DISTRIBUTED AND CAPE-OPEN COMPLIANT PLATFORM FOR PLANNING AND SCHEDULING

1. Spanish – Bulgarian Collaborative Project DISTRIBUTED AND CAPE-OPEN COMPLIANT PLATFORM FOR PLANNING AND SCHEDULING MULTI-SITE MANUFACTURING SYSTEMS Technical Report 2005-2007 Chemical Engineering Department, Universitat Politècnica de Catalunya Barcelona, Spain Institute of Chemical Engineering, Bulgarian Academy of Sciences, Sofia, Bulgaria

2. Optimal Product portfolio Distribution on SC elements DISTRIBUTED AND CAPE-OPEN COMPLIANT PLATFORM FOR PLANNING AND SCHEDULING MULTI-SITE MANUFACTURING SYSTEMS Supply Chain models PLANNING Manufacturing system Information: Products Markets Suppliers Transportation Warehouses Distributors Plants Scheduling SC elements Scheduling

3. DISTRIBUTED AND CAPE-OPEN COMPLIANT PLATFORM FOR PLANNING AND SCHEDULING MULTI-SITE MANUFACTURING SYSTEMS Research steps: 1. Methodology for determining generalized constraints to assess product portfolio feasibility for each multipurpose plant; 2. Deterministic mathematical model for optimal product portfolio planningand its distribution taking into account the generalized feasibility constraints; 3. Distributed framework for planning and scheduling of batch plants - standard tool.

4. 1. DETERMINATION THE FEASIBILE PRODUCT PORTFOLIO FRAMEWORK

5. 1. DETERMINATION THE FEASIBILE PRODUCT PORTFOLIO FRAMEWORK

6. 1. DETERMINATION THE FEASIBILE PRODUCT PORTFOLIO FRAMEWORK

7. 1. DETERMINATION THE FEASIBILE PRODUCT PORTFOLIO FRAMEWORK Task 1 Task 2 Task 3 Task 4 Task 5 Task 6 Task 1 Task 2 Task 3 Task 4 Task 5 Task 6 Task 1 Task 2 Task 3 Task 4 Task 5 Task 6

8. 1. DETERMINATION THE FEASIBILE PRODUCT PORTFOLIO FRAMEWORK Task 1 Task 2 Task 3 Task 4 Task 5 Task 6 Task 1 Task 2 Task 3 Task 4 Task 5 Task 6 Task 1 Task 2 Task 3 Task 4 Task 5 Task 6 H

9. 1. DETERMINATION THE FEASIBILE PRODUCT PORTFOLIO FRAMEWORK Task 1 Task 2 Task 3 Task 4 Task 5 Task 6 Task 1 Task 2 Task 3 Task 4 Task 5 Task 6 Task 1 Task 2 Task 3 Task 4 Task 5 Task 6 H

10. 2. DETERMINISTIC SUPPLY CHAIN MODEL Problem Description and Data Variables Supply Chain Model Constraints Objective Functions

11. 2. DETERMINISTIC SUPPLY CHAIN MODEL Problem Description and Data

12. 2. DETERMINISTIC SUPPLY CHAIN MODEL Variables - Control Variables Design Variables -

13. 2. DETERMINISTIC SUPPLY CHAIN MODEL Supply Chain Model Mass balance of the subsystem multipurpose plants – resource centers Mass balance of multipurpose plants Mass balance of the subsystem multipurpose plants – markets

14. 2. DETERMINISTIC SUPPLY CHAIN MODEL Constraints Products portfolio feasibilities constraints Resource centers constraints Markets constraints

15. 2. DETERMINISTIC SUPPLY CHAIN MODEL Objective functions One-objective – maximum profit for production complex Multi -objective – optimal trade off between actors in SC

16. 2. DETERMINISTIC SUPPLY CHAIN MODEL Example from dairy industry Maximum profit for dairy complex Optimal trade off between SC actors Joint publications; Sub-optimal solution Total site profit – 307265 BGN Best solution Total site profit - 308073 BGN • 1. N. G. Vaklieva-Bancheva, E. G. Shopova, A. Espuña, L. Puigjaner, Product Portfolio Optimization for Dairy Industry, Proceedings of the International Mediterranean Modelling Multiconference, ISBN 84-690-0726-2, pp.101-110, October 4-6, 2006, Barcelona, Spain. • 2. N. Vaklieva-Bancheva, A. Espuña, E. Shopova, L. Puigjaner and B. Ivanov, Multi-Objective Optimization of Dairy Supply Chain, book series on Computer Aided Chemical Engineering, Elsevier, volume 25, pp. 781-786, ESCAPE 17th , May 27-30, Bucharest, Romania . Optimal Product Portfolio [tons] Optimal Product Portfolio [tons] Pareto-Frontier contour plot

17. 3. DISTRIBUTED FRAMEWORK FOR PLANNING AND SCHEDULING OF BATCH PLANTS “SUPPLY CHAIN” software – IChE (BAS) Distributors Markets Suppliers Plants Warehouses MOPP scheduling software – UPC ((SPAIN) MOPP B.B Ivanov, K.I. Mintchev, Supply chain optimization of batch chemical plants comprising continuous flexible process networks, Bulgarian Chemical Communication,Volume 39, No2, pp.106-118, 2007.

18. 3. DISTRIBUTED FRAMEWORK FOR PLANNING AND SCHEDULING OF BATCH PLANTS Architecture Server BAS.BG Planning of SC Package “Supply Chain” Numerical methods Client Server UPC.ES Production and resources scheduling Package MOPP Numerical methods Analysis and control of schedules

19. 3. DISTRIBUTED FRAMEWORK FOR PLANNING AND SCHEDULING OF BATCH PLANTS Functionalities • Initiation and access to both simulating packages; • 2. Input, manage and update all required information; • 3. Set up variables needed for calculation in each package; • 4. Access and choice the appropriated numerical methods to solve respective problems; • 5. Run problems and obtain respective results; • 6. Ensure forward and back communication between both levels; • 7. Analysis and control of the results at each level; • 8. Provide different intersection of the results obtained at each level.

20. 3. DISTRIBUTED FRAMEWORK FOR PLANNING AND SCHEDULING OF BATCH PLANTS Information Flows

21. 3. DISTRIBUTED FRAMEWORK FOR PLANNING AND SCHEDULING OF BATCH PLANTS Results: J. M. Laínez, C. Benqlilou, A. Espuña, B. Ivanov, N. Vaklieva, L. Puigjaner, Use of CAPE-OPEN standards in the coordinated optimization of plant production scheduling and supply chain planning, Book of Abstracts, 6th European Congress of Chemical Engineering, September 16-21, 2007, Copenhagen, Denmark

22. ACKNOWLEDGEMENTS: The collaborative project: “Distributed and CAPE-OPEN Compliant Platform for Planning and Scheduling of Multi-Site Manufacturing Systems” is carried out by the financial support of : 1. Bulgarian NCSR- contract I-1404 2. IX Commission for Scientific and Technical Cooperation between Spain and Bulgaria The investigations under this project are done by the following researchers: THANK YOU !