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Zero Defect Manufacturing ontology: A preliminary version based on standardized terms. COMPUT IND 2023. [DOI: 10.1016/j.compind.2022.103832] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
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Wan PK, Leirmo TL. Human-centric zero-defect manufacturing: State-of-the-art review, perspectives, and challenges. COMPUT IND 2023. [DOI: 10.1016/j.compind.2022.103792] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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Joshi S, Sharma M, Bartwal S, Joshi T, Prasad M. Critical challenges of integrating OPEX strategies with I4.0 technologies in manufacturing SMEs: a few pieces of evidence from developing economies. TQM JOURNAL 2022. [DOI: 10.1108/tqm-08-2022-0245] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
PurposeThe study proposes to determine the impending challenges to lean integration with Industry 4.0 (I4.0) in manufacturing that aims at achieving desired operational performance. Integrating lean and Industry 4.0 as the two industrial approaches is synergetic in providing operational benefits such as increasing flexibility, improving productivity, reducing cost, reducing delivery time, improving quality and value stream mapping (VSM). There is an urgent need to understand the integrated potential of OPEX strategies like lean manufacturing and also to determine the challenges for manufacturing SMEs and further suggest a strategic roadmap for the future.Design/methodology/approachThe current work has used a combined approach on interpretative structural modeling (ISM) and fuzzy Matrice d'impacts croisés multiplication appliquée á un classment (MICMAC) approach to structure the multiple level analysis for the implementation challenges to integrate OPEX strategies with Industry 4.0.FindingsThe research has found that the indulgence of various implementation issues like lack of standardization, lack of vision and lack of trained support, all are the major challenges that inhibit the integration of OPEX strategies with I4.0 technologies in manufacturing.Research limitations/implicationsThe research has investigated the internal factors acting as a roadblock to lean and Industry 4.0 adoption. Further studies may consider external factors to lean and Industry 4.0 implementation. Also, further research may consider other operational excellence approaches and extend further to relevant sectors.Practical implicationsThis study provides the analysis of barriers that is useful for the managers to take strategic actions for implementing OPEX strategies with I4.0 in smart manufacturing.Originality/valueThe research determines the adoption challenges towards the integrated framework. This is the first study to explore challenges in integrating OPEX strategies with I4.0 technologies in manufacturing SMEs.
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Unveiling the relation between the challenges and benefits of operational excellence and industry 4.0: a hybrid fuzzy decision-making approach. TQM JOURNAL 2022. [DOI: 10.1108/tqm-07-2022-0237] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
PurposeOperational excellence (OpEx) is a direction toward learning and developing an excellent culture in all aspects of an organization. To reach this culture, revolutionizing activities using industry 4.0 (i4.0) technologies might be a significant empowering tool. This study aims to identify the challenges and benefits of both concepts and investigate their interrelationship to be considered in applying industry 4.0 technologies toward operational excellence.Design/methodology/approachThe challenges and benefits of OpEx and i4.0 are identified and finalized by reviewing the literature. The causal relations between the considered factors are extracted using the fuzzy DEMATEL (Decision Making Trial and Evaluation Laboratory) method. Then, the analytical network process (ANP) is applied to determine the importance and weight of the factors (challenges and benefits of OpEx and i4.0) according to the constructed network.FindingsThe findings illustrated a strong network structure between the factors. First, the causal factors included OpEx and i4.0 challenges, while the OpEx challenges also affected the i4.0 challenges. Both group challenges had a significant effect on OpEx and i4.0 benefits. This means that challenges are the causal factors to be considered in the alignment of i4.0 toward OpEx. Among the OpEx challenges, lack of strategic planning and proper infrastructure were the main influential factors. In contrast, lack of government support and undeveloped business models were identified as the main challenges of i4.0.Originality/valueOpEx and i4.0 concepts are reviewed and their pros and cons are studied. Previous studies determined an interaction among these concepts. However, from a practical viewpoint, the relation between the challenges and benefits of i4.0 and OpEx was studied for the first time for their alignment.
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Zero Defect Manufacturing in the Food Industry: Virgin Olive Oil Production. APPLIED SCIENCES-BASEL 2022. [DOI: 10.3390/app12105184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
This paper provides a zero defect manufacturing (ZDM) approach designed for the virgin olive oil (VOO) industry, with the objective of producing the best possible product using sustainable methods. A deep analysis of related work for ZDM and the current state-of-the-art technology in the VOO elaboration process is presented, along with the implications of the well-known trade-off between quality and extraction yield and the importance of having the right information on the state of the fruits and the main technological variables of the process. Currently available new technologies, such as smart devices with cloud connectivity, enable having the required amount of data and information in real-time, thus making the concept of ZDM possible. Together with the proposed ZDM approach and strategies, the basic requirements and the first steps towards the implementation of ZDM in this productive sector are identified.
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Methodology to Optimize Quality Costs in Manufacturing Based on Multi-Criteria Analysis and Lean Strategies. APPLIED SCIENCES-BASEL 2022. [DOI: 10.3390/app12073295] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
Manufacturing quality cost optimization is a priority in any manufacturing sector due to quality issues impacting companies’ reputations and has financial consequences. Quality costs are composed of tangible and intangible costs, however, only tangible costs used to be analyzed because there is no suitable methodology for measuring intangible costs. In this context, an innovative decision support system is developed with an empirical base, applying Analytical Hierarchy Process (AHP), Analytical Network Process (ANP), and Lean methodology to reduce all quality costs in an efficient way. In quality departments, perceptions, thoughts, and judgments (intangible costs) are not measured and controlled. This study develops an innovative methodology that allows to address this issue in an effective way. Another major innovation is the application of both multi-criteria methodologies to obtain the best combined result for decision making and the optimization of this result, developing an effort–impact matrix based on Lean manufacturing methodology. This system speeds up the decision-making process and assures its efficiency for quality department applications. Moreover, this decision support system may be applicable to any manufacturing sector.
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Kelz RR, Tong J. Examining Quality Improvement in Medicine and Business. J Am Coll Surg 2021; 233:809-810. [PMID: 34823683 DOI: 10.1016/j.jamcollsurg.2021.09.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Accepted: 09/13/2021] [Indexed: 10/19/2022]
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Abstract
Risks arising from the effect of disruptions and unsustainable practices constantly push the supply chain to uncompetitive positions. A smart production planning and control process must successfully address both risks by reducing them, thereby strengthening supply chain (SC) resilience and its ability to survive in the long term. On the one hand, the antidisruptive potential and the inherent sustainability implications of the zero-defect manufacturing (ZDM) management model should be highlighted. On the other hand, the digitization and virtualization of processes by Industry 4.0 (I4.0) digital technologies, namely digital twin (DT) technology, enable new simulation and optimization methods, especially in combination with machine learning (ML) procedures. This paper reviews the state of the art and proposes a ZDM strategy-based conceptual framework that models, optimizes and simulates the master production schedule (MPS) problem to maximize service levels in SCs. This conceptual framework will serve as a starting point for developing new MPS optimization models and algorithms in supply chain 4.0 (SC4.0) environments.
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