• Transactions of the Korean Society of Mechanical Engineers A
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• v.22 no.2
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• pp.444-450
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• 1998

In the present investigation, it is attempted to derive a yield function and associated flow rules of loose metal powders to predict plastic deformation and density change during compaction. The loose metal powders yield by shear stress as well as hydrostatic stress and the yield strength is much smaller in tension than compression. Therefore, a yield function for the powders is expressed as a shifted ellipse toward the negative direction in the hydrostatic stress axis in the space defined by the two stresses. Each of parameters A, B and .delta. used in the yield function is expressed as a function of relative density and it is determined by uniaxial strain and hydrostatic compressions using Cu powder. Flow rules obtained by imposing the normality rule to the yield function are applied to the analyses of unidirectional, bidirectional and hydrostatic compressions, resulting in an excellent agreement with experiments. The yield function is further examined by checking volume changes in plane stain, uniaxial strain and shear deformations.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.1
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• pp.10-19
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• 2013

Dispatching rule plays an important role in a hybrid flow shop. Finding the appropriate dispatching rule becomes more challenging when there are multiple criteria, uncertain demands, and dynamic manufacturing environment. Using a single dispatching rule for the whole shop or a set of rules based on a single criterion is not sufficient. Therefore, a multi-criteria decision making technique using 'the order preference by similarity to ideal solution' (TOPSIS) and 'analytic hierarchy process' (AHP) is presented. The proposed technique is aimed to find the most suitable set of dispatching rules under different manufacturing scenarios. A simulation based case study on a PCB manufacturing process is presented to illustrate the procedure and effectiveness of the proposed methodology.

• IE interfaces
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• v.12 no.3
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• pp.468-479
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• 1999

Lean production system can be defined as customer(product)-oriented production system with small lot size and flow-shop layout based on the JIT(Just-in-time) principles. In this paper, we introduce a case example of implementation of the Lean product ion system for manufacturing line of electronic component which has both machine processes and manual jobs. We also investigate the issues of implementing the Lean production system with the viewpoints of layout design scheme and JIT management rules. In the layout design, we propose the cell-line which has flow-shop layout with small lot size. In the management rules, the superior cell rule is applied in order to boost the needs of kaisen up. As the results of implementing the Lean production system, production lead time is decreased from 5 days to 1.5 days and also productivity and quality level arc surprisingly increased.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.767-772
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• 2005

The Internet is a packet switched network which offers best-effort service, but current IP network provide enhanced services such Quality of Services, Virtual Private Network (VPN) services, Distribute Firewall and IP Security Gateways. All such services need packet classification for determining the flow. The problem is performing scalable packet classification at wire speeds even as rule databases increase in size. Therefore, this research offer packet classification algorithm that increase classifier performance when working with enlarge rules database by rearrange rule structure into Bitmap Intersection Lookup (BIL) tables. It will use packet's header field for looking up BIL tables and take the result with intersection operation by logical AND. This approach will use simple algorithm and rule structure, it make classifier have high search speed and fast updates.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.1
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• pp.67-95
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• 1998

This research addresses flow time prediction in the dynamic unbalanced job shop scheduling environment. The specific purpose of the research is to develop the job flow time prediction model in the dynamic unbalance djob shop. Such factors as job characteristics, job shop status, characteristics of the shop workload, shop dispatching rules, shop structure, etc, are considered in the prediction model. The regression prediction approach is analyzed within a dynamic, make-to-order job shop simulation model. Mean Absolute Lateness (MAL) and Mean Relative Error (MRE) are used to compare and evaluate alternative regression models devloped in this research.

• Tunnel and Underground Space
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• v.10 no.2
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• pp.173-179
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• 2000

The influence of the plastic flow rules on the elasto-plastic behaviour of a discrete joint element was investigated by performing the numerical direct shear tests under both constant normal displacement and normal displacement conditions. The finite interface elements obeying Plesha’s joint constitutive law was used to allow the relative motion of the rock blocks on the joint surface. Realistic results were obtained in the tests adopting the non-associated flow rule, while the associated flow rule overestimated the joint dilation. To overcome the computational drawbacks coming from the non-symmetric element stiffness matrix in the conventional non-associated plasticity, the symmetric formulation of the tangential stiffness matrix for a non-associated joint element was proposed. The symmetric elasto-plastic matrix it derived by assuming an imaginary equivalent joint with associated flow rule which shows the same plastic response as that of original Joint with non-associated flow rule. The validity of the formulation was confirmed through the numerical direct shear tests under constant normal stress condition.

• Journal of Intelligence and Information Systems
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• v.12 no.1
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• pp.57-73
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• 2006

This paper describes a methodology for automating the material handling equipment (MHE) evaluation and selection processes by combining knowledge-based rules and fuzzy multi-criteria decision making approach. The methodology is proposed to solve the MHE selection problems under fuzzy environment. At the primary stage, the most appropriate MHE type among the alternatives for each material flow link is searched. Knowledge-based rules are employed to retrieve the alternatives for each material flow link. To consider and compare the alternatives, multiple design factors are considered. These factors include both quantitative and qualitative measures. The qualitative measures are converted to numerical measures using fuzzy logic. The concept of fuzzy logic is applied to evaluation matrices used for the selection of the most suitable MHE through a fuzzy linguistic approach. Thus, this paper demonstrates the potential applicability of fuzzy theory in the MHE applications and provides a systemic guidance in the decision-making process.

• The Journal of Society for e-Business Studies
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• v.14 no.4
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• pp.315-332
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• 2009

In logistic environments, a process, in that it manages the flow of materials among partners, involves more than one organization. In this regard, a logistic process, as a combined process consisting of multiple sub processes, needs to be managed with controling interaction among partners. In achieving systematic management of a logistic process, traditional Business Process Management (BPM) cannot be used for the entire flow, since it lacks the ability to manage interactions among partners. Particularly in logistic environments where RFID technologies are used, how to deal with the connection between RFID event and logistic flow has not been properly addressed. To overcome this limitation, this paper proposes a new method of managing multi-organizational logistic processes based on RFID events. We define inter-workflow pattern, and suggest ECA(Event-Condition-Action) rules for auto triggering of logistic processes. To adjust the rules to RFID events, we invent RFID-based ECA rules using complex event. A prototype system has been developed for the purpose of demonstrating the effectiveness of our approach.

• Journal of Korean Society for Quality Management
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• v.47 no.4
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• pp.823-835
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• 2019

Purpose: This study deals with a production planning and scheduling problem to minimize the total weighted tardiness on hybrid flow shop with sets of non-identical parallel machines on stages, where parallel machines in the set are dedicated to perform specific subsets of jobs and sequence-dependent setup times are also considered. Methods: A two-stage approach, that applies MILP model in the 1st stage and dispatching rules in the 2nd stage, is proposed in this paper. The MILP model is used to assign jobs to a specific machine in order to equalize the workload of the machines at each stage, while new dispatching rules are proposed and applied to sequence jobs in the queue at each stage. Results: The proposed two-stage approach was implemented by using a commercial MILP solver and a commercial simulation software and a case study was developed based on the spark plug manufacturing process, which is an automotive component, and verified using the company's actual production history. The computational experiment shows that it can reduce the tardiness when used in conjunction with the dispatching rule. Conclusion: This proposed two-stage approach can be used for HFS systems with dedicated machines, which can be evaluated in terms of tardiness and makespan. The method is expected to be used for the aggregated production planning or shop floor-level production scheduling.

• Journal of Internet Computing and Services
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• v.22 no.6
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• pp.1-8
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• 2021

With the rapid growth of intelligent devices and communication technologies, 5G network environment has become more heterogeneous and complex in terms of service management and orchestration. 5G architecture requires supportive technologies to handle the existing challenges for improving the Quality of Service (QoS) and the Quality of Experience (QoE) performances. Among many challenges, traffic steering is one of the key elements which requires critically developing an optimal solution for smart guidance, control, and reliable system. Mobile edge computing (MEC), software-defined networking (SDN), network functions virtualization (NFV), and deep learning (DL) play essential roles to complementary develop a flexible computation and extensible flow rules management in this potential aspect. In this proposed system, an accurate flow recommendation, a centralized control, and a reliable distributed connectivity based on the inspection of packet condition are provided. With the system deployment, the packet is classified separately and recommended to request from the optimal destination with matched preferences and conditions. To evaluate the proposed scheme outperformance, a network simulator software was used to conduct and capture the end-to-end QoS performance metrics. SDN flow rules installation was experimented to illustrate the post control function corresponding to DL-based output. The intelligent steering for network communication traffic is cooperatively configured in SDN controller and NFV-orchestrator to lead a variety of beneficial factors for improving massive real-time Internet of Things (IoT) performance.