Presenting an intelligent decision optimization system that aims at helping steelmakers to make strategic decisions on procurement and production planning. It’s able to improve company’s overall profitability by optimizing complete value chain of steel process and adjusting S&OP process based on changing market conditions. Implementation of this system at steel production sites can achieve annual benefit in the range of $2-5 per ton of steel. As demonstrated through several real-world case studies, the benefit achieved by the intelligent decision optimization system will make significant contribution to improving company’s cost competitiveness even when market is facing severe challenges.
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Beijing Steel Congress 2016
2. 交流提纲/Outline
? N-SIDE 公司介绍
? 钢铁公司危机与挑战
? 智能决策优化系统的功能特点
? 产购销一体优化实例
? 总结
? Highlight of N-SIDE
? Challenges for steel industry
? Intelligent decision optimization
? Case studies
? Summary & Conclusions
7. Intelligent decision optimization
system functions
Financial planning
Profit, cost or production optimization
Procurement cost Production cost Energy cost Revenue
Raw
Material
purchase
optimiza-
tion
Process Optimization
Resource allocation
optimization, focusing
on production volume
Energy
optimi-
zation
Advanced scheduling, focusing
on time and sequence
Intelligent decision
optimization system
Corporate strategic goal
(e.g. EBITDA)
Changes in raw
material market
price and
availability
Changes in
product market
demand and
price
Supply Demand
Product
profile
and mix
optimiza-
tion
? RM dynamic
assessment
? Optimal selection
& purchase plan
? Price negotiation
based on “Limit
Marginal Price”
? External purchase
or sale strategy of
intermediate
product
? Identify profitable
products and
optimal production
routes based on
marginal cost
? RM allocation and optimal
blending
? Optimal operating point and
production level for each unit
? Waste recovery
? Production bottleneck
identification for higher ROI
? Complete energy balance,
optimal allocation of COG, BFG
& LDG with reduced
consumption of NG.
? Calculation of SOx, NOx and
CO2 emission and penalty cost
? Cost and profit report for each unit
? Achieve max profit, min cost or max
production based on corporate
strategic goal
8. 智能决策优化系统特点
intelligent decision optimization system features
敏捷生产
Agile
manufactur-
ing
精细管理
Delicacy
management
智能决策
Intelligent
decision
making
协同优化
Collaborative
optimization
预案比较
Scenario
comparison
指标分析
KPI analysis
开放平台
Open
platform
10. Integrated optimization & collaboration
10
Should we increase the production due
to good market condition? Which end
product to make for more profit? Which
facility route to use?
What is the best S content in hot metal,
taking into account the trade off
between coke production cost (cheaper
coal with high S content) and
desulfurization cost?
Does desulfurization station have
enough capacity to treat high-S hot
metal?
Similar question to Si content in hot
metal.
Should we increase MnO in
sinter in order to reduce
consumption of FeMn at
SMS?
Should we increase coke
strength? What will be the
cost impact?Depending on pellets availability
and price, what will be the best
production level for sinter?
Should we produce more
coke for external sale, or
more COG to reduce energy
bill?
Which raw material to choose,
and at what blend ratio?
How to distribute internal
gases given the gas
mixing constraint?
12. ? Hundreds decision variables, which may have impact on various aspects
of the entire steelmaking process
? Many plants have developed process models, but common practice is to
run model simulations by “trial
and error” approach, which is
difficult to find the optimal
point.
? Intelligent optimization
technology maximizes overall
profit, while satisfying all
technical & economic
constraints to ensure the
solution is optimal & feasible.
Delicacy management & intelligent decision
12
Optimization
Simulation
Cost competitiveness
13. 钢铁成本优化系统
Steel COst OPtimization (SCOOP) system
一个智能决策优化系统如何帮助提升钢铁公司成本竞争力
How an intelligent decision optimization system can help
improving steel production cost-competitiveness
16. Raw material value assessment:
Limit Marginal Price
16
Limit Marginal Price
? Computes real value of the raw
material for the process
? Dynamic (depends on the rest)
? Negotiation tool by comparing
with market price
Optimal purchase volume
17. 用户实例
Case study #1
One steel company has two integrated steel
production sites with annual production of 9.5 million
tons. SCOOP system was implemented in 2009 with
SCOOP enterprise version for coordination between
sites. Within one year, they continuously increased the
usage of one coal according to SCOOP optimization
results and achieved significant benefits.
某钢铁公司拥有两个全流程
生产厂,产能950万吨。
2009年实施SCOOP以及
SCOOP公司版用以协调多厂
优化。在一年的时间内根据
SCOOP优化结果逐渐增加某
煤种的使用量.
17
18. 生产过程优化
Process optimization
财务计划
公司总体利润最优、成本最低或产量最大
采购成本 生产成本 能源成本 收益
原料
采购
优化
产物
组合
优化
生产过程优化
产量为中心的生
产资源配置优化
能源
优化
时间为中心的
生产排程优化
SCOOP系统
公司战略目标
(例如 EBITDA)
原材料市场
价格和可获
得性的变化
产物市场需
求和价格的
变化
供
给
侧
需
求
侧
? 进行原材料厂间分配,计算最
优配煤配矿比
? 确定各生产单元最优生产量及
操作点
? 合理回收废料,减少资源浪费
? 确定生产瓶颈,提高投资回报
? RM allocation and optimal
blending
? Optimal operating point and
production level for each unit
? Waste recovery
? Production bottleneck
identification for higher ROI
19. 用户实例
Case study #2
A cheap but high-S PCI becomes
available in the market. One steel
company used SCOOP to evaluate
the impact of this new PCI on slab
production cost to determine
whether it should be used and if so,
how much is needed.
某钢铁厂使用SCOOP系统来评价
一种新的市场上可获得的喷煤对
钢坯生产成本的影响。这种喷煤
价格便宜,但是含硫量较高。通
过SCOOP系统可以决策是否试用,
若是,最优使用量是多少。
19
S (%) BF1 BF2 BF3
Base case without new
PCI
0.041 0.040 0.042
Alternative case with
new PCI
0.081 0.079 0.082
Financial impact on Difference
hot metal production cost -8.71 /thm
desulfurization cost +0.66 /tst
slab production cost -7.34 /tst
20. 产物组合优化
财务计划
公司总体利润最优、成本最低或产量最大
采购成本 生产成本 能源成本 收益
原料
采购
优化
产物
组合
优化
生产过程优化
产量为中心的生
产资源配置优化
能源
优化
时间为中心的
生产排程优化
SCOOP系统
公司战略目标
(例如 EBITDA)
原材料市场
价格和可获
得性的变化
产物市场需
求和价格的
变化
供
给
侧
需
求
侧
? 制定中间产物外
销外购策略
? 基于“边际成本”
计算产物盈亏,
寻找最优产物组
合和生产路径
? External purchase
or sale strategy of
intermediate
product
? Identify profitable
products and
optimal production
routes based on
marginal cost
21. 边际成本和最优生产量的确定
Marginal cost & optimal production level
21
售价
sale price
边际成本
Marginal cost
生产量 production level
总利润
Total profit
加入生石灰提高烧结矿产量
Quicklime to increase sinter production
高炉使用球团
Pellet used at BF
消耗额外的废钢
Consumption of extra scrap
购买外部焦炭
External coke used
边际成本=售价, 利润最大方案
MC=Price, max profit solution
边际成本>售价, 增加生产量提高销售收入但利润下降
MC>Price, inc. production makes higher revenue, but declined profit
转炉使用铁硅合金
FeSi alloy used at CV
边际成本<售价,增加生产量获利
MC<Price, increase product for profit
22. 800
850
900
950
1000
1050
1100
800 850 900 950 1000 1050 1100
Marginalcost[/t]
Selling price [/t]
用户实例
Case study #3
某钢铁公司利用SCOOP计算边际成本并对产物按边际利润排序
A steel company used SCOOP calculate marginal cost and
sort all products based on marginal profit.
22
最优产物组合 / Optimal product mix
? 获利产物 (销售价格>边际成本) -> 扩大生产以最大满足市场需求或至最大产能
Profitable product (Price>MC) -> increase production to meet max market demand
? 无利可图 (销售价格<边际成本) -> 减少生产至满足最小市场需求
Non-profitable product (Price<MC) -> reduce production to meet min market demand
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Marginal profit [/t]
Products
边际利润 Marginal profit
产物排序Sortedproducts
边际成本Marginalcost
销售价格 Sale price
25. SCOOP Achievement
Carbon steel, stainless steel producers and raw material suppliers
? Applied to world-wide 15+
steel companies.
? ~10% global steel production
? Significant cost savings of 2-
5 Euros per ton
? Integrated optimization of complete value chain,
instead of each individual operation unit.
? Understanding of processes and complex
impacts involving multiple operation units hence
decisions can be made based on appropriate
trade-offs to achieve maximum overall profit.
? Negotiation power gained by assessing true
value of raw materials using LMP.
? Improved collaboration and info sharing of all
stakeholders by breaking down internal “silos”.