More on completion time algorithms for intermediate storage tanks in multiproduct batch process scheduling using matrix representation
In batch process scheduling, the introduction of intermediate storage tanks between process stages result in increasing the efficiency and productivity of the process. The main purpose of this is to minimize the process completion time, i.e. makespan. However, it is important to determine the right...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Published: |
2008
|
| Subjects: | |
| Online Access: | http://eprints.utp.edu.my/540/1/paper.pdf http://www.scopus.com/inward/record.url?eid=2-s2.0-64549124236&partnerID=40&md5=e51bff552be29e610099c9b35592a6dc http://eprints.utp.edu.my/540/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Universiti Teknologi Petronas |
| Summary: | In batch process scheduling, the introduction of intermediate storage tanks between process stages result in increasing the efficiency and productivity of the process. The main purpose of this is to minimize the process completion time, i.e. makespan. However, it is important to determine the right number and respective locations of the intermediate storage to ensure optimal investment and operational cost. The generally adopted transfer policies for handling intermediate storage tanks in batch processes are unlimited intermediate storage (UIS) and finite intermediate storage (FIS). In this work, new completion time algorithms for UIS and FIS transfer policies are proposed using matrix representation. The objective of the proposed approach is to calculate the makespan for all possible production sequences for given batch product recipes while at the same time determining the number and location of intermediate storage tanks required. With the assumptions that the intermediate storage could be used to store any intermediate product, the method is verified against the Gantt chart method and the results agreed well. A number of different product recipes are analyzed using a developed computer code. This enables the proposed algorithms to produce solution options for large size batch scheduling problems. © 2008 American Chemical Society.
|
|---|