Efficient slop oil processing plant

2019 ◽  
Vol 56 (1) ◽  
pp. 14-15
2020 ◽  
Vol 124 ◽  
pp. 104590 ◽  
Author(s):  
Panagiotis K. Marhavilas ◽  
Michail Filippidis ◽  
Georgios K. Koulinas ◽  
Dimitrios E. Koulouriotis

2018 ◽  
Vol 28 ◽  
pp. 01012 ◽  
Author(s):  
Bartosz Szulczyński ◽  
Tomasz Dymerski ◽  
Jacek Gębicki ◽  
Jacek Namieśnik

The paper describes an operation principle of odour nuisance monitoring network in a city agglomeration. Moreover, it presents the results of investigation on ambient air quality with respect to odour obtained during six-month period. The investigation was carried out using a network comprised of six prototypes of electronic nose and Nasal Ranger field olfactometers employed as a reference method. The monitoring network consisted of two measurement stations localized in a vicinity of crude oil processing plant and four stations localized near the main emitters of volatile odorous compounds such as sewage treatment plant, municipal landfill, phosphatic fertilizer production plant. The electronic nose prototype was equipped with a set of six semiconductor sensors by FIGARO Co. and one PID-type sensor. The field olfactometers were utilized for determination of mean concentration of odorants and for calibration of the electronic nose prototypes in order to provide their proper operation. Mean monthly values of odour concentration depended on the site of measurement and on meteorological parameters. They were within 0 – 6.0 ou/m3 range. Performed investigations revealed the possibility of electronic nose instrument application as a tool for monitoring of odour nuisance.


2020 ◽  
Vol 8 (6) ◽  
pp. 4966-4972

The aim of the present paper is to analysis the reliability of the system by using CAS Mathematica and also, it’s comparative study with CAS Maxima. The butter oil manufacturing plant consists of seven units i.e. separator, pasteurizer, continuous butter making, melting vats, butter oil clarifier, packaging and standby state. Model is developed by using Markov birth-death process. The first order differential equations are derived by using model and then solved for comparative study of reliability to give accuracy in result. By using Mathematica, we calculate probability of each state, which is beneficial to plant owners because better accuracy in result enhance reliability of the plant Graphs are plotted and tables are developed with the help of CAS Mathematica and Maxima, graphs show the variation and tables shows the fluctuations in reliability in comparative manner.


Processes ◽  
2019 ◽  
Vol 7 (7) ◽  
pp. 436
Author(s):  
Nayher Clavijo ◽  
Afrânio Melo ◽  
Maurício M. Câmara ◽  
Thiago Feital ◽  
Thiago K. Anzai ◽  
...  

Predictive analytics is usually cited as one of the most important pillars of the digital transformation. For the oil industry, specifically, it is a common belief that issues like integrity and maintenance could benefit from predictive analytics. This paper presents the development and the application of a process-monitoring tool in a real process facility. The PMA (Predictive Maintenance Application) system is a data-driven application that uses a multivariate analysis in order to predict the system behavior. Results show that the use of a multivariate approach for process monitoring could not only detect an early failure at a metering system days before the operation crew, but could also successfully identify, among hundreds of variables, the root cause of the abnormal situation. By applying such an approach, a better performance of the monitored equipment is expected, decreasing its downtime.


2020 ◽  
Vol 10 (2) ◽  
pp. 95-103
Author(s):  
Agung Ikhssani

Identification of potential hazards is the basis of modern occupational safety management and hazards can threaten whenever and wherever including the agricultural sector. To develop the economic strength of the agricultural sector, it is necessary to increase productivity. One way that can be done is to increase employee productivity through the Employee Safety and Health program. The purpose of this study was to determine the potential physical hazards in the PPKS PTPN VII Bekri Business Unit. This type of research is interviews and observations that aim to find an overview of the assessment of physical potential hazards in the palm oil processing PT. Perkebunan Nusantara VII Bekri business unit. The physical potential hazards found in the Palm Oil Processing Plant (PPKS) are the potential hazards of noise generated by machines> 85dB, hot working climate inside the factory, vibrations from the processing process, and improper lighting in the factory. Physical potential hazards contained in the PPKS unit are auditory and non-auditory disturbances on the dangers posed by noise, headaches and dehydration as well as attacks that can arise due to heat, discomfort due to inappropriate lighting resulting in potential work accidents and the appearance of musculoskeletal disorders due to a potential vibration hazard


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