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Datasets on mathematical modeling of multi-product multi-stage production to analyze the relationship between production yield, demand, and costs.

ABSTRACT: The data presented in this article are related to the research article "Optimal procurement and production planning for multi-product multi-stage production under yield uncertainty" (Talay and Özdemir-Akyıldırım, in press) [1]. The data includes: 1) the input parameters (production yield, demand, and costs) collected through comprehensive review of the literature and diversified further to enrich the analytical results, and 2) results from mathematical modeling and analysis on the optimal procurement and semi-processed material allocation decisions for different parameter sets. The dataset is particularly constructed for a production system with two stages and three final products.

SUBMITTER: Talay I

PROVIDER: S-EPMC6355965 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

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Datasets on mathematical modeling of multi-product multi-stage production to analyze the relationship between production yield, demand, and costs.

Talay Işılay I Özdemir-Akyıldırım Öznur Ö

Data in brief 20190118

The data presented in this article are related to the research article "Optimal procurement and production planning for multi-product multi-stage production under yield uncertainty" (Talay and Özdemir-Akyıldırım, in press) [1]. The data includes: 1) the input parameters (production yield, demand, and costs) collected through comprehensive review of the literature and diversified further to enrich the analytical results, and 2) results from mathematical modeling and analysis on the optimal procur ...[more]

PMID: 30740488

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Project description:BackgroundEthanol biorefineries need to lower their overall production costs to become economically feasible. Two strategies to achieve this are to reduce costs using cheaper feedstocks or to increase the ethanol production yield. Low-cost feedstocks usually have high non-structural components (NSC) content; therefore, a new process is necessary to accommodate these feedstocks and overcome the negative effects of NSC. This study developed a novel ethanol biorefinery process including a biomass preprocessing step that enabled the use of lower-cost feedstocks while improving ethanol production without detoxification (overliming). Two types of poplar feedstocks were used, low-quality whole-tree chips (WTC) and high-quality clean pulp chips (CPC), to determine if the proposed process is effective while using feedstocks with different NSC contents.ResultsTechnical assessment showed that acidic preprocessing increased the monomeric sugar recovery of WTC from 73.2% (untreated) to 87.5% due to reduced buffering capacity of poplar, improved sugar solubilization during pretreatment, and better enzymatic hydrolysis conversion. Preprocessing alone significantly improved the fermentability of the liquid fraction from 1-2% to 49-56% for both feedstocks while overliming improved it to 45%. Consequently, it was proposed that preprocessing can substitute for the detoxification step. The economic assessment revealed that using poplar WTC via the new process increased annual ethanol production of 10.5 million liters when compared to using CPC via overliming (base case scenario). Also, savings in total operating costs were about $10 million per year when using cheaper poplar WTC instead of CPC, and using recycled water for preprocessing lowered its total operating costs by 45-fold.ConclusionsThe novel process developed in this study was successful in increasing ethanol production while decreasing overall costs, thus facilitating the feasibility of lignocellulosic ethanol biorefineries. Key factors to achieving this outcome included substituting overliming by preprocessing, enabling the use of lower-quality feedstock, increasing monomeric sugar recovery and ethanol fermentation yield, and using recycled water for preprocessing. In addition, preprocessing enabled the implementation of an evaporator-combustor downstream design, resulting in a low-loading waste stream that can be treated in a wastewater treatment plant with a simple configuration.

Dataset Information

Datasets on mathematical modeling of multi-product multi-stage production to analyze the relationship between production yield, demand, and costs.

Publications

Datasets on mathematical modeling of multi-product multi-stage production to analyze the relationship between production yield, demand, and costs.

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