• 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.

• Knowledge Management Research
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• v.22 no.2
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• pp.209-225
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• 2021

Product Lifecycle Management is a well-defined management method consisting of 8 knowledge areas. Since the 4th industrial revolution is closely related to smart factories, the importance of product lifecycle management, which effectively manages the entire process from product idea generation to disposal, is emerging. This study analyzed the current and future applications of the knowledge domain of product life cycle management from the perspective of the 4th industrial revolution for experts in the field of product life cycle management. The expert's perception was analyzed from the current point of view and the future point of view to see how the product life cycle management knowledge area is applied in the field. The current and future application degree of the knowledge domain of product life cycle management was analyzed, and whether there was a difference between the knowledge domains in terms of the level of application was analyzed. Based on the analyzed results, its meaning and future flow are presented.

• Korean Journal of Computational Design and Engineering
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• v.16 no.4
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• pp.268-276
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• 2011

The product-level carbon footprint (PCF) is a comprehensive and widely accepted metric for sustainable product development. However, since a full PCF study in general is time and cost intensive, it is not feasible for the product development team to synchronize the activity to the main product development process. In addition, the current dedicated life cycle assessment (LCA) tools for calculating PCF, separated from the main product data management systems, have limitations to provide timely PCF information for design decision makings and collaborations between design and environment engineers. This paper examines the possibility of the extension of the current product data model that can support the PCF calculation with PDM (Product Data Management) databases. The product data model can represent not only the content of products but also context or system information of the products. The product data model can be implemented as a PDM database that can satisfy the needs for handy and timely PCF calculations from the consistent product data for dynamic design decision makings and engineering collaborations.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.3 s.180
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• pp.22-31
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• 2006

This paper introduces an approach to an ontology-based knowledge framework for product life cycle management (PLM). Participants in a product life cycle want to share comprehensive product knowledge without any ambiguity and heterogeneity. However, previous knowledge management approaches are limited in providing those aspects. Therefore, we suggest an ontology-based knowledge framework including knowledge maps, axioms and specific knowledge far domain. The bottom level, the axiom, specifies the semantics of concepts and relations of knowledge so that ambiguity of the semantics can be alleviated. The middle level is a product development knowledge map; it defines the concepts and the relations of the product domain common knowledge and guides engineers to process their engineering decisions. The middle level is then classified further into more detailed levels, such as generic product level, specific product level, product version level, and product item level for PLM. The top level is specialized knowledge fer a specific domain that gives the solution of a specific task or problem. It is classified into three knowledge types: expert knowledge, engineering function knowledge, and data-analysis-based knowledge. This proposed framework is based on ontology to accommodate a comprehensive range of unambiguous knowledge for PLM and is represented with first-order logic to maintain a uniform representation.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.103-112
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• 1996

Optimal pricing research in general has been focused on profit maximizing strategy under the given product life-time T. Here we have tried to study the effect of uncertain product life-time on dynamic optimal pricing strategy. In reality, the life-time of product is more likely to be uncertain and not known as well. In terms of approximating the model to the concerned reality, so-called model validity, it seems to be more desirable to consider the uncertainty of product life-time into the optimal pricing strategy model, For this purpose, we tried two different approaches. One is to consider diverse product life-time probability functions under fixed life-time T. In this case, we might have the same product life-time as the previous study, but the process could be different in the expectation of product's discontinuity. The other is that life-time itself is not determined and thus it is the situation in which we can only decide optimal price on incremental basis. The former is the situation in which although we got some strong guess on life-time of a certain product, the pattern of expected life-time probability could be different. The question is what could be optimal pricing strategies on such different product life-time situations. But since in the latter, we don't assume any idea on the life-time of product. proper optimal pricing could be derived only from the past prices and diffusion information. While the latter seems to be safer in the aspect of model assumption, the former could be more realistic because we might have more or less a prior knowledge on the product life-time itself.

• Korean Journal of Computational Design and Engineering
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• v.9 no.3
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• pp.260-265
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• 2004

This paper proposed a Web-based training service for product data management by supporting an integrated product data management system, various technical documents. and efficient communication systems. It also supports a general product development process and a consistent product data model that enable participants to experience management of consistent product information during the product development life cycle. The Web based environment of the service also provides participants with a collaborative workplace with other participants and a Web portal for all the components of the service.

• Journal of Service Research and Studies
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• v.10 no.4
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• pp.89-100
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• 2020

The smart factory is an important axis of the 4th industrial revolution. Smart factory is a system that induces the maximum efficiency and effectiveness of production using the IoT and intelligent sensing systems. The product lifecycle management technique is a method that can actively reflect the consumer's requirements in the smart factory and manage the entire process from the consumer to the post management. There have been many studies on product lifecycle management, but studies on how to organize product lifecycle management knowledge domains in preparation for the era of the 4th industrial revolution were insufficient. This study analyzed the opinions of a group of experts preparing for the 4th industrial revolution in terms of product lifecycle management. The impact of the 4th industrial revolution on the detailed knowledge areas of product lifecycle management was investigated. The changes in product lifecycle management were summarized using a qualitative data analysis technique for a group of experts. Based on the opinions of experts, the product lifecycle management, which consists of a total of 30 detailed knowledge areas, was prepared to supplement or prepare for the 4th industrial revolution. This study investigates changes in product lifecycle management in preparation for the 4th industrial revolution in the knowledge domain of the existing defined product life cycle management. In future research, it is necessary to redefine the knowledge domain of product life cycle management suitable for the era of the 4th industrial revolution and investigate the perception of experts. Considering the social culture and technological change factors of the 4th industrial revolution, the scope and scope of product life cycle management can be newly defined.

• IE interfaces
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• v.21 no.1
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• pp.18-32
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• 2008

In recent, a general trend is observed towards more customized products and shorter product life cycles in manufacturing companies. In these companies, customers often wish to influence the product they order and to get a variant of product that meets their requirements. This environment is called as a customer-oriented manufacturing companies. This paper presents a procedure of product specification management for customer-oriented manufacturing companies by using product specification framework. This framework is founded on the product specification based product structure which is made of model, specification, function, and part. Also, a product specification management system(PSMS) is implemented by using the proposed product specification framework and is a core system in product data integration system. To illustrate an utilization of the proposed framework and procedure, a case of a ship engine product is applied. As a result, PSMS reduces delivery time and improves customer relationships. Moreover, the case shows that PSMS can be used as a tool for improving inter-department coordination within a company during product life cycle.

• Journal of Ocean Engineering and Technology
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• v.26 no.2
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• pp.58-67
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• 2012

Recently, both the integration of product data during design and production and the effective management of information during full lifecycles have attracted attention from shipyards and ship owners as a result of recycling regulations and a desire for efficient operations. Generally, PLM (Product Lifecycle Management) supports a collaborative environment during the BOL (Beginning of Life) stage, while an ALM (Asset Lifecycle Management) system provides all of the information required to maintain, overhaul, and discard/recycle all or part of a vessel during the MOL (Middle of Life) and EOL (End of Life) stages. The main goal of this paper is to suggest the fundamental configuration of a PALM (Product Asset Lifecylce Management) system and a method that can be used to utilize a marine vessel's lifecycle information during the MOL, emphasizing the maintenance information during the middle of life. The authors also suggest a PALM system configuration in which lifecycle information can be collected by a PEID (Product Embedded Information Device) integrating a microcomputer, sensors, and wireless network communication. Through a prototype PALM system, the suggested features and PALM system configuration are implemented.