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39 results for “Production costs”
GNSS troposphere products from a network of low-cost GNSS receivers, Wroclaw, Poland, March-April 2021
<p>This dataset contains multi-GNSS troposphere products, i.e. ECEF coordinates, zenith total delay (ZTD), and horizontal gradients, together with their uncertainties. These products were obtained using 3 processing strategies:</p> <p>1) real-time (for details see https://link.springer.com/article/10.1007/s10291-020-01014-w, under to "advanced strategy" configuration, with the exception that only GPS and Galileo observations were considered);</p> <p>2) near real-time (NRT, for details see http://egvap.dmi.dk/);</p> <p>3) final (using CSRS online service, https://webapp.geod.nrcan.gc.ca/geod/tools-outils/ppp.php).</p> <p>Products are stored as standard Matlab MAT files. Each file contains a set of table arrays (Matlab format). Each table array contains the selected set of estimated parameters for a single station. Table columns are labeled and self-explanatory. A comma-delimited text file can be obtained using the in-build Matlab function "writetable.m".</p> <p>For convenience, the same information is stored in alternative data formats:</p> <p>1) for NRT and Final products: troposphere SINEX v1 (TRO / TRP)</p> <p>2) for real-time products: semicolon-delimited text files, with a self-explanatory header line; each file contains daily products for one station.</p>
Joint Optimization of Production and Maintenance for Cost-effective Manufacturing and Demand Response Participation Dataset - Machine Breakdown Event
<p>Using the previous dataset at <<a href="https://zenodo.org/record/4106746">https://zenodo.org/record/4106746</a>> an announcement of a machine breakdown event was simulated on Friday at 6:00, describing that machine MAQ119 could breakdown at any moment, detected using a predictive maintenance system. Accordingly, the proposed scheduler imposed a machine available frames constraint, during its event, of 0 usable frames, thus removing the machine from production. The proposed genetic algorithm was executed for 1 hour at period 769 (Friday at 7:00) until the remainder of the schedule’s time window. Also, the predefined optimization weights were 1 for total cost and 0 for machine occupancy deviation.</p> <p> </p> <p>File Description:</p> <ul> <li>Input_JSON_Machine_Breakdown_Optimization - JSON input data for the machine breakdown event</li> <li>Output_JSON_Machine_Breakdown_Optimization - JSON output data for the machine breakdown event</li> <li>Output_Statistics_Machine_Breakdown_Optimization - Excel output machine breakdown event statistics</li> </ul>
Joint Optimization of Production and Maintenance for Cost-effective Manufacturing and Demand Response Participation Dataset - Maintenance Optimization
<p>Using the previous dataset at <<a href="https://zenodo.org/record/4106746">https://zenodo.org/record/4106746</a>> a maintenance optimization scenario was formulated to validate the scheduler's ability to schedule tasks as well as maintenance activities while also minimizing the total costs. Accordingly, it was considered an optimization weight of 1 for the total cost and 0 for machine occupancy deviation, as well as a 2-hour execution time for the genetic algorithm. Each maintenance activity, for every machine, has a duration of 6 hours and 10 minutes, with a labor cost of 3,22 EUR/hour during the stipulated maintenance hours and a monetary penalty, that doubles the cost (i.e., 6.44 EUR/hour) if done out of maintenance hours.</p> <p> </p> <p>File Description:</p> <ul> <li>Input_JSON_Maintenance_Optimization - JSON input data for the maintenance optimization</li> <li>Output_JSON_Maintenance_Optimization - JSON output data for the maintenance optimization</li> <li>Output_Statistics_Maintenance_Optimization - Excel output maintenance optimization statistics</li> </ul>
Joint Optimization of Production and Maintenance for Cost-effective Manufacturing and Demand Response Participation Dataset - Total Cost and Machine Occupancy Deviation Optimization
<p>Using the previous dataset at <<a href="https://zenodo.org/record/4106746">https://zenodo.org/record/4106746</a>> a total cost and machine occupancy deviation optimization scenario was formulated that aims to demonstrate how the proposed scheduler is able to balance tasks between machines while also reducing overall costs. For this scenario, it was considered an optimization weight of 0.5 for both the total costs and machine occupancy deviation objectives and the genetic algorithm was executed for 2 hours.</p> <p> </p> <p>File Description:</p> <ul> <li>Input_JSON_Total_Cost_Machine_Occupancy_Deviation_Optimization - JSON input data for the total cost and machine occupancy deviation optimization</li> <li>Output_JSON_Total_Cost_Machine_Occupancy_Deviation_Optimization - JSON output data for the total cost and machine occupancy deviation optimization</li> <li>Output_Statistics_Total_Cost_Machine_Occupancy_Deviation_Optimization - Excel output total cost and machine occupancy deviation optimization statistics</li> </ul>
Joint Optimization of Production and Maintenance for Cost-effective Manufacturing and Demand Response Participation Dataset - Energy Cost Optimization with Energy Selling
<p>Using the previous dataset at <<a href="https://zenodo.org/record/4106746">https://zenodo.org/record/4106746</a>> an energy cost optimization considering the presence of an energy buyer is proposed to validate the scheduler’s ability to maximize profits while also minimizing energy costs. The scenario considers an added sales value corresponding to 50% of the buying. For this scenario, the genetic algorithm was executed for 2 hours, with 1 and 0 for the optimization weights total cost and machine occupancy deviation, respectively.</p> <p> </p> <p>File Description:</p> <ul> <li>Input_JSON_Energy_Cost_Energy_Selling_Optimization - JSON input data for the energy cost optimization with energy selling</li> <li>Output_JSON_Energy_Cost_Energy_Selling_Optimization - JSON output data for the energy cost optimization with energy selling</li> <li>Output_Statistics_Energy_Cost_Energy_Selling_Optimization - Excel output energy cost optimization with energy selling statistics</li> </ul>
Joint Optimization of Production and Maintenance for Cost-effective Manufacturing and Demand Response Participation Dataset - Joint Optimization of Production and Maintenance
<p>Using the previous datasets at <<a href="https://zenodo.org/record/4106746">https://zenodo.org/record/4106746</a>>, <<a href="https://zenodo.org/record/7055698">https://zenodo.org/record/7055698</a>>, <<a href="https://zenodo.org/record/7055580">https://zenodo.org/record/7055580</a>>, and <<a href="https://zenodo.org/record/7055573">https://zenodo.org/record/7055573</a>> a joint optimization of production and maintenance scenario was formulated which aims at combining all the features from the cited scenarios. For energy selling, it was considered an added sales value corresponding to 50% of the buying. Regarding maintenance activities, it was simulated an announcement of a maintenance activity for MAQ118 from Monday at 07:00 (i.e., period 1) to Monday at 17:00 (i.e., period 120), and another for MAQ120 which can be done at any time. These maintenance activities take 6 hours and 10 minutes to complete and have an associated labor cost of 3,22 EUR/hour in maintenance hours, and a double cost penalty (i.e., 6.44 EUR/hour) if done out of maintenance hours. The scenario was executed in 2 hours, with the corresponding optimization weights of 0.8 and 0.2 for the total cost and machine occupancy deviation, respectively.</p> <p> </p> <p>File Description:</p> <ul> <li>Input_JSON_Joint_Optimization_Production_Maintenance - JSON input data for the joint optimization of production and maintenance</li> <li>Output_JSON_Joint_Optimization_Production_Maintenance - JSON output data for the joint optimization of production and maintenance</li> <li>Output_Statistics_Joint_Optimization_Production_Maintenance - Excel output joint optimization of production and maintenance statistics</li> </ul>
Data for Cost Optimization of Shedding Mechanisms as a Product Family
<p>This the data from the numerical examples presented in "Accelerating Cost Optimization of Existing Product Family Designs Using Sensitivity Analysis on Component Commonalities" article. It contains the data of the results for the cost optimization of a shedding mechanism as a product family from two types of optimization: (i) brute-force and (ii) guided optimization: proposed method which uses sensitivity analysis on component commonalities. Each datum (.mat file) contains design variables (length of the four-bar mechanisms and motor locations) of a specific commonality matrix.</p>
Cost of ligno-cellulosic biomass production for bioenergy in 45 countries
<p>This database provides data on ligno-cellulosic biomass production costs in 45 countries. It is the result of a compilation of data from a literature search carried out on the Google Scholar platform based on the following keywords: ‘biomass’, ‘bioenergy’, ‘energy crops’, ‘cost’, ‘economics’, ‘analysis’, ‘ligno-cellulosic’, ‘managed forest’, ‘wood crop’, ‘grass crop’, ‘crop residues’ (similar keywords such as wood crop or gass crop were also used). It includes 106 documents published between 1988 and 2018, including 59 journal articles, 15 non peer-reviewed articles, 6 conference publications, 20 government agency reports, and 4 PhD or Master’s theses. The total number of data points is 410, unevenly distributed among the five biomass types (managed forest, wood energy crops, grass energy crops, agricultural residues and forest residues and six global regions (Africa, Asia, Latin America, Former Soviet Union, Europe and North America).</p>
Production costs and their effect on the profitability of the SMES in Latin America
<p><span>The micro, small and medium-sized enterprises (SMEs) play a pivotal role in the Latin America economy, creating jobs, boosting local economic activity and contribute to the socio-economic development of the region. The purpose is to reflect on the current costs management prices, the common challenges faced by SMEs in the region, and effective strategies to improve the profitability and sustainability of these companies.</span></p>
The oxidative cost of competing for egg fertilization exceeds the cost of egg production
<p><span>Measuring reproductive costs is crucial to understanding sexual conflict and its evolutionary outcomes. Sexual conflict is thought to originate from anisogamy – the size difference between male and female gametes; if sperm are tiny and not produced in vastly greater numbers than eggs, at any mating females' gametic investment is larger than that of males. Testing this prediction has proven difficult, especially because males and females differ in many more traits than just gamete size. We overcame this difficulty by exposing simultaneously hermaphroditic polychaete worms <em>Ophryotrocha diadema</em> (two sexual functions in the same body) to two social conditions, pairs and groups>2, where hermaphrodites invest either relatively more in the female function or relatively more in the male function, respectively. Then we measured four markers of cellular oxidative status, a physiological mediator of life-history strategies. Less female-biased hermaphrodites produced fewer eggs but, unexpectedly, had lower levels of antioxidant protection than more female-biased hermaphrodites, which produced more eggs. Male-biased hermaphrodites compete for mating as males (hermaphrodites in pairs do not) suggesting that in the short-term male competition might be costlier than egg production in terms of regulation of oxidative status. These results highlight the need of including behavioral traits, namely competition over egg fertilization, in the measures of reproductive costs.</span></p>
True cost accounting of organic and conventional food production
<p>This is the electronic supplementary data for the article "True cost accounting of organic and conventional food production" published in Journal of Cleaner Production (2023), https://doi.org/10.1016/j.jclepro.2023.137134.</p>
The oxidative cost of competing for egg fertilization exceeds the cost of egg production
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Data from: The price of insurance: costs and benefits of worker production in a facultatively social bee
Kin selection theory is foundational in helping to explain the evolution of sociality; however, the degree to which indirect fitness benefits may underlie helping behavior in species of early stage sociality has received relatively little empirical attention. Facultatively social bees, which demonstrate multiple forms of social organization, provide prime systems in which to empirically test hypotheses regarding the evolutionary origins of sociality. The subsocial small carpenter bee, Ceratina calcarata, may establish a social nest by manipulating brood provisions to rear a worker daughter, which then assists in critical late-season alloparental care. Here, we combine nest demographic and behavioral data with genetic relatedness estimates to calculate the relative inclusive fitness of both subsocial and social reproductive strategies in C. calcarata. Social mothers benefit from improved likelihood of brood survivorship and have higher fitness than subsocial mothers. Worker daughters have low indirect fitness on average, and will not produce their own offspring. Among-sibling relatedness is significantly higher in social nests than subsocial nests, though mothers of either reproductive strategy may mate multiply. Though this study corroborates the ultimate role of indirect fitness and assured fitness returns in the evolution of social traits, it also offers additional support for maternal manipulation as the proximate mechanism underlying evolutionary transitions in early stage insect societies.
The cost and benefit of quorum sensing controlled bacteriocin production in Lactobacillus plantarum
Bacteria eliminate competitors via 'chemical warfare' with bacteriocins. Some species appear to adjust bacteriocin production conditionally in response to the social environment. We tested whether variation in the cost and benefit of producing bacteriocins could explain such conditional behaviour, in the bacteria Lactobacillus plantarum. We found that: (1) bacterial bacteriocin production could be upregulated by either the addition of a synthetic autoinducer peptide (PLNC8IF; signalling molecule), or by a plasmid which constitutively encodes for the production of this peptide; (2) bacteriocin production is costly, leading to reduced growth when grown in poor and, to a lesser extent, in rich media; (3) bacteriocin production provides a fitness advantage, when grown in competition with sensitive strains; (4) the fitness benefits provided by bacteriocin production is greater at higher cell densities. These results show how the costs and benefits of upregulating bacteriocin production can depend upon abiotic and biotic conditions.
Dataset about "An autonomous low‑cost studio to record production‑ready instructional videos"
<p>Dataset used in the article "An autonomous low‑cost studio to record production‑ready instructional videos".</p> <p>The dataset contains two excel files. One for the TAM model applied to the autonomous low-cost studio (called SAGA), and one with the student perceptions about the resulting videos.</p> <p>Much more information is available in the publication in the journal.</p>
Low-cost, local production of a safe and effective disinfectant for resource-constrained communities
<p>Improved hygiene depends on the accessibility and availability of effective disinfectant solutions. These disinfectant solutions are unavailable to many communities worldwide due to resource limitations, among other constraints. Safe and effective chlorine-based disinfectants can be produced via simple electrolysis of salt water, providing a low-cost and reliable option for on-site, local production of disinfectant solutions to improve sanitation and hygiene. This study reports on a system (herein called "Electro-Clean") that can produce concentrated solutions of hypochlorous acid (HOCl) using readily available, low-cost materials. With just table salt, water, graphite welding rods, and a DC power supply, the Electro-Clean system can safely produce HOCl solutions (~1.5 liters) of up to 0.1% free chlorine (i.e.,1000 ppm) in less than two hours at low potential (5 V DC) and modest current (~5 A). Rigorous testing of free chlorine production and durability of the Electro-Clean system components, described here, has been verified to work in multiple locations around the world, including microbiological tests conducted in India and Mexico to confirm the biocidal efficacy of the Electro-Clean solution as a surface disinfectant. Cost estimates are provided for making HOCl locally with this method in the USA, India, and Mexico. Findings indicate that Electro-Clean is an affordable alternative to off-the-shelf commercial chlorinator systems in terms of first costs (or capital costs), and cost-competitive relative to the unit cost of the disinfectant produced. By minimizing dependence on supply chains and allowing for local production, the Electro-Clean system has the potential to improve public health by addressing the need for disinfectant solutions in resource-constrained communities.</p>
Data on digitization, unit labour costs and capital stock based productivity indicators
<p>Dataset was collected from Eurostat involving 9 indicators included in 2 panel data regression models</p>
Elevated energy costs of biomass production in mitochondrial-respiration deficient Saccharomyces cerevisiae
<p>The <em>pcYeast8</em> model and data, required to reproduce the figures in the preprint "Elevated energy costs of biomass production in mitochondrial-respiration deficient <em>Saccharomyces cerevisiae</em>". Data bundle uploaded by Pranas Grigaitis, p.grigaitis [at] vu.nl.</p> <p><em>Abstract</em></p> <p>Microbial growth requires energy for maintaining the existing cells and producing components for the new ones. Microbes therefore invest a considerable amount of their resources into proteins needed for energy harvesting. Growth in different environments is associated with different energy demands for growth of yeast <em>Saccharomyces cerevisiae</em>, although the cross-condition differences remain poorly characterized. Furthermore, a direct comparison of the energy costs for the biosynthesis of the new biomass across conditions is not feasible experimentally; computational models, on the contrary, allow comparing the optimal metabolic strategies and quantify the respective costs of energy and nutrients. Thus in this study, we used a resource allocation model of <em>S. cerevisiae</em> to compare the optimal metabolic strategies between different conditions. We found that <em>S. cerevisiae</em> with respiratory-impaired mitochondria required additional energetic investments for growth, while growth on amino acid-rich media was not affected. Amino acid supplementation in anaerobic conditions also was predicted to rescue the growth reduction in mitochondrial respiratory shuttle-deficient mutants of <em>S. cerevisiae</em>. Collectively, these results point to elevated costs of resolving the redox imbalance caused by <em>de novo</em> biosynthesis of amino acids in mitochondria. To sum up, our study provides an example of how resource allocation modeling can be used to address and suggest explanations to open questions in microbial physiology.</p>
Low-cost, local production of a safe and effective disinfectant for resource-constrained communities
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Data from: Cooking, heating, insulating products and services (CHIPS) for Mongolian ger: Reducing energy, cost, and indoor air pollution
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