Latest_Trends_in_ERP___Manufacturing_v2

Latest Trends in ERP -
A Manufacturing Perspective
Trends, Challenges, Investments and Roadmap
Debashis Majumder
SAP India
National Seminar on Leadership through Manufacturing Excellence,
02 September 2010, Kolkata

© SAP AG 2009. All rights reserved. / Page 2
1. Trends and Challenges
2. Investments in Manufacturing
3. Road Map and Summary
Agenda

Trends in Manufacturing

Flat World Dynamics

The Perfect Plant
Mastering Complex Manufacturing Network Interdependencies

The Perfect Plant
Leverages the Synchronized Flow of Information with the Flow of Material

Yesterday’s Manufacturing Solutions
Fall Short

The Perfect Plant
Engineering, Planning, and Execution Are Aligned

1. Evolution of Manufacturing Software
2. Supporting Technological Developments
1. Data Mining in Manufacturing
2. RFID
3. In Memory
Agenda

Manufacturing Software Evolution
Manufacturing
Execution
•Business Processes and
Software Functions
•Improve Product quality
and production
•Speed up Throughput
•Enable Preventative
maintenance
•Ensure Compliance
•Flexible Production
•Work-in-process
engineering
•Business Benefits
•Improve control over
manufacturing operations
•Decrease costs and
speed time to market
•Meet highly specific and
time-sensitive customer
demands
•Reduce compliance costs
and risks
Manufacturing
Integration &
Intelligence
•Business Processes and
Software Functions
•Optimize Manufacturing
asset utilization
•Synchronized Business
planning
•Improved uptime and
reliability
•Business Benefits
•Increased uptime
•Greater product
consistency
•Lower costs
•Optimized performance
and reduced waste
•Increased
responsiveness to
changing market
Lean Planning and
Optimization
•Lean Planning
•Pacemaker planning and
heijunka scheduling
•Material pull or kanban
planning
•Safety stock and buffers
planning
•Demand and
collaborative planning
•Lean Execution
•Support different
techniques for pull signal
creation
•Different flavors of
kanban
•Support for different
replenishment flavors
•RFID-enabled kanban
•Manual and automatic
supply to production
•Operational method
sheets
•Production tracking and
back flushing

Other Supporting Applications
Supply Chain Management
Planning
• Features
• Demand planning and
forecasting
• Safety stock planning
• Supply network planning
• Distribution planning
• Strategic supply chain design
• Key Benefits
• Increase demand accuracy
and order fulfillment
satisfaction levels
• Reduce inventory levels and
increased inventory turns
across the network
• Increase profitability and
productivity
• Integrate sales and operations
planning process
Execution
• Features
• Order fulfillment
• Procurement
• Transportation
• Warehousing
• Real-world awareness
• Key Benefits
• Improved order, production,
and execution tracking with
RFID-enabled processes
• Seamless integration and
global visibility of different
transportation process steps,
and higher transparency
• Improved warehouse efficiency
and extend real-time visibility
and control of warehouse
operations
• Reduced costs of goods sold
throughout company
Collaboration
• Features
• Suppliers Collaboration
• Customers Collaboration
• Contract Manufacturers
Collaboration
• Key Benefits
• Streamline collaboration with
suppliers, contract
manufacturers, and customers
• Significantly decrease
procurement, sales, and
inventory costs
• Enhance supply chain visibility
and increases adaptability of
your supply network
• Reduce inventory levels while
managing variations in supply
and demand
• Improve communications and
reduces errors and processing
costs

Other Supporting Applications
Integrated Product Development
Collaborative
Development
• Product structure
management and
variant configuration
• Material master
management and
document management
• Development
collaboration
• Product costing
• Quality engineering
• Engineering change
management
• Manufacturing
collaboration
• Complaints and returns
analysis
Sharing Product Data for
Component and Task
Sourcing
• Supplier identification
and on-boarding
• Collaborative bidding
and purchase-order
management
• Spare parts
management
Synchronizing Design
with Manufacturing
• Prototyping and
manufacturing ramp-up
• Quality control
• Quality improvement
• Handover to
manufacturing and
service
• Service ramp-up
• Manufacturing process
planning

2. RFID
3. In Memory
Agenda

Creating Value From Increasing Access to
Granular Level Data
n Engineering Design
n Engineering design is a multidisciplinary, multidimensional, and non-linear decision-making process where parameters,
actions, and components are selected. This selection is often based on historical data, information, and knowledge. It is
therefore a prime area for data mining applications
n Manufacturing Systems
n Data collection in manufacturing is common but its use tends to be limited to rather few applications. Machine learning
and computational intelligence tools provide excellent potential for better control of manufacturing systems, especially in
complex manufacturing environments where detection of the causes of problems is difficult
n Decision Support Systems
n Decisions are made based on a combination of judgment and knowledge from various domains. Decision support,
knowledge management, and processing are interdependent activities in many organizations. The knowledge extracted
from databases can be integrated with existing expert systems
n Shop Floor Control and Layout
n The shop floor control and layout problems are concerned with the efficient and effective utilization of resources, at the
lowest level of control in manufacturing. A vast amount of data is recorded during the operation of a shop floor, often to
ensure that parts and production steps can be traced
n Fault Detection and Quality Improvement
n Data mining can help in identifying the patterns that lead toward potential failure of manufacturing equipment. This
methodology helps in identifying not only the defective products but can also simultaneously determine the significant
factors that influence the success or failure of the process
n Data Mining in Maintenance
n Preventive maintenance is of key importance in process and manufacturing engineering. Databases containing the
events of failure of the machines and the behavior of the relevant equipment at the time of the failure can be used in the
design of the maintenance management systems

1. Manufacturing Execution
2. Manufacturing Integration and Intelligence
3. Lean Planning and Optimization
4. Supply Chain Management
5. Product Lifecycle Management
2. RFID
3. In Memory
Agenda

Why RFID in Manufacturing
nLoss of Material
nRecall Return Cost
nNo Data for Important Decisions
nCustomer Mandates
nHuge Paper Trail
nStale Products
nHandling Mistakes

RFID in Manufacturing
Manufacturing Execution
n WIP Tracking
n Error Proofing
n Tool Management
n Quality Control
n Production Monitoring
n Machine Maintenance Management
Asset Management
n Durables Management
n Secure Access Control
n Product Security
n Inventory Control
n Remote Facilities Management
Supply Chain Management
n Lot Tracking
n Warehouse Management
n Logistics
n Yard Management
n Product Genealogy
n Warranty Recall - Trace

RFID Creates Value
Mandate Compliance
Reduce Data Entry Error
Operational Visibility
Reduced Shrinkage
Reduced Overstock
Fulfill Orders More Fully
Reduce Cycle Time
Effective use of Manpower
Item Tracking for Greater Visibility
Automate Anomaly Situation
Data Systems Combined into Temporal
Act On Collaborated Data

1. Manufacturing Execution
2. Manufacturing Integration and Intelligence
3. Lean Planning and Optimization
4. Supply Chain Management
5. Product Lifecycle Management
2. RFID
3. In Memory
Agenda

In-Memory Computing is Game Changing
1 server ...
can execute 64 things (threads) in parallel
A A A A A A A A A A A A A A A A can hold memory modules adding up to ~2TB today
8 servers ...
can execute 512 things (threads) in parallel
A A A A A A A A A A A A A A A A
can hold memory modules adding up to ~16TB
... can work on 160-800TB of data in memory for less than $1m
... can work on 20-100TB of data in memory for less than $100.000

Information at the Speed of Thought
Imagine access to business data,
supporting analytical queries on the transactional data,
no need for data replication, and zero response time
How would this change the way you work with data?
How would this change your perception of information availability?
How would this new information influence your decisions?
In-memory databases are a technology
with huge disruption potential,
we need to assume a competitive leadership position.
In-memory databases are a technology
with huge disruption potential,
we need to assume a competitive leadership position.

In-Memory Computing
Next Wave of Technology Innovation
Exponential potential for change
n Ground-breaking innovation
n 10,000x improvement in speed of access from
disc to memory
n Movement to main memory from disk storage:
viable performance with increasing data
volumes
n Affordable servers >1 TB system memory
n CPUs - multi-core for rapid parallel processing
n Data more easily shared between systems,
structured/unstructured
n Cost feasible technology: mass adoption
n Business user access to rapid data processing
è In-Memory Computing: Speed, Volume, Flexibility, Reach
Desirability
Viability
Feasibility

Applications with In-Memory Computing
Benefits for Business Users
Business
User
è Run Faster, Plan Smarter, Perform Better
Empowered Business User
è Reduced reliance on IT resources
è Accelerated business performance and
reduced TCO
è Real-time visibility to complete
data for transaction and analytics
processing
è Make timely insightful decisions
§ Planning, forecasting, financial
close, pricing optimization

Applications with In-Memory Computing
Challenges and Benefits for IT
Data Volume
Challenges
In-Memory Computing
Solutions
Costly for IT
n Must purchase, maintain separate
business warehouse and transaction
systems
n Processing iterative requests
inefficient
¢ Dissatisfied business users
è Processing and analysis results
delayed
è Data not real time
Value for IT
n ROI
èFree IT resources from data volume
maintenance, query support
èReduce cost of equipment, maintenance
n Innovative
èSatisfied, empowered customers
èEase of technology adoption
n Optimized performance
èEfficiently manage large volume data
èDeliver integrated systems and data

Agenda

Business Challenges for Innovative Companies

Perfect Plant and its Impact on
Shareholder Value
Business
Goal Financial Strategies Perfect Plant Levers
Increase
Shareholder
Value
Increase
Profits
Reduce Costs
Increase
Revenues
Reduce
Operating
Costs
Reduce
Working
Capital
Reduce Fixed
Capital
–
+
=
Meet Time and Volume Targets:
n Improved order fill rated & on-time shipments
n Faster response to changed demand
n Higher volumes / yields with shorter lead times
n Increased throughput
Minimize Operating Costs:
n Reduce overtime & exception resolution costs
n Less waste, less WIP and finished goods inventory
n Elimination of redundant manual data entry costs
n Reduced cash-to-cash cycles
Meet Quality and Regulatory Compliance:
n Lower quality/EH&S compliance related penalties
n Minimize reject, rework, and warranty costs
n Higher value per product through better quality
Optimize return on Assets:
n Increased overall asset utilization (OEE)
n Reduce physical asset base

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