• The Journal of Bigdata
• /
• v.7 no.1
• /
• pp.75-87
• /
• 2022

This study investigates a dynamic flexible flow shop scheduling problem under uncertain rework operations for an automobile pipe production line. We propose a weighted dispatching rule (WDR) based on the multiple dispatching rules to minimize the weighted sum of average flowtime and tardiness. The set of weights in WDR should be carefully determined because it significantly affects the performance measures. We build a discrete-event simulation model and propose a genetic algorithm to optimize the set of weights considering complex and variant operations. The simulation experiments demonstrate that WDR outperforms the baseline dispatching rules in average flowtime and tardiness.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1993.06a
• /
• pp.975-976
• /
• 1993

This talk presents the overview of the author's research and development activities on fuzzy inference hardware. We involved it with two distinct approaches. The first approach is to use application specific integrated circuits (ASIC) technology. The fuzzy inference method is directly implemented in silicon. The second approach, which is in its preliminary stage, is to use more conventional microprocessor architecture. Here, we use a quantitative technique used by designer of reduced instruction set computer (RISC) to modify an architecture of a microprocessor. In the ASIC approach, we implemented the most widely used fuzzy inference mechanism directly on silicon. The mechanism is beaded on a max-min compositional rule of inference, and Mandami's method of fuzzy implication. The two VLSI fuzzy inference chips are designed, fabricated, and fully tested. Both used a full-custom CMOS technology. The second and more claborate chip was designed at the University of North Carolina(U C) in cooperation with MCNC. Both VLSI chips had muliple datapaths for rule digital fuzzy inference chips had multiple datapaths for rule evaluation, and they executed multiple fuzzy if-then rules in parallel. The AT & T chip is the first digital fuzzy inference chip in the world. It ran with a 20 MHz clock cycle and achieved an approximately 80.000 Fuzzy Logical inferences Per Second (FLIPS). It stored and executed 16 fuzzy if-then rules. Since it was designed as a proof of concept prototype chip, it had minimal amount of peripheral logic for system integration. UNC/MCNC chip consists of 688,131 transistors of which 476,160 are used for RAM memory. It ran with a 10 MHz clock cycle. The chip has a 3-staged pipeline and initiates a computation of new inference every 64 cycle. This chip achieved an approximately 160,000 FLIPS. The new architecture have the following important improvements from the AT & T chip: Programmable rule set memory (RAM). On-chip fuzzification operation by a table lookup method. On-chip defuzzification operation by a centroid method. Reconfigurable architecture for processing two rule formats. RAM/datapath redundancy for higher yield It can store and execute 51 if-then rule of the following format: IF A and B and C and D Then Do E, and Then Do F. With this format, the chip takes four inputs and produces two outputs. By software reconfiguration, it can store and execute 102 if-then rules of the following simpler format using the same datapath: IF A and B Then Do E. With this format the chip takes two inputs and produces one outputs. We have built two VME-bus board systems based on this chip for Oak Ridge National Laboratory (ORNL). The board is now installed in a robot at ORNL. Researchers uses this board for experiment in autonomous robot navigation. The Fuzzy Logic system board places the Fuzzy chip into a VMEbus environment. High level C language functions hide the operational details of the board from the applications programme . The programmer treats rule memories and fuzzification function memories as local structures passed as parameters to the C functions. ASIC fuzzy inference hardware is extremely fast, but they are limited in generality. Many aspects of the design are limited or fixed. We have proposed to designing a are limited or fixed. We have proposed to designing a fuzzy information processor as an application specific processor using a quantitative approach. The quantitative approach was developed by RISC designers. In effect, we are interested in evaluating the effectiveness of a specialized RISC processor for fuzzy information processing. As the first step, we measured the possible speed-up of a fuzzy inference program based on if-then rules by an introduction of specialized instructions, i.e., min and max instructions. The minimum and maximum operations are heavily used in fuzzy logic applications as fuzzy intersection and union. We performed measurements using a MIPS R3000 as a base micropro essor. The initial result is encouraging. We can achieve as high as a 2.5 increase in inference speed if the R3000 had min and max instructions. Also, they are useful for speeding up other fuzzy operations such as bounded product and bounded sum. The embedded processor's main task is to control some device or process. It usually runs a single or a embedded processer to create an embedded processor for fuzzy control is very effective. Table I shows the measured speed of the inference by a MIPS R3000 microprocessor, a fictitious MIPS R3000 microprocessor with min and max instructions, and a UNC/MCNC ASIC fuzzy inference chip. The software that used on microprocessors is a simulator of the ASIC chip. The first row is the computation time in seconds of 6000 inferences using 51 rules where each fuzzy set is represented by an array of 64 elements. The second row is the time required to perform a single inference. The last row is the fuzzy logical inferences per second (FLIPS) measured for ach device. There is a large gap in run time between the ASIC and software approaches even if we resort to a specialized fuzzy microprocessor. As for design time and cost, these two approaches represent two extremes. An ASIC approach is extremely expensive. It is, therefore, an important research topic to design a specialized computing architecture for fuzzy applications that falls between these two extremes both in run time and design time/cost. TABLEI INFERENCE TIME BY 51 RULES {{{{Time }}{{MIPS R3000 }}{{ASIC }}{{Regular }}{{With min/mix }}{{6000 inference 1 inference FLIPS }}{{125s 20.8ms 48 }}{{49s 8.2ms 122 }}{{0.0038s 6.4㎲ 156,250 }} }}

• Journal of the Institute of Convergence Signal Processing
• /
• v.6 no.2
• /
• pp.89-94
• /
• 2005

In this paper, we propose a fuzzy PID controller of new method. There are two problems in absolute digital PID controller. First, much calculation time need for obtain the sum of data at each period. Second, this is problem need much memory because to storage every data at the before period. We use the speed type PID digital controller to improvement such problems. In the propose controller doesn't use without adjustment the crisp output error and we doesn't use nile tables in the fuzzy inference process at the forward stage fuzzifier. We inference output member ship function by using the relation and range of two variable of PID gain parameters. We can obtained desired results through the simulation and a experiment of the hydraulic servo motor control system.

• The Bulletin of The Korean Astronomical Society
• /
• v.40 no.1
• /
• pp.44.1-44.1
• /
• 2015

We present joint constraints on the number of effective neutrino species $N_{eff}$ and the sum of neutrino masses ${\Sigma}m_{\nu}$, based on a technique which exploits the full information contained in the one-dimensional Lyman-${\alpha}$ forest flux power spectrum, complemented by additional cosmological probes. In particular, we obtain $N_{eff}=2.91{\pm}0.22$ (95% CL) and ${\Sigma}m_{\nu}$ < 0.15 eV (95% CL) when we combine BOSS Lyman-${\alpha}$ forest data with CMB (Planck+ACT+SPT+WMAP polarization) measurements, and $N_{eff}=2.88{\pm}0.20$ (95% CL) and ${Sigma}m_{\nu}$ < 0.14 eV (95% CL) when we further add baryon acoustic oscillations. Our results tend to favor the normal hierarchy scenario for the masses of the active neutrino species, provide strong evidence for the Cosmic Neutrino Background from $N_{eff}{\approx}3$($N_{eff}=0$ is rejected at more than $14{\sigma}$), and rule out the possibility of a sterile neutrino thermalized with active neutrinos (i.e., $N_{eff}=4$) - or more generally any decoupled relativistic relic with $${\Delta}N_{eff}{\sim_=}1$$ - at a significance of over $5{\sigma}$, the strongest bound to date, implying that there is no need for exotic neutrino physics in the concordance ${\Lambda}CDM$ model.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2008.04a
• /
• pp.567-572
• /
• 2008

This paper's purpose is to improve determining of the critical response of curved bridge to multi-component seismic motion. There are several methods to combine responses by multi-component excitation response, 30%, 40% rules and square-root-of-sum (SRSS). These combination rules determine same value of critical response in straight bridges. However, each method has critical response value of different magnitude in curved bridges. Thus a study about critical response of curved bridges is required. This paper presents comparison critical responses value as each combination rule, 30%, 40% rules and SRSS on curved bridges with the different radiuses of curvature. This study was carried out by response spectrum analysis of OO IC steel box girder bridge using SAP2000. It is concluded as follows: 1) In curved bridges, 30% and 40% rules tend to underestimate the critical response relatively to SRSS. 2) When bridges have smaller radiuses than 100m, difference between SRSS and 30% or 40% rules let run errors up as radiuses of curvature decreased.

• Journal of Information Technology Services
• /
• v.14 no.2
• /
• pp.69-86
• /
• 2015

The current contract awarding process regulated by laws and ordinances is analyzed and more reasonable processes are suggested. To this end, the principle of economic analysis is described with emphasis on the cost-effectiveness analysis, and the laws and ordinances regulating the process are thoroughly examined. The current contract awarding rule is based on the weighted sum of effectiveness score and cost score. This may not conform to the framework of economic analysis where effectiveness is supposed to be measured as an output and cost measured as an input. An improvement is attempted to the defense acquisition system and it is recognized that the economic analysis and policy consideration should be performed separately. Concept of statistical testing is introduced to see if the results of the cost effectiveness analyses show the significant difference between the alternatives. It is suggested that the contract awarding process can be improved by performing significance test followed by the aggregation of the two analyses. A minor improvement is also suggested on the application of current rules.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.57 no.3
• /
• pp.518-526
• /
• 2008

The fuzzy self-tuning PID controller is a PID controller with a fuzzy logic mechanism for tuning its gains on-line. In this structure, the proportional, integral and derivative gains are tuned on-line with respect to the change of the output of system under control. This paper deals with two types of fuzzy self-tuning PID controllers, rule-based fuzzy PID controller and learning fuzzy PID controller. As a medical application of fuzzy PID controller, the proposed controllers were implemented and evaluated in a laparoscopic surgery robot system. The proposed fuzzy PID structures maintain similar performance as conventional PID controller, and enhance the position tracking performance over wide range of varying input. For precise approximation, the fuzzy PID controller was realized using the linear reasoning method, a type of product-sum-gravity method. The proposed controllers were compared with conventional PID controller without fuzzy gain tuning and was proved to have better performance in the experiment.

• Journal of Korean Society for Quality Management
• /
• v.17 no.2
• /
• pp.17-26
• /
• 1989

This paper is concerned with forecasting the existing number of errors in the computer software and optimizing the stopping time of the software test based upon the forecasted number of errors. The most commonly used models have assessed software reliability under the assumption that the software failure late is proportional to the current fault content of the software but invariant to time since software faults are independents of others and equally likely to cause a failure during testing. In practice, it has been observed that in many situations, the failure rate decrease. Hence, this paper proposes a mathematical model to describe testing situations where the failure rate of software limearly decreases proportional to testing time. The least square method is used to estimate parameters of the mathematical model. A cost model to optimize the software testing time is also proposed. In this cost mode two cost factors are considered. The first cost is to test execution cost directly proportional to test time and the second cost is the failure cost incurred after delivery of the software to user. The failure cost is assumed to be proportional to the number of errors remained in the software at the test stopping time. The optimal stopping time is determined to minimize the total cost, which is the sum of test execution cast and the failure cost. A numerical example is solved to illustrate the proposed procedure.

• Journal of Korean Institute of Industrial Engineers
• /
• v.36 no.2
• /
• pp.125-137
• /
• 2010

This study focuses on the problem of scheduling wafer lots of several product families in the deposition workstation in a semiconductor wafer fabrication facility. There are multiple identical parallel machines in the deposition workstation, and two types of setups, record-dependent setup and family setup, may be required at the deposition machines. A record-dependent setup is needed to find optimal operational conditions for a wafer lot on a machine, and a family setup is needed between processings of different families. We suggest two-phase heuristic algorithms in which a priority-rule-based scheduling algorithm is used to generate an initial schedule in the first phase and the schedule is improved in the second phase. Results of computational tests on randomly generated test problems show that the suggested algorithms outperform a scheduling method used in a real manufacturing system in terms of the sum of weighted flowtimes of the wafer lots.

• Korean Management Science Review
• /
• v.29 no.3
• /
• pp.45-65
• /
• 2012

Test and evaluation of weapon system is an important task to evaluate the performance of overseas weapon system purchasing project. Especially, quantitative evaluation of performances is hardly completed in defense projects where multiple criteria are conflicted each other. In order to solve this problem, we apply Axiomatic Design (AD) and Inner Dependence AHP method. First, finite functional requirements (FRs) are categorized in hierarchy structure by selecting proper design parameters (DPs) to implement their corresponding FRs. If there are no ways to select DPs when design is coupled between FRs and DPs, then inner dependence is allowed to overcome the strict rule of independence in AHP. Second, the weights of DPs are calculated by applying both Inner Dependence AHP method for coupled design and normal AHP method for uncoupled or decoupled design. Finally, information axiom of AD is applied to the proposed weapon systems by calculating information contents for all parameters. Weapon system with minimum sum of information contents is considered as the best solution. The proposed method in this study should be used in multiple criteria decision making problems involving various conflicting criteria.