Planning and Scheduling in Manufacturing and · PDF fileDetailed Scheduling Production...
Transcript of Planning and Scheduling in Manufacturing and · PDF fileDetailed Scheduling Production...
Planning and Scheduling in
Manufacturing and Services
Michael Pinedo
Stern School of Business
New York University
Planning and Scheduling
Issues in Manufacturing Planning and Scheduling Issues in Services System Implementation Issues Research Issues
Planning and Scheduling
Issues in Manufacturing Planning and Scheduling Issues in Services System Implementation Issues Research Issues
Plants DCs Customers Products Resources Supplier
Nowadays - Global Supply Chains
Supply Chains in Different Industries
PC-ASSEMBLY AUTOMOTIVE ASSEMBLY PAPER PRODUCTS
(Process Industries)
Glass
Monitors
Micro Processors
Memories
PC-Assembly
Iron ore Bauxite
Steel Aluminum
Electronic
Components
Engine
Car Assembly
Wood Chips
Chemicals
Reels
Rolls Ink
Paper Products
(Cutsize; Bags)
Supply Chain Characteristics
ASSEMBLY CONSUMER
PRODUCTS
(PC; Xerox machines)
AUTOMOTIVE
ASSEMBLY
BULK/PROCESS INDUSTRIES
(Paper; Pharmaceuticals; Plastics)
No Setup Times
In Assembly
Distribution (Fast)
(UPS)
MTO/MTS High
Impact of
E-Commerce High
B2C
DTC
Call-Center
Webcentric
Planning Horizon
Short
Scheduling:
More Dynamic (reactive)
Setup Costs in
Paint Shop
Distribution
(Trailer, (fast) ships)
MTO/MTS Medium
Impact of
E-Commerce Lower
B2C-B2B
EDI
Planning Horizon
Medium
Major Setup Costs
(Long Runs (Affect Quality))
Distribution (Slow)
(Trains, Barges, (slow) ships)
MTO/MTS Low
Impact of
E-Commerce Lowest
B2B
Planning Horizon
Long
Scheduling:
More Static
Applications of Planning and Scheduling
Theory in Various Supply Chain Models
• Applications in Process Industries
• Upstream: multi-echelon inventory theory
• Downstream: scheduling theory
• Applications in Automobile Manufacturing
• Finite horizon grouping and spacing heuristics
• Reactive (adaptive) scheduling
• Applications in PC Assembly
• Reactive (adaptive) scheduling
• Scheduling subject to disruptions
Classification of planning and
scheduling problems
Detailed
Scheduling
Production
Planning
Deployment
Supply Network
Planning
Detailed Planning
Aggregated Planning
Tactical (medium
term)
Operational (short term)
Aggregation
Medium vs. Short Term Planning
Medium Term Planning
Global Optimization
Maximum Profit
Product Hierarchies
Time Buckets (days, weeks, …)
Decide
Where to produce
How much to produce
How much to deliver
How much capacities
Medium vs. Short Term Planning
Short Term Scheduling
Local Optimization
Disaggregate global plan
Time continuous (seconds)
Decide
When to produce
On which resources to produce
Optimize production sequence
Buffer inventory may decouple medium Term Planning
Medium
Term
Planning
Short
Term
Scheduling
Upstream downstream
Stage 1 Stage 2 Stage 3 Stage 4 Stage 5
Planning and Scheduling in Supply Chains
facility
Planning system
Scheduling system
Integration between Medium and
Short Term Planning
Scheduling in Medium and Short
Term Planning Medium Term Planning
• Respects Short Term planning
orders as fixed
Capacity reduction from
Short Term Planning Orders
Material flow
Short Term Planning
• Respects medium term planned demands as due dates
No capacity reduction from medium term planning orders
Material flow
Short Term Horizon
Medium Term Horizon
Example: Short Term Optimization
Genetic Algorithm Optimized Period: 7 days
Only one operation per product
Sequence dependent set-up times
Due dates are the planned transports
from the medium term optimization
Up to three alternatives resources
Number of operations: 20-30
Runtime: 1 min
Scheduling Optimizer Architecture
Core Model
LiveCache
Model Generator
Campaign
Optimizer
Constraint
Programming
Genetic
Algorithm
Basic Optimizer
Time
Decomposition
Bottleneck
Meta-Heuristics
Reporting
GUI
Control
Checking
Short Term Scheduling User Interface
Example: Medium Term Optimization
MIP Program (3 MIPs)
309 number of products – 3184 number of location products (1.run)
Planning period 12 weeks – the first 5 weeks in daily buckets
432631 number of variables (1.run)
132649 number of constraints (1.run)
66083 number of discrete variables (1.run)
Using product decomposition (5% partition)
Pre-Phase to calculate starting solution
Pre-Phase to calculate product priority for the product decomposition
Result quality
Runtime 10 hours
LP solves problem in less than 15 minutes optimal
Solution quality: 1-3% > compared to relaxation solution
Medium Term Planning User Interface
• Two Schools of Thought
Mathematical Programming
Constraint Programming
• Hybrid Algorithms
Research Issues in Planning and
Scheduling in Supply Chains
Research Issues in Planning and
Scheduling in Supply Chains
• Robustness; how to measure the robustness
of a schedule
• Interrelationship between scheduling
and quality control
• The longer the run lengths in the process industries,
the higher the quality
• The better the grouping and spacing in automobile
manufacturing, the higher the quality
Impact of Internet on Planning and
Scheduling Algorithms and Systems
• Adaptive (Reactive) Scheduling after
Disruptions (Repair Algorithms)
• Bidding and Pricing Mechanisms; Auctions
• Remote use and Development of
Scheduling Algorithms and Engines
• Relevant information (with regard to disruptions)
moves forward and backward through the supply chain.
• Adaptive scheduling after disruptions
• Repair algorithms
MRP Production
Production Upstream Downstream Pricing
Disruption
JOB AGENT
CALL FOR BIDS
(DESIRED TIME
FRAMES)
BIDS (PRICES, SPECIFIC
TIME FRAMES)
AWARD
COMPARISON
ALGORITHM
PRICING AND
TIMING
ALGORITHM
$
MACHINE AGENT
Bidding and Pricing Mechanism
Bidding and Pricing Mechanisms
• Budgeting Constraints
• Information Infrastructure
• Bidding and Pricing Rules and Algorithms
Bidding and Pricing
Rules and Algorithms
• Goodness of Fit of Operations in Current
Machine Schedule
• Anticipated Supply of Machine Capacity
and Competition Level
• Anticipated Demand for Machine Capacity
• Learning Mechanisms
Some System Implementation Companies
SAP — APO (Advanced Planning and Optimization)
ASPROVA — No: 1 in Japan
Preactor — Subsidiary of Siemens
ORTEMS — Based in Lyon
Cybertec — Based in Trieste
Taylor --- Based in Canada
Then and now
• A lot of work had been done then on
theoretical scheduling (classification
schemes, complexity results, etc.)
• Now a lot of work is going on in applied
scheduling (unfortunately, no classification
scheme - a little bit of chaos)
Planning and Scheduling Issues in
Manufacturing Planning and Scheduling Issues in Services Systems Implementations Research Issues
General Scheduling Areas
in Service Industries:
1. Project planning and scheduling.
2. Tournament scheduling.
3. Scheduling in Health Care.
4. Transportation scheduling.
5. Workforce scheduling.
Application Areas:
• Consulting projects.
• Scheduling meetings, exams.
• Broadcast television network scheduling.
• Operating Room Scheduling
• Tanker scheduling, aircraft scheduling.
• Train timetabling.
• Workforce scheduling in call centers.
Thank You !