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MAnufacturing Planning

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Title: MAnufacturing Planning & Scheduling (MAPS) Group STRATEGY DISCUSSION Author: Sanjay Jain Last modified by: Industrial Engineering Created Date – PowerPoint PPT presentation

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Title: MAnufacturing Planning


1
Agenda
  • Introduction
  • Factory Design and Planning
  • Scheduling System
  • Simulation engine with parallel and distributed
    processing capability
  • Industrial Application - MNC Computer
    Manufacturer

2
MAPS Vision Directions
Planning Horizon
  • Trends
  • Factory planning ? Global planning
  • Centralized computing ? Distributed
  • Generic solutions ? Industry specific
  • Point solutions ? Integrated solution
  • Component based Innovative features

GOAL A unified distributed framework for global
Planning Scheduling
3
Agenda
  • Introduction
  • Factory Design and Planning
  • Scheduling System
  • Simulation engine with parallel and distributed
    processing capability
  • Industrial Application - MNC Computer
    Manufacturer

4
Industrial Land in Singapore
  • High Property Prices
  • Small Factory Size
  • Competition
  • Limited Supply of Industrial Land
  • Need for Intensive Use of Land
  • Need for Productive Use of Land

5
Factory Planning and Design
Factory Planning
Resource
Physical
Automation Planning
Capacity Planning
Operation
Layout Planning
Production Planning
Materials Planning
Expansion Planning
Manpower Planning
Logistics Planning
6
Current Activities in Gintic
7
Current Activities in Gintic
8
Scope And Approach
Systematic Layout Planning (S.L.P.) Macro
Simulated WIP and Job Flow Micro
5th Storey
4th Storey
3rd Storey
2nd Storey
1st Storey
Other issues - WIP - Policy - Requirements
9
Industrial Projects
Project Title

Co. S P VP SchI99-M-033
Development of Industry Sector
JTC
I99-M-021 Development of Industry Sector
Specific JTC
I98-M-100 Plant Layout and Resource Capacity
GE
I98-M-060 Auditing and Recommendation to Enhance
.. Stamf I98-S-064
Test Optimization and Scheduling System (TOSS)
Siemen I97-S-061 AFS
of proposed new plant using simulation (Ph 2)
ATS I97-S-039 Business
Process Improvement to drive ..
NS I97-S-005 Study to Enhance
the Waste Management ... Stamf
I97-S-001 Regional Wide
Productivity Improvement Philips
I96-S-056 AFS of proposed new plant using
simulation (Ph 1) ATS
I96-S-047 Productivity improvement and
automation . CSG
I95-S-061 Business Process Improvement Project
to drive NS I95-S-060
Macro Plant Layout Design and Micro
Stamf I94-S-038
PSA-Container Operations Simulation (Ph 2)
Uraco I93-S-100
PSA-Container Operations Simulation (Ph 1)
Uraco
?
S - Situation Analysis P - Plant Layout
VP - Verify Plans Sch - Scheduling
10
Industrial Project - 1(Printing Company -
Expansion Planning)
11
Industrial Project - 2(Printing company -
Extension Planning)
12
Industrial Project - 3 (Aircraft Component
repair - New Plant Layout)
13
Current Activities in Gintic
Factory Planning
Resource
Physical
Automation Planning
Capacity Planning
Operation
Layout Planning
Production Planning
Materials Planning
Expansion Planning
Manpower Planning
Logistics Planning
14
Proposed System Overview
Factory
Situation Analyzer
Plant Layout
Improved
Scheduling System
Visualizer
15
Plant Layout
  • Space
  • Ergonomics
  • Workflow
  • Restrictions

Plant Layout
Layout Design
Verification
  • Challenges
  • Factory Layout Methodologies
  • Layout Optimization
  • Linkage of Layout to Model

Situation Analyzer
16
Visualizer
  • Look and feel
  • Volumetric Space (Head room)
  • Detailed Ergonomics

Visualizer
Physical Information
  • Challenges
  • 3-D Stereo-graphics Technology
  • Virtual Reality Walk through Technology

Plant Layout
17
Situation Analyzer
  • Model to conduct experiments
  • Ability to verify plans
  • Ability to generate indicators

Situation Analyzer
  • Challenges
  • Input requirements to Model
  • Output requirements to Scheduling System
  • Model Logic requirements
  • Attribute driven / Interactive

Schedule
  • Distance
  • Resources

Scheduling System
18
Current State of Technology
Technology
Applications
  • Simulation
  • What If ?
  • Capacity Planning
  • System improvement
  • Plans Verification

Situation Analyzer
Plant Layout
  • Systematic Layout Planning
  • Efficient work-flow
  • Efficient work-flow
  • Space utilization
  • Rule Based
  • Simulation Based
  • Time line Heuristics

Scheduling System
  • Production Planning
  • VRML
  • QuickTime VR
  • Auto-View
  • CASUS System
  • Visual layout
  • Animation

Visualizer
19
Integrated Solution
Situation Analyzer
Facility Layout Advisor
3D Visualizer
Scheduling System
20
Factory Layout Design Example
21
Benefits
  • Use of advanced technologies to transform the
    industrial facility development business.
  • For Industrial Facility Developers
  • New Value Added Service.
  • New Business Opportunity.
  • For SMEs
  • Cost Effective Simulation-based Facility Layout
    Design.
  • Reduced time for regulatory approvals.
  • Factory optimization.

22
Agenda
  • Introduction
  • Factory Design and Planning
  • Scheduling System
  • Simulation engine with parallel and distributed
    processing capability
  • Industrial Application - MNC Computer
    Manufacturer

23
Our Capability in Planning Scheduling
  • Started Since 1987
  • GSS, an in-house developed FCS system has been
    successfully implemented
  • GSS development team in OSCA group has more than
    18 professionals.
  • FCS implementation is done through Scheduling
    Center and IDS-Gintic

24
Our Capability in Planning Scheduling
  • Specialized in Analysis, Design, Modeling and
    Implementation
  • Requirement Analysis
  • Design, Modeling and Analysis
  • Recommendations
  • Development and Customization
  • Implementation and Integration
  • User Training
  • Systems Phasing-in

25
Our Electronics Partners in Shop Floor
Finite Capacity Scheduling
Industry
Example
  • Computer
  • Semiconductor
  • Disk Drive
  • Consumer Electronics
  • Other Electronics
  • Electronics Components
  • Apple Computer
  • National Semiconductor
  • Amkor Anam
  • PT Astra Microtronics
  • Hewlett Packard
  • Seagate Technology International
  • International Video Products
  • Philips Singapore
  • Elbiru Electronics
  • Plaskon Electronics Material

26
GSS Overview
27
GSS
  • Highly configurable for batch-oriented
    manufacturing environment
  • Forward, Backward and bottleneck scheduling
    algorithms
  • Initial Lot Release Generator (customized module
    for semi-conductor assembly environment)
  • Constraints are handled as parameters or in a
    table format
  • Model Single-stage or Multi-stage production
  • Can be customized to integrate into specific
    manufacturing environment

28
Functional Modules of GSS
Operations Management Reports (Client
Internet)
CRM/Web
Graphical User Interface
Environment Model
Customer Orders, Product Priority, Part
Master, Routing
Rule Criteria Repository
WIP
Sub-Contractor Allocation
Resource Tree
Calendar Tree
M/C Setting Grouping
Report Generation
Inventory Management
Changeover Grouping
Tools Fixtures
Customer Requirements Management (CRM)
Capacity, Material Resource Constraints
Inventory Status
Net Work Orders
Gross Work Orders
Scheduling Re-scheduling Engines
29
At Each Operation
  • Min. Buffer Stock
  • Max. Buffer Stock
  • Transit Time
  • Batching Hours/Days
  • Scheduling Criteria
  • Job-Prioritisation Rules
  • Machine-Assignment Rules
  • Conversion Matrix
  • Blockout Period
  • Centre level
  • Machine Level
  • Repetitive
  • Operator Productivity
  • Flexible of Machines
  • Operating Vs Non-operating
  • Machine Efficiency
  • Preventive Maintenance 1. Operation Level 2.
    Machine Level
  • Staggered Meal Shift
  • MUST machines
  • MUST_NOT machines
  • PREFERENCE machines
  • Non-Overlap Scheduling
  • Production Rate

30
Additional Features ...
  • Flexible Scheduling Period
  • Flexible number of Operations
  • Flexible number of Machines
  • Ability to handle Multiple constraints
  • Ability to take WIP into consideration
  • Tooling / fixture Constraints at operation
  • Calendaring at Individual Resource
  • Powerful What-if analysis capability
  • Application of GT to eliminate setup losses
  • Graphical User Interface
  • Mouse and Menu Driven
  • A platform for fully integrated solution

31
Report Module
Operation
Management
Company Specific
  • Gantt Chart
  • By Resource
  • By Job
  • Unassigned Job
  • Schedule by Job
  • Schedule by Machine
  • Late Jobs
  • Throughput
  • Fixture Usage
  • Weekly Machine Requirements
  • Daily M/C Utilisation
  • with changeover
  • without changeover
  • Scheduling Model
  • WIP

32
Technical Specifications
  • Microsoft Windows 95 (client) and Windows NT 4.0
    (server)
  • SQL Server ver. 6.50
  • Client-Server architecture utilizes Microsoft
    Windows NT operating system running Microsoft
    Windows client and Microsoft SQL Server.
  • Minimum Hardware Configuration -
  • Client - PC (486 above) with 16 MB RAM
  • Server - PC (Pentium 133 above) with 64 MB RAM

33
Key Benefits (1/3)
  • Improved resource utilization
  • Reduce schedule changes, decrease in overheads
    overtime charges
  • Reduce the inventory levels of raw materials,
    work-in-process and finished goods
  • Improve planner productivity by eliminating the
    tedious manual planning process and reduce the
    planning time from days to minutes
  • Improve delivery performance and customer
    satisfaction
  • React quickly and effectively to unexpected
    changes
  • Provide accurate, reliable and realistic schedules

34
Specific Benefits (2/3)
Example 1 - (Disk Drive Company) Planning time
is reduced 24 hours 0.5 hours per
week WIP is reduced 6.5 days 3.5
days Consistent and more accurate
schedule, better machine utilization
35
Specific Benefits (3/3)
Example 2 In IC assembly test, a 3
improvement in valuable operating time at
constraint machine may result in a capital
avoidance in the order of US 1,000,000 to US
2,000,000.
36
RD Roadmap
SC- Test/PE/PCBA Knowledge OO Methodology Advanced
DB System Architecture GA Knowledge
ATP Knowledge Schedule Analysis Approaches Other
Databases Internet Technology
3C/Mass Storage Knowledge Advanced Schedule
Analysis Technique Queuing Theory
Rule-based Engines SC-A T Knowledge ERP/MES
knowledge RDBMS GUI Tech
Product
2002
  • SemiCon-Test (OO-Platform)
  • PE Features
  • PCBA Features
  • 3-Tier Architecture
  • Upgrade to SQL 7.0
  • GA engine development

Development
2003
2004
2001
2000
  • SemiCon-Assembly (Rule-Based Engine)
  • Daily Lot Release Module
  • Multi-Plant Capacity Planning
  • Integration - ERP MES
  • Oracle DB Compatibility
  • SemiCon - Wafer Fab Features
  • Advanced features
  • Multi-Resources
  • User defined rules
  • Multi-pass algorithm
  • Parallel Processing
  • Available-To-Promise Module
  • GA Engine Integration
  • Schedule Analysis Module (using VF)
  • Multi-DB Platform
  • Web Interfaces
  • 3C/Mass Storage Features
  • Auto Engine Selector Module
  • Queuing Theory based Cap. Plng. Lot Release
  • Manual modification from Gantt Chart

37
Agenda
  • Introduction
  • Factory Design and Planning
  • Scheduling System
  • Simulation engine with parallel and distributed
    processing capability
  • Industrial Application - MNC Computer
    Manufacturer

38
A Joint Project
Gintic Institute of Manufacturing
Technology School of Computer
Engineering Nanyang Technological University
Parallel And Distributed Simulation (PADS)
Optimization Logistic Supply Chain
39
Virtual Semiconductor Supply Chain
Wafer Fab 1
Wafer Fab 2
ICs
Wafers
Assembly Test
Shipment to Customers
Wafer Fab 3
Wafer Fab 4
40
Georgia Tech CollaborationThe Supply Chain Model
Wafer Fab
AT
Warehouses
Distribution Centers
End Customers
41
Obstacles
  • Large scale supply chain simulation is time
    consuming
  • Involves multiple companies that are
    geographically distributed
  • Importance of data security for supply chain that
    crosses the enterprise boundaries

42
Enabling Technology Parallel Simulation
User interacts with tool as usual for model
building and running
  • In the background, the system
  • executes using PADS, and,
  • compiles results together

User gets the results in the usual format but
MUCH FASTER!
43
Virtual Semiconductor Supply Chain
Business simulates production and inventory
planning
Manufacturing simulates transformation of
materials
44
Enabling Technology Distributed Simulation
  • In the background, the system
  • initiates remote model
  • send/receive interactions through Internet
  • compiles results together

HLA-RTI Internet
Users at different plant interact independently
with tool as usual for model building
45
Execution of Virtual Supply Chain Simulation
Single Owner/Driver
Independent Partners
HQ
Distributed Simulation via Internet
Centralized Simulation (Parallel Engine)
Data security / information hidding
46
Distributed Simulation Across Internet
Supply Chain Model
Partition 2
Partition 1
Sub-Models
Internet
Future Expansion to Other Locations
Gintic NTU (Singapore)
Georgia Tech MARC(U.S.A.)
Lotus Spreadsheets
47
System Architecture
Application
Virtual Factory Modeling Simulator
Conservative synchronization protocol
High Level Architecture Runtime Infrastructure
Parallel Simulation Kernel
Message Passing Library
Multithreaded Library
Interface Layer
Distributed Memory System
Shared Memory Multiprocessor
Hardware
LAN
Internet
48
Distributed Simulation Added Benefits
  • Real-time data for model construction
  • Rapid model development
  • Reusability
  • Interoperability
  • Low costs alternative to parallel computing
    systems

Industrial Users and Partner Needed
49
Agenda
  • Introduction
  • Factory Design and Planning
  • Scheduling System
  • Simulation engine with parallel and distributed
    processing capability
  • Industrial Application - MNC Computer
    Manufacturer

50
Industrial Application
  • Joint project with MNC Computer Manufacturer in
    Singapore to build an integrated virtual factory
    and logistics model.
  • The model will allow the company to evaluate and
    select ways to improve their supply chain.
  • It will also enable the company to improve the
    integration of manufacturing capability with the
    operations of their logistics provider.

51
Challenges of the Project
  • Require innovative approach and knowledge
    intensive solutions.
  • Require integration of manufacturing, inbound
    logistics, outbound logistics and closely related
    business processes in the simulator.
  • Data driven discrete event simulator requiring
    low maintenance cost.
  • Simulator enables future integration to
    information systems for auto model generation

52
Objectives
  • To build a simulator to model part of supply
    chain
  • Production
  • Inbound outbound logistics
  • Closely related business processes
  • Enable studying different scenarios
  • Schedules
  • Order arrivals
  • To study impact on
  • Cycle time
  • Inventory
  • Resource utilization
  • Cost

53
Why?
  • Supply chain model to evaluate, select and
    implement policies for improved...
  • Cycle time through process predictability
  • Utilization through resource planning and opn.
  • Material replenishment
  • Flow of material
  • Overall operation
  • Prove advanced ideas and implement

Customer focus
Mfg. focus
Supplier Focus
Logistics Focus
Systems View
54
Scope
  • Manufacturing process
  • assembly, testing, packing, shipping
  • operators, material handlers, downtimes
  • Inbound logistics
  • material delivery, handling and usage
  • material storage
  • Outbound logistics
  • shipping,
  • Shipping schedules
  • delivery to WH or customers

55
Simulation Mimics Real-Life Factory
Simulated Factory
Real Life Factory
Logical Model
3D Visualization
56
Virtual Factory
Real Factory
Business Processes
Manufacturing, Inbound Outbound logistics
57
Virtual Logistics
58
Virtual Supply Chain
Squeezing the time Cost
Outbound Logistics Process Model
Inbound Logistics Process Model
Outbound Logistics Process Model
Virtual Computer Assembly
59
  • Reports
  • Cycle Time
  • Inventory
  • Utilization
  • UPH
  • Cost
  • Inputs
  • Schedules
  • Customer Order Arrivals
  • Material Deliveries
  • Inputs
  • Schedules
  • Customer Order Arrivals
  • Material Deliveries
  • Inputs
  • Schedules
  • Customer Order Arrivals
  • Material Deliveries

Simulation Model
  • Evaluation Factors
  • Rework
  • Yield
  • of operator
  • Line replenishment
  • Station process time
  • Logistics Parameters

60
Conclusions
  • Simulator for offline use.
  • Data Driven model, Can be updated by novice
    users.
  • Iterative experiments needed for improving the
    solution.
  • Computational model with no emphasis on 3D
    animation.
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