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Approaches to an available-to-promise system

Approaches to an available-to-promise system. 2004. 5. 17 MAI Lab. 김지연. Papers. An available-to-promise system for TFT LCD manufacturing in supply chain Bongju Jeong, et. al. (2002) A Web-enhanced dynamic BOM-based available-to-promise system MohuaXiong. et. al. (2003).

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Approaches to an available-to-promise system

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  1. Approaches to an available-to-promise system 2004. 5. 17 MAI Lab. 김지연

  2. Papers • An available-to-promise system for TFT LCD manufacturing in supply chain • Bongju Jeong, et. al. (2002) • A Web-enhanced dynamic BOM-based available-to-promise system • MohuaXiong. et. al. (2003)

  3. An available-to-promise systemfor TFT LCD manufacturingin supply chain Computers & Industrial Engineering 43 (2002) 191-212 Bongju Jeong*, Seung-Bae Sim, Ho-Sang Jeong, Si-Won Kim Department of Industrial Systems Engineering, Yonsei University

  4. Contents • Importance of ATP • TFT LCD Manufacturing Process • Proposal of an ATP system • A scheduling heuristics for TFT LCD module assembly line • The computational Procedure of CATP* • Computational results • Conclusion *Capacity Available To Promise

  5. TFT LCD Manufacturing Process • Module Assembly stage에서 customer spec에 맞는 제품을 생산한다→ 이 단계에서의 capacity allocation이 ATP에 영향을 미친다 TFT Fabrication LC Assembly Module Assembly 4 days 3 days 8 hours

  6. The Architecture of ATP System Demand Planning ATP System Material Requirement Planning Shop Floor Control Capacity Allocation (CATP) DC Inventory Allocation Computing ATP Customer

  7. ATP System 1 : Indices • QTYj : the order quantity for order j • Dj : the due date for order j • Prj : the priority of order j • Pj[Fm] : the production quantity in Fm for product of order j • mjs : the quantity of material s required for producing one unit of the product of order j • ms[Fm] : the planned incoming quantity of material s to factory m • LOCAj : the delivery location for order j • LOCADCl : the location of DCl • LOCAfm : the location of factory m • Time[LOCAj, DCl] : the expected transportation time from DCl to LOCAj • Time[DCl, Fm] : the transportation time between DCl and factory m • INVj[DCl,] : the inventory in DCl for product of order j • ∆INV[Fm, DCl] : the available inventory from factory m to DCl for product of order j • ∆INVjold[DCl] : the planned incoming inventory to DCl for product of confirmed order j • INVj[Fm,] : the inventory in Fm for product of order j • INV[mjs,] : the inventory of material s used for product of order j

  8. ATP System 2 • The selection priority for order j • ci : the weight factor for order type i • Isj : the arrival sequence of order j

  9. ATP System 3 : Procedure of SC-ATP • Step 1 : Determine order priority • For all the orders placed on the same day, determine SEQj • Step 2 : Determine DC priority • Step 3 : Compute DC inventory • 1) Compute the factory inventory, INVj[Fm,]for all j, m • 2) Compute the DC inventory, INVj[DCl,] for all j, l

  10. ATP System 4 : Inventory Change • The production inventory change • Case 1 : no material shortage • Case 2 : there is material shortage • The material inventory change • The DC inventory change

  11. ATP System 5 : Procedure of SC-ATP • Step 4 : Compute ATP • 1) The DC inventory is greater than order quantity, the earliest ATP is • If EATPj≤ due date • Otherwise, check the unused capacity.. • 2) otherwise check the unused capacity. If there is not enough additional capacity, inform the customer the unfulfillment • Step 5 : Update data and repeat

  12. Results : ATP computation • Data • 2 DCs, 3 factories, the module assembly schedule during 30 days • 8 parallel machine, 10 different types of products • 78 distinct customer orders ere randomly placed during the first 15 days • Factory-ATP : use average throughput rate and do not consider DC inventory • Factory-ATP’ : Factory-ATP – Time[DCl, Fm] • DC-ATP : use only the average DC inventory and do not consider the unused factory capacity

  13. Scheduling the Module Assembly Line - indices

  14. Scheduling the Module Assembly Line - LP formulation • Object function • Subject to

  15. Scheduling Heuristics Start Select one product type • Linear programming → MST(Minimum Setup Time) • MRFS(Material Requirement Feasible Solution)→ CFS(Capacity Feasible Solution) • Termination Conditions • 1) There exists no remained production capacity fir all machines • 2) There exists no remained product if there exists a machinewhich required no setup time no For planned product type Assign the producton the machine For unplanned product type If all product typesare tested no Apply MST rule toall unscheduled products End

  16. Results : The Scheduling Heuristics • Data • A set of actual data collected during 5 days, 11 types of products

  17. Results : The Scheduling Heuristics • PR : Production progressiveness

  18. Results : The Scheduling Heuristics

  19. Computing CATP • Step 1 : Forward calculation • Compute the earliest start time(ES) and the earliest finish time(EF) • Step 2 : Backward calculation • Compute the latest start time(LS) and the latest finish time(LF) • Step 3 : CTP calculation • Case 1 : CTPit≥QTYjTjm • Cjm*t : the completion time for order j on machine m* starting at period t • D’j : the factory-out due date in order to meet the customer due data • Case 2 : Otherwise → Order cannot be satisfied

  20. Numerical Example

  21. Numerical Example • If we received a new orderat time period 9 • 133*6 product, quantity=3factory-out due data=26 • CATP=9+3*5=24

  22. A Web-enhanced dynamic BOM-basedavailable-to-promise system Int. J. Production Economics 84 (2003) 133–147 MohuaXionga, Shu Beng Tora, Li Pheng Khoob, Chun-Hsien Chenb a Singapore-MIT Alliance, SMA-NTU Office, N2-B2C-15, Nanyang Technological University, Singapore b School of Mechanical and Production Engineering, Nanyang Technological University, Singapore

  23. Contents • Introduction • Web-based engineering applications • Dynamic BOM and ATP • ATP Computation • System Architecture of an ATP System • Implementation issues • A case study • Conclusions

  24. The basic notions of ATP • Bjk : k the number of kth child component required to produce a single unit of jth type of parent component • Qimax(t) : the maximum number of product type i available at time bucket t • Ri(t) : the quantity required to produce product type i • Qi(t) : the actual quantity planned to deliver at time bucket t • Qi1(t) : the finished product inventory, which can be delivered to customer at time bucket t • Qi2(t) : the number of product, which is scheduled to produce based on the BOM explosion in relation to the availability of each component • Oi(t) : the customer order quantity to be delivered at time bucket t for product type i • ∆Qi(t) : the quantity, which the planner adjusts for time bucket t

  25. Dynamic BOM • : the BOM quantity • : the lead-time accumulated along the BOM structure, • A dynamic BOM : a single-level structure consist of critical items Updated by replacing the critical item with its immediate child items • A critical item : a component that restricts the full commitment due to its material availability Qisj(t) : the scheduled quantities received for the jth type of component

  26. ATP computation • 1. Sequence Pi ; for i=1, 2, .., n, according to the priority of finished products from high to low • 2. For product i, Compute finished product inventory, Qi1(t) If Qi1(t) ≥ Ri(t), consume product availability and go to 1 • 3. Otherwise search for the critical item and update dynamic BOM If the critical item has an immediate child item, calculate Qi2(t) • If Qi2(t) ≥ Ri(t)-Qi1(t), consume material availability for all dynamic BOM components and go to 1 • Otherwise consume material availability for all dynamic BOM components and repeat this step Otherwise compute material shortfall • 4. Repeat for all the products

  27. System Architecture • IIS : Microsoft Internet Information Server • MTS : Microsoft Transaction Server • MSMQ : Microsoft Message Queue Server • ADO : ActiveX Data Object • ODBC : Open Database Connectivity

  28. A Case Study

  29. A Case Study : Result

  30. Conclusion • Because of availability of timely and appropriate information, the proposed system should improve the decision-making process. • Based on dynamic BOM, ATP computation is easy to take into consideration the material availability for all components. • Advantages Web based ATP system systems: • easy to use, easy to update, cater for a number of users simultaneously • better and faster response time to users requirement • enterprise-wide, even world-wide, accessibility to the Web from any computing platform • substantial cost savings in investment • But there are no capacity constraints!

  31. Discussion • ATP 기능을 수행하는 application들은 상당수 존재하나, ATP system을 다루는 연구는 많지 않다. • 상용화된 제품들에 사용된 알고리즘은 어떤 것인가? • 앞으로는 여러 분야의 논문과 책들을 다양하게 공부할 예정.

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