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Healthcare Training 2019 - Root Cause Failure Analysis Closed Loop Corrective Action

Date2019-05-21

Deadline2019-05-21

VenueOnline Event, USA - United States USA - United States

KeywordsFDA Compliance; Healthcare; Pharmaceutical

Websitehttps://www.traininng.com/webinar/-20087...

Topics/Call fo Papers

Overview
Root Cause Failure Analysis is an analytical approach used to identify and solve problems. Analysis is presented in the Seven Basic Tools of Quality in addition to advanced methods used to increase organizations effectiveness, efficiency and reliability.
Specific areas presented:
Look for Evidence
The Post-it Exercise
Pareto Chart
Fish Bone Diagramming
Process Reliability Modeling
Critical Path Analysis
Value Stream Mapping
Failure Mode Effects Analysis
Process Improvement and Problem Solving:
Reality Charting
Model for Improvement
Why should you Attend
Traditional methods of Process Improvement demonstrate high failure rates: Business Process Reengineering (BPR) 50% TO 85%, Total Quality Management (TQM) 75% and Six Sigma 90% Proactive methods used in Process Reliability Modeling (PRM) will identify organizational issues before they result in loss of revenue.
Areas Covered in the Session
The Post-it Exercise: Root Causes to process ineffectiveness are identified by Post-it survey.
Pareto Chart: The most common chart used by management; the Pareto is an ordered histogram that displays defects in order of frequency.
Cause and Effect diagrams (Fishbone or Ishikawa Diagram): The Ishikawa Fishbone Diagram (IFD) is a tool used to identify and present possible root causes to a problem. IFD was created by Dr. Kaoru Ishikawa; his method was popularized in early 1960s and used in the Kawasaki shipyards.
Process Reliability Modeling: Process Reliability Modeling (PRM) is a very sensitive measurement instrument used to identify areas of transactional or manufacturing processes contributing to loss of revenue and customer dissatisfaction. PRM is suited for any industry or service including medical processes. P
RM has its roots in reliability engineering. Through employee surveys qualitative information is converted into quantitative data to determine the likelihood of passing work through the entire organization error free. Processes with a low reliability score are flagged and root cause failure analysis methods engaged.
Failure Mode Effects Analysis (FMEA): A step by step approach for identifying and resolving process problems effecting organization effectiveness, efficiency, reliability and safety.
Value Stream Mapping: Method used to document, analyze and improve the flow of information or materials required to produce a product or service for a customer.
Who Will Benefit
Senior Executives
Strategic Leaders
Quality Managers
Product Managers
Manufacturing and R&D Managers
Quality Professionals/Consultants
Presidents/Vice Presidents/CEOs
ISO Coordinators/Management Representatives
Engineers and Supervisors
Laboratory Quality Professionals
Speaker Profile
Dr. Michael Abitz is an Professor Emeritus at New Mexico Jr. College, Hobbs, NM. He received his Doctorate in Management from Colorado Technical University and Master of Science in Quality Assurance from California State University. He is a certified Six Sigma Quality Black Belt.
His areas of interest include teaching online; providing training to pacific rim suppliers in accelerated life testing of communications, computer and digital storage products; mentoring organizations in problem solving and process improvement; and to date cost savings include $15.6M in addition to $14M in sales.
Dr. Abitz's experiences include: aerospace and computer industries where he developed and presented training in: Organizational Process Improvement, Six Sigma (35 classes) and Root Cause Failure Analysis to U.S. companies and Pacific Rim suppliers
Event link: https://www.traininng.com/webinar/-200870live?chan...
Contact Info
Traininng.com LLC
Email: traininngdotcom-AT-gmail.com
Phone: US: (510) 962-8903
Phone: Zurich: +41 - 43 434 80 33
Website : https://www.traininng.com

Last modified: 2019-04-02 17:47:09