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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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Industrial Engineering and Management Systems
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Journal DOI :
Korean Institute of Industrial Engineers
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Volume & Issues
Volume 14, Issue 4 - Dec 2015
Volume 14, Issue 3 - Sep 2015
Volume 14, Issue 2 - Jun 2015
Volume 14, Issue 1 - Mar 2015
Selecting the target year
A Quantitative Study of Influencing Factors on Crowd Participation in a Crowdsourcing Project for Consumer Product Design
Tran, Tuananh ; Park, Joon Young ;
Industrial Engineering and Management Systems, volume 14, issue 4, 2015, Pages 325~334
DOI : 10.7232/iems.2015.14.4.325
Nowadays, crowdsourcing has become a popular concept and is widely used in many social, economical and technological areas. For consumer product design, crowdsourcing is implemented extensively with many cases. Although there has been a lot of research on the application of crowdsourcing for product design, the big picture of how factors influence the participartion of individuals from the crowd in a crowdsourcing project for product design has not yet been understood. This paper aims to investigate the relationships of crowd participation and influencing factors including: process, product, and reward. To do this, we conducted a survey on a crowd of engineering individuals and analyzed the collected data with data mining techniques. Main findings include the relationships of crowd participation versus process, product, and reward factors as well as regression models to predict crowd participation.
A New Latent Class Model for Analysis of Purchasing and Browsing Histories on EC Sites
Goto, Masayuki ; Mikawa, Kenta ; Hirasawa, Shigeichi ; Kobayashi, Manabu ; Suko, Tota ; Horii, Shunsuke ;
Industrial Engineering and Management Systems, volume 14, issue 4, 2015, Pages 335~346
DOI : 10.7232/iems.2015.14.4.335
The electronic commerce site (EC site) has become an important marketing channel where consumers can purchase many kinds of products; their access logs, including purchase records and browsing histories, are saved in the EC sites' databases. These log data can be utilized for the purpose of web marketing. The customers who purchase many product items are good customers, whereas the other customers, who do not purchase many items, must not be good customers even if they browse many items. If the attributes of good customers and those of other customers are clarified, such information is valuable as input for making a new marketing strategy. Regarding the product items, the characteristics of good items that are bought by many users are valuable information. It is necessary to construct a method to efficiently analyze such characteristics. This paper proposes a new latent class model to analyze both purchasing and browsing histories to make latent item and user clusters. By applying the proposal, an example of data analysis on an EC site is demonstrated. Through the clusters obtained by the proposed latent class model and the classification rule by the decision tree model, new findings are extracted from the data of purchasing and browsing histories.
A Hybrid Approach Based on Multi-Criteria Satisfaction Analysis (MUSA) and a Network Data Envelopment Analysis (NDEA) to Evaluate Efficiency of Customer Services in Bank Branches
Khalili-Damghani, Kaveh ; Taghavi-Fard, Mohammad ; Karbaschi, Kiaras ;
Industrial Engineering and Management Systems, volume 14, issue 4, 2015, Pages 347~371
DOI : 10.7232/iems.2015.14.4.347
A hybrid procedure based on multi-Criteria Satisfaction Analysis (MUSA) and a Network Data Envelopment Analysis (NDEA) is proposed to evaluate the relative efficiency of customer services in bank branches. First, a three-stage process including sub-processes such as customer expectations, customer satisfaction, and customer loyalty, is defined to model the banking customer services. Then, fulfillment of customer expectations, customer loyalty level, and the customer satisfaction degree are measured and quantified through a multi-dimensional questionnaire based on customers' perceptions analysis and MUSA method, respectively. The customer services scores and the other criteria such as mean of employee evaluation score, operation costs, assets, deposits, loans, number of accounts are considered in network three-stage DEA model. The proposed NDEA model is formed based on multipliers perspective, output-oriented, and constant return to scale assumptions. The proposed NDEA model quantifies and assesses the total efficiency of main process and assigns the efficiency to customer expectations, customer satisfactions, and customer loyalties sub-processes in bank branches. The whole procedure is applied on 30 bank branches in IRAN. The proposed approach can be used in other organizations such as airports, airline agencies, urban transportation systems, railway organizations, chain stores, chain restaurants, public libraries, and entertainment centers.
Rules of Three Untrained Workers' Assignment Optimization in Reset Limited-Cycled Model with Multiple Periods
Song, Peiya ; Kong, Xianda ; Yamamoto, Hisashi ; Sun, Jing ; Matsui, Masayuki ;
Industrial Engineering and Management Systems, volume 14, issue 4, 2015, Pages 372~378
DOI : 10.7232/iems.2015.14.4.372
In labor-intensive enterprise, such as garment factory, assembly line is widely used as a manufacturing process for reducing costs and production time. However, for the sake of the various working capacity of worker, idle or delay may happen and influence the rear processes. If these unforeseeable delay happened continuously, it may influence the whole manufacturing process and a model, which is called limited-cycle model with multiple periods (LCMwMP), is assumed to evaluate the influence risk. In order to minimize the risk, the assignment of the workers is focused on. In this paper, we deal with an assembly line as LCMwMP model when two kinds of workers exist, whose efficiency is assumed to two different groups. We consider an optimization problem for finding an assignment of workers to the line that minimizes total expected risk, which is exchanged to expected cost by reset model of LCMwMP. First, reset model as a simple model of LCMwMP is introduced. Then, some hypotheses of the rules of the optimal worker assignment are proposed and some numerical experiments are researched assuming the processing time as Erlang distribution. Finally, the other rules on other certain conditions are discussed.
Hazard Analysis and Risk Assessments for Industrial Processes Using FMEA and Bow-Tie Methodologies
Afefy, Islam H. ;
Industrial Engineering and Management Systems, volume 14, issue 4, 2015, Pages 379~391
DOI : 10.7232/iems.2015.14.4.379
Several risk assessment techniques have been presented and investigated in previous research, focusing mainly on the failure mode and effect analysis (FMEA). FMEA can be employed to determine where failures can occur within industrial systems and to assess the impact of such failures. This research proposes a novel methodology for hazard analysis and risk assessments that integrates FMEA with the bow-tie model. The proposed method has been applied and evaluated in a real industrial process, illustrating the effectiveness of the proposed method. Specifically, the bowtie diagram of the critical equipment in the adopted plant in the case study was built. Safety critical barriers are identified and each of these is assigned to industrial process with an individual responsible. The detection rating to the failure mode and the values of risk priority number (RPN) are calculated. The analysis shows the high values of RPN are 500 and 490 in this process. A global corrective actions are suggested to improve the RPN measure. Further managerial insights have been provided.
Quantitative Analysis for Plasma Etch Modeling Using Optical Emission Spectroscopy: Prediction of Plasma Etch Responses
Jeong, Young-Seon ; Hwang, Sangheum ; Ko, Young-Don ;
Industrial Engineering and Management Systems, volume 14, issue 4, 2015, Pages 392~400
DOI : 10.7232/iems.2015.14.4.392
Monitoring of plasma etch processes for fault detection is one of the hallmark procedures in semiconductor manufacturing. Optical emission spectroscopy (OES) has been considered as a gold standard for modeling plasma etching processes for on-line diagnosis and monitoring. However, statistical quantitative methods for processing the OES data are still lacking. There is an urgent need for a statistical quantitative method to deal with high-dimensional OES data for improving the quality of etched wafers. Therefore, we propose a robust relevance vector machine (RRVM) for regression with statistical quantitative features for modeling etch rate and uniformity in plasma etch processes by using OES data. For effectively dealing with the OES data complexity, we identify seven statistical features for extraction from raw OES data by reducing the data dimensionality. The experimental results demonstrate that the proposed approach is more suitable for high-accuracy monitoring of plasma etch responses obtained from OES.
Production Planning Method Using the Push-back Heuristic Algorithm: Implementation in a Micro Filter Manufacturer in South Korea
Sung, Shin Woong ; Jang, Young Jae ; Lee, Sung Wook ;
Industrial Engineering and Management Systems, volume 14, issue 4, 2015, Pages 401~412
DOI : 10.7232/iems.2015.14.4.401
In this paper, we present a modeling approach to production planning for an actual production line and a heuristic method. We also illustrate the successful implementation of the proposed method on the production line. A heuristic algorithm called the push-back algorithm was designed for a single machine earliness/tardiness production planning with distinct due date. It was developed by combining a minimum slack time rule and shortest processing time rule with a push-back procedure. The results of a numerical experiment on the heuristic's performance are presented in comparison with the results of IBM ILOG CPLEX. The proposed algorithm was applied to an actual case of production planning at Woongjin Chemical, a leading manufacturer of filter products in South Korea. The seven-month execution of our algorithm led to a 24.5% decrease in the company's inventory level, thus demonstrating its practicality and effectiveness.
Heuristic-Based Algorithm for Production Planning Considering Allocation Rate Conformance to Prevent Unstable Production Chain
Kim, Taehun ; Ji, Bongjun ; Cho, Hyunbo ;
Industrial Engineering and Management Systems, volume 14, issue 4, 2015, Pages 413~419
DOI : 10.7232/iems.2015.14.4.413
This study solved the problem of unstable production chains by considering allocation rate conformance. We proposed two phased algorithm suitable for solving production planning that considers allocation rate conformance; the first phase was heuristic initial solution generation, and the second phase was tabu-search based solution improvement. By using three data sets which have different sizes of data and three different criteria, the results of proposed algorithm were compared with MIP results. The proposed algorithm showed the best production plan in terms of allocation rate conformance, and it was appropriate for other criteria; it solved the problem of unstable production chains by solving concentrated and unfair allocation.