Studies in systems, decision and control, Год журнала: 2024, Номер unknown, С. 1 - 19
Опубликована: Янв. 1, 2024
Язык: Английский
Springer series in reliability engineering, Год журнала: 2024, Номер unknown, С. 155 - 168
Опубликована: Янв. 1, 2024
In the era of Industry 4.0, "Digital Twins" emerges as a ground breaking approach, offering fusion physical and digital worlds. This chapter talks deep into understanding twins virtual replicas tangible systems, accentuating their transformative potential in Product Lifecycle Management (PLM). Through real-time monitoring capabilities, can revolutionize design, testing, maintenance phases product's life, providing predictive insights facilitating proactive system health checks. However, with all technological advancements, there are challenges—navigating vast data volume, ensuring synchronization, addressing hurdles remain at forefront. illustrative case studies, this highlights practical applications across diverse industries such aerospace, manufacturing, healthcare, energy. Emphasizing significance, it is evident that not just fleeting trend but pivot towards more integrated efficient future. As continue to evolve, opportunities for leveraging vast, promising horizon filled innovation, optimization, unparalleled growth.
Язык: Английский
Процитировано
4
Springer series in reliability engineering, Год журнала: 2024, Номер unknown, С. 79 - 103
Опубликована: Янв. 1, 2024
This comprehensive exploration goes into the principles, techniques, and real-world applications of Reliability-Centered Design (RCD) system resilience in engineering. The paper begins by elucidating core principles RCD, which include identifying critical components, assessing failure modes, designing for redundancy, devising effective maintenance strategies, mitigating consequences failures. In-depth discussions on these provide engineers designers with a robust framework enhancing reliability products, systems, processes. chapter proceeds to dissect powerful design emphasizing role Experiments (DOE), tolerance analysis, quality control improving reliability. Systematically addressing variations uncertainties, can develop products systems that consistently meet performance standards, even under adverse conditions. System redundancy analysis are explored extensively, focusing diverse types implementing failover mechanisms absorb shocks recover from disruptions. Risk assessment is central element, as guides readers through parameters, quantifying risks, developing risk mitigation strategies. Through compelling case studies best practices, this offers practical insights how RCD applied across industries. Industry-specific examples showcase successful application while lessons past failures underscore importance continuous improvement engineering design. resource engineers, designers, practitioners seeking create robust, reliable, adaptable withstand challenges disruptions minimizing risks empowers professionals knowledge tools excel dynamic demanding
Язык: Английский
Процитировано
3
Studies in systems, decision and control, Год журнала: 2025, Номер unknown, С. 31 - 50
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
0
The International Journal of Advanced Manufacturing Technology, Год журнала: 2025, Номер unknown
Опубликована: Май 28, 2025
Язык: Английский
Процитировано
0
The International Journal of Advanced Manufacturing Technology, Год журнала: 2025, Номер unknown
Опубликована: Май 30, 2025
Язык: Английский
Процитировано
0
Springer series in reliability engineering, Год журнала: 2024, Номер unknown, С. 1 - 16
Опубликована: Янв. 1, 2024
The rapidly evolving landscape of industrial systems has witnessed significant advancements over the years, with computational mathematics emerging as a pivotal influencer in shaping their reliability and maintainability. This chapter looks into multifaceted realm systems, offering granular classification tracing evolutionary trajectory from rudimentary mechanization to sophisticated automation bolstered by computer technologies. A particular emphasis is placed on system maintainability, two crucial metrics that dictate system's longevity operational efficiency. In this context, carves out niche for itself, showcasing its prowess predictive maintenance, simulation-based decision-making, probabilistic modelling, thereby enhancing robustness systems. However, it also imperative acknowledge potential limitations these methodologies, including dependency data precision requisites specialized expertise. Real-world applications further elucidate transformative impact strategies global conglomerates. Through comprehensive overview, underscores inextricable bond between future reliable maintainable
Язык: Английский
Процитировано
1
Studies in systems, decision and control, Год журнала: 2024, Номер unknown, С. 167 - 172
Опубликована: Янв. 1, 2024
Язык: Английский
Процитировано
1
Studies in systems, decision and control, Год журнала: 2024, Номер unknown, С. 147 - 165
Опубликована: Янв. 1, 2024
Язык: Английский
Процитировано
1
Studies in systems, decision and control, Год журнала: 2024, Номер unknown, С. 109 - 120
Опубликована: Янв. 1, 2024
Язык: Английский
Процитировано
0
Studies in systems, decision and control, Год журнала: 2024, Номер unknown, С. 1 - 19
Опубликована: Янв. 1, 2024
Язык: Английский
Процитировано
0