Product Quality Improvement Policies in Industry 4.0: Characteristics, Enabling Factors, Barriers, and Evolution Toward Zero Defect Manufacturing

Abstract

In the competitive market of manufacturing, quality is a criterion of primary importance in order to win market share. Quality improvement must be coupled with performance point of view. Lean Manufacturing, Six Sigma, Lean Six Sigma, Total Quality Management, Theory of Constraints, and their combination are philosophies dedicated to this goal. This study is a literature review on the implementation of these philosophies to improve quality of processes and products in a system, and also covers the commonalities and differences with Zero Defect Manufacturing (ZDM) philosophy. In this study, 45 articles have been analyzed. These articles have been selected by a research on several scientific libraries with specific keywords. The methodology is based on a list of information extracted from each paper. The data searched are on the tool selections, critical factors of implementations and the benefits obtained from them. Based on the review and analysis of the literature and practices, we provide the top 10 main components of the tools used for quality improvement, enabling factors, benefits, and barriers to implementation. Moreover, we present and discuss categorization of quality improvement methods and the way toward ZDM. The need of standardized toolkits for different levels of maturity in quality management systems and a better education have been enlightened. Thanks to technological improvement in information flow management, ZDM seems close to be achieved even though some new risks and wastes have to be taken care of within the implementation.

Smart Master Production Schedule for the Supply Chain: A Conceptual Framework

“…The ZDM management model is often associated with I4.0 for presenting largely compatible objectives and providing synergistic and complementary approaches [17,93,94]. Beyond the most well-known ZDM objectives, such as minimizing failures and defects and their early online detection, this management model shares with I4.0 the purpose of minimizing production costs and making production more efficient and sustainable by reducing the number of failures, breakdowns and defective parts [95].…”

Cost-Based Decision Support System: A Dynamic Cost Estimation of Key Performance Indicators in Manufacturing

“…Quality control process could increase the cost of the product significantly, but also defective parts lead to yield loss. ZDM approach is one of the latest quality assurance paradigms that aims to eliminate defective parts ensuring that customers receive products free from defects and meet their requirements [13]- [15]. In this point should be mentioned that for achieving ZDM all parts need to be inspected for assuring that the quality meets the required levels and if the product is defective to identify if it is repairable or not [52].…”

“…The motivation of the current study is to develop a solution to interpret sustainable manufacturing [13], inspired by practical implementation of Industry 4.0, AI-driven, and zero-defect manufacturing (ZDM) principles and technologies into monetary value. We present a novel cost estimation tool for properly selecting the manufacturing parameters that will allow productivity, but at the same time, they will give the opportunity to implement ZDM and have the desired product quality levels [13]- [15]. Decision-making process in complex manufacturing environments poses a major challenge for managers.…”

A semantic systems engineering framework for zero-defect engineering and operations in the continuous process industries

“…Recent practice has moved from statistical methods towards data-driven technologies coming from the Industry 4.0 concept. Traditional QI methods were designed using the technologies available at the time, without the knowledge of recent technological advances under the framework of Industry 4.0 (Psarommatis et al, 2020b). Methods such as artificial intelligence, machine learning or semantic modelling present new ways for manufacturers to achieve targets that would have been impossible in the past (Lindström et al, 2020).…”