Incident Management and Root Cause Analysis

2014 ◽  
pp. 1017-1036 ◽  
Author(s):  
Yasmine Motarjemi ◽  
Carol A. Wallace
Keyword(s):  
Root Cause Analysis ◽  
Incident Management ◽  
Cause Analysis ◽  
Root Cause

scholarly journals Incident Management for Explainable and Automated Root Cause Analysis in Cloud Data Centers    

2021 ◽  
Vol 27 (11) ◽  
pp. 1152-1173
Author(s):  
Arnak Poghosyan ◽  
Ashot Harutyunyan ◽  
Naira Grigoryan ◽  
Nicholas Kushmerick
Keyword(s):  
Rule Learning ◽  
Root Cause Analysis ◽  
Rule Induction ◽  
Incident Management ◽  
Data Sets ◽  
Classification Problems ◽  
Cause Analysis ◽  
Cloud Data ◽  
Root Cause ◽  
High Level

Effective root cause analysis (RCA) of performance issues in modern cloud environ- ments remains a hard problem. Traditional RCA tracks complex issues by their signatures known as problem incidents. Common approaches to incident discovery rely mainly on expertise of users who define environment-specific set of alerts and >target detection of problems through their occurrence in the monitoring system. Adequately modeling of all possible problem patterns for nowadays extremely sophisticated data center applications is a very complex task. It may result in alert/event storms including large numbers of non-indicative precautions. Thus, the crucial task for the incident-based RCA is reduction of redundant recommendations by prioritizing those events subject to importance/impact criteria or by deriving their meaningful groupings into separable situations. In this paper, we consider automation of incident discovery based on rule induction algorithms that retrieve conditions directly from monitoring datasets without consuming the sys- tem events. Rule-learning algorithms are very flexible and powerful for many regression and classification problems, with high-level explainability. Since annotated or labeled data sets are mostly unavailable in this area of technology, we discuss data self-labelling principles which allow transforming originally unsupervised learning tasks into classification problems with further application of rule induction methods to incident detection.

Root Cause analysis of SG tube ODSCC indications within the tube sheets of NPP biblis unit A

2011 ◽  
pp. 78-86
Author(s):  
R. Kilian ◽  
J. Beck ◽  
H. Lang ◽  
V. Schneider ◽  
T. Schönherr ◽  
...  
Keyword(s):  
Root Cause Analysis ◽  
Cause Analysis ◽  
Root Cause

Rule Construction and its Execution for Root Cause Analysis

2012 ◽  
Vol 132 (10) ◽  
pp. 1689-1697
Author(s):  
Yutaka Kudo ◽  
Tomohiro Morimura ◽  
Kiminori Sugauchi ◽  
Tetsuya Masuishi ◽  
Norihisa Komoda
Keyword(s):  
Root Cause Analysis ◽  
Cause Analysis ◽  
Root Cause

Root Cause Analysis Techniques Using Picosecond Time Resolved LADA

2014 ◽  
Author(s):  
Dan Bodoh ◽  
Kent Erington ◽  
Kris Dickson ◽  
George Lange ◽  
Carey Wu ◽  
...  
Keyword(s):  
Integrated Circuits ◽  
Picosecond Laser ◽  
Root Cause Analysis ◽  
Fault Isolation ◽  
Time Resolved ◽  
Cause Analysis ◽  
Root Cause ◽  
Design And Manufacturing ◽  
Multiple Interactions ◽  
Established Technique

Abstract Laser-assisted device alteration (LADA) is an established technique used to identify critical speed paths in integrated circuits. LADA can reveal the physical location of a speed path, but not the timing of the speed path. This paper describes the root cause analysis benefits of 1064nm time resolved LADA (TR-LADA) with a picosecond laser. It shows several examples of how picosecond TR-LADA has complemented the existing fault isolation toolset and has allowed for quicker resolution of design and manufacturing issues. The paper explains how TR-LADA increases the LADA localization resolution by eliminating the well interaction, provides the timing of the event detected by LADA, indicates the propagation direction of the critical signals detected by LADA, allows the analyst to infer the logic values of the critical signals, and separates multiple interactions occurring at the same site for better understanding of the critical signals.

Root Cause Analysis for Pin Leakage

2016 ◽  
Author(s):  
Zhigang Song ◽  
Jochonia Nxumalo ◽  
Manuel Villalobos ◽  
Sweta Pendyala
Keyword(s):  
Failure Analysis ◽  
Root Cause Analysis ◽  
Advanced Technology ◽  
Process Step ◽  
Cause Analysis ◽  
Hard Mask ◽  
Technology Node ◽  
Root Cause ◽  
Tools And Techniques

Abstract Pin leakage continues to be on the list of top yield detractors for microelectronics devices. It is simply manifested as elevated current with one pin or several pins during pin continuity test. Although many techniques are capable to globally localize the fault of pin leakage, root cause analysis and identification for it are still very challenging with today’s advanced failure analysis tools and techniques. It is because pin leakage can be caused by any type of defect, at any layer in the device and at any process step. This paper presents a case study to demonstrate how to combine multiple techniques to accurately identify the root cause of a pin leakage issue for a device manufactured using advanced technology node. The root cause was identified as under-etch issue during P+ implantation hard mask opening for ESD protection diode, causing P+ implantation missing, which was responsible for the nearly ohmic type pin leakage.

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