Can robustness analysis be applied to moral and ethical philosophies, and if so, how?4 answersRobustness analysis can indeed be applied to moral and ethical philosophies. In the philosophy of science and epistemology, robustness analysis encompasses various strategies with distinct justifications. Furthermore, in the realm of moral responsibility, the concept of robustness is crucial for grounding an agent's responsibility. It is argued that for an agent to have a robust alternative, they must possess the right kind of ability, where their actions are genuinely up to them. This stringent requirement for robustness in moral responsibility highlights the importance of preserving an agent's genuine ability to choose among alternatives, rather than just the mere possibility. By incorporating robustness analysis, moral and ethical philosophies can delve deeper into the foundations of responsibility and free will, enriching the discourse with a more nuanced understanding of human agency.
Resilience and Robustness in flexible manufactering system ?5 answersResilience and robustness are important concepts in flexible manufacturing systems. Resilience refers to the ability of a system to endure disruptive changes, such as the recent COVID pandemic, by embracing automation, digitization, and AI. Robustness, on the other hand, focuses on the ability of a system to handle resource failures and reduce production inefficiencies caused by failure blockings (FBs) and deadlocks. In the context of manufacturing systems, robustness is achieved through the design of control policies and controllers that can ensure smooth completion of tasks even in the presence of unreliable resources. By combining concepts of resilience and robustness, manufacturing systems can be designed to improve their ability to withstand disruptions and maintain efficient production processes.
Robust Design and Reliability Engineering in Product Development related research articles?5 answersRobust Design and Reliability Engineering are important areas of research in product development. Robust Design focuses on exploring the design space and integrating different design decisions to improve product performance and functionality. It aims to minimize the impact of variations on a product and improve its quality and cost-effectiveness. Reliability-based robust design methods have been applied in various fields, such as rolling bearing fatigue failure and brushless direct current (BLDC) motors, to enhance product reliability and reduce failure rates. These methods involve considering manufacturing uncertainties and conducting reliability analysis to optimize the design and improve product performance. The combination of Robust Design with other optimization methods has also been explored to further enhance the design and optimization of manufacturing processes. Overall, these research articles highlight the significance of Robust Design and Reliability Engineering in product development for achieving high-quality and reliable products.
How does transfer learning impact the robustness of machine learning models?4 answersTransfer learning has an impact on the robustness of machine learning models. Retraining ML models on corrupted data enhances their robustness to data quality degradation in image classification scenarios. Additionally, transfer learning can improve the performance of ML models in real application scenarios. It allows for the reuse of pretrained ML systems even when input data values or application domains have changed. Transfer learning can also enhance the robustness of deep convolutional neural networks (DCNNs) to distortions in images. By using autoencoders as intermediaries between pre-trained DCNNs and classifiers, models achieve increased accuracy and reduced loss, even for images with unseen distortions. Overall, transfer learning plays a vital role in improving the robustness of machine learning models in various scenarios.
What's the constraints in flexible job shop scheduling problem?5 answersThe constraints in the flexible job shop scheduling problem (FJSP) include setup and transport resource constraints. Other constraints that have been considered in the literature include sequence-dependent setup times and resource constraints. Additionally, the distributed FJSP considers dual resource constraints and the influence of workpiece transportation time between factories and machines. The FJSP with job precedence constraints also takes into account hierarchical precedence constraints due to dependencies between manufactured parts.
What are the features of a flexible supply chain?3 answersA flexible supply chain is characterized by several features. Firstly, it involves the use of generalized production/warehousing nodes instead of individual plants and warehouses, allowing for greater adaptability to demand uncertainty. Secondly, flexibility is achieved through scenario-based approaches that consider inventory management, facility location, production rate, warehouse capacity, demand allocation, and product flows. Thirdly, supply chain flexibility is not limited to a single company but requires an integrated perspective that considers the needs and priorities of all chain members. Additionally, supply chain flexibility is seen as a strategic ability that enables organizations to rapidly sense and respond to internal and external uncertainties through effective collaboration and responsiveness. Finally, a flexible supply chain is able to adjust and absorb uncertainties, making it more resilient and adaptable to unforeseen situations.