Optimizing tablets' quality with multiple responses using fuzzy goal programming

Abbas Al-Refaie, Ali Diabat, Ming Hsien Li

    Research output: Contribution to journalArticle

    Abstract

    Process analytical technology is considered to be a system for designing, analyzing, and controlling pharmaceutical manufacturing to ensure final product quality. This research, therefore, utilized the process analytical technology framework to improve the performance of tableting process. Two main responses are of main interest including hardness and weight. At initial factor levels, the x̄-s charts are established and found in control for both responses. However, the process capability index, Ĉpm, values are calculated to be 0.42 and 0.51 for hardness and weight, respectively. Moreover, the multiple process capability index, MCpm, is 0.46. These values indicate that the tableting process is incapable of producing quality tablets. The L27 is used for conducting designed experiments. The weighted additive model in fuzzy goal programming is then used to determine optimal factor settings. Confirmation experiments are then conducted at optimal factor settings. It is found that the Ĉpm values are calculated to be 2.13 and 1.85 for hardness and weight, respectively. The MCpm value significantly improved to 1.99, which means that the process is highly capable. Consequently, the T2 and the sample generalized variance control charts are established and further used for monitoring future production. In conclusion, the tools used in the process analytical technology framework are found effective for improving the performance of tableting process.

    Original languageEnglish (US)
    Pages (from-to)115-126
    Number of pages12
    JournalProceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering
    Volume228
    Issue number2
    DOIs
    StatePublished - Jan 1 2014

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    Hardness
    Drug products
    Experiments
    Monitoring
    Control charts

    Keywords

    • control charts
    • Process analytical technology
    • process capability
    • weighted additive model

    ASJC Scopus subject areas

    • Mechanical Engineering
    • Industrial and Manufacturing Engineering

    Cite this

    Optimizing tablets' quality with multiple responses using fuzzy goal programming. / Al-Refaie, Abbas; Diabat, Ali; Li, Ming Hsien.

    In: Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering, Vol. 228, No. 2, 01.01.2014, p. 115-126.

    Research output: Contribution to journalArticle

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