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Agent-based supply chain planning in the forest products industry

Agent-based supply chain planning in the forest products industry. Sophie D’Amours Ph.D. Professor, Université Laval General Director, Research Consortium FOR@C Canada Research Chair on planning value creation network. Agenda. FOR@C Research Consortium Forest products industry

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Agent-based supply chain planning in the forest products industry

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  1. Agent-based supply chain planning in the forest products industry Sophie D’Amours Ph.D. Professor, Université Laval General Director, Research Consortium FOR@C Canada Research Chair on planning value creation network

  2. Agenda • FOR@C Research Consortium • Forest products industry • Supply chain planning challenges in the forest products industry • Supply chain scheduling: application to the lumber industry • FOR@C V-Lumber Experimental Platform • Agent-based simulation in supply chain

  3. T o become a Canadian and International centre of expertise in the development of the knowledge and skills required to integrate and optimize value creation networks in the forest products industry by taking advantage of the potential of new technologies and electronic business models. Mission of the Consortium

  4. Partners

  5. Supply chain

  6. Forest products supply chain

  7. Canadian Industry Snapshot • 3% GDP • Exports for 45 billion $ of lumber, pulp and paper every year • Contributing 60% to the net export of Canada • 900 000 direct and indirect jobs • More than 350 localities depend economically on the industry Source: FPAC, March 2006

  8. Québec 80% is public land • The forests of the province of Quebec cover 750 000 km², that is the equivalent of Sweden and Norway combined. • It counts for 20 % of forested land in Canada and 2 % of all the world’s forests. • This is why the vast majority of foreigners see Quebec as a huge green carpet.

  9. Fiber flow

  10. Fiber transformation

  11. Forest supply chain customers customers customers

  12. Pulp and paper supply chain

  13. Transportation in the supply chain

  14. Supply chain planning challenges in the forest products industry

  15. Top 5 International paper (~$26 B) Weyerhaeuser (~ $20 B) Georgia Pacific (~ $20 B) Stora Enso (~ $15 B) Kimberly Clark (~ $15 B) PWC – Global Forest and Paper Industry Survey 2005 • In the United States at December 31, 2005, the Company operated 23 pulp, paper and packaging mills, 93 converting and packaging plants, 25 wood products facilities, six speciality chemicals plants and 270 distribution branches.

  16. Merchants Converters Mills Satellite Warehouses Distribution Centers Ship to points Domtar supply chain

  17. Harvesting/procurement plan 2007 2008 2006 Sustainable developmentRoad construction Mixed of products, uneven aged Plantation

  18. Alternative divergent processes • Trees are cut to produce a set of logs • Logs are cut to produce a set of lumbers • Chips are mixed to produce different grades of pulp and paper • Rolls are cut to produce a set of rolls or sheets Recipe/cutting pattern Attribute basedproducts Recipe/cutting pattern Recipe/cutting pattern Productivity not always linear Sequence dependent set-ups

  19. Commodity Price Trends N. American Consumption/Real GDP Global Consumption/Real GDP Source: RISI, CIBC World Markets Source: RISI, CIBC World Markets • In North America, the link between consumption and real GDP is falling for all the major grades of paper, but worst for newsprint. • Even globally, the link between consumption and real GDP plateaued in the mid-1990s. Source; Roberts, 2005, Vision 2015 FOR@C

  20. Markets Facilities Demand/supply propagation Mix of spot market and contracts

  21. Advanced Planning System for the Pulp and Paper Industry (APS-PPI)

  22. Distributed planning systems Top level planning problem Final Set ofdecisions IN* Anticipationfunctions Instructions Anticipation model ofthe base levelplanning problems ReactionRE* InstructionIN* Base level planning model Schneeweiss (2003)

  23. Supply chain scheduling: application to the lumber industry

  24. Scheduling • Decide what to do, when to do it and how to do it • Support mixed mode: Pull & Push • Satisfy demand (committed orders & contracts) • Maximize throughput value • Constraints: • Planned available inventory • Machine capacity (potential bottlenecks)

  25. Customers Customers Customers The lumber supply chain

  26. Log Requirement

  27. Sawing Line Plan Solved usingmathematicalprogramming (MIP or LP)

  28. Type 1 Type 2 Type 3 Sawing Cutting Pattern #9 2x3 2x4 Cutting Pattern #25 2x6 1x6 Cutting Pattern #12 Cutting Pattern #57

  29. Drying Plan Solved usinga constraint programmingmodel

  30. Drying Different Loading Patterns (products distribution) Kiln Dried Green Kiln Drying Different Drying Process Kiln Kiln Kiln Kiln Kiln Kiln Air Drying Yard Equalizing Kiln Drying

  31. Finishing Line Plan Solved usingheuristics

  32. Co-Products Management: Finishing 1 product type can results in 11 different product types simultaneously All of them can have demand: they are not by-products Campaign Optimization (Setup management) Finishing

  33. Shipment Orders Solved usinga linear programmingmodel

  34. order Supplier Production site Warehouse Sales Decentralised material Planning centre Supplier Production Site Warehouse Sales Centralised material Integration and system dynamics • Simple integration • Limited information exchanged • Impact of the bullwhip effect • Minimum return – local optimisation • Multi-site integration • Standardisation of exchanges and management objectives • Global optimisation • Large quantity of information (collect and maintain) • Transactional technologies available • Great potential return – but little success

  35. Planning challenges Global Performanceof the entire supply chain network (avoid local optimum et information distortion) Synchronization of decisions d-APS Manufacturing and logisticAgility (ability to re-plan quickly) Operation plans feasibility (avoid plans that are not feasible) Specialization of decisionsmodels and algorithms Decisions distribution and localizationwhere events must be managed

  36. Raise the needs for tools designed • To evolve in a decentralized, dynamic and specialized environment • To support demand and supply propagation with optimization (e.g. revenue management) • To integrate real-time execution information (e.g. event management systems, contingency planning) • To support collaboration (e.g. collaborative workflows)

  37. FOR@C V-Lumber Experimental Platform

  38. Distributed & Specialized Tools

  39. Planning Unit Planning Unit Planning Unit Supply Chain Planning Analysis Tools Agents Data Tactical planning unit Demand Plan Supply Plan Demand Plan Supply Plan Source Agent Deliver Agent Source Agent Deliver Agent Make Agent Make Agent Source Agent Deliver Agent Make Agent

  40. Agent Architecture

  41. Customer Agent Supplier Agent Workflow Workflow Workflow Conversation Conversation Conversation Event Event Event Event New Customer Supply New Customer Demand New Supplier Demand New Supplier Supply Planning © FOR@C – experimental platform

  42. Definition of collaboration • An intended cooperative action between two or more entities that exchange or share resources in order to take decisions or pursue an activity that will generate benefits or loss that are to be shared. From an intra-organizational perspectiveall resources can be view as shareable resources D’Amours et Frayret (2003)

  43. Concepts of collaboration • Main characteristics of inter-organizational collaboration (from literature): • Common goals and objectives, shared or jointly decidedJacobs (2002) • Implication of decision makersPollard (2002) • Mutual trust Jacobs (2002) • Through organisational structures Pollard (2002) • Shared operation planning and executionSimatupang and Sridharan (2002), Jacobs (2002), Schrage (1990) • Sharing of risk, rewards and responsibilitiesLambert and al. (1999) • Be more efficient, get a competitive advantageSimatupang and Sridharan (2002), Lambert and al. (1999), Pollard (2002) Three important dimensions of collaboration : Humain Organisationnal (strategy & process) Technology

  44. Concepts of collaboration Nature of exchanges Co-evolution complex Collaborative operation planning and execution • Contracts & mechanisms • Collaborative rules • Allocation • Pricing • Incentives… • Local & collective goals • Information & decisiontechnologies • Protocols & workflows Joint planning Information exchange relationship Transactionnal relationship simple weak strong Intensity of the collaboration Frayret, D’Amours and D’Amours 2003

  45. Value of collaboration • What to share? Information sharing • Information • Product • Antitrust law • How to share? Collaboration mechanism • Minimum cost solution • Equal % of benefit (e.g. Shapley value, Nucleus, externalities, etc.) • Equilibrium in between? • How to motivate? Contract and incentive designs • Premium • Volume guarantee

  46. Strategic game • Precisely, a strategic game consists of • a set of players • for each player, a set of actions (sometimes called strategies) • for each player, a payoff function that gives the player's payoff to each list of the players' actions. http://www.chass.utoronto.ca/~osborne/2x3/tutorial/SGAME.HTM

  47. Complex Sawing Wholesaler Wood Retailer Wood FOREST The wood supply game Retailer Paper Wholesaler Paper Saw Mill Satisfy demand Minimize inventory

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