Selecting a Biomass Pelleting Processing Depot Using a Data Driven Decision-Making Approach
Bioenergy is one of the potential solutions to satisfy the extensive demand for energy and reduce fossil fuel dependency. For biomass to be an efficient source of bioenergy, it must be converted to a usable form, one of which is pellets. This study compares three commonly used methods to produce pel...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-05-01
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| Series: | Systems |
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| Online Access: | https://www.mdpi.com/2079-8954/9/2/32 |
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| author | Siham Tazzit Niamat Ullah Ibne Hossain Farjana Nur Fatine Elakramine Raed Jaradat Safae El Amrani |
| author_facet | Siham Tazzit Niamat Ullah Ibne Hossain Farjana Nur Fatine Elakramine Raed Jaradat Safae El Amrani |
| author_sort | Siham Tazzit |
| collection | DOAJ |
| description | Bioenergy is one of the potential solutions to satisfy the extensive demand for energy and reduce fossil fuel dependency. For biomass to be an efficient source of bioenergy, it must be converted to a usable form, one of which is pellets. This study compares three commonly used methods to produce pellets in a biomass depot and presents a framework to select the most effective and economic pelleting processes. The comparison is performed using a data driven decision-making method called the Preference Index Selection Method (PSI). We considered three main pelletization technologies and compared four of their most critical attributes. The three popular biomass pellet processing methods used for this study are the conventional pelleting process (CPP), the high moisture pelleting process (HMPP), and the ammonia fiber expansion (AFEX). These processes were evaluated from both economic and environmental perspectives. We used the state of Mississippi as a testing ground for our analyses. The results obtained through the PSI method were validated with the Grey relational analysis (GRA) method. The results revealed that of the three available pelleting processes, the conventional pelleting process and the high moisture pelleting process were the most economic and environmentally friendly. |
| first_indexed | 2024-03-10T11:39:49Z |
| format | Article |
| id | doaj.art-57a28685c403420e8941f683290d3482 |
| institution | Directory Open Access Journal |
| issn | 2079-8954 |
| language | English |
| last_indexed | 2024-03-10T11:39:49Z |
| publishDate | 2021-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Systems |
| spelling | doaj.art-57a28685c403420e8941f683290d34822023-11-21T18:35:12ZengMDPI AGSystems2079-89542021-05-01923210.3390/systems9020032Selecting a Biomass Pelleting Processing Depot Using a Data Driven Decision-Making ApproachSiham Tazzit0Niamat Ullah Ibne Hossain1Farjana Nur2Fatine Elakramine3Raed Jaradat4Safae El Amrani5Department of Industrial and Systems Engineering, Bagley College of Engineering, Mississippi State University, Mississippi State, MS 39762, USADepartment of Industrial and Systems Engineering, Bagley College of Engineering, Mississippi State University, Mississippi State, MS 39762, USADepartment of Industrial and Systems Engineering, Bagley College of Engineering, Mississippi State University, Mississippi State, MS 39762, USADepartment of Industrial and Systems Engineering, Bagley College of Engineering, Mississippi State University, Mississippi State, MS 39762, USADepartment of Industrial and Systems Engineering, Bagley College of Engineering, Mississippi State University, Mississippi State, MS 39762, USADepartment of Industrial and Systems Engineering, Bagley College of Engineering, Mississippi State University, Mississippi State, MS 39762, USABioenergy is one of the potential solutions to satisfy the extensive demand for energy and reduce fossil fuel dependency. For biomass to be an efficient source of bioenergy, it must be converted to a usable form, one of which is pellets. This study compares three commonly used methods to produce pellets in a biomass depot and presents a framework to select the most effective and economic pelleting processes. The comparison is performed using a data driven decision-making method called the Preference Index Selection Method (PSI). We considered three main pelletization technologies and compared four of their most critical attributes. The three popular biomass pellet processing methods used for this study are the conventional pelleting process (CPP), the high moisture pelleting process (HMPP), and the ammonia fiber expansion (AFEX). These processes were evaluated from both economic and environmental perspectives. We used the state of Mississippi as a testing ground for our analyses. The results obtained through the PSI method were validated with the Grey relational analysis (GRA) method. The results revealed that of the three available pelleting processes, the conventional pelleting process and the high moisture pelleting process were the most economic and environmentally friendly.https://www.mdpi.com/2079-8954/9/2/32biomasspelleting processpreference selection indexgrey relational analysismulti-criteria decision making |
| spellingShingle | Siham Tazzit Niamat Ullah Ibne Hossain Farjana Nur Fatine Elakramine Raed Jaradat Safae El Amrani Selecting a Biomass Pelleting Processing Depot Using a Data Driven Decision-Making Approach Systems biomass pelleting process preference selection index grey relational analysis multi-criteria decision making |
| title | Selecting a Biomass Pelleting Processing Depot Using a Data Driven Decision-Making Approach |
| title_full | Selecting a Biomass Pelleting Processing Depot Using a Data Driven Decision-Making Approach |
| title_fullStr | Selecting a Biomass Pelleting Processing Depot Using a Data Driven Decision-Making Approach |
| title_full_unstemmed | Selecting a Biomass Pelleting Processing Depot Using a Data Driven Decision-Making Approach |
| title_short | Selecting a Biomass Pelleting Processing Depot Using a Data Driven Decision-Making Approach |
| title_sort | selecting a biomass pelleting processing depot using a data driven decision making approach |
| topic | biomass pelleting process preference selection index grey relational analysis multi-criteria decision making |
| url | https://www.mdpi.com/2079-8954/9/2/32 |
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