scholarly journals Analisis Mutu Proses Produksi Kertas Dupleks dengan Mempertimbangkan Waktu Kerusakan untuk Meminimumkan Biaya Cacat

2019 ◽  
Vol 9 (02) ◽  
pp. 87
Author(s):  
Asti Widayanti ◽  
Ike Rostika
Keyword(s):  
Process Control ◽  
Production Process ◽  
Statistical Process Control ◽  
Power Law ◽  
Failure Time ◽  
Coating Process ◽  
Paper Machine ◽  
Statistical Process ◽  
Maintenance Time

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.

scholarly journals Statistical Process Control in Automotive Industry

2013 ◽  
Vol 16 (2) ◽  
pp. 39-42
Author(s):  
Maroš Korenko ◽  
Pavol Kaplik ◽  
Marian Bujna ◽  
Miroslav Pristavka
Keyword(s):  
Process Control ◽  
Production Process ◽  
Statistical Process Control ◽  
Statistical Methods ◽  
Automotive Industry ◽  
Statistical Process ◽  
Quality Of Products

Abstract Organisations active in the market, regardless of the sphere of action, must constantly face pressures from an uncompromising competition. Therefore, if organisations wish to be successful in the market and constantly move forward, they must draw attention to the quality of products in the market. Statistical process control is the implementation of such statistical methods through which the production process is regulated and controlled to ensure the production of the highest possible amount of products that comply with requirements imposed on them.

scholarly journals Use of quality tools to evaluate forest seedlings production in the nursery stage

2021 ◽  
Vol 8 (2) ◽  
pp. 1425-1432
Author(s):  
Rafael Eloy de Souza ◽  
Alfredo José dos Santos Junior ◽  
Alan Henrique Marques de Abreu ◽  
Natália Dias de Souza ◽  
Ananias Francisco Dias Júnior
Keyword(s):  
Process Control ◽  
Root Growth ◽  
Production Process ◽  
Statistical Process Control ◽  
Production System ◽  
Statistical Process ◽  
Production Processes ◽  
Definition Of ◽  
Quality Tools

The control of production processes can assist in the standardization of variability, reducing waste, and improving the quality of a service or product. Thus, this study aimed to analyze the non-conformities in a production system of forest seedlings from Atlantic Forest aiming at the standardization of the production system and adjustments for field cultivation. The definition of the attributes was made through a technical visit to the forestry nursery to know the location and the production process of the seedlings. For the process evaluation, statistical process control tools were used. The non-conformities analyzed were: coiled root growth, disintegrated substrates of plants, presence of roots fixed to the ground, presence of phytopathogen attack symptoms and/or herbivory and symptoms of nutritional deficiency. In general, variability was detected in the production process, compromising the success in planting the seedlings in the field, as well as their quality.

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

2022 ◽  
Vol 26 (3) ◽  
pp. 226-235
Author(s):  
Gabriel G. Zimmermann ◽  
Samir P. Jasper ◽  
Daniel Savi ◽  
Leonardo L. Kmiecik ◽  
Lauro Strapasson Neto ◽  
...  
Keyword(s):  
Angular Velocity ◽  
Process Control ◽  
Statistical Process Control ◽  
Industrial Process ◽  
Descriptive Statistics ◽  
Flow Data ◽  
Statistical Process ◽  
Flow Rates ◽  
Angular Velocities

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.

scholarly journals KONSEP DAN TEKNIK MANAIEMEN MUTU TERPADU

2017 ◽  
pp. 94-101
Author(s):  
Saut Pruba
Keyword(s):  
Process Control ◽  
Statistical Process Control ◽  
Continuous Improvement ◽  
Six Sigma ◽  
Employee Empowerment ◽  
Just In Time ◽  
Statistical Process

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.

QUALIDADE NA COLHEITA MECANIZADA DE MILHO SEMEADO EM DIFERENTES VELOCIDADES

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 ◽  
...  
Keyword(s):  
Process Control ◽  
Statistical Process Control ◽  
Plant Density ◽  
Plant Population ◽  
Longitudinal Distribution ◽  
Statistical Control ◽  
Individual Values ◽  
Sowing Time ◽  
Statistical Process

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.

Sign in / Sign up

Export Citation Format

Share Document