Investment on research and development of science technology to solve social issues such as the environment or security and to improve the quality of life for citizens is constantly increasing. But the fast changing technical environment; replacing of existing technology with the new; and inaccurate...
Investment on research and development of science technology to solve social issues such as the environment or security and to improve the quality of life for citizens is constantly increasing. But the fast changing technical environment; replacing of existing technology with the new; and inaccurate prediction regarding practical demand resulted in excessive R&D planning quantitatively as well as inadequacy qualitatively, which eventually leads to failure in the outcome of R&D. With the society’s increased attention on disasters following the recent disasters, enlarging in scale, including the Fukushima nuclear accident, Nepal earthquake, and the sinking of MV Sewol, robots to search life, rescue, and prevent disasters have been in consistent development, but almost none of such robots have been commercialized and put to actual disaster sites. This is because the development plans for such robots that accurately take into account the demands of firemen on site and the technological feasibility, were not put to consideration from the early stages of R&D Planning. The scope of R&D planning today even requires economic feasibility of research outcome to acquire feasibility for a policy enactment. Under such circumstances, this paper examines the problems in R&D planning and analyzes case study R&D models by field to elicit factors that can be applied even to the field of fire disaster, which were then used to suggest an effective new R&D planning model that even extends to economic benefit estimation. The model (step 1)first searches for opportunities in technology, (step 2)analyzes technology in site environment and researches priorities by function, (step 3)approaches with a function-centered technology system plan and selects tasks for candidates, (step 4)chooses highest priority research task, and (step 5)conducts economic assessment, which includes actual field surveys(firemen) in three out of five steps and a discussion with the nation’s top technological expert in the field. To assess validity of the paper’s R&D planning model, a comparison analysis was conducted with the existing model. The significant factors of the validity assessment were the outcome of the priority research task that can be ultimately elicited from the planning process and the results of the benefit analysis. There are three kinds of outcome data from the priority research task: first is outcome elicited from surveys of demanders starting from the analysis of technology usage possibility of users and field environment to the final key task; second is from the choices made by technology suppliers in the middle stage; and third is created by mainly technology suppliers from the beginning to the end stages. These three types were used for a demand aptness analysis to test the validity of the paper’s R&D planning model. In economic assessment, the method of approach for the fire disaster robotics field fit better with cost reduction method than with the traditional market creation method. The R&D planning model for the fire disaster robotics field developed from this research will be used with reliability as foundational data to create large-scale national R&D programs as the nation is devising policies to support up-to-date technology research for the field of disaster safety. The R&D planning model requires constant improvement and development and can be strengthened in reliability and effectiveness with follow up researches such as a correlation study between fire disaster robots and a reduction in the number of disasters to heighten data reliability in terms of future economic efficiency analysis, as well as research to develop weighted scale methodology for assessing demanders’ and technology suppliers’ scores that help set priorities in R&D for the fire and disaster field.
Investment on research and development of science technology to solve social issues such as the environment or security and to improve the quality of life for citizens is constantly increasing. But the fast changing technical environment; replacing of existing technology with the new; and inaccurate prediction regarding practical demand resulted in excessive R&D planning quantitatively as well as inadequacy qualitatively, which eventually leads to failure in the outcome of R&D. With the society’s increased attention on disasters following the recent disasters, enlarging in scale, including the Fukushima nuclear accident, Nepal earthquake, and the sinking of MV Sewol, robots to search life, rescue, and prevent disasters have been in consistent development, but almost none of such robots have been commercialized and put to actual disaster sites. This is because the development plans for such robots that accurately take into account the demands of firemen on site and the technological feasibility, were not put to consideration from the early stages of R&D Planning. The scope of R&D planning today even requires economic feasibility of research outcome to acquire feasibility for a policy enactment. Under such circumstances, this paper examines the problems in R&D planning and analyzes case study R&D models by field to elicit factors that can be applied even to the field of fire disaster, which were then used to suggest an effective new R&D planning model that even extends to economic benefit estimation. The model (step 1)first searches for opportunities in technology, (step 2)analyzes technology in site environment and researches priorities by function, (step 3)approaches with a function-centered technology system plan and selects tasks for candidates, (step 4)chooses highest priority research task, and (step 5)conducts economic assessment, which includes actual field surveys(firemen) in three out of five steps and a discussion with the nation’s top technological expert in the field. To assess validity of the paper’s R&D planning model, a comparison analysis was conducted with the existing model. The significant factors of the validity assessment were the outcome of the priority research task that can be ultimately elicited from the planning process and the results of the benefit analysis. There are three kinds of outcome data from the priority research task: first is outcome elicited from surveys of demanders starting from the analysis of technology usage possibility of users and field environment to the final key task; second is from the choices made by technology suppliers in the middle stage; and third is created by mainly technology suppliers from the beginning to the end stages. These three types were used for a demand aptness analysis to test the validity of the paper’s R&D planning model. In economic assessment, the method of approach for the fire disaster robotics field fit better with cost reduction method than with the traditional market creation method. The R&D planning model for the fire disaster robotics field developed from this research will be used with reliability as foundational data to create large-scale national R&D programs as the nation is devising policies to support up-to-date technology research for the field of disaster safety. The R&D planning model requires constant improvement and development and can be strengthened in reliability and effectiveness with follow up researches such as a correlation study between fire disaster robots and a reduction in the number of disasters to heighten data reliability in terms of future economic efficiency analysis, as well as research to develop weighted scale methodology for assessing demanders’ and technology suppliers’ scores that help set priorities in R&D for the fire and disaster field.
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