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Trim Loss Optimization in Paper Production Using Reinforcement Artificial Bee Colony
- Source :
- IEEE Access, Vol 8, Pp 130647-130660 (2020)
- Publication Year :
- 2020
- Publisher :
- IEEE, 2020.
-
Abstract
- 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.
- Subjects :
- Mathematical optimization
General Computer Science
Computer science
swarm intelligence
General Engineering
Paper production
Stock cutting
Inventory cost
Trim
Artificial bee colony algorithm
pulp and paper industry
Cutting stock problem
General Materials Science
artificial bee colony algorithm
lcsh:Electrical engineering. Electronics. Nuclear engineering
Reinforcement
Integer programming
optimization
lcsh:TK1-9971
Subjects
Details
- Language :
- English
- ISSN :
- 21693536
- Volume :
- 8
- Database :
- OpenAIRE
- Journal :
- IEEE Access
- Accession number :
- edsair.doi.dedup.....3fc36b7d0fbcf0a46e34e454a6992697