• Biomaterials and Biomechanics in Bioengineering
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• v.3 no.1
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• pp.1-14
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• 2016

Well-ordered porous materials are very promising in orthopedics since they allow tailoring the mechanical properties. Finite element (FE) analysis is commonly used to evaluate the mechanical behavior of well-ordered porous materials. However, FE results generally differ importantly from experimental data. In the present article, three types of manufacturing irregularities were characterized on an additive manufactured porous titanium sample having a simple cubic unit-cell: strut diameter variation, strut inclination and fractured struts. These were included in a beam FE model. Results were compared with experimental data in terms of the apparent elastic modulus (Eap) and apparent yield strength (SY,ap). The combination of manufacturing irregularities that yielded the closest results to experimental data was determined. The idealized FE model resulted in an Eap one order of magnitude larger than experimental data and a SY,ap almost twice the experimental values. The strut inclination and fractured struts showed the strongest effects on Eap and SY,ap, respectively. Combining the three manufacturing irregularities produced the closest results to experimental data. The model also performed well when applied to samples having different structural dimensions. We recommend including the three proposed manufacturing irregularities in the FE models to predict the mechanical behavior of such porous structures.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.36 no.1
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• pp.24-35
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• 2013

A cell formation approach based on cluster analysis is developed for the configuration of manufacturing cells. Cell formation, which is to group machines and parts into machine cells and the associated part families, is implemented to add the flexibility and efficiency to manufacturing systems. In order to develop an efficient clustering procedure, this paper proposes a cluster analysis-based approach developed by incorporating and modifying two cluster analysis methods, a hierarchical clustering and a non-hierarchical clustering method. The objective of the proposed approach is to minimize intercellular movements and maximize the machine utilization within clusters. The proposed approach is tested on the cell formation problems and is compared with other well-known methodologies available in the literature. The result shows that the proposed approach is efficient enough to yield a good quality solution no matter what the difficulty of data sets is, ill or well-structured.

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.1
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• pp.57-62
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• 2002

The semiconductor industry has continuously been looking for the ways to improve yield and to reduce manufacturing cost. The layout modification approach, one of yield enhancement techniques, is applicable to all design styles, but it does not require any additional resources in terms of silicon area. The layout modification method for yield enhancement consists of making local variations in the layout of some layers in such a way that the critical area, and consequently the sensitivity of the layer to point defects, is reduced. Chen and Koren (1995) proposed a greedy algorithm that removes defect sensitive area using via moving, but it is easy to fall into a local minimum. In this paper, we present a via moving algorithm using simulated annealing and enhance yield by diminishing defect sensitive area. As a result, we could decrease the defect sensitive area effectively compared to the greedy algorithm presented by Chen and Koren. We expect that the proposed algorithm can make significant contributions on company profit through yield enhancement.

• Journal of the Korean Wood Science and Technology
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• v.39 no.2
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• pp.163-171
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• 2011

Because Japanese cedar shows lower mechanical performance, glued-laminated timber (glulam) can be a better way to utilize Japanese cedar for structural purpose. However, low yield of higher grade lamination from log makes it difficult to design structural glulam. This study was aimed to increase the yield of higher grade lamination and provide higher efficiency of manufacturing structural lamination by ultrasonic log sorting technology. Logs were sorted by an existing log grading rule regulated by Korea Forest Research Institute (KFRI). It was found that the KFRI log grading rule contributed to finding better logs in viewpoint of the volumetric yield and it can reduce the number of rejected lumber by visual grading. However, it could not identify better logs to produce higher-grade products. To find an appropriate log-sorting-method for structural products, log diameter and ultrasonic time of flight (TOF) for the log were considered as factors to affect mechanical performance of resulting products. However, it was found that influence of log diameter on mechanical performance of resulting products was very small. The TOF showed a possibility to sort logs by mechanical performance of resulting products even though a coefficient of correlation was not strong (R = 0.6). In a case study, the log selection based on the ultrasonic TOF of the log increased the yield of the outermost tension lamination (E8 or better grade, KS F 3021) from 2.6% to 12.5% and reduced LTE5 (lower than E5 grade) lamination from 43.6% to 10.3%, compared with the existing KFRI log grading rule.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.2
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• pp.69-76
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• 2024

The rheological properties of fresh concrete significantly influence its manufacturing and performance. However, the diversification of newly developed mixtures and manufacturing techniques has made it challenging to accurately predict these properties using traditional empirical methods. This study introduces a multiscale rheological property prediction model designed to quantitatively anticipate the rheological characteristics from nano-scale interparticle interactions, such as those among cement particles, to micro-scale behaviors, such as those involving fine aggregates. The Yield Stress Model (YODEL), the Chateau-Ovarlez-Trung equation, and the Krieger-Dougherty equation were utilized to predict the yield stress for cement paste and mortar, as well as the plastic viscosity. Initially, predictions were made for the paste scale, using the water-cement ratio (W/C) of the cement paste. These predictions then served as a basis for further forecasting of the rheological properties at the mortar scale, incorporating the same W/C and adding the cement-sand volume ratio (C/S). Lastly, the practicality of the predictive model was assessed by comparing the forecasted outcomes to experimental results obtained from rotational rheometer.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.6
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• pp.579-587
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• 2015

Semiconductor manufacturing industry is a high density integration industry because it generates a vest number of data that takes about 300~400 processes that is supervised by numerous production parameters. It is asked of engineers to understand the correlation between different stages of the manufacturing process which is crucial in reducing production costs. With complex manufacturing processes, and defect processing time being the main cause. In the past, it was possible to grasp the corelation among manufacturing process stages through the engineer's domain knowledge. However, It is impossible to understand the corelation among manufacturing processes nowadays due to high density integration in current semiconductor manufacturing. in this paper we propose a canonical correlation analysis (CCA) using both wafer test voltage variables and fail bit counts variables. using the method we suggested, we can increase the semiconductor yield which is the result of the package test.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.9
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• pp.100-106
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• 2020

This study analyzes the residual stress of AISI 1536V for an engine shaft of the shipbuilding industry and AISI A387 for a reactor shell of the chemical refining industry by the hole drilling method with a strain gauge rosette, which transforms fine mechanical changes into electrical signals. Tensile residual stress is generated in the forging and heat treatment process because specimens are affected by thermal stress and metal transformation stress. In the heat treatment process, the residual stress of AISI A387 is almost 170% the yield strength at 402 MPa. Since during the machining process, variable physical loads are applied to the material, compressive residual stress is generated. Under the same condition, the mechanical properties greatly affect the residual stress during the machining process. After the stress-relieving heat treatment process, the residual stress of AISI A387 is reduced below the yield strength at 182 MPa. Therefore, it is necessary to control the temperature, avoid rapid heat change, and select machining conditions depending on the mechanical properties of materials during manufacturing processes. In addition, to sufficiently reduce the residual stress, it is necessary to study the optimum condition of the stress-relieving heat treatment process for each material.

• Journal of Intelligence and Information Systems
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• v.14 no.4
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• pp.89-101
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• 2008

The most used tool for quality control is control chart in manufacturing industry. But it has limitations at current situation where most of manufacturing facilities are automated and several manufacturing processes have interdependent relationship such as CCM assembly line. To Solve problems, we propose quality management system based on data mining that are consisted of monitoring system where it monitors flows of processes at single window and feature extraction system where it predicts the yield of final product and identifies which processes have impact on the quality of final product. The quality management system uses decision tree, neural network, self-organizing map for data mining. We hope that the proposed system can help manufacturing process to produce stable quality of products and provides engineers useful information such as the predicted yield for current status, identification of causal processes for lots of abnormality.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.3
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• pp.42-50
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• 2020

This study explores the effects of repair width on the deposition characteristics and mechanical properties of stainless steel samples repaired using direct energy deposition (DED). In the DED repair process, defects such as pores and cracks can occur at the interface between the substrate and deposited material. In this study, we changed the width of the pre-machined zone for repair in order to prevent cracks from occurring at the inclined surface. As a result of the experiment, cracks of 10-40 ㎛ in length were formed along the inclined slope regardless of the repair width. Yield and tensile strength decreased slightly as the repair width increased, but the total and uniform elongation increased. This is due to the orientation of the crack. For specimens with a repair width of 20 mm, yield and tensile strength were 883 MPa and 1135 MPa, respectively. Total and uniform elongations were 14.3% and 8.2%, respectively. During observation of the fracture specimens, we noted that the fracture of the specimen with an 8 mm repair width occurred along the slope, whereas specimens with 14 mm and 20 mm repair depths fractured at the middle of the repaired region. In conclusion, we found that tensile properties were dependent upon the repair width and the inclination of the crack occurred at the interface.

• Journal of the Korean Operations Research and Management Science Society
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• v.18 no.3
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• pp.151-157
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• 1993

In this paper, we investigate the effects of yield randomness for lot-sizing in a multi-stage production system. The practical importance of incorporating yield randomness into production models has been emphasized by many researchers. Yield randomness, especially in semiconductor manufacturing, poses a mojor challenge for production planning and control. The task becomes even more difficult if the demand for final product is uncertain. An attempt to meet the demand with a higher level of confidence forces one to release more input in the fabrication line. This leads to excessive work-in-process (WIP) inventories which cause jobs to spend unpredictably longer time waiting for the machines. The result is that it is more difficult to meet demand with exceptionally long cycle time and puts further pressure to increase the safety stocks. Due to this spiral effect, it is common to find that the capital tied in inventory is the msot significant factor undermining profitability. We propose a policy to determine the quantity to be processed at each stage of a multi-stage production system in which the yield at each stage may be random and may need rework.