioning computers remains difficult and time-consuming
Solution Approach 1:
The system segments the diagnosis task into two parts: (1) automated segmentation that gathers configuration information from the malfunctioning computer and segments it into comparable parameters, and (2) automated comparison with peer group configurations. This segmentation reduces diagnosis complexity by handling the data gathering and initial analysis automatically, leaving service personnel to focus on interpreting the identified configuration differences and applying appropriate fixes.
Data Source
AI summary
The present invention is a system or method for assisting in the maintenance and servicing of computers. The system, for example, comprises a cluster database containing information relating to one or more computer clusters, the information relating to each cluster comprising one or more cluster descriptions and one or more representations of configuration information values that characterize typical computer members of the cluster, and also a tracker database containing configuration information values gathered from and relating to one or more computers. The system further comprises a computer and cluster comparison routine having access to the cluster and tracker databases that compares one or more of the representations of configuration information values relating to one or more of the clusters to one or more of the corresponding configuration information values gathered from at least one given computer and that then indicates how closely the given computer's configuration conforms with the configuration of typical computer members of the one or more clusters.