Modelling of palm oil production using fuzzy expert system

Amelia, Lily; Wahab, Dzuraidah Abd; Hassan, Azmi

doi:10.1016/j.eswa.2008.12.012

Cited by 18 publications

(4 citation statements)

References 12 publications

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“…Triangular fuzzy numbers were chosen owning to their ease of application and computation. Various scales have been introduced to convert qualitative assessments to triangular fuzzy numbers 47 – 49 . The scale presented by Chan et al 48 was applied in the study as shown in Table 4 .…”

Section: Methodsmentioning

confidence: 99%

Combining semi-quantitative risk assessment, composite indicator and fuzzy logic for evaluation of hazardous chemical accidents

Thu

Tram

Tien

2020

Sci Rep

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In this study, a combination of semi-quantitative risk assessment, composite indicator and fuzzy logic has been developed to identify industrial establishments and processes that represent potential environmental accidents associated with hazardous chemicals. The proposed method takes into consideration the root causes of risk probability of hazardous chemical accidents (HCAs), such as unsafe onsite storing and usage, inadequate operation training, poor safety management and analysis, equipment failure, and factors affected by the potential consequences of the accidents, including human health, water resources, and building and construction. These issues have been aggregated in a system of criteria and sub-criteria, demonstrated by a list of non-overlapping and exhaustive categorical terms. Semi-quantitative risk assessment is then applied to develop a framework for screening industrial establishments that exhibit potential HCAs. Fuzzy set theory with triangular fuzzy number deals with the uncertainty associated with the data input and reduces the influence of subjectivity and vagueness to the final results. The proposed method was tested among 77 industrial establishments located within the industrial zones of Ho Chi Minh City, Vietnam. Eighteen establishments were categorized as high HCA risk, 36 establishments were categorized as medium HCA risk, and 23 ones were of low HCA risk. The results are compatible with the practical chemical safety situation of the establishments and are consistent with expert evaluation.

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Section: Methodsmentioning

confidence: 99%

Combining semi-quantitative risk assessment, composite indicator and fuzzy logic for evaluation of hazardous chemical accidents

Thu

Tram

Tien

2020

Sci Rep

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“…The most commonly used fuzzy inference technique, called the Mamdani Method [19], has been employed in this study because of its simplicity and ability in representing non-linear systems [20]. It has also been successfully applied as a representative method in many studies [21][22][23]. …”

Section: Fuzzy Inferencementioning

confidence: 99%

Fuzzy inference method for material loss and cost estimation under uncertainty: A case study of wooden product manufacturing

Chansaad

Chaiprapat

Yenradee

2014

Journal of Intelligent &Amp; Fuzzy Systems

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Wood is a natural derivative, it possesses randomly distributed inherent defects all over its mass. This complicates the cost estimation process; data collected showed that even planks with similar defect pattern would have different percentage of material loss. Such uncertain loss was caused by changes in cutting parameters. In this study, a Fuzzy Inference (FI) method was employed to predict wood loss in a rubber wooden toy manufacturing cutting process. Notable variables are: length of cut, and area of cut. Prediction accuracy from the FI method was compared with that of other alternative methods. Common practice assumes a constant defective proportion, resulting in inaccurate cost estimation. A regression equation allows the loss to be varied by the cutting parameters; but only one parameter was found to be significant. Experimental results show that the FI method greatly outperformed regression and conventional methods. These findings emphasize the influence of cutting parameters on product cost. Accurate cost estimation enables better planning for efficient pricing strategies and enhances business competitiveness.

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“…Piltan et al [ 25 ] have applied an FES for decision making in identifying and prioritizing potential industries relating to combined heat and power systems. Amelia et al [ 26 ] have integrated expert knowledge with processing conditions in FESs for the modelling of palm oil production in different processing stations.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy expert system for troubleshooting of the deodorizer unit in a palm oil refining plant

et al. 2022

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In this paper, a troubleshooting technique is developed to provide a sequence of necessary actions during deodorizer unit failure in a palm oil refinery. This paper introduces a fuzzy expert system that incorporates the knowledge of experienced plant workers in dealing with the complex problems of the palm oil deodorizer. The presented methodology uses both qualitative and quantitative data. Qualitative data are collected from several interview sessions with the technical staff in a palm oil refinery. Quantitative data are gathered from various sources, such as control and monitoring systems. The qualitative data are analyzed to discover the possible pattern of faults in the deodorizer failure. This tool can diagnose possible faults and provide a sequence of necessary actions when deodorizer failure occurs. The obtained results show the developed deodorizer troubleshooting tool is useful to guide plant workers/ operators in diagnosing the possible faults and abnormalities during the troubleshooting process, as well as to provide field training for inexperienced staff.

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Modelling of palm oil production using fuzzy expert system

Cited by 18 publications

References 12 publications

Combining semi-quantitative risk assessment, composite indicator and fuzzy logic for evaluation of hazardous chemical accidents

Combining semi-quantitative risk assessment, composite indicator and fuzzy logic for evaluation of hazardous chemical accidents

Fuzzy inference method for material loss and cost estimation under uncertainty: A case study of wooden product manufacturing

Fuzzy expert system for troubleshooting of the deodorizer unit in a palm oil refining plant

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