Understanding correlations between raw materials inputs
Autor(a) principal: | |
---|---|
Data de Publicação: | 2017 |
Outros Autores: | , , , , |
Tipo de documento: | Relatório |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10174/26618 |
Resumo: | Prio Biocombustveis is a company that has a biodiesel plant in Porto de Aveiro. The production capacity of this plant is 113 880 ton/year. The plant has one lab to control the Biodiesel and Raw Materials quality. Every day Prio improves its process to assure the production of the best world-class biodiesel that any costumer can buy. Prio’s raw materials include several types of oils used in different percentages in the production process. Oils quality has the denomination of characteristic X, which varies with the different types of oils. Even in the same batch of the same oil it’s possible to observe quality oscillations. Oil’s neutralization is a dynamic process. The process recipe and operational parameters determine the final quality of the oil. All production shifts collect the operational parameters and analyze the quality in the lab for both intermediate and final oils. A diagram showing the main process operations is presented in Figure 1. The raw oil is heated to achieve the required process temperature and treated with acid and base using agitation. The produced soaps are separated from the Neutral Oil using centrifuges, which requires the control of several operational parameters. In neutralization process the main reaction is: Oil Mix (Raw Oil) + Base --> Neutral Oil + Soaps. The aim of this challenge is to understand correlations between raw materials inputs (in particular characteristic X) that define the recipe and highly influence the operational parameters that allow obtaining a high quality neutral oil (outputs). |
id |
RCAP_0a429723a5fe87436d3ccf6ec3fcee34 |
---|---|
oai_identifier_str |
oai:dspace.uevora.pt:10174/26618 |
network_acronym_str |
RCAP |
network_name_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository_id_str |
7160 |
spelling |
Understanding correlations between raw materials inputsBiodieselRaw oilsNeutralization processOperational parametersPrio Biocombustveis is a company that has a biodiesel plant in Porto de Aveiro. The production capacity of this plant is 113 880 ton/year. The plant has one lab to control the Biodiesel and Raw Materials quality. Every day Prio improves its process to assure the production of the best world-class biodiesel that any costumer can buy. Prio’s raw materials include several types of oils used in different percentages in the production process. Oils quality has the denomination of characteristic X, which varies with the different types of oils. Even in the same batch of the same oil it’s possible to observe quality oscillations. Oil’s neutralization is a dynamic process. The process recipe and operational parameters determine the final quality of the oil. All production shifts collect the operational parameters and analyze the quality in the lab for both intermediate and final oils. A diagram showing the main process operations is presented in Figure 1. The raw oil is heated to achieve the required process temperature and treated with acid and base using agitation. The produced soaps are separated from the Neutral Oil using centrifuges, which requires the control of several operational parameters. In neutralization process the main reaction is: Oil Mix (Raw Oil) + Base --> Neutral Oil + Soaps. The aim of this challenge is to understand correlations between raw materials inputs (in particular characteristic X) that define the recipe and highly influence the operational parameters that allow obtaining a high quality neutral oil (outputs).Mathematics in Industry, The MIIS Eprints Archive, Study Groups, European Study Group with Industry2020-01-24T12:00:28Z2020-01-242017-09-22T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/reporthttp://hdl.handle.net/10174/26618http://hdl.handle.net/10174/26618engReport on "Understanding correlations between raw materials inputs", Problem presented by Prio Biocombustíveis at the 127th European Study Group with Industry, University of Aveiro, Aveiro, Portugal, September 22, 2017http://www.maths-in-industry.org/miis/view/studygroups/esgi127.htmlhttp://esgi2017.web.ua.pt/challenges.htmlhttp://esgi2017.web.ua.pt/participants.htmlndndndndndnd336N/AAlvelos, HelenaAndrade, MarinaCorreia, JoaquimMaypaokha, GnordRenchin-Ochir, MijiddorjXiongshieng, Xaivanginfo:eu-repo/semantics/embargoedAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-01-03T19:21:23Zoai:dspace.uevora.pt:10174/26618Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T01:16:50.021865Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Understanding correlations between raw materials inputs |
title |
Understanding correlations between raw materials inputs |
spellingShingle |
Understanding correlations between raw materials inputs Alvelos, Helena Biodiesel Raw oils Neutralization process Operational parameters |
title_short |
Understanding correlations between raw materials inputs |
title_full |
Understanding correlations between raw materials inputs |
title_fullStr |
Understanding correlations between raw materials inputs |
title_full_unstemmed |
Understanding correlations between raw materials inputs |
title_sort |
Understanding correlations between raw materials inputs |
author |
Alvelos, Helena |
author_facet |
Alvelos, Helena Andrade, Marina Correia, Joaquim Maypaokha, Gnord Renchin-Ochir, Mijiddorj Xiongshieng, Xaivang |
author_role |
author |
author2 |
Andrade, Marina Correia, Joaquim Maypaokha, Gnord Renchin-Ochir, Mijiddorj Xiongshieng, Xaivang |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Alvelos, Helena Andrade, Marina Correia, Joaquim Maypaokha, Gnord Renchin-Ochir, Mijiddorj Xiongshieng, Xaivang |
dc.subject.por.fl_str_mv |
Biodiesel Raw oils Neutralization process Operational parameters |
topic |
Biodiesel Raw oils Neutralization process Operational parameters |
description |
Prio Biocombustveis is a company that has a biodiesel plant in Porto de Aveiro. The production capacity of this plant is 113 880 ton/year. The plant has one lab to control the Biodiesel and Raw Materials quality. Every day Prio improves its process to assure the production of the best world-class biodiesel that any costumer can buy. Prio’s raw materials include several types of oils used in different percentages in the production process. Oils quality has the denomination of characteristic X, which varies with the different types of oils. Even in the same batch of the same oil it’s possible to observe quality oscillations. Oil’s neutralization is a dynamic process. The process recipe and operational parameters determine the final quality of the oil. All production shifts collect the operational parameters and analyze the quality in the lab for both intermediate and final oils. A diagram showing the main process operations is presented in Figure 1. The raw oil is heated to achieve the required process temperature and treated with acid and base using agitation. The produced soaps are separated from the Neutral Oil using centrifuges, which requires the control of several operational parameters. In neutralization process the main reaction is: Oil Mix (Raw Oil) + Base --> Neutral Oil + Soaps. The aim of this challenge is to understand correlations between raw materials inputs (in particular characteristic X) that define the recipe and highly influence the operational parameters that allow obtaining a high quality neutral oil (outputs). |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-09-22T00:00:00Z 2020-01-24T12:00:28Z 2020-01-24 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/report |
format |
report |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10174/26618 http://hdl.handle.net/10174/26618 |
url |
http://hdl.handle.net/10174/26618 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Report on "Understanding correlations between raw materials inputs", Problem presented by Prio Biocombustíveis at the 127th European Study Group with Industry, University of Aveiro, Aveiro, Portugal, September 22, 2017 http://www.maths-in-industry.org/miis/view/studygroups/esgi127.html http://esgi2017.web.ua.pt/challenges.html http://esgi2017.web.ua.pt/participants.html nd nd nd nd nd nd 336 N/A |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/embargoedAccess |
eu_rights_str_mv |
embargoedAccess |
dc.publisher.none.fl_str_mv |
Mathematics in Industry, The MIIS Eprints Archive, Study Groups, European Study Group with Industry |
publisher.none.fl_str_mv |
Mathematics in Industry, The MIIS Eprints Archive, Study Groups, European Study Group with Industry |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
|
_version_ |
1799136650566041600 |