Trim Loss Optimization in Paper Production Using Reinforcement Artificial Bee Colony
In paper production, a jumbo reel is cut into multiple intermediate rolls, and each intermediate roll is then sheeted as finished goods. This problem is called a cutting stock problem and is proven to be NP-hard. The objective is to minimize material waste or trim loss from all the cuttings. In the...
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doaj-5384fe836168487ba70824f2e57a881a2021-03-30T04:48:55ZengIEEEIEEE Access2169-35362020-01-01813064713066010.1109/ACCESS.2020.30089229139502Trim Loss Optimization in Paper Production Using Reinforcement Artificial Bee ColonySuthida Fairee0https://orcid.org/0000-0003-2746-0595Charoenchai Khompatraporn1https://orcid.org/0000-0002-0828-5798Booncharoen Sirinaovakul2https://orcid.org/0000-0001-8541-1922Santitham Prom-On3Department of Computer Engineering, King Mongkut’s University of Technology Thonburi, Bangkok, ThailandDepartment of Production Engineering, King Mongkut’s University of Technology Thonburi, Bangkok, ThailandDepartment of Computer Engineering, King Mongkut’s University of Technology Thonburi, Bangkok, ThailandDepartment of Computer Engineering, King Mongkut’s University of Technology Thonburi, Bangkok, ThailandIn paper production, a jumbo reel is cut into multiple intermediate rolls, and each intermediate roll is then sheeted as finished goods. This problem is called a cutting stock problem and is proven to be NP-hard. The objective is to minimize material waste or trim loss from all the cuttings. In the case that any intermediate roll is not entirely used for its associated order, the intermediate roll itself could turn to be a dead stock. We use the concept of universal sizes of intermediate rolls to eliminate the dead stock. A pre-defined number of universal sizes of intermediate rolls is to be used to serve all the orders. The problem is solved using Reinforcement Artificial Bee Colony algorithm with Integer Linear Programming subroutine. This proposed approach is then tested with a set of 1,055 orders and 127 different sizes of sheet papers from a paper manufacturer. The results reveal that our method outperforms other algorithms. Our method offers the total trim loss of 3.51%, compared to the trim loss reported by the industry of at least 5%. This approach not only reduces the number of partially cut rolls, but also decreases the number of the jumbo reels needed to serve all the orders. Therefore, both the inventory cost and material cost can be saved.https://ieeexplore.ieee.org/document/9139502/Stock cuttingoptimizationswarm intelligenceartificial bee colony algorithmpulp and paper industry |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Suthida Fairee Charoenchai Khompatraporn Booncharoen Sirinaovakul Santitham Prom-On |
spellingShingle |
Suthida Fairee Charoenchai Khompatraporn Booncharoen Sirinaovakul Santitham Prom-On Trim Loss Optimization in Paper Production Using Reinforcement Artificial Bee Colony IEEE Access Stock cutting optimization swarm intelligence artificial bee colony algorithm pulp and paper industry |
author_facet |
Suthida Fairee Charoenchai Khompatraporn Booncharoen Sirinaovakul Santitham Prom-On |
author_sort |
Suthida Fairee |
title |
Trim Loss Optimization in Paper Production Using Reinforcement Artificial Bee Colony |
title_short |
Trim Loss Optimization in Paper Production Using Reinforcement Artificial Bee Colony |
title_full |
Trim Loss Optimization in Paper Production Using Reinforcement Artificial Bee Colony |
title_fullStr |
Trim Loss Optimization in Paper Production Using Reinforcement Artificial Bee Colony |
title_full_unstemmed |
Trim Loss Optimization in Paper Production Using Reinforcement Artificial Bee Colony |
title_sort |
trim loss optimization in paper production using reinforcement artificial bee colony |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2020-01-01 |
description |
In paper production, a jumbo reel is cut into multiple intermediate rolls, and each intermediate roll is then sheeted as finished goods. This problem is called a cutting stock problem and is proven to be NP-hard. The objective is to minimize material waste or trim loss from all the cuttings. In the case that any intermediate roll is not entirely used for its associated order, the intermediate roll itself could turn to be a dead stock. We use the concept of universal sizes of intermediate rolls to eliminate the dead stock. A pre-defined number of universal sizes of intermediate rolls is to be used to serve all the orders. The problem is solved using Reinforcement Artificial Bee Colony algorithm with Integer Linear Programming subroutine. This proposed approach is then tested with a set of 1,055 orders and 127 different sizes of sheet papers from a paper manufacturer. The results reveal that our method outperforms other algorithms. Our method offers the total trim loss of 3.51%, compared to the trim loss reported by the industry of at least 5%. This approach not only reduces the number of partially cut rolls, but also decreases the number of the jumbo reels needed to serve all the orders. Therefore, both the inventory cost and material cost can be saved. |
topic |
Stock cutting optimization swarm intelligence artificial bee colony algorithm pulp and paper industry |
url |
https://ieeexplore.ieee.org/document/9139502/ |
work_keys_str_mv |
AT suthidafairee trimlossoptimizationinpaperproductionusingreinforcementartificialbeecolony AT charoenchaikhompatraporn trimlossoptimizationinpaperproductionusingreinforcementartificialbeecolony AT booncharoensirinaovakul trimlossoptimizationinpaperproductionusingreinforcementartificialbeecolony AT santithampromon trimlossoptimizationinpaperproductionusingreinforcementartificialbeecolony |
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