Academic literature on the topic 'Farm machinery industry'

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Journal articles on the topic "Farm machinery industry"

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., A. K. M. Saiful Islam, M. A. S. Kowser Sarker ., M. A. Rahman ., M. M. Hossain ., and M. M. Alam . "Production Problems of Farm Machinery Manufacturing Industry in Bangladesh." Journal of Biological Sciences 1, no. 10 (2001): 955–59. http://dx.doi.org/10.3923/jbs.2001.955.959.

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Pudup, Mary Beth. "From Farm to Factory: Structuring and Location of the U.S. Farm Machinery Industry." Economic Geography 63, no. 3 (1987): 203. http://dx.doi.org/10.2307/143950.

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GEARY, U., N. LOPEZ-VILLALOBOS, D. J. GARRICK, and L. SHALLOO. "Spring calving versus split calving: effects on farm, processor and industry profitability for the Irish dairy industry." Journal of Agricultural Science 152, no. 3 (2013): 448–63. http://dx.doi.org/10.1017/s0021859613000397.

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SUMMARYA combined farm systems and processing sector model was used to determine the effect on industry profitability of changing from the current seasonal milk supply profile to a less seasonal milk supply profile. Differences in investment costs, product portfolio, product storage and financing costs at processor level were included in the analysis. It was found, based on the underlying model assumptions, that a less seasonal supply profile allowed better capacity utilization, enabled higher volumes of high-value products to be produced and generated higher net returns (€1540·7 million) for the processing sector than the seasonal milk supply profile (€1474·9 million); it therefore warranted paying a higher milk price to farmers. In contrast, at farm level the seasonal milk supply profile resulted in lower costs and higher net farm profit, with net margin per litre being 1·6 cents per litre higher relative to the less seasonal milk supply profile. Higher concentrate, labour, silage, machinery hire and heifer replacement costs in the less seasonal supply profile relative to the seasonal milk supply profile were the main factors that contributed to the lower farm profitability. From a national perspective, including processor and farm sector interests, the seasonal milk supply profile was more profitable by an estimated €83 million; the difference in costs at farm level outweighed the increased milk price at processor level found in the less seasonal milk supply profile.
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Smith, Donalda M. "Health and Disease in Farm Workers." Outlook on Agriculture 15, no. 3 (1986): 115–20. http://dx.doi.org/10.1177/003072708601500303.

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Occupational diseases, such as silicosis in miners, are widespread but it is only comparatively recently that they have received the serious attention they demand. Leaving aside accidents associated with machinery and agrochemicals, farm workers are particularly liable to a large number of health hazards – physical, chemical, and biological. The nature of the industry – small groups of workers often employed in remote places under primitive conditions – makes it difficult to assess the real incidence of work-associated diseases and to organise effective treatment and preventive measures.
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Mohd Nawi, Nur Syazwani, Baba Md Deros, Norani Nordin, and Ezrin Hani Sukadarin. "DEVELOPMENT OF TECHNOLOGY MECHANIZATION ACCEPTANCE AND USE ACTION PLAN." Journal of Information System and Technology Management 5, no. 16 (2020): 62–69. http://dx.doi.org/10.35631/jistm.516005.

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The palm oil industry is an advanced industry that benefits the country's economic stability. However, working in the oil palm plantations is very challenging and the farmworkers are exposed to many risks when doing day-to-day work. Most of the work on the farm is still using manual tools. There are farm management and workers who do not want to use machine tools due to reasons such as high cost, difficult to maintain, and burdensome. This study used an observation method in oil palm plantations and interviews with field managers to collect information. Verification of a pre-action plan is made before developing the final action plan. As such, the model was proposed as a step towards increasing the use of machinery in oil palm plantations to help ease the workload that the workers are carrying.
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Cardenas, Victor M., Ruiqi Cen, Melissa M. Clemens, et al. "Morbidity and Mortality from Farm Tractor and Other Agricultural Machinery-Related Injuries in Arkansas." Journal of Agricultural Safety and Health 24, no. 4 (2018): 213–25. http://dx.doi.org/10.13031/jash.12828.

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Abstract. This study applied a text string search algorithm to ascertain suspect farm tractor or agricultural machinery-related injuries in data sources available for 2000-2014 in the state of Arkansas. The occurrences of tractor or other agricultural machinery-related injuries were compared with data available from the Centers for Disease Control and Prevention’s National Center for Health Statistics (NCHS) and the Bureau of Labor Statistics’ Census of Fatal Occupational Injuries (CFOI). For death certificates that assigned an external cause of death, the authors first collected all those that were coded as related to agricultural machinery, based on search strings for occupation and industry and a description of how the injury occurred. They then inspected each case individually and removed those that were likely unrelated to agricultural machinery. This approach significantly increased (by 7.8 times) the number of suspect agricultural machinery-related fatalities compared to the number reported to CFOI, but there was only a 17% (not statistically significant) increase compared to NCHS. All hospital records with any discharge diagnosis coded as related to agricultural machinery were selected. Descriptive analysis of the fatalities and hospital records showed a significantly increased risk among men above retirement age, peaks during the summer, and an increased risk in the Mississippi delta region. About one-third of the agricultural machinery-related fatalities were due to overturns. The use of the algorithm can improve ascertainment of fatal agricultural machinery-related injuries in Arkansas. The death records were found to be rich in data on the circumstances of the injuries, which can be used to screen for tractor-related fatalities and, if confirmed, translated into action to improve the safety of Arkansas farmers. Keywords: Agricultural machinery, Farm, Farming, Injury, Risk, Statistics, Tractors.
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H. Kursat CELIK, Allan E. W. RENNIE, and Ibrahim AKINCI. "A Potential Research Area Under Shadow In Engineering: Agricultural Machinery Design and Manufacturing." ISPEC Journal of Agricultural Sciences 4, no. 2 (2020): 66–86. http://dx.doi.org/10.46291/ispecjasvol4iss2pp66-86.

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As a branch of the global machinery industry, the agricultural (farm) machinery design and manufacturing or agricultural engineering industry has become one of the most important industries to be supported and focussed on in the era of hunger threats foreseen in the World’s future. In order to produce sufficient volumes of food from current limited agricultural land, well-designed machinery and high technology-supported mechanisation of the agricultural production processes is a vital necessity. However, although novel improvements are observed in this area, they are very limited. There is a lack of implementation of advanced engineering design and manufacturing technologies in this industry, therefore agricultural engineering could be considered a potential engineering research area with this in mind. This study aims to highlight the potential, gaps, sector specific challenges and limitations of the agricultural engineering research area at a macro level. Under consideration of the sector‑specific indicators, the study revealed a major result: there is an insufficient level of sector-specific research on implementation strategies for up-to-date design and manufacturing technologies.
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WINDER, CORDON M. "Following America into the second industrial revolution: new rules of competition and Ontario's farm machinery industry, 1850–1930." Canadian Geographer/Le Géographe canadien 46, no. 4 (2002): 292–309. http://dx.doi.org/10.1111/j.1541-0064.2002.tb00752.x.

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Prikner, P., and A. Grečenko. "Farmland protection by means of tyre load rating." Research in Agricultural Engineering 53, No. 1 (2008): 8–13. http://dx.doi.org/10.17221/2131-rae.

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At present, the professionals in the industry and farming still miss comparative technical data indicating the potential of agricultural vehicles and mobile machinery to inflict compaction damage upon the cultivated soil. Harmful compaction means especially the increase of soil bulk density above a critical level required for efficient plant production. In general, it seems reasonable to restrict the excessive soil compaction by loaded wheels starting from the design of farm power and machinery, which means to provide technical data on the compaction potential of tyres. This paper presents the technique of tyre rating by means of the index Compaction Capacity (<i>CC</i>), which simply reflects the compaction potential of any individual tyre contained in a tyre catalogue within the whole range of loads and inflation pressures.
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İnanç, Taş, and Akay Abdullah Emin. "Productivity Analysis of Modified Farm Tractors in Forwarding Industrial Wood Products." Наукові праці Лісівничої академії наук України, no. 20 (June 4, 2020): 196–205. http://dx.doi.org/10.15421/412018.

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Public demands for forest products and services have been increasing gradually in many countries all over the world. Among the forest products, mostly round woods are produced in Turkey due to high economic value. On the other hand, there is a significant increase in demand for industrial woods in the domestic market in recent years. The reason behind this increase is the need of domestic companies in the wood-based panel industry for a large amount of wood raw material. . Farm tractors are the most widely used forest machinery in the extraction of industrial wood in Turkey. Farm tractors can be effectively used in mechanized harvesting operations after receiving some modifications and additional attachments. The modified farm tractors are affordable machinery for small logging contractors since their initial purchasing costs and hourly operating costs are quite low comparing with the forest harvesting equipment (i.e. skidder, forwarder, cable yarder). In this study, productivity of a modified farm tractor was analyzed during forwarding of industrial wood products. The study was implemented in Pinus nigra stand located in (?) the city of Afyonkarahisar in Turkey. In the study, the effects of forwarding distance on productivity were evaluated using statistical analysis. The results indicated that the most time-consuming work stage was unloading the truck and piling the wood products at the landing area, followed by ( in terms of time-consumption) collecting woods and loading the tractor at the stump. The average productivity of the forwarding operation was 6.06 stere/h (stere is the amount of wood pile with the height, width, and depth of one meter). It was also found that the productivity of the forwarding was significantly affected by the forwarding distance.
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Dissertations / Theses on the topic "Farm machinery industry"

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Drake, Dawn M. "Geographies of Competitive Advantage: An Examination of the US Farm Machinery Industry." 2011. http://trace.tennessee.edu/utk_graddiss/963.

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Many explanations of competitive advantage view place as a secondary factor. Organizational studies models tend to be considered aspatially, yet most are inherently geographic. It is important to consider the impact that geography has on the success or failure of an individual firm or a sector. This dissertation examines how location impacts the US farm machinery industry through an empirical analysis of Porter’s Theory of Competitive Advantage. Contributing to this empirical test are other bodies of literature including models for headquarters and research and development siting, product life cycle theory, industry life cycle theory, and green technologies as a driver of competitive advantage. The US farm machinery industry is composed of three firms: Deere and Company, Case New Holland, and the Allis-Gleaner Corporation. Theory-elaborating case study methodology, informed by archival data, publically available documents, trade show reconnaissance, and plant tours, coupled with map and content analysis allows for a deeper understanding of how geography impacts competitive advantage in the sector. Comparing findings from these geographic case studies to Porter’s results led to a new understanding of competitive advantage for mature manufacturing in a globalized economy. Previous analysis found Porter’s single diamond, which focuses on local conditions for competitive advantage, most appropriate for explaining mature industries in advanced market economies. This study found, however, that as mature industries increasingly pursue a global focus, a double diamond model, which takes into account both local and global conditions for competitive advantage, is more appropriate, even in an advanced economy. This research also found that, much like second-tier cities are desirable for headquarters and research and development siting, second-tier countries (that can provide high-skill labor at lower prices) are increasingly attractive for manufacturing operations. The need for modifications to product life cycle theory that take into account the impact of these countries as well as the effects of nationalism on manufacturing decisions in mature economies were also uncovered by this dissertation. This research demonstrates the continued importance of place to understanding competitive advantage, not only in the US farm machinery industry, but generally for mature manufacturing as a whole.
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Books on the topic "Farm machinery industry"

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Hanthorn, Michael. Selected farm machinery statistics. U.S. Dept. of Agriculture, Economic Research Service, 1986.

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Rukes, Brian. American farm tractor & implement dealerships. KP Books, 2004.

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Diwakar, D. M. Agriculture and industry: Dynamics of imbalances in India. Manak Publications, 1991.

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Pakosh, Jarrod. Versatile tractors: A farm boy's dream. Boston Mills Press, 2003.

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Usenko, L. N. Innovat︠s︡ionno-investit︠s︡ionnai︠a︡ dei︠a︡telʹnostʹ organizat︠s︡iĭ po proizvodstvu selʹskokhozi︠a︡ĭstvennoĭ tekhniki: Analiz i prognozirovanie : monografii︠a︡. Rostovskiĭ gos. ėkon. universitet, 2009.

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Kent, Borghoff, and American Society of Agricultural Engineers., eds. International Harvester farm equipment: Product history, 1831-1985. American Society of Agricultural Engineers, 1997.

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Mishra, Satish Chandra. Technological adaptation and employment in the small-scale farm machinery industry: Uttar Pradesh, India. International Labour Office, 1985.

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Cornelius, Lawrence L. Farm implement manufacturers and dealers in early Rock Island County: Including wagon and buggy manufacturers and dealers, 1836-1926. Midland Press Corp., 1992.

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Die Alpenländische Sensenindustrie um 1900: Industrialisierung am Beispiel des Redtenbacherwerks in Scharnstein, Oberösterreich. Böhlau, 1995.

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Vedenin, N. N. Pravovoe regulirovanie proizvodstvenno-tekhnicheskogo obespechenii͡a︡ selʹskogo khozi͡a︡ĭstva. Nauka, 1988.

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Book chapters on the topic "Farm machinery industry"

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Mishra, S. C. "12. The small-scale farm machinery industry in Uttar Pradesh." In The Technological Transformation of Rural India. Practical Action Publishing, 1994. http://dx.doi.org/10.3362/9781780446196.012.

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Kako, Toshiyuki. "The Development of the Farm Machinery Industry: Case Study of the Walking-Type Tractor." In Acquiring, Adapting and Developing Technologies. Palgrave Macmillan UK, 1995. http://dx.doi.org/10.1007/978-1-349-23775-3_6.

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Habyarimana, Ephrem. "Future Vision, Summary and Outlook." In Big Data in Bioeconomy. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-71069-9_21.

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AbstractThe DataBio’s agriculture pilots were carried out through a multi-actor whole-farm management approach using information technology, satellite positioning and remote sensing data as well as Internet of Things technology. The goal was to optimize the returns on inputs while reducing environmental impacts and streamlining the CAP monitoring. Novel knowledge was delivered for a more sustainable agriculture in line with the FAO call to achieve global food security and eliminate malnutrition for the more than nine billion people by 2050. The findings from the pilots shed light on the potential of digital agriculture to solve Europe’s concern of the declining workforce in the farming industry as the implemented technologies would help run farms with less workforce and manual labor. The pilot applications of big data technologies included autonomous machinery, mapping of yield, variable rate of applying agricultural inputs, input optimization, crop performance and in-season yields prediction as well as the genomic prediction and selection method allowing to cut cost and duration of cultivar development. The pilots showed their potential to transform agriculture, and the improved predictive analytics is expected to play a fundamental role in the production environment. As AI models are retrained with more data, the decision support systems become more accurate and serve the farmer better, leading to faster adoption. Adoption is further stimulated by cooperation between farmers to share investment costs and technological platforms allowing farmers to benchmark among themselves and across cropping season.
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Catucci, Antonella, Alessia Tricomi, Laura De Vendictis, Savvas Rogotis, and Nikolaos Marianos. "Farm Weather Insurance Assessment." In Big Data in Bioeconomy. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-71069-9_19.

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AbstractThe pilot aimed to develop services supporting both the risk and the damage assessment in the agro-insurance domain. It is based on the use of remotely sensed data, integrated with meteorological data, and adopts machine learning and artificial intelligence tools. Netherlands and Greece have been selected as pilot areas . In the Netherlands, the pilot was focused on potato crops for the identification of areas with higher risk, based on the historical analysis of heavy rains. In addition, it covered automated detection of potato parcels with anomalous behaviours (damage assessment) from satellite data, meteorological parameters and soil characteristics. In Greece, the pilot worked with 7 annual crops of high economic interest to the national agricultural sector. The crops have been modelled exploiting the last 3-year NDVI measurements to identify their deviations from the normal crop health behaviour for an early identification of affected parcels in case of adverse events. The models were successfully tested on a flooding event that occurred in 2019 in the Komotini region. Even though the proposed methodologies should be tested over larger areas and compared against a larger validation dataset, the results already now demonstrate how to reduce the operating costs of damage assessors through a more precise and automatic risk assessment. Additionally, the identification of parameters that most affect the crop yield could transform the insurance industry through index-based solutions allowing to dramatically cut costs.
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Bauer, Fabian, Jessica Hagner, Peter Bretschneider, and Stefan Klaiber. "Improvement of the prediction quality of electrical load profiles with artificial neural networks." In Machine Learning for Cyber Physical Systems. Springer Berlin Heidelberg, 2020. http://dx.doi.org/10.1007/978-3-662-62746-4_2.

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AbstractAgainst the backdrop of the economically and ecologically optimal management of electrical energy systems, accurate predictions of consumption load profiles play an important role. On this basis, it is possible to plan and implement the use of controllable energy generation and storage systems as well as energy procurement with the required lead-time, taking into account the technical and contractual boundary conditions.The recorded electrical load profiles will increase considerably in the course of the digitization of the energy industry. In order to make the most accurate predictions possible, it is necessary to develop and investigate models that take account of the growing quantity structure and, due to the significantly higher number of observations, improve the forecasting quality as far as possible.Artificial neural networks (ANN) are increasingly being used to solve non-linear problems for a growing amount of data that is affected by human and other unpredictable influences. Consequently, the model approach of an ANN is chosen for predicting load profiles. Aim of the thesis is the simulative investigation and the evaluation of the quality and optimality of a prediction model based on an ANN for electrical load profiles.
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Gordon, Robert B., and Patrick M. Malone. "Work in Factories." In The Texture of Industry. Oxford University Press, 1994. http://dx.doi.org/10.1093/oso/9780195058857.003.0016.

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Factories, and the factory system, are at the heart of the American industrial experience. Since the 1790s, Americans have developed many different types of factories and varieties of work within each of them. It is a terrible mistake to think of factory workers as simply automatons who do some type of mindless, repetitive task, day in and day out. The average American has never been in a factory and knows very little about what actually goes on there. Typically, there are dozens of employee classifications in one of these highly organized and hierarchical workplaces. A person employed in a factory might be a sweeper, vatman, machine operator, machine fixer, machinist, toolmaker, millwright, stockroom supplier, shipper, overseer, foreman, draftsman, electrician, or engineer. Machine operation, only one form of factory work, requires widely varying levels of skill, depending on the type of machine and the pace of production. Some jobs are routine and undemanding, but others challenge the intellect and manual dexterity of even the most skilled and experienced employees. There are tasks to be performed by one person as well as group activities that require extensive social interaction. The work culture of the factory is, and has always been, far more complex and dynamic than an organizational chart would imply. Although factory work frequently included operations done by hand and processes that did not require any motive power, all true factories used some power-driven machinery. Mechanization was a key element in the development of the factory system. Additionally, the owners of many factories followed the principle of uniformity, aiming to make standardized products from parts that were, to some degree, interchangeable. The first American factories, as we have seen in Chapter 8, were textile mills; but soon after Americans began to make yarn in places like the Slater Mill, they were also shifting the manufacture of products such as clocks, firearms, and edge tools from craft shops to factories. In the 1790s, Samuel Slater’s youthful operatives tended a sequence of special-purpose machines powered by a waterwheel.
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"Artificial Intelligence in Practice." In Advancing Skill Development for Business Managers in Industry 4.0. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-2036-9.ch005.

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In this chapter, the authors discuss machine learning techniques and artificial intelligence applications, their role in business, and present a practical application of it. They try to highlight how important machine learning can be in data-driven organisations, where the cost and/or the advantages to implement such tools are far greater than having a human—or a team of humans—doing it.
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Garegae, Kgomotso G. "Experiencing the Functionality of Mathematical Indigenous ICTs on Community Development." In Cases on Progressions and Challenges in ICT Utilization for Citizen-Centric Governance. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2071-1.ch012.

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The use of Information Communication Technologies (ICTs) in agriculture is fundamental to rural development especially in the 21st century (Rashid, et al., 2007). This chapter thus illustrates the use of an indigenous technology using the case of Madila production in a Dairy House Farm at Molapowabojang, a rural village in Southern District of Botswana. The Dairy House Farm started production in 2002 with the aim of producing both fresh and sour or curdled milk (Madila). Although traditionally madila was for subsistence family consumption, the use of community-compatible ICT, namely, sieve like plastic bag, natural sun beam and cooling system made from a wooden shelter, combined with modern machines such as milking machines (milk tubes attached to the cow’s udder) have enabled the Dintwa family to convert the practice into commercial industry.
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Asogwa, Benjamin Chijioke, Joseph Chinedu Umeh, and Simon Terhemba Penda. "Evaluating Gains of Friendly Policy Environment in India." In Advances in Electronic Government, Digital Divide, and Regional Development. IGI Global, 2014. http://dx.doi.org/10.4018/978-1-4666-4639-1.ch017.

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The purpose of this chapter is to evaluate the gains of friendly policy environment in the cassava sub-sector among cassava farmers in Nigeria using farm-level data collected from randomly sampled 360 cassava farmers in Benue State. The study showed that the policy intervention, which opened up a lot of marketing opportunities for increased income in the cassava industry, encouraged the cassava farmers to diversify into value addition in their cassava business for increased income generation. It also encouraged increased adoption of improved processing machines/equipment at the farm level and increased accessibility to markets. Policies that would guarantee provision of adequate modern production resources to the cassava farmers are strongly advocated. Policies that would ensure that adequate farm and market information are made available to the rural farmers to make them abreast of current agricultural innovations and have access to much better market opportunities should be sufficiently reinforced.
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Wilshire, Howard G., Richard W. Hazlett, and Jane E. Nielson. "Harvesting the Future." In The American West at Risk. Oxford University Press, 2008. http://dx.doi.org/10.1093/oso/9780195142051.003.0007.

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For most of two centuries, the United States was a nation of small farms and many farmers, raising much of their own food along with one or more cash crops and livestock for local markets. Today, farms run by families of weatherbeaten farmers, pie-baking farm wives, and earnest 4-H offspring are disappearing. Americans live on supermarket or take-out food, mostly produced on extensive, highly mechanized and chemical-dependent industrial-scale “conventional” farms, raising single-crop monocultures or single-breed livestock. The larger farms cover tens of thousands of acres, too much for single families to manage. It is not agriculture, but agribusiness— an industry run by corporations. Conventional industrial agriculture is highly productive, and supermarket food is cheap. So why should anyone worry about growing food with chemical fertilizers, expensive equipment, pesticides, and pharmaceuticals? The reasons, acknowledged even by the industry, are that agribusiness “saddles the farmer with debt, threatens his health, erodes his soil and destroys its fertility, pollutes the ground water and compromises the safety of the food we eat.” Croplands presently encompass some 57 million acres in the 11 western states (table 2.1). Giant plantations consume huge amounts of natural resources—soil, fertilizers, fuels, and water. Synthetic fertilizers keep overused soils in production, until they become too salty (salinated) and must be abandoned. Industrial farming has taken over large areas of wildlife habitat, including forest, scrub, desert, or prairie, to replace degraded croplands. The clearings and massive pesticide applications threaten or endanger large and increasing numbers of plant and animal species in the western United States. Pesticide exposures sicken family farmers and agribusiness workers in the fields, and add environmental poisons to our diet. Pesticides and other problematic agricultural chemicals accumulate in our bodies. Agribusiness consumes especially huge amounts of increasingly costly, nonrenewable petroleum. “Every single calorie we eat is backed by at least a calorie of oil, more like ten” to run fleets of immense plowing, planting, cultivating, harvesting, and processing machines, plus countless irrigation pumps. Growing a pound of American beef consumes half a gallon of petroleum. A top executive of the giant agriculture-chemical corporation Monsanto has admitted that “current agricultural technology is not sustainable.” High-tech agriculture, such as cloning and genetically modifying crops, does not help conventional agriculture become more sustainable.
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Conference papers on the topic "Farm machinery industry"

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Olson, G. M., and R. R. Johnson. "The Impact of Conservation Tillage on Farm Machinery Design." In 37th Annual Earthmoving Industry Conference. SAE International, 1986. http://dx.doi.org/10.4271/860742.

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Wang, Li, and Dinh-Nhon Truong. "Stability improvement of a DFIG-based offshore wind farm fed to a multi-machine power system using a static VAR compensator." In 2012 IEEE Industry Applications Society Annual Meeting. IEEE, 2012. http://dx.doi.org/10.1109/ias.2012.6374094.

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Chang, Zhiyong, Zezhong C. Chen, Jie Zhao, and Dinghua Zhang. "A Generic Approach to Modeling Geometry of Un-Deformed Chip by Mathematical Representing Envelopes of Swept Cutter in Five-Axis CNC Milling." In ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/detc2014-34135.

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To pursue high performance 5-axis CNC milling in industry, it is crucial to simulate each specific mill process in high fidelity beforehand, which should model the machined surfaces and predict the cutting forces in the process planning. However, the kernel technique, representation of the un-deformed chip geometry removed by cutter in 5-axis milling, is far from mature. Aiming to solve the problem, this paper presents a generic approach to representing un-deformed chip geometry mathematically in 5-axis CNC milling. The unique features of this research are: (1) the machine tool kinematics chain is investigated and a 5-axis CNC interpolation algorithm is adopted to establish the tool kinematics model, and (2) the closed-form equation of the un-deformed chip geometry representation is derived based on the machined shape being the envelope of a group of ellipses. This approach can model a machined surface with high accuracy and efficiently, and can be used to evaluate the machine surface quality and machining parameters. It can greatly promote the technique of high performance 5-axis CNC milling.
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Taherimoghaddam, Mahdi, and Halat Binaie. "Pre-Delivery Testing of Centrifugal Compressors Within the Petroleum Industry: A User’s View." In ASME 2004 International Mechanical Engineering Congress and Exposition. ASMEDC, 2004. http://dx.doi.org/10.1115/imece2004-59050.

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In oil and gas applications where centrifugal compressors play a central role, their availability is essential for continued production; typically the loss of a day’s revenue can far exceed the capital value of the machine. Performing more rigorous inspection and testing prior to accepting delivery of centrifugal compressors can reveal a fairly large percentage of mechanical and performance failures. This paper is devoted to illustrate the crucial importance of centrifugal compressors testing within the petroleum industry with a special attention to the performance test and complete-unit test.
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Peeters, Cédric, Timothy Verstraeten, Ann Nowé, Pieter-Jan Daems, and Jan Helsen. "Advanced Vibration Signal Processing Using Edge Computing to Monitor Wind Turbine Drivetrains." In ASME 2019 2nd International Offshore Wind Technical Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/iowtc2019-7622.

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Abstract This paper illustrates an integrated monitoring approach for wind turbines exploiting this Industry 4.0 context. Our combined edge-cloud processing approach is documented. We show edge processing of vibration data captured on a wind turbine gearbox to extract diagnostic features. Focus is on statistical indicators. Real-life signals collected on an offshore turbine are used to illustrate the concept of local processing. The NVIDIA Jet-son platform serves as edge computation medium. Furthermore, we show an integrated failure detection and fault severity assessment at the cloud level. Health assessment and fault localization combines state-of-the-art vibration signal processing on high frequency data (10kHz and higher) with machine learning models to allow anomaly detection for each processing pipeline. Again this is illustrated using data from an offshore wind farm. Additionally, the fact that data of similar wind turbines in the farm is collected allows for exploiting system similarity over the fleet.
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Ruszkiewicz, Brandt J., Christopher Scriva, Zachary C. Reese, Chetan P. Nikhare, John T. Roth, and Ihab Ragai. "Direct Electric Current Spot Treatment’s Effect on Springback of 90 Degree Bent 2024-T3 Aluminum." In ASME 2015 International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/msec2015-9433.

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One of the largest issues for sheet metal forming techniques such as stamping and incremental forming is springback. Springback is the elastic recovery of a material after it has been formed resulting in distorted part geometries. Springback can be compensated for during the forming process, however, this often requires forming the metal further than the desired shape. Unfortunately, if a formed part is designed such that it is close to its forming limit, compensation could push the material too far and cause fracture. It has been shown that by pulsing electric current throughout an entire workpiece during forming, springback can be greatly reduced and sometimes eliminated. This paper examines the effect of pulsing direct electric current, through localized points of a workpiece after it has been deformed into a 90-degree bend, but prior to the reversal of the bending die (i.e., while the part is still constrained). It was found that, with a high current density for a short amount of time, springback could be greatly reduced without the need to run a larger current through the entire workpiece. The largest springback reduction was seen when the electric current was forced to flow across the bend in the specimen. This finding is advantageous for industry as it will allow springback reduction in large parts that would normally require much larger power sources to generate the correct current density, if current is run through the entire part. A potential barrier between industry and this technology is that machines would need to be either created or modified to apply electric current at known places at a specific current density and time. To modify an existing machine may be difficult because the machine would need to be insulated from the electric current.
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7

Taylor, J. V., B. Conduit, A. Dickens, C. Hall, M. Hillel, and R. J. Miller. "Predicting the Operability of Damaged Compressors Using Machine Learning." In ASME Turbo Expo 2019: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/gt2019-91339.

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Abstract The application of machine learning to aerospace problems faces a particular challenge. For successful learning a large amount of good quality training data is required, typically tens of thousands of cases. However, due to the time and cost of experimental aerospace testing, this data is scarce. This paper shows that successful learning is possible with two novel techniques: The first technique is rapid testing. Over the last five years the Whittle Laboratory has developed a capability where rebuild and test times of a compressor stage now take 15 minutes instead of weeks. The second technique is to base machine learning on physical parameters, derived from engineering wisdom developed in industry over many decades. The method is applied to the important industry problem of predicting the effect of blade damage on compressor operability. The current approach has high uncertainty, it is based on human judgement and correlation of a handful of experimental test cases. It is shown using 100 training cases and 25 test cases that the new method is able to predict the operability of damaged compressor stages with an accuracy of 2% in a 95% confidence interval; far better than is possible by even the most experienced compressor designers. Use of the method is also shown to generate new physical understanding, previously unknown by any of the experts involved in this work. Using this method in the future offers an exciting opportunity to generate understanding of previously intractable problems in aerospace.
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8

Sodemann, A., Y. Li, J. Lee, et al. "Data-Driven Surge Map Modeling for Centrifugal Air Compressors." In ASME 2006 International Mechanical Engineering Congress and Exposition. ASMEDC, 2006. http://dx.doi.org/10.1115/imece2006-13103.

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Surge is a phenomenon of large oscillations of pressure and flow that occurs in dynamic compressors when the compressor is operated at too low a flow rate for a given discharge pressure. In order to prevent damage to the compressor, surge must be avoided. A typical surge prevention measure for compressor operation is so-called surge avoidance control, which normally relies on a map of the operating conditions for surge occurrence, i.e. surge map or surge line. The surge map currently used in industry practice is insufficient since surge occurrence is affected by many more process variables, especially ambient air conditions. If large uncertainty exists in surge conditions, the compressor has to be operated conservatively far away from the surge line, which limits the dynamic range and usually sacrifices the efficiency. In order to obtain more accurate surge map adaptively, a data-driven surge map modeling approach has been developed using support vector machine (SVM) approach based on surge test data. Surge map is obtained as the classification surface between surge and not-surge data. Principal components analysis (PCA) is used to identify the variables that contribute most to surge. The method of asymmetric support vector machines (ASVM) is developed to reduce the possibilities of missed surge prediction. The developed methodology was verified with the actual testing data on the centrifugal air compressor in Toyota Motors.
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9

Falode, Olugbenga, and Christopher Udomboso. "Efficient Crude Oil Pricing Using a Machine Learning Approach." In SPE Nigeria Annual International Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/207152-ms.

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Abstract Crude oil, a base for more than 6000 products that we use on a daily basis, accounts for 33% of global energy consumption. However, the outbreak and transmission of COVID-19 had significant implications for the entire value chain in the oil industry. The price crash and the fluctuations in price is known to have far reaching effect on global economies, with Nigeria hard. It has therefore become imperative to develop a tool for forecasting the price of crude oil in order to minimise the risks associated with volatility in oil prices and also be able to do proper planning. Hence, this article proposed a hybrid forecasting model involving a classical and machine learning techniques – autoregressive neural network, in determining the prices of crude oil. The monthly data used were obtained from the Central Bank of Nigeria website, spanning January 2006 to October 2020. Statistical efficiency was computed for the hybrid, and the models from which the proposed hybrid was built, using the percent relative efficiency. Analyses showed that the efficiency of the hybrid model, at 20 and 100 hidden neurons, was higher than that of the individual models, the latter being the best performing. The study recommends urgent diversification of the economy in order not for the nation to be plunged into a seemingly unending recession.
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Perez-Diaz, J. L., I. Valiente-Blanco, E. Diez-Jimenez, et al. "Contactless Superconducting Magnetic Instrument for Precise Positioning in Cryogenic Environments." In ASME 2013 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/imece2013-63742.

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There is an increasing demand of nanotechnology and nano-devices in microelectronics, optics, biomedical and precision engineering industries. In this context, a wide range of applications require micrometer/nanometer positioning within a long range. Ultra precision manufacturing and inspection systems in micro-automating semiconductor fabrication, nanopositioning and nanomeasuring machines (NPM-Machine), development of MEMS and NEMS, copying machines, stepper stages for photolithography, small-scale measuring machines (CMMs) for large area scanning or surface imaging in scanning probe microscopy (SPM) are a few examples of these applications. In some applications, cryogenic environments (temperatures below 120 K) are a desirable or mandatory condition. The sensitivity of a large number of sensors is greatly increased when they are at cryogenics temperatures, like for example, those required for far infrared interferometer spectroscopy. The operating conditions in these environments include very low temperatures but also high vacuum. In this context, it is challenging for mechanisms to overcome all the tribological problems associated with these conditions. In addition very low energy consumption is also desirable in cryogenic environments. The invention here presented is a contactless linear slider that gets benefit of superconducting magnetic levitation to obtain a nanometer resolution within a long stroke (∼ 15 mm), minimizing run-outs of the slider (in the micron scale). Moreover, due to self-stable levitation and guidance of the slider, the complexity of the control is significantly reduced and the power consumption minimized (of the order of mW). The linear slider can be divided in two subsystems: the guidance system and the actuating system. The guidance system is composed of a static guideline, made of two superconducting disks and a slider composed of a long permanent magnet. Due to the high translational symmetry of the magnetic field generated by the PM, a contactless sliding kinematic pair is established between the PM and the superconductors in the sliding DoF. Thus, the slider is able to be moved in the sliding direction with very low resistance. However, greater restoring forces appear if the PM is moved in any other direction. Due to the lack of contact between the moving parts is also suitable for operation in clean-room applications, like in semiconductor manufacturing industry. Ultimately, the device was designed, built and tested in a relevant cryogenic environment (15 K and high vacuum) and the results introduced and discussed.
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