Přístupnostní navigace
E-application
Search Search Close
Publication detail
TENG, S., HOW, B., LEONG, W., TEOH, J., LAM, H.
Original Title
Bottleneck Tree Analysis (BOTA) with green and lean index for process capacity debottlenecking in industrial refineries
Type
journal article in Web of Science
Language
English
Original Abstract
This paper presents a novel Bottleneck Tree Analysis (BOTA) to cope with the increasing capacities within industrial refineries. BOTA is a clear and concise heuristic graphical debottlenecking method that can accurately pinpoint the process capacity bottlenecks. Coupled with BOTA, four multiple criteria decision-making methods are used for an ensemble with Spearman’s correlation to assess the Green and Lean Index (GLI) of industrial processes. The decision-making tool is formulated to improve operational performance with the consideration for environmental conditions. Empirically, BOTA demonstrated a debottleneck stopping mechanism which can be theoretically explained with the reversed onion model. An additional advantage is that retrofit projects can be guided by BOTA with effective scheduling. From an industrial case study, BOTA improved normalized Global Warming Potential by 94.43 %, normalized energy consumption by 93.09 % and return on investment by 58.36 %. Project implementation by scheduling also reduced payback period from 85 to 66 months. (C) 2019 Published by Elsevier Ltd.
Keywords
Capacity debottlenecking, Lean and green, Multiple criteria decision making, Expert system, Reversed onion model, Bottleneck Tree Analysis (BOTA)
Authors
Released
16. 3. 2020
Publisher
Elsevier
Location
Oxford, England
ISBN
0009-2509
Periodical
Chemical Engineering Science
Year of study
214
Number
v
State
United States of America
Pages from
115429
Pages to
115449
Pages count
21
URL
https://www.sciencedirect.com/science/article/pii/S0009250919309194
BibTex
@article{BUT161123, author="Sin Yong {Teng}", title="Bottleneck Tree Analysis (BOTA) with green and lean index for process capacity debottlenecking in industrial refineries", journal="Chemical Engineering Science", year="2020", volume="214", number="v", pages="115429--115449", doi="10.1016/j.ces.2019.115429", issn="0009-2509", url="https://www.sciencedirect.com/science/article/pii/S0009250919309194" }