Quality-Continuous Improvement

This paper introduces a machine learning-based strategy to improve data cleaning by integrating unstructured textual data with traditional structured datasets. Recognizing that structured data often contains errors due to inconsistencies, omissions, or conflicts, the authors propose leveraging textual descriptions, such as product titles or clinical trial summaries, to predict … [Read more...] about Improving Data Cleaning by Learning From Unstructured Textual Data

VDA 6.3 is a process audit standard designed to assess the quality and stability of manufacturing and supply chain processes. Structured around seven core elements—ranging from supplier evaluation to production, customer service, and continuous process monitoring—it emphasizes risk management and process reliability. Each area is scored to identify non-conformities and … [Read more...] about Why Non-Automotive Companies Need Process Audits

Conventional quality management, rooted in audits and regulatory compliance, is no longer sufficient to meet the demands of today’s competitive and volatile business environment. Chief Quality Officers (CQOs), now entering the C-suite, are expected to shift away from reactive, siloed practices and toward strategic leadership. Despite widespread compliance, product recalls have … [Read more...] about How Embedded Quality guides organizations moving from strictly compliance to delivered quality

The study explores the relationship between organizational culture, TQM interventions, and benchmarking in driving business performance, particularly within manufacturing SMEs in Jordan. While previous research has presented conflicting views on whether culture positively impacts performance, this study confirms that a well-defined organizational culture strengthens TQM … [Read more...] about Total Quality Management Interventions and Benchmarking in the Impact of Organizational Culture and Performance

Quality 5.0 marks a transformative shift in quality management, redefining excellence through the synergy of human intelligence and machine capabilities. Unlike previous iterations that focused on inspection, process control, or digital enhancements, this new paradigm integrates artificial intelligence, robotics, and data-driven decision-making with human creativity, … [Read more...] about Quality 5.0 – Redefining Excellence In Human-Machine Collaboration Age

A Data Quality Management System (DQMS) offers organizations a structured approach to managing data quality, adapting ISO 9001 principles to the data domain. While ISO 27001 is widely recognized for information security, and ISO 8000 focuses on specific aspects of data quality, ISO 9001 provides a general framework that can be effectively applied to ensure high data quality … [Read more...] about A Management System for Data Quality

Pareto analysis, derived from the 80/20 rule, enables project managers to focus on the 20% of tasks that deliver 80% of the value, enhancing efficiency and productivity. This approach helps teams identify and address the root causes of issues, providing a clear roadmap for prioritizing impactful tasks. By organizing issues into categories, scoring their significance, and … [Read more...] about Using Pareto Analysis to Boost Efficiency

The quality profession must evolve to meet modern industry demands by embracing a unifying principle grounded in "value and balance." Value is the ratio of utility produced to resources consumed, highlighting the need to eliminate waste and maximize efficiency. This approach extends beyond traditional quality definitions, like fitness for use or conformance to requirements, … [Read more...] about A Single Quality Principle for Value and Balance

In regulated industries such as pharmaceuticals, medical devices, and food manufacturing, validation of Quality Management Systems (QMS) ensures compliance with standards like FDA 21 CFR Part 11, ISO 13485, and EU MDR. (These tools, while not required in less regulated industries, are valuable for maintaining product/service integrity and can be used as models there.) … [Read more...] about Critical Aspects of Quality Management Systems: Focusing on the Validation Process

Data validation and accuracy are often conflated in data quality management but serve different purposes. Validation identifies incorrect values through rule-based tests, while accuracy requires comparing data to authoritative sources. Validation alone cannot guarantee accuracy, as it may overlook errors in seemingly valid records.Achieving true accuracy demands supplementary … [Read more...] about Data Speaks for Itself: Data Validation – Data Accuracy Imposter or Assistant?