• The Korean Journal of Food And Nutrition
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• v.25 no.1
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• pp.205-213
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• 2012

This study investigated the life cycle of menus and made suggestions on the appropriate time for when new menus should be developed. For this purpose, a total of 636 customers who visited 'T' Restaurant more than 25 times in the past three years were used for analysis. After estimating product life cycles based on sales and selling period, an empirical study was conducted. In terms of product life cycle, a growth stage was observed in the category of pasta and pizza in both stores A and B, whereas sales in the rice category stayed constant. Regarding trend in seasonal sales, a big difference was detected between the two stores. While store A was already in the decline stage of the life cycle in all menu categories, store B remained in the growth stage. In terms of menu life cycle, the product life cycle of long-lived products was observed in the pasta category in both stores A and B. While the pizza category was in the growth stage, the product life cycle of long-lived products was observed in the rice category. It is expected that the results of this study could be useful in development of new menus and product life cycle management to fulfill diverse customer needs in the dining-out business.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.358-362
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• 2001

Environmental Product Life Cycle Management is an activity for defining and describing the product, process of activity environmentally. The activity involves the full life cycle stages of the product; evaluating environmental releases at each stage, determining the aggregate and specific impacts of the releases, developing opportunities to effect environmental improvements. This paper presents a methodological approach for database modeling to build Product Life Cycle Management system and show a set of database modeling. Additionally, a key issue for database is the quality of the provided information.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.115-120
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• 1997

Environmental Product Life Cycle Management is an activity for defining and describing the product, process or activity environmentally. Especially, the main responsibility for the environmental impact of products lies in the design phase of product. Designers cany a heavy responsibility to determine technical, economic and ecological properties of the product. So in order to help designers, structured understanding and application of treating large amount of data and infonnation should be considered. This paper presents a methodological approach for decision supporting to build Product Life Cycle Management system and show a set of database modeling. Additionally, a key issue for databases is the quality of the provided information.

• Proceedings of the KAIS Fall Conference
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• 2004.06a
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• pp.335-338
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• 2004

Life-Cycle Engineering(LCE) is a decision-making methodology that considers environmental and cost needs during the product life-cycle. Environmental conscious design and manufacturing has become more and more important and it has been enforced by governmental regulations and used as trade restriction. LCE involves integrating environmental consideration into new product development including design, material selection, manufacturing processes and distribution of the product to the consumers, plus the end-of-life management such as disassembly, material recovery, remanufacturing of the product after discarding it. In this paper, a state-of-the-art survey of LCE is presented.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.9
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• pp.85-94
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• 2004

As over 70% of the total life cycle cost (LCC) of a product is committed at the early design stage, designers are in an important position to substantially reduce the LCC of the products they design by giving due to life cycle implications of their design decisions. During early design stages, there may be competing concepts with dramatic differences. In addition, the detailed information is scarce and decisions must be made quickly. Thus, both the overhead in developing parametric LCC models fur a wide range of concepts, and the lack of detailed information make the application of traditional LCC models impractical. A different approach is needed, because a traditional LCC method is to be incorporated in the very early design stages. This paper explores an approximate method for providing the preliminary LCC, Learning algorithms trained to use the known characteristics of existing products might allow the LCC of new products to be approximated quickly during the conceptual design phase without the overhead of defining new LCC models. Artificial neural networks are trained to generalize product attributes and LCC data from pre-existing LCC studies. Then the product designers query the trained artificial model with new high-level product attribute data to quickly obtain an LCC for a new product concept. Foundations fur the learning LCC approach are established, and then an application is provided.

• Journal of Mechanical Science and Technology
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• v.17 no.12
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• pp.1969-1976
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• 2003

In the early phases of the product life cycle, Life Cycle Assessment (LCA) is recently used to support the decision-making for the product concepts, and the best alternative can be selected based on its estimated LCA and benefits. Both the lack of detailed information and time for a full LCA for a various range of design concepts need a new approach for the environmental analysis. This paper explores a new approximate LCA methodology for the product concepts by grouping products according to their environmental characteristics and by mapping product attributes into environmental impact driver (EID) index. The relationship is statistically verified by exploring the correlation between total impact indicator and energy impact category. Then, a neural network approach is developed to predict an approximate LCA of grouping products in conceptual design. Trained learning algorithms for the known characteristics of existing products will quickly give the result of LCA for newly designed products. The training is generalized by using product attributes for an EID in a group as well as another product attributes for the other EIDs in other groups. The neural network model with back propagation algorithm is used, and the results are compared with those of multiple regression analysis. The proposed approach does not replace the full LCA but it would give some useful guidelines for the design of environmentally conscious products in conceptual design phase.

• Proceedings of the KSR Conference
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• 2005.05a
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• pp.1028-1032
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• 2005

Life cycle assessment(LCA) has been developed from the concept of life cycle thinking. Life cycle thinking implies that everyone in the whole chain of a product's life cycle, from cradle to grave, has a responsibility and a role to play, taking into account all the relevant external effects. LCA is an analytical tool for identifying environmental loads and assessing the environmental impact in the whole chain of a product's life cycle. In Europe and Japan, LCA and ecodesign study for railway industry have been actively carried out recently. However, LCA for railway industry in domestic is still infant. LCA is standardized in International Organization of Standardization(ISO), base on the ISO 14040 standards, 307 life cycle inventory(LCI) database for infrastructure and base materials have been established in total since 1999. Some of LCI database can use in performing LCA for trains and railway infrastructure, but still not enough to derive accurate LCA result. Therefore, railway oriented LCA methodology and LCI DB are needed to be developed.

• Journal of the Korean Society of Costume
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• v.56 no.3 s.102
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• pp.81-90
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• 2006

The objective of the study is to review trends of clothing export in important countries of the world and thus to know the present stage of clothing export in Korea. For the purpose, changes of export amount, competitiveness and product life cycle were analysed in the countries from the 1960's to the 1990's. The results are as following: First, on the aspect of export amount, industrialized countries lost the lead to newly industrializing countries from the 1960's. Developing countries, as China, win the lead. Second, on the competitiveness aspect, industrialized countries lost competitiveness to newly industrializing countries before the 1960's. And newly industrializing countries were outpaced by China in the export competitiveness from the early 1990's. Third, on the aspect of product life cycle, industrialized countries go first through each period of product life cycle, introduction, growth, maturity and decline, and they all, excluding Japan, sustained period of Maturity for a long time. newly industrializing countries and developing countries go orderly through each period of product life cycle after industrialized countries. As to Korea, duration of each period was short. Specially characteristics of decline period appeared partly in the early 1990's. From the results, the theory of product life cycle, helping to explain changes in production and trade in new product lines, estimated to applicable to clothing export. The phenomena, Italy, Hong Kong and America sustain high competitiveness in the world clothing market for a long time, is needed to be studied carefully. The study about strong points in their clothing industries and competitiveness drive program be to influence Korean export policy in the future.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.667-678
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• 2021

The industrial life cycle theory was extended to the product life cycle theory and the corporate life cycle theory, but a conceptual life cycle was presented, and quantitative empirical evidence for this was insufficient. It is intended to improve appropriate resource planning and resource allocation by quantitatively predicting the industrial cycle and its position (age) in the cycle. Human resources, tangible assets, and industrial output analysis were conducted based on 28 years of actual data of 39 industries in Korea by applying the Gompertz model, which is a population ecology prediction model. By predicting with the Gompertz model, the coefficient of determination R2 value was 97% or more, confirming the high suitability with the actual cumulative sales value of the industry. A numerical model for calculating the life cycle of each industry, calculating the saturation of input resources for each industry, and diagnosing the financial stability of the industry was presented. These results will contribute to the decision-making of industrial policy officers for budget planning appropriately for each stage of industry development. Future research will apply the numerical model of this study to foreign national industries, complete an inter-industry convergence diagnostic model (e.g. ease of convergence, suitability of convergence, etc.) for renewal of fading industries.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.3
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• pp.221-229
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• 2003

In the early phases of the product life cycle, Life Cycle Assessment (LCA) is recently used to support the decision-making fer the conceptual product design and the best alternative can be selected based on its estimated LCA and its benefits. Both the lack of detailed information and time for a full LCA fur a various range of design concepts need the new approach fer the environmental analysis. This paper suggests a novel approximate LCA methodology for the conceptual design stage by grouping products according to their environmental characteristics and by mapping product attributes into impact driver index. The relationship is statistically verified by exploring the correlation between total impact indicator and energy impact category. Then a neural network approach is developed to predict an approximate LCA of grouping products in conceptual design. Trained learning algorithms for the known characteristics of existing products will quickly give the result of LCA for new design products. The training is generalized by using product attributes for an ID in a group as well as another product attributes for another IDs in other groups. The neural network model with back propagation algorithm is used and the results are compared with those of multiple regression analysis. The proposed approach does not replace the full LCA but it would give some useful guidelines fer the design of environmentally conscious products in conceptual design phase.