1. Universitat Politècnica de Catalunya
Enhancing Sustainability Performance of the whole supply Chain Management in the Chemical Process Industries
Luis Puigjaner
Chemical Engineering Department
Universitat Politècnica de Catalunya

2. Index Introduction- Sustainability criteria and the SC
Integrated SC: actual challenges and oportunities
Integrated platform architecture
DSS components: forecasting, negotiation, financial,
environmental, control & diagnosis
Tutorial example
Education on Sustainability: Pioneer experience (UC)

3. Index Introduction- Sustainability criteria and the SC
Integrated SC: actual challenges and oportunities
Integrated platform architecture
DSS components: forecasting, negotiation, financial,
environmental, control & diagnosis
Tutorial example
Education on Sustainability: Pioneer experience (UC)

4. Introduction: Sustainability criteria
Enterprise sustainibility considers fundamental aspects:
Innovation
Economy and finances
Environment and safety
Productivity and quality
Social responsibility
At different levels:
Bussines
Multi plant
Production chain
In a integrated way in its production and supply chains

5. Sustainability Global Index-AIChE
Value-Chain
Management
Social
Responsibility
Safety
Performance
Innovation
Strategic
Commitment
Environmental
Product
Stewardship
Chemical companies from
Global Fortune 500
U.S. Chemical
Manufacturing Sector

6. Index Introduction- Sustainability criteria and the SC
Integrated SC: actual challenges and oportunities
Integrated platform architecture
DSS components: forecasting, negotiation, financial,
environmental, control & diagnosis
Tutorial example
Education on Sustainability: Pioneer experience (UC)

7. Integrated SC: Challenges and opportunities
Production within a Supply Chain: a complex management issue
Supply Chain Management (SCM) includes decision making aiming to integrate plants with their suppliers and customers so that can be managed as a single entity.

8. Integrated SC Supply chain ISA SP 95 time horizon & spatial scope
supply chain network
Integrated SC
time horizon & spatial scope
production
Strategy
SC configuration
Operation
SC planning and coordination:
production, logistics, distribution
Tactic
SC planning
control
finances
others
Supply chain
manufacturing plant
ISA SP 95
Supervisory control
Monitoring, fault diagnosis
Local control
Unit coordination & local control
Global supervision
Production Scheduling
Detailed plant production planning
Execution
Systems and equipment execution
Production Planning
Approximated plant production planning
Strategy
Plant design, retrofit
Operational accounting
Strategic financial planning
Single site
An important point is to see which is the position of the SCM with regard to the other activities in a company and in a chemical plant.
We have to keep in mid that we have a manufacturing site that belongs to a SC network. So, these are the two areas in which this diagram is divided. In general, on managing the plant, more detailed information is used than for SCM.
The activities (refer to the presentation of Anna, Ignacio and Estanislao) are related to control, production, economy and finances, etc., and can be located at different level as the slide shows (read the slide if necessary).
In the area of SCM, three levels are usually considered, which, in increasing order of detail are: strategic, tactical and operational. More detail will be given in next slides.
Some standards have been developed in order to specify the exchange of information between the different levels. The most accepted are the Standard ISA SP88 that relates the supervisory with the execution levels specially in the areas o production and control. And the ISO SP 95 that relates the business level with the plant level, in the boundaries between the plant and its SC.
So, this is the whole scenery in which solutions have to consider larger time horizon and spatial scope as they tackle problems located higher on the pyramid.
production line
ISA
SP 88
equipment

9. Integrated SC: Challenges and opportunities
weeks for transport
hours or days for storing
minutes for chemical reactions
Wide temporal scale
The problem of SCM can be considered as the complexity management.
On managing a SC network, the following issues appear:
wide temporal scale, for example (Read the slide)
multiple spatial scale (Read the slide),
and high degree of uncertainty (Read the slide).
manufacturing plants
production lines
individual equipments
Multiple spatial scale
market level: demand, prices, stock availability
plant level: yield, quality, processing time
business level: reliability, profitability
High degree of uncertainty

10. Integrated SC: Challenges and opportunities
Basic questions to production engineering
Demand forecast?
How much?
Planning and Scheduling
When?
Where?
Logistics planning

11. Integrated SC: Challenges and opportunities
Advanced questions:
Management/Environmental
Engineering
Environmental Impact?
Intelligent
Negotiation
Social Impact?
Intelligent
Financial Engineering
Financial Impact?
Multi-objective optimization
Optimization?

12. Integrated SC: Challenges and opportunities
Present Applications
Partial
Forecasting?
Finite capacity planning
Advanced questions?
Optimization?
Rigid architecture
Absent standards
High cost
Challenges & Opportunities
Integrated
Forecasting under uncertainty
Detailed planning resource constrained
Answers to advanced questions
Multi-objective optimization
Open, reconfigurable architecture
Standard compliant (GCO, CO, ISA...)
Accessible to SME
e-bussiness oriented

13. Integrated SC: Challenges and opportunities
Software vendors
AspenTech i2
ILOG
Manugistics
SAP
Industrial Efforts
INFOR
Industrial Applications
Air Products
BASF
Bayer
Dow
Dupont
ExxonMobil
Mitsubishi
Shell

14. Index Integrated SC: actual challenges and oportunities
Introduction- Sustainability criteria and the SC
Integrated platform architecture
DSS components: forecasting, negotiation, financial,
environmental, control & diagnosis
Tutorial example
Education on Sustainability: Pioneer experience (UC)

15. Integrated Platform architecture
Software Agents
An agent is an encapsulated computer system that is situated in some environment, and that is capable of flexible, autonomous action in that environment in order to meet its design objectives.
Wooldridge and Jennings, 1995
What is a software agent?
(Read the slide)
The same authors suggest that any computer system (software or hardware) should have the following properties to be termed as an agent:
Autonomy. (read the slide)
Social ability.
Reactivity.
Pro-activeness.
The above-mentioned properties are generic for an agent, and it may exhibit more of one property than another based on its architecture and embedded abilities or skills.
Autonomy. It should have some control over its actions and should work without human intervention.
Social ability. It should be able to communicate with other agents and/or with human operators.
Reactivity. It should be able to react to changes in its environment.
Pro-activeness. It should also be able to take initiative based on pre-specified goals.

16. Integrated Platform architecture
Utilities (Modules)
(decision support)
Financial
Environ-mental
Fore-casting
...
Intelligent architecture (software agents)
Modular, adaptable solution
Supplier
Manufacturer
Warehouse
Retailer
Client
Real (Phisical) Agents
(reproduce chain echelons)
Learning, reconfigurable, updated, reactive…

17. Integrated Platform architecture
So, now, I’d like to explain the Methodology used for representing the SC with software agents.
The framework here proposed to represent the SC network consists of a multi-agent system composed, of emulation agents, which map one-to-one each real node or entity of the SC network, and the messages, which are exchanged between them. (read the slide)
Moreover, the system perform the activities aided by a set of calculation modules (read the slide).
It is important to highlight that this simulation model works at a tactical and operational level from the SC point of view. It means that decisions are updated every month or quarter and it answers questions like (Read the slide)
Tactical and operational level deci-sions updated monthly to quarterly:
which products are manufactured
which factory produce each product
which supplier is selected
. . .

18. Integrated Platform architecture

19. Integrated Platform architecture
Agent-Based Simulation Model
In turns, each agent is represented by a set of sub-agents. In this particular case of a Factory agent, we consider three regions into the agent:
The storage of raw materials, the production area and the storage of final products. The sub-agents involved are Sales, Inventory, Purchasing, Transport and Production.
Built on a client – server paradigm
Programming language: C#, .NET by Microsoft ®.
SC Model: XML extension .scm.
Network structure.
Parameters for production, storage and transportation. Structure of time & costs.
Client demand model.

20. Index Integrated SC: actual challenges and oportunities
Introduction- Sustainability criteria and the SC
Integrated platform architecture
DSS components: forecasting, negotiation, financial,
environmental, control & diagnosis
Tutorial example
Education on Sustainability: Pioneer experience (UC)

21. Demand forecasting module
¿How much must I produce?
Demand forecasting
Obtention of future demand based on historical data
Complex decisions
Reduction of inventory costs
Optimal planning of resources

22. Negociation module
¿What conditions must I fix with customers and suppliers?
Determines contractual optimal parameters
Negociation module
Fair commercial relationship
Higher customer satisfaction
Increase of future sales

23. Financial Impact module
¿What is the financial impact of my decisions?
Evaluation of the economic impact of chain activities
Financial Agent
Incorporating production decisions
Optimization of portfolio ( financial engineering)
Bank debt management

24. Environmental Impact model
¿Which is the environmental impact of my chain?
Evaluation of environmental impact of chain activities
Environmental agent
Environmental respectful decisions
Process sustainability
Incorporates current legislation

25. Coordination and supervision module
¿How to execute decisions taken in a robust way?
Control, coordination and supervision of productivity activites
Control/Supervision plant agent
Execution of production operations
Monitoring of production process
Detection and diagnosis of perturbances and alarm management
Reaction to incidences

26. Index Integrated SC: actual challenges and oportunities
Introduction- Sustainability criteria and the SC
Integrated platform architecture
DSS components: forecasting, negotiation, financial,
environmental, control & diagnosis
Tutorial example
Education on Sustainability: Pioneer experience (UC)

27. Tutorial Example

28. Utilities Modules: chain management
Tutorial Example
Paris
Lisboa
Representative example
Multi-product plants manufacturing
Final product storage warehouses
Distribution to retailers
Sales to Clients
Physical Agent: Execute & Supervise
PROCEL Plant
Plant management
Supervisory control
Utilities Modules: chain management
Forecasting
Financial
Enviromental
Planning/
optimization
Negociation
Resheduling

29. Flexible Pilot Plant PROCEL

30. The Global Picture Warehouse Central Agent Forecasting: ForeST
Negotiation, Financial & Environmental Opt.
Planning & scheduling: MOPP
Coordination Control
Parameter estimation and data reconciliation
Fault Diagnosis: ExSit-M

32. Index Integrated SC: actual challenges and oportunities
Introduction- Sustainability criteria and the SC
Integrated platform architecture
DSS components: forecasting, negotiation, financial,
environmental, control & diagnosis
Tutorial example
Education on Sustainability: Pioneer experience (UC)

33. Master on Process sustainability (UC)
Summary of Master Contents (60 ECTS)
Process Intensification (9 ECTS)
Process Integration in the Supply Chain (9 ECTS)
Sustainability Indicators (metrics) (9 ECTS)
Case Studies (12 ECTS)
Laboratory/Master’s Final Project de Grado(12 ECTS)
Free electives (9 ECTS)

34. Sponsors
SOPTIA
URQUIMA
Z. A. Pulawy

35. Thanks for your attention
further information:

36. References
Musulin, E., Benqlilou, C., Bagajewicz, M., Puigjaner, L. “Instrumentation design based on optimal Kalman filtering”, Journal of Process Control , 15, pp (2005).
Tona, R.V., Benqlilou, C., Espuña, A., Puigjaner, L. “Dynamic Data Reconciliation Based on Wavelet Trend Analysis”, Ind. Eng. Chem. Res, 44, pp (2005).
Guillén, G., Pina, C., Espuña, A., Puigjaner, L. “Optimal Offer Proposal Policy in an Integrated Suply Chain Management Environment”, Ind. Eng. Chem. Res, 44, pp (2005).

37. References
Guillén, G., Badell, M., Espuña, A., Puigjaner, L. “Simultaneous optimization of process operations and financial decisions to enhance the integrated planning/scheduling of chemical supply chains”, Computers and Chemical Engineering, 30, pp (2006).
Mele, F.D., Espuña, A., Puigjaner, L. “Supply Chain Management through Dynamic Model Parameters Optimization”, Ind. Eng. Chem. Res, 45, pp (2006).
Musulin, E., Yélamos, I., Puigjaner, L. “Integration of Principal Component Analysis and Fuzzy Logic Systems for Comprehensive Process Fault Detection and Diagnosis”, Ind. Eng. Chem. Res, 45, pp (2006).

38. References
Mele, F.D., Guillén, G., Espuña, A., Puigjaner, L. “A Simulation-Based Optimization Framework for Parameter Optimization of Supply-Chain Networks”, Ind. Eng. Chem. Res, 45, pp (2006).
Guillén, G., Espuña, A., Puigjaner, L. “Addressing the scheduling of chemical supply chains under demand uncertainty”, AIChE Journal, 52 (11),, pp (2006).
Guillén, G., Mele, F.D., Espuña, A., Puigjaner, L. “Addressing the Design of Chemical Supply Chains under Demand Uncertainty”, ”, Ind. Eng. Chem. Res, 45 (22), pp 7566 – 7581 (2006).

39. References
Heluane, H., Colombo, M., Hernández, M.R., Graells, M., Puigjaner, L. “Enchancing sugar cane process performance through optimal production scheduling”, Chemical Engineering and Processing, 46, pp (2007).
Guillén, G., Badell, M., Puigjaner, L. “A holistic framework for short term supply chain management integrating production and corporate financial planning”, International J. of Production Economics, 106, pp (2007)
Ferrer-Nadal, S., Yélamos Ruiz, I., Graell, M., Puigjaner, L., “An integrated framework for on-line supervised optimization”, Especial Issue : Escape-15, Editor: Luis Puigjaner, Computers and Chemical Engineering, 31, pp , (2007).

40. References
Mele, F.D., Guillén, G., Espuña, A., Puigjaner, L., “An agent-based approach for suppy chain retrofiting under uncertainty”, Especial Issue : Escape-15, Editor: Luis Puigjaner, Computers and Chemical Engineering, 31, pp , (2007).
Badell, M., Fernandez, E., Guillén, G., Puigjaner, L. “ Empowering financial tradeoff with joint financial and supply chain planning models”, Mathematical and Computer Modelling, 46, pp (2007).
Yélamos, I., Mendez, C., Puigjaner, L., “Enhancing dynamic data reconciliation performance through time delays identification”, Chemical Engineering and Processing, 46, pp , (2007).

41. References
Ferrer-Nadal, S; Méndez, C; Graells, M; Puigjaner, L; “Optimal reactive scheduling of manufacturing plants with flexible batch recipes”, Ind. Eng. Chem. Res., 46, ISSN: , pp , (2007).
Yélamos, I.; Graells, M.; Puigjaner, L.; “ Simultaneous fault diagnosis in chemical plants using a multilabel approach”, AIChE Journal, 53, ISSN: , pp , (2007).
Laínez, J.M.; Guillén-Gonsálbez, G.; Badell, M.; Espuña, A.; Puigjaner, L.; “Enhancing corporate value in the optimal design of chemical supply chains”; Ind. Eng.Chem. Res., 46, pp , (2007)

42. References
Arbiza, J.M., Bonfill, A., Guillén,G., Mele, F., Espuña,A., Puigjaner, L. “Methauristic multiobjective optmisation approach for the scheduling of multiproduct batch dinamical plants”, Journal of cleaner productions, 16, ISSN: , pp , (2008).
Puigjaner, L.; Guillén-Gonsálvez, G.; “Towards an integrated framework for supply chain management in the batch process industry”; Computers and Chemical Engineering, 32, pp , (2008).
Ferrer-Nadal, S.; Puigjaner, L.; Guillén-Gonsálvez, G.; “Managing risk through a flexible recipe framework”, AIChE Journal, 53(3), pp , (2008).

43. References
Bonfill, A., Espuña, A., Puigjaner, L., “Decision support framework for coordinated production and transport scheduling in SCM”, Computers and Chemical Engineering, 32, pp , (2008).