scholarly journals Fertilizer deposition as a function of angular velocity and inclination of the helical dosing mechanism

Author(s):  
Gabriel G. Zimmermann ◽  
Samir P. Jasper ◽  
Daniel Savi ◽  
Leonardo L. Kmiecik ◽  
Lauro Strapasson Neto ◽  
...  

ABSTRACT The establishment of grain crops in Brazil is an important industrial process in the agricultural chain, requiring the correct deposition of granular fertilizer over the sowing furrow and more efficient, precise, and sustainable assessments in the operation, which can be achieved with the statistical process control. This study aimed to assess the effect of the angular velocity on different inclinations of the helical metering mechanism on the granular fertilizer deposition. An automated electronic bench was used to assess the deposition quality of granular fertilizers considering different angular velocities (1.11, 1.94, and 2.77 m s-1) and longitudinal and transverse inclinations (+15, +7.5, 0, −7.5, and −15°), with the helical doser by overflow. Flow data were collected and submitted to descriptive statistics and statistical process control. The metering mechanism showed expected variations, with acceptable performance under process control. The values of the flow rates of the granular fertilizer increased as velocity increased, standing out longitudinal inclinations of +7.5 and +15°, providing higher fertilizer depositions.

2017 ◽  
pp. 94-101
Author(s):  
Saut Pruba

Quality is a term that has diflferent meanings to different people. Quality set out in this paper are the features and characteristics of the total of a product or service associated with its ability to satisfij the needs of the visible or disguised. The quality of the environment requires an establishment of TQM because quality can not be examined only in a product. In this paper also discussed the concept of the seven TQM: continuous improvement, Six Sigma, employee empowerment, benchmarking, just in time, the concept of Taguchi TQM techniques and knowledge. TQM is the seventh technique check sheet, scatter diagrams, cause-effect diagrams, Pareto charts, flow charts, histograms, and statistical process control.


2016 ◽  
Vol 15 (3) ◽  
pp. 582 ◽  
Author(s):  
ANTONIO TASSIO SANTANA ORMOND ◽  
MURILO APARECIDO VOLTARELLI ◽  
CARLA SEGATTO STRINI PAIXÃO ◽  
ALINE SPAGGIARI ALCÂNTARA1 ◽  
ELIZABETH HARUNA KAZAMA ◽  
...  

RESUMO - As perdas na colheita podem estar relacionadas tanto a colhedora, como também a fatores ligados a cultura como: mau preparo do solo, densidade de plantas, inadequação da época de semeadura são alguns deles. O presente estudo objetivou determinar a influência da velocidade de semeadura no processo de colheita mecanizada de milho, por meio do controle de qualidade do processo. O experimento foi conduzido em Latossolo Vermelho, textura argilosa e relevo suave ondulado. O delineamento foi baseado na óptica do Controle Estatístico de ProcessoCEP, onde os dados foram coletados em pontos aleatórios em função do tempo. Os indicadores de qualidade avaliados foram divididos em parâmetros de semeadura (população de plantas e distribuição longitudinal de plântulas); e de colheita (Perdas de grãos e distribuição de palha) em função de seis velocidades de deslocamento (aproximadamente 2,0; 4,0; 6,0; 9,0; 10,0 e 12,0 Km.h-1). Os dados foram submetidos a análise descritiva para análise do comportamento. Como ferramentas do controle estatístico de processo utilizou-se, run charts ou gráfico sequencial e carta de controle de valores individuais para análise da qualidade do processo. A maior velocidade (V6) apresentou a maior variabilidade dos dados para todas as variáveis. A operação da colheita mecanizada de milho foi influenciada por fatores extrínsecos e intrínsecos a ela.Palavras-chave: Controle estatístico de processo, espaçamentos normais, perdas, população de plantas.QUALITY IN MECHANIZED HARVEST OF CORN SOWN IN DIFFERENT SPEEDSABSTRACT - The harvest losses may be associated to harvester as well as factors related to cultivation such as poor soil preparation, plant density, unsuitable sowing time. This study aimed to determine the effect of speed sowing in the mechanized harvest of corn, through the control of the quality of the process. The experiment was conducted in a clayey Oxisol and undulate relief. The design was based on the optics of the Statistical Process Control SPC, and the data were collected at random points in function of time. The quality indicators evaluated were divided into sowing parameters (plant population and longitudinal distribution of seedlings) and harvesting (loss of grain and straw distribution) in function of six displacement speeds (approximately 2.0, 4.0, 6.0, 9.0, 10.0 and 12.0 Km.h-1). The data were submitted to descriptive analysis for behavior analysis. As tools for the statistical control of the process, run charts or sequential graph were used, and control chart of individual values for analysis of the quality of the process. The highest speed (V6) showed the highest variability of the data for all variables. The operation of mechanized harvest of corn was influenced by extrinsic and intrinsic factors.Keywords: statistical process control, normal spacings, losses, plant population.


Author(s):  
Ho Hwi Chie ◽  
Januar Nasution ◽  
Ketut Gita Ayu ◽  
Nike Septivani ◽  
Yualfin Renaldi

PT. XYZ is a company engaged in manufacturing porcelain dinner ware such as plates, cups, teapot, bowl, etc Porcelain product is safe for use and product defect will only affect the aesthetic not the functional side. The company always maintain the quality of the products produced as by maintaining a good product, in terms of visuals, will keep customers interested in the product. Good quality products characterized by quality A / B and C, and the product defect characterized by the quality of D, Lost, and BU. Concepts and methods used to analyze is a statistical process control (SPC) which includes Pareto diagram, fraction nonconformities, flow charts and fishbone diagrams and management tools (fault tree analysis). Statistical Process Control (SPC) is one of the methods, which includes Pareto charts, fraction nonconformities, flow chart, and fishbone diagram and also management tools (fault tree analysis). SPC is useful to find the facts from the problems and factors that affect the quality of the products, while fault tree analysis is useful to analyze each of the production process.


Author(s):  
Rizaldi Sardani ◽  
Devi Faradila ◽  
Suci Oktri Viarani M ◽  
Eko Supriadi

Quality is a benchmark to determine the level of good and bad of a product. The level of quality of a product will affect customer satisfaction, hence, to produce high quality products, it is necessary for a company to have a quality control process. Quality control is a process that aims to maintain the quality of products and services that have been promised to consumers. In this study, quality control is carried out in the sugar packaging process. Where in the sugar packaging process found the resulting product has a poor quality, defective and not in accordance with specifications. This study uses the Statistical Process Control (SPC) method which aims to determine the causes of defective products with the intention that the packaging process can further minimize the level of product defects. The SPC method is a statistical analysis technique with seven statistical tools or seven tools. Based on the results of the study it can be seen that the cause of product damage / defects in the product packaging process is caused by three types of damage namely damage due to conveyor (38.17%), damage due to machine pinched (35.82%), and damage due to loose seams (26,00%) This type of damage can be caused by human error and other factors such as engine condition, engine cleanliness and the monitoring process. Proposed improvements recommended for the company are to provide training to employees, make clear work instructions, conduct periodic maintenance for the machines used, supervise all work areas, and carry out quality control for every acceptance of raw materials.


2019 ◽  
Vol 9 (02) ◽  
pp. 87
Author(s):  
Asti Widayanti ◽  
Ike Rostika

Penelitian ini menganalisis kualitas proses produksi kertas dupleks yang diproduksi PT.X paper mill dan menentukan waktu pemeliharaan optimum yang meminimumkan biaya cacat, dengan identifikasi proses produksi dominan penyebab cacat menggunakan Statistical Process Control (SPC). Tahapan yang paling dominan dalam terjadinya cacat pada proses produksi kertas dupleks paper machine 3 adalah proses coating yang mengakibatkan kerugian bagi perusahaan sebesar 32,96% atau Rp893.140.000,00. Cacat pada proses coating disebabkan faktor bahan, mesin, operator dan pengukuran pengujian, denganfaktor mesin berkontribusi terbesar yaitu 81,50%. Waktu antar kerusakan pada proses coating memiliki model proses posson non homogen model power law dengan rata-rata 4 jam. Waktu pemeliharaan pencegahan optimum mesin coating adalah setelah mesin beroperasi 199,32 jam dengan resiko biaya Rp13.719.929,00. Resiko biaya ini senilai Rp602.983.033,00 setahun atau mengurangi biaya cacat pada proses coating Rp290.156.967,00.  Analysis Quality of Production Process Duplex Paper by Considering Failure Time to Minimize Failure CostAbstractThis research analyzing the quality of the PT. X duplex paper production process and determine the optimum maintenance time that can minimize failure cost, through identification of the dominant production process that causes defects by using the Statistical Process Control (SPC). Coating process are the most dominant stages in the occurrence of defects in the duplex paper machine 3, which resulted in a loss for the company of 32.96% or Rp893,140,000.00. Defects in the coating process are caused by material, machine, operator and test measurements, with machine factor as the largest contributor by 81.50%. The time between failure in the coating process have non-homogeneous posson process, power law model with a mean time of 4 hours. The optimum preventative maintenance time for a coating machine is after a 199.32 hour operation with a risk of Rp13,719,929.00. This cost risk is Rp602,983,033.00 a year or reduce the defects cost in the coating process by Rp290,156,967.00.


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