310,250 research outputs found

    DECISION SUPPORT MODEL IN FAILURE-BASED COMPUTERIZED MAINTENANCE MANAGEMENT SYSTEM FOR SMALL AND MEDIUM INDUSTRIES

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    Maintenance decision support system is crucial to ensure maintainability and reliability of equipments in production lines. This thesis investigates a few decision support models to aid maintenance management activities in small and medium industries. In order to improve the reliability of resources in production lines, this study introduces a conceptual framework to be used in failure-based maintenance. Maintenance strategies are identified using the Decision-Making Grid model, based on two important factors, including the machines’ downtimes and their frequency of failures. The machines are categorized into three downtime criterions and frequency of failures, which are high, medium and low. This research derived a formula based on maintenance cost, to re-position the machines prior to Decision-Making Grid analysis. Subsequently, the formula on clustering analysis in the Decision-Making Grid model is improved to solve multiple-criteria problem. This research work also introduced a formula to estimate contractor’s response and repair time. The estimates are used as input parameters in the Analytical Hierarchy Process model. The decisions were synthesized using models based on the contractors’ technical skills such as experience in maintenance, skill to diagnose machines and ability to take prompt action during troubleshooting activities. Another important criteria considered in the Analytical Hierarchy Process is the business principles of the contractors, which includes the maintenance quality, tools, equipments and enthusiasm in problem-solving. The raw data collected through observation, interviews and surveys in the case studies to understand some risk factors in small and medium food processing industries. The risk factors are analysed with the Ishikawa Fishbone diagram to reveal delay time in machinery maintenance. The experimental studies are conducted using maintenance records in food processing industries. The Decision Making Grid model can detect the top ten worst production machines on the production lines. The Analytical Hierarchy Process model is used to rank the contractors and their best maintenance practice. This research recommends displaying the results on the production’s indicator boards and implements the strategies on the production shop floor. The proposed models can be used by decision makers to identify maintenance strategies and enhance competitiveness among contractors in failure-based maintenance. The models can be programmed as decision support sub-procedures in computerized maintenance management systems

    PERFORMANCE AND DECISION SUPPORT SYSTEM FOR CANE SUGAR PRODUCTION PROCESS CONTROL AT PT. RAJAWALI II, JATITUJUH FACTORY UNIT, MAJALENGKA

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     Main problem in sugar production is inefficiency of process due to unreliable old machines and equipments. The second problem is low performance of sugar processing, and the third is due to the inefficiency of production management inovation of the company. The objectives of this research were to identify sugar process production factors, process monitoring and capability measurement in each step of process, identification of critical points on sugar processing, production efficiency in PG Jatitujuh, to construct the decision support system for formulating cane sugar production process control. We named the system as SWEETCON.PROSION which is able to provide alternatives for monitoring the production process, and for maintaining scheduling. This system consists of a model base management system, a database management system, and a dialogue management system that are integrated within a central processing system. It is suported with four models, namely critical component model, process performance model, production efficiency model, and process control model. Process performance analysis shows that all of the process stations were under controlled. Critical component analysis shows that extraction machines was the most critical component. Relative efficiency analysis of each indicator shows that all indicators were efficient. However, absolute efficiency analysis showed that the final product environment and input were inefficient both technically and economically. It is shown that technical efficiency of final product environmental was 31.90%, technical efficiency of input was 73%, economical efficiency of final product environmental was 43% and economical efficiency of input was 125.5%. The overall decision hierarchy process control analysis shows that the milling station was the most critical process, and it is to be controlled accordingly. Keywords :equipment critically rating, analytical hierarchy process, data envelopment analysis.

    Development of titanium dioxide nanoparticles/nanosolution for photocatalytic activity

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    Biological and chemical contaminants by man-made activities have been serious global issue. Exposure of these contaminants beyond the limits may result in serious environmental and health problem. Therefore, it is important to develop an effective solution that can be easily utilized by mankind. One of the effective ways to overcome this problem is by using titanium dioxide (TiO2). TiO2 is a well-known photocatalyst that widely used for environmental clean-up due to its ability to decompose organic pollutant and kill bacteria. Although it is proven TiO2 has an advantage to solve this concern, its usefulness unfortunately is limited only under UV light irradiation. Therefore, the aim of this work was to investigate the potential of TiO2 that can be activated under visible light by the incorporation of metal ions (Fe, Ag, Zr and Ag-Zr). In this study, sol-gel method was employed for the synthesis of metal ions incorporated TiO2. XRD analysis revealed that all samples content biphasic anatase-brookite TiO2 of size 3 nm to 5 nm. It was found that the incorporation of these metal ions did not change the morphology of TiO2 but the crystallinity and optical properties were affected. The crystallinity of anatase in the biphasic TiO2 was found to be decreased and favored brookite formation. PL analysis showed metal ions incorporation suppressed the recombination of electron-hole pairs while the band gap energy of TiO2 (3.2 eV) was decreased by the incorporation of Fe (2.46 eV) and Ag (2.86 eV). Among this incorporation, Ag-Zr incorporated TiO2 showed highest performance for methyl orange degradation (93%) under fluorescent xxv light irradiation for 10 h. This follows by Zr-TiO2 (82%), Fe-TiO2 (75%) and Ag�TiO2 (43%). Meanwhile, the highest antibacterial performance was exhibited by Ag�TiO2. TEM images showed that E.coli bacterium was killed within 12 h after treated with Ag-TiO2. The results obtained from the fieldwork study established that Ag-Zr incorporation have excellent performances for VOC removal and antibacterial test. The VOC content after treated with Ag-Zr-TiO2 fulfilled the Industry Code of Practice on Indoor Air Quality 2010 which is lower than 3 ppm. In addition, the percentage of microbes also found to be decrease around 45 % within 5 days of monitoring

    Feedbacks from the metabolic network to the genetic network reveal regulatory modules in E. coli and B. subtilis

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    The genetic regulatory network (GRN) plays a key role in controlling the response of the cell to changes in the environment. Although the structure of GRNs has been the subject of many studies, their large scale structure in the light of feedbacks from the metabolic network (MN) has received relatively little attention. Here we study the causal structure of the GRNs, namely the chain of influence of one component on the other, taking into account feedback from the MN. First we consider the GRNs of E. coli and B. subtilis without feedback from MN and illustrate their causal structure. Next we augment the GRNs with feedback from their respective MNs by including (a) links from genes coding for enzymes to metabolites produced or consumed in reactions catalyzed by those enzymes and (b) links from metabolites to genes coding for transcription factors whose transcriptional activity the metabolites alter by binding to them. We find that the inclusion of feedback from MN into GRN significantly affects its causal structure, in particular the number of levels and relative positions of nodes in the hierarchy, and the number and size of the strongly connected components (SCCs). We then study the functional significance of the SCCs. For this we identify condition specific feedbacks from the MN into the GRN by retaining only those enzymes that are essential for growth in specific environmental conditions simulated via the technique of flux balance analysis (FBA). We find that the SCCs of the GRN augmented by these feedbacks can be ascribed specific functional roles in the organism. Our algorithmic approach thus reveals relatively autonomous subsystems with specific functionality, or regulatory modules in the organism. This automated approach could be useful in identifying biologically relevant modules in other organisms for which network data is available, but whose biology is less well studied.Comment: 15 figure

    Black Holes at Future Colliders and Beyond: a Topical Review

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    One of the most dramatic consequences of low-scale (~1 TeV) quantum gravity in models with large or warped extra dimension(s) is copious production of mini black holes at future colliders and in ultra-high-energy cosmic ray collisions. Hawking radiation of these black holes is expected to be constrained mainly to our three-dimensional world and results in rich phenomenology. In this topical review we discuss the current status of astrophysical observations of black holes and selected aspects of mini black hole phenomenology, such as production at colliders and in cosmic rays, black hole decay properties, Hawking radiation as a sensitive probe of the dimensionality of extra space, as well as an exciting possibility of finding new physics in the decays of black holes.Comment: 31 pages, 10 figures To appear in the Journal of Physics

    Strategy management through quantitative modelling of performance measurement systems

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    This paper is based on previous works on performance measurement and on quantification of relationships between factors which affect performance. It demonstrates how tools and techniques developed can be used to evaluate the performance of alternative strategic choices through a quantitative approach to modelling of performance measurement systems. The paper provides a brief background to the research problem and preceding works. The tools and techniques used are briefly introduced. Use of these tools and techniques to evaluate the performance of alternative manufacturing strategies is demonstrated. Finally, the capability of the approach to deal with dynamic environments is demonstrated using sensitivity analysis
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