• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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• pp.100-107
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• 2015

Recently as the manufacturers want competitiveness in dynamically changing environment, they are trying a lot of efforts to be efficient with their production systems, which may be achieved by diminishing unplanned operation stops. The operation stops and maintenance cost are known to be significantly decreased by adopting proper maintenance strategy. Therefore, the manufacturers were more getting interested in scheduling of exact maintenance scheduling to keep smooth operation and prevent unexpected stops. In this paper, we proposedan integrated maintenance approach in injection molding manufacturing line. It consists of predictive and preventive maintenance approach. The predictive maintenance uses the statistical process control technique with the real-time data and the preventive maintenance is based on the checking period of machine components or equipment. For the predictive maintenance approach, firstly, we identified components or equipment that are required maintenance, and then machine parameters that are related with the identified components or equipment. Second, we performed regression analysis to select the machine parameters that affect the quality of the manufactured products and are significant to the quality of the products. By this analysis, we can exclude the insignificant parameters from monitoring parameters and focus on the significant parameters. Third, we developed the statistical prediction models for the selected machine parameters. Current models include regression, exponential smoothing and so on. We used these models to decide abnormal patternand to schedule maintenance. Finally, for other components or equipment which is not covered by predictive approach, we adoptedpreventive maintenance approach. To show feasibility we developed an integrated maintenance support system in LabView Watchdog Agent and SQL Server environment and validated our proposed methodology with experimental data.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.04a
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• pp.263-269
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• 2012

Condition-based maintenance (CBM) has been used as a useful concept for optimizing maintenance plan and decreasing maintenance cost in several kinds of plant sites. This study introduced an example that developed an integrated management system for maintenance parameters and hydraulic turbine of hydro-power plant in order to improve its maintenance system as applying CBM techinique. The integrated management system consists of three parts. One is a hardware part including PDA inspection system and several kind of precision measuring instruments. Another is a vibration monitoring system on hydraulic turbine. The other is a software part that takes charge of making hierarchy tree of maintenance parameters and their inspection route, managing accumulated database, assessing health condition of components, and supporting interface with other enterprise management system. The system has been installed at Chuncheon Hydro-power plant for test and demonstration. It is expected that the system can contribute database construction for diagnostics and prognostics on facility health condition and systematic accumulation of know-how on operation and maintenance of plant.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.6
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• pp.574-581
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• 2012

Condition-based maintenance(CBM) has been used as a useful concept for optimizing maintenance plan and decreasing maintenance cost in several kinds of plant sites. This study introduced an example that developed an integrated management system for maintenance parameters and hydraulic turbine of hydro-power plant in order to improve its maintenance strategy as applying CBM techinique. The integrated management system consists of three parts. One is a hardware part including PDA inspection system and several kind of precision measuring instruments. Another is a vibration monitoring system on hydraulic turbine. The other is a software part that takes charge of making hierarchy tree of maintenance parameters and their inspection route, managing accumulated database, assessing health condition of components, and supporting interface with other enterprise management system. The system has been installed at Chuncheon hydro-power plant for test and demonstration. It is expected that the system can contribute database construction for diagnostics and prognostics on facility health condition and systematic accumulation of know-how on operation and maintenance of plant.

• International Journal of Reliability and Applications
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• v.12 no.1
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• pp.41-48
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• 2011

This paper considers the maintenance model suggested by Jung and Park (2010) to adopt the Bayesian approach and obtain an optimal replacement policy following the expiration of NFRRW. As the criteria to determine the optimal maintenance period, we use the expected cost during the life cycle of the system. When the failure times are assumed to follow a Weibull distribution with unknown parameters, we propose an optimal maintenance policy based on the Bayesian approach. Also, we describe the revision of uncertainty about parameters in the light of data observed. Some numerical examples are presented for illustrative purpose.

• Journal of Periodontal and Implant Science
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• v.36 no.1
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• pp.69-84
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• 2006

Reports on the comparison of clinical effect between non-surgical and surgical therapy, and the change of the clinical parameters during maintenance phase have been rarely presented in Korea. This study was to observe the clinical changes during maintenance phase of 6 months in patients with chronic periodontitis treated by non-surgical or surgical therapy in Department of Periodontics, Chonnam National University Hospital. Among the systemically healthy and non-smoking patients with moderate to severe chronic periodontitis, twenty eight patients (mean age: 47.5 years) treated by non-surgical therapy (scaling and root planning) and nineteen patients (mean age: 47.3 years) treated by surgical therapy (flap surgery) were included in this study. The periodontal supportive therapy including recall check and oral hygiene reinforcement was started as maintenance phase since 1 month of healing after treatment. Probing depth, gingival recession. clinical attachment level and tooth mobility were recorded at initial, baseline and 1, 2, 3 and 6 month of maintenance phase. The clinical parameters were compared between the non-surgical and surgical therapies using Student t-test and repeated measure ANOVA by initial probing depth and surfaces. Surgical therapy resulted in greater change in clinical parameters than non-surgical therapy. During the maintenance phase of 6 months, the clinical effects after treatment had been changed in different pattern according to initial probing depth and tooth surface. During maintenance phase, probing depth increased more and gingival recession increased less after surgical therapy, compared to non-surgical therapy. The sites of initial probing depth less than 3 mm lost more clinical attachment level, and the sites of initial probing depth more than 7 mm gained clinical attachment level during maintenance phase after non-surgical therapy, compared to surgical therapy. Non-surgical therapy resulted in greater reduction of tooth mobility than surgical therapy during maintenance phase. These results indicate that the clinical effects of non-surgical or surgical therapy may be different and may change during the maintenance phase.

• Journal of the Korean Data and Information Science Society
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• v.18 no.3
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• pp.689-696
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• 2007

This paper considers a Bayesian approach to determine an optimal PM policy with random maintenance quality. Thus, we assume that the quality of a PM action is a random variable following a probability distribution. When the failure time is Weibull distribution with uncertain parameters, a Bayesian approach is established to formally express and update the uncertain parameters for determining an optimal PM policy. Finally, the numerical examples are presented for illustrative purpose.

• Journal of the Korea institute for structural maintenance and inspection
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• v.3 no.2
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• pp.147-154
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• 1999

A new approach to conducting the vibration parameters identification algorithm is proposed. The approach employs the concept of modal amplitude ratio implemented in a mode shape estimation. The accuracy of the improved Ibrahim Time Domain identification algorithm in extracting structural modal parameters from free response functions has been studied using computer simulated data for 9 stations on the two-span continuous beam. Simulated responses from the lumped and distributed parameter system demonstrate that this algorithm produces excellent results, even in the 300% noise response.

• Journal of Korean Association for Spatial Structures
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• v.20 no.1
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• pp.95-102
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• 2020

The structural design of arch roofs or bridges requires the analysis of their unstable behaviors depending on certain parameters defined in the arch shape. Their maintenance should estimate the parameters from observed data. However, since the critical parameters exist in the equilibrium paths of the arch, and a small change in such the parameters causes a significant change in their behaviors. Thus, estimation to find the critical ones should be carried out using a global search algorithm. In this paper we study the parameter estimation for a shallow arch by a quantum-inspired evolution algorithm. A cost functional to estimate the system parameters included in the arch consists of the difference between the observed signal and the estimated signal of the arch system. The design variables are shape, external load and damping constant in the arch system. We provide theoretical and numerical examples for estimation of the parameters from both contaminated data and pure data.

• International Journal of Computer Science & Network Security
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• v.24 no.1
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• pp.215-225
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• 2024

Predictive maintenance has been considered fundamental in the industrial applications in the last few years. It contributes to improve reliability, availability, and maintainability of the systems and to avoid breakdowns. These breakdowns could potentially lead to system shutdowns and to decrease the production efficiency of the manufacturing plants. The present article aims to study how predictive maintenance could be planed into the production scheduling, through a systematic review of literature. . The review includes the research articles published in international journals indexed in the Scopus database. 165 research articles were included in the search using #predictive maintenance# AND #production scheduling#. Press articles, conference and non-English papers are not considered in this study. After careful evaluation of each study for its purpose and scope, 50 research articles are selected for this review by following the 2020 Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA) statement. A benchmarking of predictive maintenance methods was used to understand the parameters that contributed to improve the production scheduling. The results of the comparative analysis highlight that artificial intelligence is a promising tool to anticipate breakdowns. An additional impression of this study is that each equipment has its own parameters that have to be collected, monitored and analyzed.

• Tuberculosis and Respiratory Diseases
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• v.76 no.1
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• pp.1-7
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• 2014

Maintenance therapy has emerged as a novel therapeutic paradigm for advanced non-small-cell lung cancer (NSCLC). Maintenance therapy that aims to sustain a clinically favorable state after first-line chemotherapy has two strategies. Switch maintenance therapy entails switching to a new and non-cross-resistant agent in an alternating or sequential manner, on completion of first-line chemotherapy. Continuous maintenance therapy keeps ongoing administration of a component of the current regimen after four to six cycles of chemotherapy, if there is a stable disease, or better response. Both maintenance therapies can be continued, until disease progression. The potential evidence regarding maintenance therapy includes providing the opportunity to receive additional treatment, through sustaining tumor shrinkage, and delayed emergence of tumor-related symptom. Thus far, debates over the parameters used to predict the effectiveness of maintenance therapy, financial burden, and uncertainty of improving the quality of life exist. Despite many debates, maintenance therapy, which is currently recommended, has been disclosed to be beneficial.