Study on Indian Sugar Industry & Estimation of the Production of Sugarcane & White Sugar in the Country Using SPSS Through Cobb Douglas Model

2012 ◽  
Author(s):  
Gaurav Kalra
Keyword(s):  
Sugar Industry ◽  
White Sugar

Floc in acidified solutions of white sugar – a literature review

2012 ◽  
pp. 449-453 ◽  
Author(s):  
Jan Iciek ◽  
Ilona Baszczyk ◽  
Joanna Biernasiak ◽  
Krystyna Lisik ◽  
Maciej Wojtczak
Keyword(s):  
Chemical Composition ◽  
Literature Review ◽  
Sugar Beet ◽  
Microbial Activity ◽  
Sugar Industry ◽  
Raw Material ◽  
Direct Impact ◽  
Microbial Biofilms ◽  
Current State ◽  
White Sugar

The main aim of this paper is to discuss the current state of knowledge on the chemical composition of floc isolated from acidified sugar solutions and explain the mechanism of its formation. The literature data shows that depending on the raw material used for the production of white sugar, i.e. sugar beet and sugarcane, the chemical composition of floc is different. The presence of polysaccharides i.e. dextran or levan in floc is a consequence of microbial activity. Therefore, it cannot be explicitly assumed that the origin of individual ingredients of floc is only the raw material, i.e. beets or sugarcane. Taking into account the literature data concerning the chemical composition of floc, it seems reasonable to link the direct impact of microbial biofilms present in sugar industry installations to the tendency of the final product to create floc. Currently, the basis for assessment of the proneness of sugar to create floc is the result of a 10-day test (ICUMSA Method GS2/3-40A). From the perspective of both producers and consumers of sugar, there is a need to develop and validate quick methods for assessing the tendency of sugar to create floc. This task is only possible to complete, when the mechanism of floc formation is fully explained.

scholarly journals DESAIN PELETAKAN PENYANGGA DAN EVALUASI TEGANGAN PADA SISTEM PERPIPAAN FLUIDA MASSECUITE DARI REHEATER MENUJU FEED MIXER

2020 ◽  
Vol 6 (1) ◽  
pp. 39
Author(s):  
Pekik Mahardhika
Keyword(s):  
Sugar Industry ◽  
Domestic Market ◽  
White Crystal ◽  
Line Pipe ◽  
Stress Evaluation ◽  
Process Piping ◽  
White Sugar

The sugar industry is a very important industry in Indonesia to meet the needs of the domestic market. One of the products of the sugar company is white crystal sugar. In the process of producing white sugar there is a fluid called Massecuite. Massecuite is a mixture of fluid crystals of sugar and water. Massecuite can cause sedimentations and blockages in the pipeline from the heater to the feed mixer. The line pipe from the reheater to the feed mixer has been redesigned. But the line pipe has not been designed for laying penyangga and evaluate piping stress. So that the line pipe needs to be designed for laying penyangga and evaluate piping stress. Evaluation of piping stress accordance to ASME B31.3 Process Piping. This evaluation aims to ensure that the line pipe design comply with ASME B31.3 requirements. The evaluation results evidence that the stress in the line pipe from the reheater to the feed mixer still meets the ASME B31.3 criteria. The line pipe design from the reheater to the feed mixer can be declared safe.

Preventive maintenance optimization of sugarcane harvester machine based on FT-Bayesian network reliability

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Fatemeh Afsharnia ◽  
Afshin Marzban ◽  
Mohammadamin Asoodar ◽  
Abas Abdeshahi
Keyword(s):  
Bayesian Network ◽  
Preventive Maintenance ◽  
Sugar Industry ◽  
Maintenance Scheduling ◽  
Sugar Production ◽  
Content Type ◽  
Machine Reliability ◽  
Sugarcane Harvester ◽  
White Sugar ◽  
Production Losses

PurposeThe purpose of this paper is to optimize the preventive maintenance based on fault tree (FT)–Bayesian network (BN) reliability for sugarcane harvester machine as a fundamental machine in the sugar industry that must be operated failure-free during a given period of the harvesting process.Design/methodology/approachTo determine machine reliability using the algorithm developed based on mapping FTs into BNs, the common failures of 168 machines were carefully investigated over 12 years (2007–2019). This algorithm was then used to predict the harvester reliability, estimate delays by machine downtimes and their consequences on white sugar production losses that can be reduced by optimizing the preventive maintenance scheduling.FindingsThe optimization of preventive maintenance scheduling based on estimated reliability of sugarcane harvester machines using FT–BNs can reduce white sugar production losses, the operation-stopping breakdowns and the downtime costs as a crisis that the sugar industry is facing.Practical implicationsMachine reliability gradually decreased by 31.08% approximately, which resulted in a working time loss of 26% in the 2018–19 harvesting season. In total, the white sugar losses were estimated as 204.17 tons for burnt canes and 114.53 tons for green canes. The losses of the 2018–19 harvesting season have been 11.85 times greater than the first harvesting season. The proposed maintenance interval for critical subsystems including the hydraulic, chopper and base cutter were obtained as 1.815, 1.12 and 1.05 h, respectively.Originality/valueIn this study, a new approach was used to optimize preventive maintenance to reduce delays and their implications upon costs in time, inconvenience and white sugar losses. The FT–BNs algorithm was found a useful tool that was over-fitting of failure occurrence probabilities data for sugarcane harvester machine.

Sign in / Sign up

Export Citation Format

Share Document