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The BALTPORTS-IT Project:

The BALTPORTS-IT Project:. Dr.Eberhard BLUMEL 1 , prof.,habil.dr. Leonid NOVITSKI 2 , prof.,habil.dr. Henrikas PRANEVICIUS 3 , prof.,habil.dr. Yuri MERKURYEV 2. Application of Simulation Models and IT solutions in Maritime Sector of the Baltic States. 1 Frauhofer IFF, Germany

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The BALTPORTS-IT Project:

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  1. The BALTPORTS-IT Project: Dr.Eberhard BLUMEL1, prof.,habil.dr. Leonid NOVITSKI2, prof.,habil.dr. Henrikas PRANEVICIUS3, prof.,habil.dr. Yuri MERKURYEV2 • Application of Simulation Models and IT solutions in Maritime Sector of the Baltic States 1Frauhofer IFF, Germany 2Riga Technical University, Latvia 3Kaunas University of Technology, Lithuania WP7 Marine information Systems KUT

  2. WP7 Marine information Systems KUT H.Pranevicius

  3. WP7 Marine information Systems KUT H.Pranevicius

  4. Objectives • Set-up of  the Baltic sub-regional Competence Center for promoting and supporting the distribution of research knowledge in the field of advanced IT-solutions and simulation with maritime applications, Riga (Latvia) • Dissemination of research knowledge gained during the execution of the EC projects AMCAI, DAMAC-HP and SPHERE and regional project in the field of IT-solutions and simulation of harbor managing • Industrial customisation and exploitation of the project results from AMCAI, DAMAC-HP, ITMK and SPHERE by involving user groups in the Baltic region • Development of recommendations for the application of results and thus creating new market opportunities • Creating opportunities for the training of specialists in maritime information systems design and port logistics by using web-based technologies and distance learning courses WP7 Marine information Systems KUT H.Pranevicius

  5. Expected Results The industrial customisation of simulation systems in collaboration with  user groups from the Baltic region will provide new approaches for • the non-monetary evaluation of general characteristics for port operations • the optimisation of logistic operations in container terminals • the optimisation of logistic processes in oil terminals • a methodology of combining port simulation and information systems. A demonstrator for distributed and web-based simulation of port environments will be built. WP7 Marine information Systems KUT H.Pranevicius

  6. Piece-linear aggregate formalism for business process analysis WP7 Marine information Systems KUT H.Pranevicius

  7. Purpose • To create the dynamical models of business processes in Klaipeda oil terminal, which could be used to evaluate logistic processes of oil transportation and in terminal operative information system WP7 Marine information Systems KUT H.Pranevicius

  8. Concepts of Business Process Modeling • Goal; • Activity; • Time; • Change; • Chronicle; • Event. WP7 Marine information Systems KUT H.Pranevicius

  9. PIECE-LINEAR AGGREGATES (PLA) FORMALISM WP7 Marine information Systems KUT H.Pranevicius

  10. DEFINITION OF PIECE-LINEAR AGGREGATES (PLA) • PLA belongs to the class of automata models and defined by • The state of aggregate consists of two components: where WP7 Marine information Systems KUT H.Pranevicius

  11. TRAJECTORY OF PLA • In time intervals when there are no input signals • The state of aggregate changes in discrete time instances • input signal arrives, • continuous component acquires zero value. Transition and output operators WP7 Marine information Systems KUT H.Pranevicius

  12. Piece-linear Markov processes (PLMP) ( prof. I. Kovalenko ) Modelling Piece-linear aggregates (PLA) PLA = Aggregates + PLMP ( prof. N. Buslenko ) Simulation PLA + Controlling Sequences ( prof. H. Pranevicius ) Formal specification, simulation & validation Behavior analysis Performance analysis THEORETICAL BACKGROUNDOF PLA WP7 Marine information Systems KUT H.Pranevicius

  13. THE USE OF CONTROL SEQUENCES FOR FORMAL SPECIFICATION OF PLA • Two kinds of events are introduced: (injection). • The set of operations is introduced: • - duration of the i-th operation. WP7 Marine information Systems KUT H.Pranevicius

  14. THE USE OF CONTROL SEQUENCES FOR FORMAL SPECIFICATION OF PLA • The time instant when the j-th operation ends is defined by co-ordinate: • – number of events which have occurred during time interval . WP7 Marine information Systems KUT H.Pranevicius

  15. THE USE OF CONTROL SEQUENCES FOR FORMAL SPECIFICATION OF PLA • The set of co-ordinates defines the continuous component of PLA: • Remark. Co-ordinates , , can change their values only in discrete time instances WP7 Marine information Systems KUT H.Pranevicius

  16. TIME OF EVENT OCCURENCE • Next time instant when internal event occurs is calculated: • Recalculation of continuous co-ordinates: WP7 Marine information Systems KUT H.Pranevicius

  17. Relation between concepts used in conceptual description of business process and PLA Goal Final state: Z(tm) Activity Operation: Time Time: tm Change Transition operator: H(e) Event Events: E’, E’’ Chronicle Z(t1), Z(t2), … Z(tm) WP7 Marine information Systems KUT H.Pranevicius

  18. Methodology used for creation dynamical models of harbor business processes • Object-oriented analysis and design method (OOA&D); • Piece-linear aggregate formalism (PLA); • The use UML for integration OOA&D and PLA. WP7 Marine information Systems KUT H.Pranevicius

  19. Main activities of OOA&D method Problem- domain analysis Application-domain analysis Req. Model Component design Spec. Spec. Architectural design WP7 Marine information Systems KUT H.Pranevicius

  20. Customization and exploitation of port simulation systems • Simulation system for evaluation of logistics process of oil terminal WP7 Marine information Systems KUT H.Pranevicius

  21. The main components of logistic process of oil transportation through Klaipeda WP7 Marine information Systems KUT H.Pranevicius

  22. Streams interaction scheme WP7 Marine information Systems KUT H.Pranevicius

  23. The structure of model WP7 Marine information Systems KUT H.Pranevicius

  24. Streams in oil terminal • Stream of orders transported oil products through terminal • Stream of trains • Stream of tankers WP7 Marine information Systems KUT H.Pranevicius

  25. Parameters of model (1) • Parameters of terminal input streams: • Annual amount of transported oil. • Part of total amount of transported oil for each kind of oil. • Size of ordered oil. • Time interval during which oil products have to be delivered by trains. • Time interval after the start of service, after which the tanker have to arrive. • Number of wagons in train. • Capacity of wagon. WP7 Marine information Systems KUT H.Pranevicius

  26. Parameters of model (2) • Parameters characterizing the structure of terminal: • Number of reservoirs and their capacities which are used for each kind of oil. • Number platforms. • Subsets of platforms used to service of different kind of oil • Number of wagons in each platform which can be served at the same time. • Subsets of embankments used to service of different kind of oil. WP7 Marine information Systems KUT H.Pranevicius

  27. Parameters of model (3) • Technological parameters of terminal: • Time during which oil products are poured from wagons to reservoirs for each kind of oil • Rate of pouring oil from reservoirs to tanker WP7 Marine information Systems KUT H.Pranevicius

  28. Parameters of model (4) • Parameters characterizing control of terminal: • Order performance decision making algorithm which evaluates the number of wagons which are in railway station. • Order performance decision making algorithm which does not evaluate the number of wagons which are in railway station. • Algorithm carrying orders of tankers and evaluating only needed amount empty reservoir for realization of order. • Algorithm carrying orders of tankers and evaluating needed amount empty reservoir for realization of order and number of wagons in railway station. WP7 Marine information Systems KUT H.Pranevicius

  29. Simulated characteristics (1) • Characteristics characterizing terminal processes: • Number of wagons in terminal railway stations. • Number of wagons in terminal railway station for each kind of oil product. • Occupation coefficient of each platform. • Average level of oil in reservoirs. • Occupation coefficient of each embankments. WP7 Marine information Systems KUT H.Pranevicius

  30. Simulated characteristics (2) • Characteristics about performance of order for oil transportation: • Wagons stay time in terminal, for different kinds of oil. • Tankers stay time in terminal, for different kinds of oil. • The performance time of order from time instant when the order has been done till tanker leaves the terminal, for different kinds of oil products. • The performance time of order from time instance when begins the transportation oil to terminal till tanker leaves the terminal, for different kinds of oil products. • Average time of storing of oil products in terminal reservoirs for different kinds of oil. WP7 Marine information Systems KUT H.Pranevicius

  31. Average level of oil in reservoirs WP7 Marine information Systems KUT H.Pranevicius

  32. Average transportation time of oil WP7 Marine information Systems KUT H.Pranevicius

  33. Average service time of orders WP7 Marine information Systems KUT H.Pranevicius

  34. Maximum and average number wagon in railway station WP7 Marine information Systems KUT H.Pranevicius

  35. Distribution function service time of orders WP7 Marine information Systems KUT H.Pranevicius

  36. Distribution function of wagons stay time in terminal WP7 Marine information Systems KUT H.Pranevicius

  37. Conclusions • The use of aggregate method permitted to formalize logistic process of oil transportation. • Performed investigations with simulation model showed main factors that influence transportation duration through Klaipeda terminal are annual amount of transported oil and used operative control algorithms. • In order to fulfill user requirements to deliver oil to destination during specified time in some cases it is needed to restrict incoming stream of orders. WP7 Marine information Systems KUT H.Pranevicius

  38. Integration of Klaipeda Oil Terminal Simulation System into IMS WP7 Marine information Systems KUT H.Pranevicius

  39. Operative control system of Klaipeda oil terminal Service of tankers Service of wagons DB WP7 Marine information Systems KUT H.Pranevicius

  40. Service of wagons • Registration of orders for load of oil products • Creation of monthly schedule for loading wagons • Receiving telegrams about arriving trains • Unloading wagons WP7 Marine information Systems KUT H.Pranevicius

  41. Service of tankers • Registration of request about possible arrival of tankers • Confirmation that tanker will be served • Registration of information about arriving tankers • Loading of tankers • Creation and adjustment of loading schedule for tankers WP7 Marine information Systems KUT H.Pranevicius

  42. Table views SQL queries Creation of loading schedule for tankers Visualization Simulation model DB WP7 Marine information Systems KUT H.Pranevicius

  43. The use of simulation for forecasting • Forecasting of business process can be evaluated by means of simulation; • For realization forecasting it is needed to create simulation model which have to be integrated to information system. WP7 Marine information Systems KUT H.Pranevicius

  44. Creation of simulation models methodology • Methodology use : • UML for problem domain analysis; • PLA for creating simulation model; • Microsoft .NET Framework for simulation model implementation and integration to IS. WP7 Marine information Systems KUT H.Pranevicius

  45. DataSet Use ADO.NET for integration ADO.NET Simulation model DataAdapter Connection DB WP7 Marine information Systems KUT H.Pranevicius

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