| Start Date | End Date | Country | City |
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+966 920007771
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Objectives
This course will enable participants to understand root cause analysis as a procedure for ascertaining and
- analyzing
- the causes of problems in an effort to determine what can be done to solve or prevent them. This course is designed to provide attendees with an in-depth understanding of how to analyze a system in order to identify the root causes of problems. This course will help enable you to:
- Enhance problem-solving effectiveness by providing a model for in-depth analysis of problem situations.
- Clarify the difference between analytical and creative thinking, and when each is most useful.
- Promote the ability to provide problem-solving support in situations where one is not an expert in the process or technology involved.
- Expand the range of tools available for analysis of problem situations.
Outlines
- The difference between problem solving and root cause analysis
- Why effective root cause analysis is more important in today\\\'s world
- Some common problem solving models and their weaknesses
- Five steps for performing the root cause analysis part of problem solving
- What each step accomplishes and some tools available for carrying it out
- Problem understanding
- How the understanding step prevents working on the wrong problem and builds a base for later analyses
- Different forms of flow diagrams for clarifying the process and interrelationships
- Tools for priority setting (performance matrix, radar chart, critical incidents)
- Requirements
- Identifying possible cause generation and focusing
- Why this step is critical to effective root cause determination
- Different forms of brainstorming and the processes for carrying them out
- Questions to ask when seeking possible causes
- Other resources for possible cause ideas
- Creative versus analytical thinking
- Reducing the list through nominal group technique, multivoting, paired comparison, or matrix
- Data collection
- How this step avoids shotgun problem solving by identifying the most likely cause(s)
- Population versus sampling; options for sampling
- Check sheets and graphs for discrete data collection
- Surveys, interviews and field observation for opinions or less precise data
- Data analysis
- Tools for discrete data analysis (run charts, histograms, pareto diagram, scatter diagram)
- Tools for softer type data (affinity diagram, relationship digraph)
- Technical versus organization problems, and analytical versus creative problems
- Statistical tools for data analysis (z, t, & F tests; ANOVA, chi-square) and use of MS Excel
- Cause and effect analysis
- How this step links data analysis and possible causes
- Tools for performing cause & effect analysis, such as cause & effect diagrams, structural diagrams, logic tree diagrams, matrix diagrams, and 5-whys
- The importance of understanding the multiple cause, multiple effect chain
- When to stop the analysis and return to the problem solving process
- The rest of the problem-solving process
- Identifying and selecting solutions
- The importance of project management, and consideration of change management issues
- Some models for understanding resistance and planning change
- Implementation, follow-up, and standardization
Who Should Attend
Quality, safety, risk and reliability managers, process engineers, technicians, operations supervisors and personnel, process owners, occurrence investigators, analysts, maintenance directors, reliability professionals and anyone who wants to improve their ability to solve recurring problems.
Duration
3 Days
