The 2-round Delphi survey and Focus Group Interview (FGI) survey method, in this study, are sequentially applied for the level analysis of the high-level radioactive waste (HLW) management technologies, that are classified into transport/storage, site evaluation, and disposal categories. The 2- round Delphi survey was conducted on domestic 56 experts in the HLW field in Korea, and survey answers were managed with questionnaires distributed by e-mail. In the FGI survey, domestic 24 experts from management field were formed into three groups to conduct in-depth interviews. Past research achievements including journal papers, intellectual properties and the expert opinions presented at expert hearing on HLW technology were used as reference materials. As a result of the survey, in this study, the average domestic technology level compared to the leading countries was 83.1% in transport area, 79.6% in storage area, 62.2% in site evaluation area, and 57.4% in disposal area, respectively. When compared to the former level analysis results in 2017, technology level of transport-storage area increased by 8.6%, and the site evaluation-disposal technology area decreased by 7.27%. The highest factor that increase the level of technology in the transport-storage field was due to the increased R&D program resulting on journal papers, intellectual properties. In addition, the decrease factor in the level of technology in the site evaluation-disposal field was mainly due to relatively low R&D program when compared to the leading countries. Suggested method for the level survey can be used to find out the basic data of the lower tech technologies, to estimate the efficient research budgets and to prepare the R&D human resources. With this regards, R&D roadmap can be matured with suggested prediction method for the domestic technology level on HLW.

This paper proposes the heuristic algorithm for the generalized GT problem to consider the restrictions which are given the number of cell, maximum number of machines and minimum number of machines. This algorithm is classified into two stages. First stage is the course to form machine cells. we use the similarity coefficient which proposed and calculate the similarity values about each pair of all machines and align these values descending order. If any machine which is composed of selected similarity coefficient is possible to link the other machine on the edge of machine cell and have regard to restrictions and different kind relation among machines in the machine cell, then we assign the machine to the machine cell. Next stage is the course to form part families using proposed grouping efficacy. This stage is also completed when every part is assigned to the machine cell. The results of using the proposed algorithm are compared to the Modified p-median model. The computational results show that the proposed algorithm provides a powerful means of solving the machine-part grouping problem.

The recycling cell formation problem means that disposal products are classified into recycling part families using group technology in their end of life phase. Disposal products have the uncertainties of product status by usage influences. Recycling cells are formed considering design, process and usage attributes. In this paper, a novel approach to the design of cellular recycling system is proposed, which deals with the recycling cell formation and assignment of identical products concurrently. Fuzzy clustering algorithm and Fuzzy-ART neural network are applied to describe the states of disposal product with the membership functions and to make recycling cell formation. This approach leads to recycling and reuse of the materials, components, and subassemblies and can evaluate the value at each cell of disposal products. Application examples are illustrated by disposal refrigerators, compared fuzzy clustering with Fuzzy-ART neural network performance in cell formation.