Techno-economic process modelling and Monte Carlo simulation data of uncertainty quantification in field-grown plant-based manufacturing

McNulty, Matthew J.; Kelada, Kirolos; Paul, Debashis; Nandi, Somen; McDonald, Karen A.

doi:10.1016/j.dib.2021.107317

Cited by 4 publications

(3 citation statements)

References 7 publications

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“…McNulty et al [64] developed a techno-economic analysis model including process variability and related uncertainties in field-grown plant-based manufacturing. They employed the MCS to quantify the effect of variation and uncertainties in profitability-related indicators such as internal rate of return, cost of goods, and process performance forecast variables such as product purity and annual throughput [65]. The predictive modeling, uncertainty analysis, optimization, and TEA of bio-catalyzed biodiesel production from Azidirica Indica oil were accomplished by Oke et al [66].…”

Section: Content-based Analysismentioning

confidence: 99%

Techno-Economic and Life Cycle Cost Analysis through the Lens of Uncertainty: A Scoping Review

Barahmand

Eikeland

2022

Sustainability

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Researchers have long been interested in developing new economic assessment methods to provide credible information and facilitate the sustainable development of new technologies and products. The techno-economic analysis (TEA) and the life cycle cost analysis (LCCA) are the most widely used approaches for modeling and calculating processes’ economic impacts. A simulation-based TEA is a cost-benefit analysis that simultaneously considers technical and economic factors. In addition, the method facilitates the development of the entire project and provides a systematic approach for examining the interrelationships between economic and technological aspects. When it comes to economic studies, it is intimately bonded with uncertainty. There are numerous uncertainty sources, classified in various ways. The uncertainty reflects “an inability to determine the precise value of one or more parameters affecting a system.” The variability refers to the different values a given parameter may take. This implies that a probability density function (PDF), for instance, can be employed to estimate and quantify the variability of a given parameter. The bias refers to “assumptions that skew an analysis in a certain direction while ignoring other legitimate alternatives, factors, or data.” The present study identifies the frequency with which TEA/LCCA studies address uncertainty and gaps within the selected papers through a scoping review. The results indicate that the uncertainty associated with economic factors and model uncertainties were the main sources of uncertainty in TEA and LCCA. Moreover, possibilistic approaches such as the Monte Carlo methodology were the most frequently used tool to cope with the uncertainties associated with LCCA and TEA.

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Section: Content-based Analysismentioning

confidence: 99%

Techno-Economic and Life Cycle Cost Analysis through the Lens of Uncertainty: A Scoping Review

Barahmand

Eikeland

2022

Sustainability

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“…On the other hand, the application of a model allows predicting the performance of the design of experimental or under construction systems, since the manipulation of the variables and properties of the model is cheaper than creating a complete system, allowing possible improvements of the real system. and contributes to reducing the risk inherent in decision-making [30].…”

Section: A2 Benefits Of Implementing a Modelmentioning

confidence: 99%

BPM and cycle counting in the design of a model to increase the perfect order: a case study in a company in the commercial sector

Lopez¹,

Barahona²,

Altamirano-Flores³

2022

Proceedings of the 2nd LACCEI International Multiconference on Entrepreneurship, Innovation and Regional Development (LEIRD 202

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This paper aims to evaluate the level of delivery compliance in an industrial tools trading company in Metropolitan Lima, based on the decrease in sales observed in the year 2020. For this reason, a quantitative and qualitative diagnosis of the company was carried out, where a low level of delivery compliance was observed, which is generating an economic impact of about 15% of the company's annual income. Furthermore, this problem is measured through the technical gap of the percentage of perfect deliveries, which is currently 64.5%, below the current market. In this sense, a model was proposed to increase the percentage of perfect orders through the implementation of Cyclic Counting, 5S, AHP and BPM in order to increase the Inventory Record Accuracy (IRA), avoid confusion in the selection of products, make an adequate selection and evaluation of suppliers and identify those activities that do not add value. In this way, the simulation of the model will be carried out and a decrease in late and incomplete deliveries will be observed, obtaining a value of 74.3% of perfect orders and a 25% increase in sales.

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“…Plants and plant cells have a number of advantages over bacterial and mammalian platforms for production of recombinant proteins including therapeutic proteins [ 6 ]. These advantages include the low cost and relatively high speed of recombinant protein production at a large scale in plants and plant cells [ 7 , 8 ]. As eukaryotic organisms, plants can carry out many of the post-translational modifications for production of complex proteins but do not require animal derived reagents (serum-free) for cultivation [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

Maximizing the Production of Recombinant Proteins in Plants: From Transcription to Protein Stability

Feng

Fan

et al. 2022

IJMS

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The production of therapeutic and industrial recombinant proteins in plants has advantages over established bacterial and mammalian systems in terms of cost, scalability, growth conditions, and product safety. In order to compete with these conventional expression systems, however, plant expression platforms must have additional economic advantages by demonstrating a high protein production yield with consistent quality. Over the past decades, important progress has been made in developing strategies to increase the yield of recombinant proteins in plants by enhancing their expression and reducing their degradation. Unlike bacterial and animal systems, plant expression systems can utilize not only cell cultures but also whole plants for the production of recombinant proteins. The development of viral vectors and chloroplast transformation has opened new strategies to drastically increase the yield of recombinant proteins from plants. The identification of promoters for strong, constitutive, and inducible promoters or the tissue-specific expression of transgenes allows for the production of recombinant proteins at high levels and for special purposes. Advances in the understanding of RNAi have led to effective strategies for reducing gene silencing and increasing recombinant protein production. An increased understanding of protein translation, quality control, trafficking, and degradation has also helped with the development of approaches to enhance the synthesis and stability of recombinant proteins in plants. In this review, we discuss the progress in understanding the processes that control the synthesis and degradation of gene transcripts and proteins, which underlie a variety of developed strategies aimed at maximizing recombinant protein production in plants.

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Techno-economic process modelling and Monte Carlo simulation data of uncertainty quantification in field-grown plant-based manufacturing

Cited by 4 publications

References 7 publications

Techno-Economic and Life Cycle Cost Analysis through the Lens of Uncertainty: A Scoping Review

Techno-Economic and Life Cycle Cost Analysis through the Lens of Uncertainty: A Scoping Review

BPM and cycle counting in the design of a model to increase the perfect order: a case study in a company in the commercial sector

Maximizing the Production of Recombinant Proteins in Plants: From Transcription to Protein Stability

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