Hong-Bae Jun

Research issues on closed-loop PLM

This study introduces the research issues on closed-loop product lifecycle management (PLM) where product information flow is closed due to emerging technologies. PLM is a new strategic approach to manage the product lifecycle information efficiently over the whole product lifecycle. Recently, with emerging technologies, PLM enables us to gather and analyze the product lifecycle information and make decisions on several issues without spatial and temporal constraints. However, the PLM system just provides us with new opportunities to gain the competitiveness. To remove ineffectiveness within the product lifecycle and maximize the advantage of closed-loop PLM, it is necessary to look into new challenging issues. For this purpose, first, we introduce the concept of closed-loop PLM. Then, we explore several research problems that become highlighted in the closed-loop PLM. For each product lifecycle phase, we introduce research issues with the review of their previous research and address the requirements for resolving them. Finally, we close with discussion about our work and introduction of further research issues.

A framework for RFID applications in product lifecycle management

This study introduces an overall framework for radio frequency identification (RFID) applications in product lifecycle management (PLM). Recently, with emerging technologies related to product identification and wireless mobile tele-communication, PLM provides a new environment that enables lifecycle actors to gather and analyse product lifecycle information, and make efficient decisions without spatial and temporal constraints. However, previous research has paid little attention to how to apply the emerging technologies into PLM. To cope with this limitation, in the current study, RFID applications in PLM are dealt with from technical and business viewpoints. To this end, an overall framework for RFID applications in PLM is proposed. It contains the definition of a product embedded information device (PEID) that uses RFID technology, its specification and operation scenarios for each application. Furthermore, application issues and their overall procedures are introduced for each lifecycle phase.

A multi-objective evolutionary algorithm for EOL product recovery optimization: turbocharger case study

Recently, the importance of the end-of-life (EOL) product recovery process has been rising since the return rate of products is increasing due to strict environmental regulations on products and economic reasons. In addition to this, the advent of emerging product identification technologies makes product lifecycle data visible at EOL phase. In this regard, the optimization of product recovery processes becomes highlighted as a challenging issue of EOL. At the inspection phase after disassembly, each part can have various EOL recovery options such as re-use, remanufacturing, and disposal. Depending on the selected EOL options of parts, the recovery value of an EOL product will be different. Hence, it is essential to develop a decision-making method that can select the best EOL options of parts for maximizing the recovery value of an EOL product. Although some previous works have focused on improving EOL operations, there has been a lack of research which dealt with EOL product recovery optimization in a quantitative manner. To cope with this limitation, in this study, we focus on a selection problem of EOL product recovery options for a turbocharger case, for maximizing its recovery value which includes both recovery cost and quality. To solve the problem efficiently, we develop a multi-objective evolutionary algorithm (MOEA). To show the effectiveness of our algorithm, we carry out computational experiments.

On condition based maintenance policy

Abstract In the case of a high-valuable asset, the Operation and Maintenance (O&M) phase requires heavy charges and more efforts than the installation (construction) phase, because it has long usage life and any accident of an asset during this period causes catastrophic damage to an industry. Recently, with the advent of emerging Information Communication Technologies (ICTs), we can get the visibility of asset status information during its usage period. It gives us new challenging issues for improving the efficiency of asset operations. One issue is to implement the Condition-Based Maintenance (CBM) approach that makes a diagnosis of the asset status based on wire or wireless monitored data, predicts the assets abnormality, and executes suitable maintenance actions such as repair and replacement before serious problems happen. In this study, we have addressed several aspects of CBM approach: definition, related international standards, procedure, and techniques with the introduction of some relevant case studies that we have carried out.

Disassembly process planning algorithms for end-of-life product recovery and environmentally conscious disposal

Disassembly process planning is an act of preparing detailed operation instructions for disassembling used or an end-of-life (EOL) product to recover or dispose of its constituent parts or subassemblies. The main decisions are: (a) disassembly level; (b) disassembly sequence; and (c) EOL options such as reuse, remanufacturing, recycling, incineration, landfill, etc. This study deals with the three decision variables simultaneously in the parallel disassembly environment for the objective of maximising the profit. Unlike previous studies, we consider practical constraints, i.e., reuse probability and environmental impacts of parts or subassemblies, sequence-dependent setup costs, regulation on recovery rate, and incineration capacity. To represent and solve the problem, we develop an extended AND/OR graph, and then suggest a two-phase algorithm. To show the effectiveness of the proposed algorithm, two case studies have been carried out on an automatic pencil and a telephone. Also, test results on other general product structures are reported.

System architecture for closed-loop PLM

The closed-loop product life cycle management (closed-loop PLM) system focuses on tracking and managing the information of whole product life cycle, with possible feedback of information to product life cycle phases. It provides opportunities to reduce the inefficiency of life cycle operations and gain competitiveness. Thanks to the advent of hardware and software related to product identification technologies, e.g. radio frequency identification (RFID) technology, recently the closed-loop PLM has been highlighted as a tool of companies to enhance the performance of their business models. However, implementing the PLM system requires a high level of coordination and integration. To this end, it is prerequisite to investigate what are the main components for closed-loop PLM and how they are related to each other. To address this need, the curent study focuses on the system architecture of closed-loop PLM with respect to business model, hardware, and software.

Predictive algorithm to determine the suitable time to change automotive engine oil

Recently, emerging technologies related to various sensors, product identification, and wireless communication give us new opportunities for improving the efficiency of automotive maintenance operations, in particular, implementing predictive maintenance. The key point of predictive maintenance is to develop an algorithm that can analyze degradation status of automotive and make predictive maintenance decisions. In this study, as a basis for implementing the predictive maintenance of automotive engine oil, we propose an algorithm to determine the suitable change time of automotive engine oil by analyzing its degradation status with mission profile data. For this, we use several statistical methods such as factor analysis, discriminant and classification analysis, and regression analysis. We identify main factors of mission profile and engine oil quality with factor analysis. Subsequently, with regression analysis, we specify relations between main factors considering the types of mission profile of automotive: urban-mode and highway-mode. Based on them, we determine the proper change time of engine oil through discriminant and classification analysis. To evaluate the proposed approach, we carry out a case study and have discussion about limitations of our approach.

Modelling for product information tracking and feedback via wireless technology in closed-loop supply chains

Closed-loop supply chains (CLSC) consider all of the activities in the lifecycle of a product from design to end-of-life operation. These chains encompass, in addition to the traditional forward flow of products to customers, the acquisition and return flows of products for functional rehabilitation or value recovery. One critical challenge during the operation of CLSC is that information flow almost breaks down after products are delivered to customers. Nevertheless, with the fast development of information and communication technologies (ICTs), especially such as wireless technology, information flow can go beyond the customers, up to its final destiny and back to designers and producers. This paper focuses on the research of closed-loop product information (CLPI) tracking and feedback in wireless technology-enabled CLSC from the modelling point of view and models of three levels of abstraction are proposed to elucidate and decompose the whole scenario. First, from the system level, the framework of CLPI tracking and feedback is presented, which covers the related application background. Second, from the process level, the models for three major information flows are addressed, focusing on the dynamic information related flows and activities of CLPI tracking. Third, from the information and data level, the product related information is classified, and then the information structure of required information for tracking is modelled as well as the method to track and feedback the dynamic information. Finally, a case study from the EU PROMISE project is given to illustrate the modelling proposition.

Heuristic algorithms for minimising total recovery cost of end-of-life products under quality constraints

Recently, the optimisation of end-of-life (EOL) product recovery processes has been highlighted. At the inspection phase after disassembly, each part can have various recovery options such as reuse, reconditioning, remanufacturing, and disposal. Depending on the selected options of parts, the values of recovered products that are made by reassembling parts will be different. Hence, it is important to decide appropriate recovery options of parts at the treatment of EOL products, in order to maximise the values of recovered products. To this end, this study deals with a decision making problem to select the best recovery options of parts for minimising the total recovery cost of products under quality constraints. This problem is formulated with a mixed integer nonlinear programming model and heuristic search algorithms are proposed to resolve it. A case study for a turbocharger product is introduced with computational experiments of the proposed algorithms.

A primitive ontology model for product lifecycle meta data in the closed-loop PLM

In the closed-loop product lifecycle management (PLM) which allows all lifecycle actors of the whole product lifecycle to access, manage, and control product related information with emerging technologies such as radio frequency identification (RFID) and wireless communication, it is prerequisite to share and exchange the product lifecycle data and information among lifecycle actors, smart products, and a PLM system. To this end, common semantics for product lifecycle meta data are required. In this regard, the ontology model for product lifecycle meta data can play a major role in supporting the sharing of product lifecycle data and information during whole product lifecycle. It can facilitate the communication among lifecycle actors, smart products, and a PLM system. For this purpose, in this study, we propose a primitive ontology model for product lifecycle meta data in the closed-loop PLM. For this, first, we clarify what the product lifecycle data is. We then design the structure of meta data that describes contents of product lifecycle data. Subsequently, we build up a primitive ontology for product lifecycle meta data in resource description framework (RDF) and have discussion about pros and cons of the proposed model.