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Diploma Thesis Martin Homik Resource Optimization of Workflow Problems Tutors: Christian Schulte Tobias Müller
Overview ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Motivation: Bulk Production   ,[object Object],[object Object],[object Object],[object Object],[object Object],Object  A Object  B
Motivation: Bulk Production   ,[object Object],[object Object],[object Object],[object Object],[object Object],Object  A+B
Motivation ,[object Object],[object Object],[object Object],[object Object],[object Object],Abstraction as a workflow problem!
Workflow Abstraction ,[object Object],[object Object],[object Object],[object Object]
Workflow Abstraction Levels ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Process definition : is a data structure which contains informations about process logic, organisation and infrastructure.
Terms ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Attributed Resources (Workflow Participant Types) C = Cost Sut = set-up time St = Stability Skills overlap arbitrarily! 11, 12, 15 12, 13, 16, 19 17, 18, 19 C: 400  € Sut: 200 St: 95% C: 150  € Sut: 200 St: 90% C: 250  € Sut: 200 St: 95% Overlap Overlap
Partially Ordered Plan (POP) Each activity has to be executet! 0 12 13 15 16 17 18 19 100 11 Start End Activity Precedence relation
Flexible Processes 0 12 13 15 16 17 18 19 100 11 0 12 13 15 17 18 19 100 11 20 0 12 13 15 16 17 19 100 11 21 22
Continuous Supply There is always work to do at each station! Object are passed only in one direction!
Balance running time ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Problem Specification (Given) maximal cycle time 0 12 13 15 16 17 18 19 100 11 0 12 13 15 17 18 19 100 11 20 0 12 13 15 16 17 19 100 11 21 22
Problem Specification (2) Organisation? Infrastructure? Block i A j
Problem Specification (2) Organisation? Infrastructure? Process logic? Block i A j
Partitioning (Example) Partitioning guarantees a  directed data flow! 0 12 13 15 16 17 18 19 100 11 0 12 13 15 16 17 18 19 100 11
Partitioning 0 12 13 15 16 17 18 19 100 11 11, 12, 15 12, 13, 16, 19 17, 18, 19 1. Rule: 15  16:  15 in 16 in  different blocks
Partitioning (2) 11, 12, 15 12, 13, 16, 19 17, 18, 19 0 12 13 15 16 17 18 19 100 11 2. Rule: 12  15:  12 in  and 15 in  the same block
Partitioning (3) 0 12 13 15 16 17 18 19 100 11 3. Rule: 16  19:  16 in 19 in  and  a) different blocks b) the same block 11, 12, 15 12, 13, 16, 19 17, 18, 19
Basic Model ,[object Object],[object Object],[object Object],[object Object]
Model: Data Structures Number blocks: Set of all costs: General loss: Maximum cycle time : Set of all activities:  Set of all dates: Set of percentage:
Model: Resource Projections :
Model: Data Structures Costs: Participant type tuple: Number participant types tuple:
Model: POP A POP is a directed, acyclic and compound graph: We denote the set of all POPs  by : Nodes  Edges Projections :
Model: POP Union: Let Then
Model: Partition Partition of A u  in: Let and And ...next slide
Model: Partition(2) Otherwise: Properties of a directed flow:
Model: Partition(3) General Assignment:
Total Running Time per Block set-up time running times transit time total running time / block t A1 U A2 U A3 Su1 Su2
Infrastructure Number of resources in a block S i  (where WPT W i ) Number  resources Rtb
Infrastructur (2) ,[object Object],[object Object],[object Object],[object Object],26 8 7 6 5 Sum 8 7 0 1 Process 2 8 4 6 5 Process 1
Cycle Time number resources cycle time
Cycle Time (2) ,[object Object],[object Object],[object Object],0 525 510 500 Process 2 511 531 520 489 Process 1
Heuristic (Design) number blocks Number of blocks is increasing resources Choose the block with the least resource type assignment possibilities. Assign  the cheapest resource type. activities Choose the longest activity. Assign it to the block with the cheapest resource.
Goal-oriented Heuristic 2.  Order/Select: choose longest activity 1.  Filter: nondetermined activity 3.  Value: assign to the block with the cheapest WPT. 400 € 150 € 250 €
Problem: Goal-oriented Heuristic Bad! 400 € 150 € 250 €
Problem: Goal-oriented Heuristic Better! 400 € 150 € 250 €
Implementation (Woop) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Implementation (Woop) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Results ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Precise Model  ,[object Object],Reduced tool magazines More blocks Increase in complexity Costs: Resources, Blocks, Tools
Precise Model (2) ,[object Object],Local duration times: ,[object Object],More exact results No improvement in runtime!
Contribution (Summary) ,[object Object],Abstraction:  of a manufacturing problem as a ... Workflow Problem:  definition und analysis Woop:  implementation of a software for finding generic solutions ;  Mozart/Oz ; Technique: CP Identification of a new  class  of problems
Related Work ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Related Work(2) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Scheduling (Bridge) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Scheduling (Bridge) 2 4 5 6 7 3 1 8 9 11 13 14 15 16 12 17 19 20 21 22 18 23 25 26 27 28 24 10 41 29 31 32 33 34 30 36 38 39 40 35 37 42 43 44 excavator Pile driver carpentry concrete mixer worker bricklaying crane caterpillar

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Woop - Workflow Optimizer

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  1. My talk is about ...