SPC & FMEA: Integrating Systems Thinking into Your Quality Architecture to Drive Improvement | Intelex (2024)
All organizations want to make their customers happy — but don’t want to spend an excessive amount in the process. A quality management system (QMS) is usually the answer, providing a way to pull together philosophies, standards, methodologies and tools to help an organization achieve its quality-related goals. But choosing the right degree of automation (and whether or not to use software for different tasks) can affect the bottom line — especially when those choices tend to be spread out over time.
This webinar explores quality controls and quality events throughout the design and production processes. Failure Mode and Effects Analysis (FMEA) and Statistical Process Control (SPC) are emphasized as core tools for linking quality engineering and quality management. Upon completion of this webinar, attendees will be able to:
Explain how QMS components work together, including NCR, CAPA, FMEA, SPC, DMAIC, APQP/PPAP, document management, training management, audit management, design controls, material controls, equipment and facility controls, and change control
Describe how FMEA can be used to identify corrective and preventive actions, launch improvement plans, and address risk
Explain SPC terminology, basic concepts, and how to apply it — particularly beyond manufacturing
Avoid disconnected (and inefficient) management of quality events
Identify quality issues faster and more effectively
Capture opportunities for improvement more easily
Although some core concepts from ISO 9001:2015 are used as a framework for discussion, this presentation will be useful to organizations at all stages of their quality journey. By watching our latest webinar “SPC & FMEA: Integrating Systems Thinking into Your Quality Architecture to Drive Improvement”, you’ll be able to identify where to begin, or what to do next to make your quality management system more robust and strategically viable.
Speaker
Nicole Radziwill is a quality manager and data scientist with more than 20 years leadership experience in software, telecommunications, research infrastructure, and higher education. Prior to joining Intelex, she was an associate professor of data science and production systems at James Madison University, Assistant Director for End to End Operations at the National Radio Astronomy Observatory (NRAO), managed software product development for the Green Bank Observatory (GBO), and managed client engagements for Nortel Networks and Clarify (CRM). She is an ASQ-certified manager of operational excellence (CMQ/OE), an ASQ-certified Six Sigma Black Belt (CSSBB), and contributed to the development of ISO 26000—“Guidance on Social Responsibility.”
Failure Mode and Effects Analysis (FMEA) and Statistical Process Control (SPC) are emphasized as core tools for linking quality engineering and quality management.
The purpose of the FMEA is to take actions to eliminate or reduce failures, starting with the highest-priority ones. Failure modes and effects analysis also documents current knowledge and actions about the risks of failures, for use in continuous improvement. FMEA is used during design to prevent failures.
Statistical process control (SPC) is an analytical technique that plots data over time. It helps us understand variation and in so doing guides us to take the most appropriate action.
For example, MRI's produce intense magnetic fields. One patient was killed by a flying fire extinguisher pulled off the wall by the MRI. 3. Identify any Potential Effect(s) of Failure - Consequences on other systems, parts, or people.
FMEA can be used to identify gaps and develop actions to make the process more efficient and safe. FMEA also helps to prepare for implementation of new processes.
The aim of Statistical Process Control (SPC) is to establish a controlled manufacturing process by the use of statistical techniques to reduce process variation. A decrease in variation will lead to: better quality; lower costs (waste, scrap, rework, claims, etc.);
Statistical process control (SPC) is a method of monitoring and controlling the quality and variation of a process using statistical tools and techniques. SPC can help you identify and reduce sources of risk, such as errors, defects, waste, and inefficiencies, in your statistical analysis or data collection.
Statistical process control (SPC) is a data-driven approach to process improvement. It uses statistical methods to monitor and control a process, identify and eliminate sources of variation, and ensure that the process produces consistent, high-quality outputs. SPC is a key tool in Lean Six Sigma projects.
Statistical process control (SPC) is defined as the use of statistical techniques to control a process or production method. SPC tools and procedures can help you monitor process behavior, discover issues in internal systems, and find solutions for production issues.
Introduction: My name is Aron Pacocha, I am a happy, tasty, innocent, proud, talented, courageous, magnificent person who loves writing and wants to share my knowledge and understanding with you.
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