Scheduling Systems Overview

1
Topic 22

• Scheduling Systems Overview

2
Implementation

• Scheduling models
• Solution methods
• Advanced Planning and Scheduling (APS) system
• Enterprise-wide information system (ERP)

System Design
3
Overview

• Context for scheduling systems
• Enterprise Resource Planning
• Levels of planning
• Elements of scheduling systems
• Database
• Schedule generator
• User interface

4
ERP Systems

• Enterprise Resource Planning (ERP) system
• Enterprise wide information system
• Single master database
• Origins in manufacturing
• Computer Integrated Manufacturing (CIM)
• Materials Requirement Planning (MRP)
• Ties with back office functions
• Accounting, marketing, manufacturing, etc

5
ERP Systems
Database
Materials Requirement Planning (MRP)
Marketing and Sales
Scheduling
Product Definition
6
Advanced Planning and Scheduling (APS) Systems
Database Management
Automatic Schedule Generator
Schedule Editor
Performance Evaluation
Graphical User Interface (GUI)
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Generic or Application Specific

• Generic
• May require a great deal of customization
• Relatively inexpensive but slower
• Support from software vendor
• Applications specific
• Large problems/databases
• Specialized scheduling environment
• In-house maintenance

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Topic 23

• Planning Levels

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Scope of Scheduling

• Scheduling determining how to use resources in
  the optimal manner
• Many levels
• abstraction of resources
• e.g., plants, work stations, machines, tools
• time horizon

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Levels of Scheduling

• Long-range planning 2-5 years
• Middle-range planning 1-2 years
• Short-range planning 3-6 months
• Scheduling 2-6 weeks
• Reactive scheduling 1-3 days

ERP
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Industry Example Oracle
Source http//www.oracle.com/applications/B2B/Pla
nning/index.html?solution.html
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Long-Range Planning

• Problems
• Plant expansion
• Plant layout
• Plant design
• Most important forecasting issues
• Lot sizing models used but not very successfully
  (see later)
• Need stochastic models

13
Middle-Range Planning

• Problems
• Production smoothing
• Logistics
• Scheduling successful at this level
• Forecasting remains difficult

14
Short-Range Planning

• Problems
• Material Requirements Planning (MRP)
• Setting due dates and release times
• MRP
• Starts with mid-range production schedule
• Known orders statistical predictions
• Obtain master schedule
• Assumes infinite capacity and whole day buckets

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Scheduling

• Problems
• Job shop routing
• Assembly line balancing
• Process batch sizing
• Given due dates, raw material release time
• Typically develop 6 week schedule once a week

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Reactive Scheduling

• Problems
• Hot jobs
• Down machines
• Late material
• Make corrections
• Human element
• Interactive scheduling and reoptimization

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Hierarchy

• Traditional
• Top-down
• Long-range planning ?? scheduling
• New development
• ERP allows greater integration
• More interaction

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ERP System Interactions

• Advanced Planning and Scheduling
• Scheduling
• Capacity management

ASP System
Production Schedule Due Dates
Bill of Materials Routings
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ERP Systems (example)
MRP System
What if ?
Complete integration
- high priority order - schedule overtime
ASP System
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Topic 24

• Data Databases

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Databases

• Custom or commercial database system
• Microsoft SQL Server, Oracle, Sybase
• Structured Query Language (SQL)
• Basic functions
• Editing
• Sorting
• Searching

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Types of Data

• Static Data
• Number of machines
• Layout
• Due date
• Release date
• Dynamic Data
• Starting time
• Completion time
• Sequence of jobs
• Tardiness

Independent of the schedule
Depend on the schedule
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Job Data
Job Data Type
ID
Name
Type
Quantity
Priority
Ready
Due
Job Instance
2
IBM
4
160
2
10
200
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Job Object
Job ID Name Type Quantity Priority Ready Due cre
ate copy delete display
ID 2 Name IBM Type 4 Quantity
160 Priority 2 Ready 10 Due
200 create copy delete display
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General Enterprise Data

• Plant layout
• Work centers and machines
• Resource calendar
• Shift schedules, holidays, maintenance schedules
• Routing table
• Which machines can be used, precedence constraints

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Topic 25

• Schedule Generation

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Schedule Generation

• Algorithm Approach
• (This is what we have been doing.)
• Knowledge-Based Approach

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Algorithm Approach

• Mathematical formulation
• decision variables
• objectives
• constraints
• Three phases

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Knowledge-Based Approach
Scheduler knowledge of system
Rules and objects
Data Mining
Historical data

• Underlying problem structures
• Feasible/preferred solution

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Algorithm Approach Characteristics

• Is mathematical formulation possible?
• Rule of thumb should be applied for systems with
• Large number of jobs
• Minimum randomness
• Frequent real-time optimization
• Consistent general rules

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Knowledge-Based Approach Characteristics

• Any feasible schedule suffices
• May be easier to adapt to system changes
• Hybrid of both approaches?
• Recent convergence
• Unusual to find a system that does not have some
  elements of each

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Topic 26

• User Interfaces

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User Interfaces

• Very important part of the system
• May determine if system is used or not
• Several different types
• Gantt chart
• Dispatch list
• Capacity bucket list
• Throughput diagram

Graphical interfaces
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Gantt Chart

• Most popular
• Good overview of schedules
• tardy jobs
• machine utilization
• Disadvantages
• limited when many jobs/machines
• Drag-and-drop
• cascading/propagation effect, reoptimization

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Dispatch List

• Ordered list of jobs
• starting time
• machine
• processing time
• due date, etc.
• Unlimited number of jobs
• Overview with respect to time limited

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Capacity Buckets

• Partition time into slots or buckets
• Processing capacity of each machine known
• Percentage of capacity used in each bucket
• Medium to long-range planning

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Throughput Diagram

• Total orders
• received
• produced
• shipped
• Over time
• Information on
• Machine utilization
• WIP

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Topic 27

• Internet Scheduling

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E-Scheduling

• Information access systems
• Electronic Data Interchange (EDI)
• Information coordination systems
• Internet GUI
• Information processing systems
• Actual scheduling done over the Internet
• Internet scheduling systems

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Information Processing Systems

• Application Service Providers (ASP)
• Host enterprise software
• Clients access via the Internet
• Pay on per-use basis
• Advantages
• Low initial cost
• System support from ASP
• Reaches midsize to smaller enterprises
• Hot for ERP, etc.

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Possible Directions

• Standardization
• Customization

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Internet Scheduling

• Network structure
• Scheduling server(s)
• Local clients
• Advantages
• Local clients can support GUIs
• Server/clients can share data management
• Servers can jointly (distributed) solve large
  scheduling problems

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Internet System Design
Server
Client
Server Database
Client Database
Internet
Schedule Information
Process Information
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Division of Labor
Server
Client
Server Database
Client Database
Internet
Select (suggest) algorithm Run algorithm Create
schedule display
Formulate problem (Select algorithm) (Run
algorithm) Display schedule
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New Algorithm Generation
Main Algorithm Library
First Algorithm
Algorithm Generator
Composite Algorithm
Server
Internet
Local Algorithm Library
Client
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Tools

• Existing Internet support
• Markup Languages HTML, XML, DHTML
• Java Applets
• Scripting JavaScript, VBScript, etc.
• Active Server Pages (ASP)
• Browsers
• Netscape
• Internet Explorer (IE)
• Compatibility

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Applying the Tools
Server
Client
Server Database
Client Database
Internet
ASP VBScript - Select algorithm Java (other)
- Run algorithm
HTML - XML for scheduling JavaScript -
Define problem Java Applets - Display results
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Discussion

• Future of all enterprise software
• Advantages
• Higher speed at lower cost
• Challenges
• Ownership of data/systems
• Customization versus standardization
• Security
• Effective designs? Collaboration?

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Future of Scheduling

• System development
• E-Scheduling!
• Integration with other function
• Availability of data (mining?)
• Computing power
• ?
• ? Increased importance of scheduling