A decision support system for eco-efficient biorefinery process comparison using a semantic approach

Lousteau-Cazalet, Charlotte; Barakat, Abdellatif; Belaud, Jean‐Pierre; Buche, Patrice; Busset, Guillaume; Charnomordic, Brigitte; Dervaux, Stéphane; Destercke, Sébastien; Dibie-Barthelemy, Juliette; Sablayrolles, Caroline; Vialle, Claire

doi:10.1016/j.compag.2016.06.020

Cited by 21 publications

(16 citation statements)

References 40 publications

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“…Other initiatives aim to adopt shared vocabularies and data structures for specific agriculture subdomains (see for example [54] for the wheat community). This effort has prompted proposals for new open data platforms implementing FAIR-a set of guiding principles to make data Findable, Accessible, Interoperable, and Re-usable-to re-use and manage these shared vocabularies and data structures [55,56]. Before re-using data, it should first be assessed for data quality.…”

Section: Discussionmentioning

confidence: 99%

“…Before re-using data, it should first be assessed for data quality. Note that models have already been proposed to assess data-source reliability [57] and have already been implemented in data management platforms [55,56]. Note too that re-using the huge amount of text-format data in the scientific literature relevant to populating MRE systems remains a challenging task, although there are proposals to semiautomatically extract relevant data using text-mining tools guided by ontologies [58].…”

Section: Discussionmentioning

confidence: 99%

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Multi-Criteria Reverse Engineering for Food: Genesis and Ongoing Advances

et al. 2019

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Multi-criteria reverse engineering (MRE) has arisen from the cross-fertilization of advances in mathematics and shifts in social demand. MRE, thus, marks a progressive switch (a) from empirical to formal approaches able to simultaneously factor in diverse parameters, such as environment, economics, and health; (b) from mono-criterion optimization to multi-criteria decision analysis; (c) from forward engineering, observing the results of process conditions, to reverse engineering, selecting the right process conditions for a target output. The food sector has been slow to adopt reverse engineering, but interest is surging now that the industry is looking to shift production towards personalized food. MRE has followed a heterogeneous development trajectory and found applications in different disciplines. The scope of this review spans MRE applications in the food sector covering food packaging and food consumption and focuses on demonstrating potentialities of MRE in a complex field like food. We explain how MRE enables the development of sustainable processes, looking at similar approaches used in sectors other than food. Building on this extensive review, we sketch out some guidelines on approaches to be used in future MRE applications in food, working up from the problem statement.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Multi-Criteria Reverse Engineering for Food: Genesis and Ongoing Advances

et al. 2019

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“…These data are stored in INRAE dataverse and replicated in @Web data warehouse [4] ( https://www6.inra.fr/cati-icat-atweb/ ) in which the data structuration and vocabulary standardization are controlled by BIOREFINERY ontology [ [3] , [4] ]. BIOREFINERY ontology is available in INRAE dataverse ( https://doi.org/10.15454/X2MOWO , version 2.0) and Agroportal ( http://agroportal.lirmm.fr/ontologies/BIOREFINERY , version 2.1).…”

Section: Data Descriptionmentioning

confidence: 99%

“…The whole particle size distribution of a subset of produced powder samples are also provided for different milling times to illustrate the kinetics of particle size reduction. These data are stored in INRAE public repository and have been structured using BIOREFINERY ontology [3] . These data are also replicated in atWeb data warehouse providing additional query tools [ [3] , [4] ].…”

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confidence: 99%

Milling itineraries dataset for a collection of crop and wood by-products and granulometric properties of the resulting powders

et al. 2020

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Lignocellulosic biomass represents a readily available reservoir of functional elements that can be an alternative to fossil resources for energy, chemicals and materials production. However, comminution of lignocellulosic biomass into fine particles is required to reveal its functionalities, improve its reactivity and allow practical implementation in the downstream processing steps (carrying, dosage, mixing, formulation, shaping…). The sources of lignocellulosics are diverse, with two main families, being agricultural and forest by-products. Due to plant specificity and natural variability, the itineraries of particle size reduction by dry processing, the behavior upon milling and therefore the characteristics of resulting powders can deeply vary according to various raw biomasses [ [1] , [2] ]. This data article contains milling itineraries and granulometric properties of the resulting powders obtained from a collection of by-products from crops (flax fibers, hemp core, rice husk, wheat straw) and woods (pine wood pellets, pine bark, pine sawdust, Douglas shavings, chestnut tree sawdust) representative of currently used lignocellulosic biomass. Samples provided in the form of large pieces (hemp core, pine bark, Douglas shavings) were successively milled using different mills to progressively reduce the matter into coarse, intermediate and finally fine powders. The other samples, supplied as sufficiently small format, were directly processed in the fine powder mill. The machine characteristics and their operating parameters were recorded. The granulometric properties of the powders were analyzed with a laser granulometer and the main indicators related to the particle size distribution (PSD) are presented: (i) d10, d50 (or median diameter) and d90 which are the 10th, 50th and 90th percentiles of the cumulative volume distribution; (ii) the span, which evaluates the width of the particle size distribution; (iii) the calculated specific surface area of the powders which represents the sum of total surface exhibited by the particles per unit of gram and for some powders. The whole particle size distribution of a subset of produced powder samples are also provided for different milling times to illustrate the kinetics of particle size reduction. These data are stored in INRAE public repository and have been structured using BIOREFINERY ontology [3] . These data are also replicated in atWeb data warehouse providing additional query tools [ [3] , [4] ].

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“…These commonly lead to oversimplification or erroneous hypotheses in the modelling process and introduce uncertainties into the practices of decision‐making. Many decision and policy makers are not necessarily biorefinery specialists. Also, biorefinery experts might not have the computer science or software skills to be able to convert and transfer data between different tools . In the event that errors are propagated during data transfer or entry, they might not be easily located, and reconciliation to obtain reliable data cannot be guaranteed. Tools based on multi‐criteria analysis in combination with multi‐objective optimization are resource intensive and cannot be utilized when early‐stage results are required within a short time‐frame, as they often involve a team of experts from different domains.…”

Section: Introductionmentioning

confidence: 99%

Decision support systems for assessment of biorefinery transformation strategies

et al. 2018

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The development of integrated biorefineries is one of the currently proposed strategies for transforming into a low carbon bio‐economy. Although different biorefining technologies can be integrated into host mills such as the Kraft and thermomechanical pulp processes, it is important to select the most appropriate technology taking into consideration the specificities and on‐site constraints. In this work, a decision support tool was developed and applied to industrial case studies for biorefinery implementation. Firstly, the tool was used for scenario‐based simultaneous analysis of the technical, economic, and environmental impacts in a single platform for different biorefinery implementation strategies. Its robustness and flexibility were demonstrated by two comprehensive industrial cases covering biorefinery transformation strategies for a Kraft pulp corporation involving three sites and a newsprint corporation with two sites. The tool made it possible to elucidate the advantages of lignin recovery implementation at modern and median Kraft pulping sites. Also, it revealed the objective basis for selecting between lignin recovery, hemicelluloses extraction, and thermochemical platforms biorefineries. The most suitable plant capacity for profitability was determined in the case of repurposing a median or average integrated newsprint mill into a biofuel production facility based on the pyrolysis platform. In a modern integrated newsprint mill, it was shown that phenol‐formaldehyde (PF) resins production can significantly decrease production costs, diversify the product portfolio, and mitigate risks associated with the core product line.

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A decision support system for eco-efficient biorefinery process comparison using a semantic approach

Cited by 21 publications

References 40 publications

Multi-Criteria Reverse Engineering for Food: Genesis and Ongoing Advances

Multi-Criteria Reverse Engineering for Food: Genesis and Ongoing Advances

Milling itineraries dataset for a collection of crop and wood by-products and granulometric properties of the resulting powders

Decision support systems for assessment of biorefinery transformation strategies

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