An Industry 4.0 framework for tooling production using metal additive manufacturing-based first-time-right smart manufacturing system

Moshiri, Mandaná; Charles, Amal; Elkaseer, Ahmed; Scholz, Steffen; Mohanty, Sankhya; Tosello, Guido

doi:10.1016/j.procir.2020.04.151

Cited by 28 publications

(32 citation statements)

References 34 publications

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“…After analyzing the content of these 23 papers, the findings were assigned according to their relevance to each of the CI activities. As an example, Sim&Virt, through augmented/assisted reality (AR/AsR), enables real-time remote support in manual operations [8,12], relevant to the documentation management, implementation, and follow-up and standardization activities. The result is exposed in Tables A1 and A2 (Appendix B).…”

Section: Conceptual Approachesmentioning

confidence: 99%

“…Approaching LM in its purest form does not require information technology [7]. However, both LM and I4.0 paradigms aim to solve present and future challenges in manufacturing [8]. Among the publications that study the applicability of I4.0, several mention CI as a part of LM (e.g., [4,8,9]), whereas others focus exclusively on CI (e.g., [10][11][12]).…”

Section: Introductionmentioning

confidence: 99%

“…However, both LM and I4.0 paradigms aim to solve present and future challenges in manufacturing [8]. Among the publications that study the applicability of I4.0, several mention CI as a part of LM (e.g., [4,8,9]), whereas others focus exclusively on CI (e.g., [10][11][12]). The existing contributions in the literature show, directly or indirectly, the potential of CI enhancement under a I4.0 context, referring to various I4.0 technological concepts to support this transformation.…”

Section: Introductionmentioning

confidence: 99%

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PDCA 4.0: A New Conceptual Approach for Continuous Improvement in the Industry 4.0 Paradigm

et al. 2021

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Continuous improvement (CI) is a key component of lean manufacturing (LM), which is fundamental for organizations to remain competitive in an ever more challenging market. At present, the new industrial revolution, Industry 4.0 (I4.0), is taking place in the manufacturing and service markets, allowing more intelligent and automated processes to become a reality through innovative technologies. Not much research was found regarding a holistic application of I4.0′s technological concepts towards CI, which clarifies the potential for improving its effectiveness. This clearly indicates that research is needed regarding this subject. The present publication intends to close this research gap by studying the main I4.0 technological concepts and their possible application towards a typical CI process, establishing the requirements for such an approach. Based on that study, a conceptual approach is proposed (PDCA 4.0), depicting how I4.0 technological concepts should be used for CI enhancement, while aiming to satisfy the identified requirements. By outlining the PDCA 4.0 approach, this paper contributes to increasing the knowledge available regarding the CI realm on how to support the CI shift towards a I4.0 industrial paradigm.

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Section: Conceptual Approachesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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PDCA 4.0: A New Conceptual Approach for Continuous Improvement in the Industry 4.0 Paradigm

et al. 2021

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“…Industrial applications of RFT have been observed in reports by Moshiri et al [33] in additive manufacturing processes in Industry 4.0, and Eldessouky et al [34] proposed a contextual framework for RFT when the process generates waste and the raw material is expensive. Therefore, there is no doubt that RFT is part of TQM's programs.…”

Section: Doing It Rftmentioning

confidence: 99%

Effect of Quality Lean Manufacturing Tools on Commercial Benefits Gained by Mexican Maquiladoras

et al. 2021

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Companies implement lean manufacturing (LM) tools in their production processes to reduce waste; however, it is difficult to quantify the effect on benefits gained after their implementation. This article proposes a structural equations model (SEM) that relates three LM tools associated with quality as total quality management (TQM), waste, and right first time (RFT) as independent variables associated with commercial benefits gained as a dependent variable. Those four variables were related by six hypotheses that were validated with information from 169 responses to a survey applied to the Mexican maquiladora industry. Partial least squared was used to validate the hypotheses as direct effects. The sum of indirect and total effects was also estimated, and a sensitivity analysis was developed for relationships between variables. Findings indicate that TQM directly affects waste reduction, drives doing RFT, and directly and indirectly affects the commercial benefits gained.

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“…(3) The flexibility of production organization is the basis for enterprises to meet personalized customer needs. This not only requires the factory's production factors to have the ability to dynamically organize to meet production demands, but also raises the dynamic adaptability requirements of production organization for security, flexibility, and agility [5].…”

Section: Introductionmentioning

confidence: 99%

An Information Theory Inspired Real-Time Self-Adaptive Scheduling for Production-Logistics Resources: Framework, Principle, and Implementation

Yang

Cao

et al. 2020

Sensors

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The development of industrial-enabling technology, such as the industrial Internet of Things and physical network system, makes it possible to use real-time information in production-logistics scheduling. Real-time information in an intelligent factory is random, such as the arrival of customers’ jobs, and fuzzy, such as the processing time of Production-Logistics Resources. Besides, the coordination of production and logistic resources in a flexible workshop is also a hot issue. The availability of this information will enhance the quality of making scheduling decisions. However, when and how to use this information to realize the adaptive collaboration of Production-Logistics Resources are vital issues. Therefore, this paper studies the above problems by establishing a real-time reaction scheduling framework of Production-Logistics Resources dynamic cooperation. Firstly, a real-time task triggering strategy to maximize information utilization is proposed to explore when to use real-time information. Secondly, a collaborative method for Production-Logistics Resources is studied to explore how to use real-time information. Thirdly, a real-time self-adaptive scheduling algorithm based on information entropy is utilized to obtain a stable and feasible solution. Finally, the effectiveness and advancement of the proposed method are verified by a practical case.

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An Industry 4.0 framework for tooling production using metal additive manufacturing-based first-time-right smart manufacturing system

Cited by 28 publications

References 34 publications

PDCA 4.0: A New Conceptual Approach for Continuous Improvement in the Industry 4.0 Paradigm

PDCA 4.0: A New Conceptual Approach for Continuous Improvement in the Industry 4.0 Paradigm

Effect of Quality Lean Manufacturing Tools on Commercial Benefits Gained by Mexican Maquiladoras

An Information Theory Inspired Real-Time Self-Adaptive Scheduling for Production-Logistics Resources: Framework, Principle, and Implementation

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