Root cause analysis (RCA) is a class of problem solving Problem solving is a mental process and is part of the larger problem process that includes problem finding and problem shaping methods aimed at identifying the root causes A root cause is an initiating cause of a causal chain which leads to an outcome or effect of interest. Commonly, root cause is used to describe the depth in the causal chain where an intervention could reasonably be implemented to change performance and prevent an undesirable outcome of problems or events. The practice of RCA is predicated on the belief that problems are best solved by attempting to correct or eliminate root causes, as opposed to merely addressing the immediately obvious symptoms. By directing corrective measures at root causes, it is hoped that the likelihood of problem recurrence will be minimized. However, it is recognized that complete prevention of recurrence by a single intervention is not always possible. Thus, RCA is often considered to be an iterative process, and is frequently viewed as a tool of continuous improvement Some see it as a meta process for most management systems . Deming saw it as part of the 'system' whereby feedback from the process and customer were evaluated against organisational goals. The fact that it can be called a management process does not mean that it needs to be executed by 'management' merely that it makes decisions about the.

RCA, initially is a reactive method of problem detection and solving. This means that the analysis is done after an event has occurred. By gaining expertise in RCA it becomes a pro-active method. This means that RCA is able to forecast the possibility of an event even before it could occur.

Root cause analysis is not a single, sharply defined methodology; there are many different tools, processes, and philosophies of RCA in existence. However, most of these can be classed into five, very-broadly defined "schools" that are named here by their basic fields of origin: safety-based, production-based, process-based, failure-based, and systems-based.

Despite the seeming disparity in purpose and definition among the various schools of root cause analysis, there are some general principles that could be considered as universal. Similarly, it is possible to define a general process for performing RCA.

Contents

General principles of root cause analysis

  1. Aiming performance improvement measures at root causes is more effective than merely treating the symptoms of a problem.
  2. To be effective, RCA must be performed systematically, with conclusions and causes backed up by documented evidence.
  3. There is usually more than one potential root cause for any given problem.
  4. To be effective the analysis must establish all known causal relationships between the root cause(s) and the defined problem.
  5. Root cause analysis transforms an old culture that reacts to problems to a new culture that solves problems before they escalate, creating a variability reduction and risk avoidance mindset.

General process for performing and documenting an RCA-based Corrective Action

Notice that RCA (in steps 3, 4 and 5) forms the most critical part of successful corrective action, because it directs the corrective action at the root of the problem. That is to say, it is effective solutions we seek, not root causes. Root causes are secondary to the goal of prevention, and are only revealed after we decide which solutions to implement.

  1. Define the problem.
  2. Gather data/evidence.
  3. Ask why and identify the causal relationships associated with the defined problem.
  4. Identify which causes if removed or changed will prevent recurrence.
  5. Identify effective solutions that prevent recurrence, are within your control, meet your goals and objectives and do not cause other problems.
  6. Implement the recommendations.
  7. Observe the recommended solutions to ensure effectiveness.
  8. Variability Reduction methodology for problem solving and problem avoidance.

Root cause analysis techniques

Common cause analysis (CCA) common modes analysis (CMA) are evolving engineering techniques for complex technical systems to determine if common root causes in hardware, software or highly integrated systems interaction may contribute to human error or improper operation of a system. Systems are analyzed for root causes and causal factors to determine probability of failure modes, fault modes, or common mode software faults due to escaped requirements. Also ensuring complete testing and verification are methods used for ensuring complex systems are designed with no common causes that cause severe hazards. Common cause analysis are sometimes required as part of the safety engineering tasks for theme parks, commercial/military aircraft, spacecraft, complex control systems, large electrical utility grids, nuclear power plants, automated industrial controls, medical devices or other safety safety-critical systems with complex functionality.

Basic elements of root cause

Also see

Categories: Quality

 

The above information uses material from Wikipedia and is licensed under the GNU Free Documentation License The purpose of this License is to make a manual, textbook, or other functional and useful document "free" in the sense of freedom: to assure everyone the effective freedom to copy and redistribute it, with or without modifying it, either commercially or noncommercially. Secondarily, this License preserves for the author and publisher a.
Some facts may not have been fully verified for accuracy. [Disclaimers Wikipedia is an online open-content collaborative encyclopedia, that is, a voluntary association of individuals and groups working to develop a common resource of human knowledge. The structure of the project allows anyone with an Internet connection to alter its content. Please be advised that nothing found here has necessarily been reviewed by]
This page was last archived by our server on Fri Jul 17 18:59:38 2009. [ refresh local cache ]
Displaying this page or its contents does not use any Wikimedia Foundation's resources.
The owners of this site proudly support the Wikimedia Foundation.