Root cause analysis

About: Root cause analysis is a research topic. Over the lifetime, 1770 publications have been published within this topic receiving 23050 citations. The topic is also known as: RCA.

The last planner system of production control

Abstract: Project controls have traditionally been focused on after-the-fact detection of variances. This thesis proposes a control system, the Last Planner system, that causes the realization of plans, and thus supplements project management’s concern for management of contracts with the management of production. The Last Planner system has previously been successfully applied by firms with direct responsibility for production management; e.g., specialty contractors. This thesis extends system application to those coordinating specialists, both in design and construction, through a series of case studies, one of which also explores the limits of unilateral implementation by specialists. In addition to the extended application, two questions drive this research. The first question is 1) What can be done by way of tools provided and improved implementation of the Last Planner system of production control to increase plan reliability above the 70% PPC level? Previous research revealed substantial improvement in productivity for those who improved plan reliability to the 70% level, consequently there is reason to hope for further improvement, possibly in all performance dimensions, especially with application across an entire project rather than limited to individual specialty firms. That question is explored in three case studies, the last of which achieved the 90% target. The second question is 2) How/Can Last Planner be successfully applied to increase plan reliability during design processes. That question is explored in an extensive case study, which significantly contributes to understanding the design process from the perspective of active control, but unfortunately does not fully answer the question, primarily because the project was aborted prior to start of construction. However, it is argued that Last Planner is especially appropriate for design production control because of the value-generating nature of design, which renders ineffective traditional techniques such as detailed front end planning and control through after-the-fact detection of variances. Issues for future research are proposed, including root cause analysis of plan failures and quantification of the benefits of increased plan reliability for both design and construction processes.

Pinpoint: problem determination in large, dynamic Internet services

Abstract: Traditional problem determination techniques rely on static dependency models that are difficult to generate accurately in today's large, distributed, and dynamic application environments such as e-commerce systems. We present a dynamic analysis methodology that automates problem determination in these environments by 1) coarse-grained tagging of numerous real client requests as they travel through the system and 2) using data mining techniques to correlate the believed failures and successes of these requests to determine which components are most likely to be at fault. To validate our methodology, we have implemented Pinpoint, a framework for root cause analysis on the J2EE platform that requires no knowledge of the application components. Pinpoint consists of three parts: a communications layer that traces client requests, a failure detector that uses traffic-sniffing and middleware instrumentation, and a data analysis engine. We evaluate Pinpoint by injecting faults into various application components and show that Pinpoint identifies the faulty components with high accuracy and produces few false-positives.

Clustering intrusion detection alarms to support root cause analysis

Abstract: It is a well-known problem that intrusion detection systems overload their human operators by triggering thousands of alarms per day. This paper presents a new approach for handling intrusion detection alarms more efficiently. Central to this approach is the notion that each alarm occurs for a reason, which is referred to as the alarm's root causes. This paper observes that a few dozens of rather persistent root causes generally account for over 90p of the alarms that an intrusion detection system triggers. Therefore, we argue that alarms should be handled by identifying and removing the most predominant and persistent root causes. To make this paradigm practicable, we propose a novel alarm-clustering method that supports the human analyst in identifying root causes. We present experiments with real-world intrusion detection alarms to show how alarm clustering helped us identify root causes. Moreover, we show that the alarm load decreases quite substantially if the identified root causes are eliminated so that they can no longer trigger alarms in the future.

Root cause analysis of server system performance degradations

Abstract: A system for monitoring and analyzing the post-deployment performance of a web-based or other transactional server is disclosed. The monitoring system includes agent components that monitor and report various performance parameters associated with the transactional server, such as response times seen by end users, server and network times, and various server resource utilization parameters. A web-based reports server displays the data collected by the agents through a series of charts and graphs that indicate whether correlations exist between the response times and lower level parameters. A root cause analysis system applies statistical algorithms to the collected data to detect performance degradations in specific parameters, and uses predefined parameter dependency rules to correlate high level performance problems to likely sources or causes of such problems.

The causes of food waste in the supplier–retailer interface: Evidences from the UK and Spain

Abstract: Food and drink waste is a significant problem for economic, environmental and food security reasons. Government efforts have focused on diverting waste away from landfill through regulation, taxation and public awareness. However, efforts to understand why waste occurs have been limited, particularly in the interface between retailers and suppliers. This research aims to address this problem by identifying the main root causes of waste in the supplier–retailer interface. The research is exploratory in nature as there is a paucity of studies focusing on food waste across the supply chain. Data were collected through 43 interviews with managers in food manufacturing, wholesaling and retailing in two countries: the UK (24) and Spain (19). Data from the interviews and supplementary documentation were analyzed using causal maps. This approach helped to identify the main root causes of waste which were categorized into three groups: (1) mega-trends in the marketplace, (2) natural causes related to the products and processes, and (3) management root causes on which practitioners have a direct impact. The paper discusses the root causes of food waste and good practices identified from the interviews. Differences between the UK and Spain are discussed, presenting potential learning opportunities for practitioners in these countries and highlighting opportunities for further research.