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Modeling of acetosolv pulping of oil palm fronds using response surface methodology and wavelet neural networks

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Abstract

Mathematical models based on response surface methodology (RSM) and wavelet neural networks (WNNs) in conjunction with a central composite design were developed in order to study the influence of pulping variables viz. acetic acid, temperature, time, and hydrochloric acid (catalyst) on the resulting pulp and paper properties (screened yield, kappa number, tensile and tear indices) during the acetosolv pulping of oil palm fronds. The performance analysis demonstrated the superiority of WNNs over RSM, in that the former reproduced the experimental results with percentage errors and mean squared errors between 3 and 8% and 0.0054–0.4514 respectively, which were much lower than those obtained by the RSM models with corresponding values of 12–40% and 0.0809–9.3044, further corroborating the goodness of fit of the WNNs models for simulating the acetosolv pulping of oil palm fronds. Based on this assessment, it validates the exceptional predictive ability of the WNNs in comparison to the RSM polynomial model.

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Acknowledgments

Financial support from Universiti Sains Malaysia through Research University Grants No. 1001/PTEKIND/8140151 and 1001/PTEKIND/814240, and Directorate General of Higher Education of Indonesia for sponsoring postgraduate studies of Nasrullah is gratefully acknowledged.

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Authors and Affiliations

  1. Department of Chemical Engineering, Universitas Syiah Kuala, Banda Aceh, 23111, Indonesia

    Nasrullah Razali

  2. Faculty of Mechanical and Manufacturing Engineering, Universiti Tun Hussein Onn Malaysia, 86400, Parit Raja, Batu Pahat, Johor, Malaysia

    Pauline Ong

  3. Bioresource, Paper and Coating Division, School of Industrial Technology, Universiti Sains Malaysia, 11800, USM, Penang, Malaysia

    Mazlan Ibrahim & Wan Rosli Wan Daud

  4. School of Mathematical Sciences, Universiti Sains Malaysia, 11800, USM, Penang, Malaysia

    Zarita Zainuddin

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  1. Nasrullah Razali
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  2. Pauline Ong
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  3. Mazlan Ibrahim
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  4. Wan Rosli Wan Daud
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  5. Zarita Zainuddin
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Correspondence to Zarita Zainuddin.

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Razali, N., Ong, P., Ibrahim, M. et al. Modeling of acetosolv pulping of oil palm fronds using response surface methodology and wavelet neural networks. Cellulose 26, 4615–4628 (2019). https://doi.org/10.1007/s10570-019-02406-z

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