Teaching Lean and Six Sigma tools is an exciting journey, especially with statistical methods like ANOVA and regression analysis. With two decades of experience, I've seen how these concepts can be intimidating to candidates. However, mastering data and variable relationships is essential for effective problem-solving.
Quality 4.0 combines technologies like AI and IoT with quality management, enhancing real-time monitoring and decision-making. It supports continuous improvement in Lean Six Sigma, helping organizations achieve operational excellence and stay competitive.
Manufacturers can tackle production issues by accurately defining problems, using root cause analysis to identify key factors, implementing data-driven corrective actions, and continuously monitoring processes to ensure ongoing improvements and maintain a competitive edge.
If given the opportunity, existing employees are often keen to learn the enhanced processes and specialized equipment that today’s manufacturing requires.
American manufacturing is making a comeback, fueled by billions in investments and new technologies. This reshoring not only boosts job quality and economic opportunity but also mitigates supply chain risks exposed during the COVID-19 pandemic. But is there a catch?
The hype around "big data" has mainly aimed at niche market sales without delivering expected benefits. Similarly, the business world's obsession with Lean Six Sigma has shown minimal returns on investment. In contrast, over the last 25 years, I've leveraged small Excel files to significantly cut costs and increase profits, often by millions of dollars, through a reliable sequence I discovered.
The main difference between projects and programs is their scope and focus. Project management focuses on efficiently executing specific projects, while program management aligns multiple projects with overarching strategic goals.
Quality 4.0 looks at how digitization improves industry processes. Despite over 10 years of focus, there's still no clear definition or knowledge base for Quality 4.0.
Leaders prioritize efficiency and productivity over quality management, compromising long-term standards, evident in the widespread adoption of operational excellence programs like Lean and Six Sigma.
When risk management principles are integrated with Six Sigma improvements, those improvements will provide greater assurance of suitability and resilience for the expected use conditions.
This article discusses how ASQ’s Body of Knowledge for Six Sigma Certifications has added new expectations for implementing improvements, including Proof of Concepts, Try-Storming, Simulations (e.g. Monte Carlo, Dynamic Process Simulation, Queuing Theory), and Pilot Tests.