Quality professionals use deep learning AI to quickly identify and prevent significant product defects, bringing a substantial leap forward in quality assurance and process improvement. Unlike traditional automation controllers, deep learning allows computers to proactively grow their knowledge base and adapt to evolving circumstances.
In today's competitive business environment, achieving operational excellence and maintaining quality standards is crucial. Organizations can demonstrate commitment to improvement with a robust business management system and ISO certification, covering quality, environmental, and safety practices. Many seek outside ISO consultants to help navigate the certification process.
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.
In 2009, ISO proposed a standard for Quality Function Deployment (QFD) to improve product quality. QFD originated in Japanese manufacturing in the 1960s and complements traditional quality systems. The ISO standard, known as ISO 16355, includes over 100 case studies and tools from various sectors.
In 2009, ISO proposed a standard for Quality Function Deployment (QFD) to improve product quality. QFD originated in Japanese manufacturing in the 1960s and complements traditional quality systems. The ISO standard, known as ISO 16355, includes over 100 case studies and tools from various sectors.
Through improvement methods like Lean Six Sigma, root cause analysis and so many others, quality has already made a large contribution to making organizations more sustainable.
This article will demonstrate that our current approach to sustainable development is not viable for our finite and vulnerable planet. We need a new definition and an approach that focuses on the quality of all life in order to ensure a successful long-term future for organizations and society as a whole.
Just as the development of the automobile and the shift towards electricity helped alleviate problems of the past, modern innovations like renewable energy, electric vehicles, and carbon capture technologies are essential in combating climate change.
The 1894 Horse Manure Crisis revealed the negative effects of rapid industrialization. Today, we can learn from past strategies to address the current climate crisis and promote a sustainable future.
The urgency of addressing environmental issues cannot be overstated. To achieve a sustainable future, we must adopt this approach that considers the interconnections between social, economic, and environmental factors.
In a world grappling with climate change, the push for sustainability has made electric vehicles (EVs) a popular choice. Some states are even phasing out gas engine vehicle sales by 2030/2035. However, considering the total impact of producing and operating EVs reveals a more complex picture.
The singularity—or more accurately, the technological singularity—“is a hypothetical future point in time at which technological growth becomes uncontrollable and irreversible, resulting in unforeseeable consequences for human civilization.”
And how existing continuous improvement techniques can be applied to how goods and services are designed, produced, and delivered to meet unique customer requirements.
Mass customization (MC) aims to meet individual customer needs while controlling costs and maintaining quality. The paper explores the connection between kaizen, a continuous improvement tool, and mass customization practices.