In the modern era of manufacturing, it is important to optimize every design parameter in product development stage to reduce cost, material usage and to achieve the desired efficacy level. There are various models which serve those purposes, for instance, Design of Experiment (DoE) is used to check the parameters after adopting optimization tactics which results in reduced cost or saving operating time. In this regard, this research aims to construct a DoE model on a portable workstation to optimize its design parameters. The methodology of DOE would be a 2 level 3 factors full factorial DOE which is conducted to determine the optimal value for three design parameters (factors) which are material density, the length of the table and the length of the table stand in terms of the response which is the required time of fold ability function of the portable workstation. Based upon the evaluated interactions between the parameters, the optimized parameters are chosen for responses. Here, the resultant design parameters are at their lowest level, so the goal of time efficiency in fold ability function is achieved. This similar sort of DoE can be implemented in the furniture and other manufacturing industries who wish to optimize their material usage as well as increase efficiency and reduce cycle time.
Every year, floods cause substantial economic losses worldwide with devastating impacts on buildings and physical infrastructures throughout communities. Techniques are available to mitigate flood damage and subsequent losses, but the ability to weigh such strategies with respect to their benefits from a community resilience perspective is limited in the literature. Investing in flood mitigation is critical for communities to protect the physical and socioeconomic systems that depend on them. While there are multiple mitigation options to implement at the building level, this paper focuses on determining the optimal flood mitigation strategy for buildings to minimize flood losses within a community. In this research, a mixed integer linear programming model is proposed for studying the effects and trade-offs associated with pre-event short-term and long-term mitigation strategies to minimize the expected economic losses associated with floods. The capabilities of the proposed model are illustrated for Lumberton, North Carolina (NC), a small, socially diverse inland community on the Lumber River. The mathematically optimal building-level flood mitigation plan is provided based on the available budget, which can significantly minimize the total expected direct economic loss of the community. The results reveal important correlations among investment quantity, building-level short- and long-term mitigation measures, flood depths of various locations, and buildings’ structure. Additionally, this study shows the trade-offs between short- and long-term mitigation measures based on available budget by providing decision support to building owners regarding mitigation measures for their buildings.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.