defense supply chain
TRANSCRIPT
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn
Defense Supply ChainA Logistics Lifecycle Management for TACOM’sExtended Enterprise
A Short Workshop on Developing and Implementing Supply Chain
5th Annual U.S. Army Vetronics Institute Winter Workshop Series U.S. Army, TACOM, Warren, Michigan
January 9-12, 2006
Presenter: Charu Chandra, Ph.D.Associate ProfessorIndustrial and Manufacturing Systems Engineering DepartmentThe University of Michigan-DearbornEngineering Complex 22304901 Evergreen Road, Dearborn, MI 48128-1491Phone: 313-593-5258; Fax: 313-593-3692; E-mail: [email protected]: http://www-personal.engin.umd.umich.edu/~charu/
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 22
Main Topics
Module I: Supply Chain Management -Concepts and ApplicationsModule II: Supply Chain Informatics -Theory and ConceptsModule III: Military Supply Chains -Issues and PerspectivesWrap-up
Module I: Supply Chain Management
Concepts and Applications
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 44
Presentation Outline
Supply Chain: Background and PerspectivesSupply Chain Applications– Logistics Network Design– Inventory Management
Supply ContractsManaging the Bullwhip Effecte-Business Models
– Design for Logistics– Mass Customization
Supply Chain
Background and Perspectives
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 66
Supply chain
Definition:A network of independent business organizations with common goalsformed to optimize their resources to meet customers’ needs through sharing of information, expertise (technology), and resources for mutual benefits.
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 77
A supply chain
Supply
Sources:plantsvendorsports
RegionalWarehouses:stocking points
Field Warehouses:stockingpoints
Customers,demandcenterssinks
Production/purchase costs
Inventory &warehousing costsTransportation costs Inventory &
Warehousing costs
Transportation costs
Time
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 88
Supply chain network: A general representation
Supplier 1
Supplier 2
Supplier 3
Supplier 4
Plant 1
Plant 2
Distributioncenter 1
Distributioncenter 2
Distributioncenter 3
Customer 1
Customer 2
Customer 3
Customer 4
Supply stage Production stage Distribution stage Consumption stage
S upp
ly N
o de (
s)(s
o urc
e )S i
(+)
Dem
and
Nod
e(s)
(sin
k)D
j(-)
c ij, t ij
(f ij, u ij
)
Trans-shipmentnode(s)
Independent businessEntity (with uniqueobjectives and independentresources)
END-CONSUMEROEM END-PRODUCTMANUFACTURER
DISTRIBUTOR /WAREHOUSER / RETAILER
Notations:c , = cost of movement of goods from node i to node j
ijt = time elapsed in movement of goods from node i to node jij
f = flow of goods (in units) from node i to node jij
uij = capacity of arc connecting node i to node j
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 99
Supply chain management
Definition:Supply Chain Management is primarily concerned with the efficient integration of suppliers, factories, warehouses and stores so that merchandise is produced and distributed in the right quantities, to the right locations and at the right time, so as to minimize total system cost subject to satisfying service requirements.
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 1010
Supply chain management
Supplier 1
Supplier 2
Supplier 3
Supplier 4
Plant 1
Plant 2
Distributioncenter 1
Distributioncenter 2
Distributioncenter 3
Customer 1
Customer 2
Customer 3
Customer 4
Supply stage Production stage Distribution stage Consumption stage
OEM END-PRODUCTMANUFACTURER
DISTRIBUTOR /WAREHOUSER / RETAILER
END-CONSUMER
Vert
ical
Int
egra
tion
Demand Forecasts
Inventory Replenishment
Supply Echelon
Supply Networks Demand Networks
Horizontal Integration
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 1111
Conflicting objectives in the supply chain
Supplier 1
Supplier 2
Supplier 3
Supplier 4
Plant 1
Plant 2
Distributioncenter 1
Distributioncenter 2
Distributioncenter 3
Customer 1
Customer 2
Customer 3
Customer 4
Supply stage Production stage Distribution stage Consumption stage
Purchasing Manufacturing Warehousing Customers
•Stable Volume Reqmts.•Flexible DeliveryTime•Little Variations in Mix•Larger Order Quantities
•Long Production Run•High Quality•High Productivity•Low Production Cost
•Low Inventory•Reduced Transportation
Costs•Quick Replenishment
•Short Order Lead Time•High in Stock•Large Product Variety•Low Prices
Function
Minimum Total System Cost
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 1212
Supply chain costs
Supplier 1
Supplier 2
Supplier 3
Supplier 4
Plant 1
Plant 2
Distributioncenter 1
Distributioncenter 2
Distributioncenter 3
Customer 1
Customer 2
Customer 3
Customer 4
Supply stage Production stage Distribution stage Consumption stage
Management Costs
•Production / AssemblyCosts
•Raw Materials PurchaseCosts
•Transportation Costs•Raw Materials Inventory
Holding Costs
•Production Costs•Purchase Costs•Set-up Costs•Start-up Costs (FixedCosts)
•Transportation Costs•Work-in-ProcessInventory Holding Costs
•Warehousing Costs•Finished Goods
Inventory Holding Costs•Ordering Costs•Transportation Costs
•Marketing Costs
CostClassification
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 1313
Supply chain: the magnitude
In 1998, American companies spent $898 billion in supply-related activities (or 10.6% of Gross Domestic Product).– Transportation 58%
– Inventory 38%
– Management 4%
Third party logistics services grew in 1998 by 15% to nearly $40 billion.
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 1414
Supply chain: the magnitude(continued)
It is estimated that the grocery industry could save $30 billion (10% of operating cost) by using effective logistics strategies.– A typical box of cereal spends 104 days getting
from factory to supermarket.
A typical new car spends 15 days traveling from the factory to the dealership.
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 1515
Supply chain: the magnitude(continued)
Compaq computer estimates it lost $500 million to $1 billion in sales in 1995 because its laptops and desktops were not available when and where customers were ready to buy them.
Boeing Aircraft, one of America’s leading capital goods producers, was forced to announce write-downs of $2.6 billion in October 1997.The reason? “Raw material shortages, internal and supplier parts shortages…”. (Wall Street Journal, Oct. 23, 1997)
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 1616
Supply chain: the potential
Procter & Gamble estimates that it saved retail customers $65 million through logistics gains over the past 18 months.
“According to P&G, the essence of its approach lies in manufacturers and suppliers working closely together …. jointly creating business plans to eliminate the source of wasteful practices across the entire supply chain”. (Journal of Business Strategy, Oct./Nov. 1997)
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 1717
Supply chain: the potential(continued)
Dell Computer has outperformed the competition in terms of shareholder value growth over the eight years period, 1988-1996, by over 3,000% using
- Direct business model
- Build-to-order strategy
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 1818
Supply chain: the potential(continued)
In 10 years, Wal-Mart transformed itself by changing its logistics system. It has the highest sales per square foot, inventory turnover and operating profit of any discount retailer.
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 1919
Supply chain: the complexity
National Semiconductors:• Production:
– Produces chips in six different locations: four in the US, one in Britain and one in Israel.
– Chips are shipped to seven assembly locations in Southeast Asia.
• Distribution– The final product is shipped to hundreds of facilities all
over the world.– 20,000 different routes.– 12 different airlines are involved.– 95% of the products are delivered within 45 days.– 5% are delivered within 90 days.
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 2020
Supply chain challenges
Achieving Global Optimization– Conflicting Objectives– Complex network of facilities– System Variations over timeManaging Uncertainty – Matching Supply and Demand– Demand is not the only source of
uncertainty
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 2121
Sequential Optimization vs. Global Optimization
Procurement Planning
ManufacturingPlanning
DistributionPlanning
DemandPlanning
Sequential Optimization
Supply Contracts/Collaboration/Information Systems and DSS
Procurement Planning
ManufacturingPlanning
DistributionPlanning Demand
Planning
Global Optimization
Source: Duncan McFarlane
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 2222
What’s New in Logistics?
Global competition
Shorter product life cycle
New, low-cost distribution channels
More powerful well-informed customers
Internet and E-Business strategies
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 2323
New Concepts
Push-Pull strategies
Direct-to-Consumer
Strategic alliances
Manufacturing postponement
Mass Customization
Dynamic Pricing
E-Procurement
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 2424
Supply Chain ManagementKey Issues
Distribution Network ConfigurationInventory ControlSupply ContractsDistribution StrategiesSupply Chain Integration and Strategic Partnering
Outsourcing and Procurement StrategiesInformation Technology and Decision Support SystemsCustomer Value
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 2525
Supply Chain ManagementProblem-Solving Approaches
Implementing Enterprise Resource Planning (ERP) Decision Support Systems
Information Technology and Decision Support Systems
Statistical Process Control, Total Quality Management, Service Level Maximization
Customer Value
Managing risk, payoff tradeoffs with Outsourcing vs. Buying
Outsourcing and Procurement Strategies
Collaborative Planning, Forecasting and Replenishment (CPFR)
Supply Chain Integration and Strategic Partnering
Warehousing and Transportation Costs ManagementDistribution Strategies
Global OptimizationSupply Contracts
Forecasting and Inventory ManagementInventory Control
Network Flow OptimizationDistribution Network Configuration
Problem-Solving ApproachesIssues
Supply Chain Applications
Logistics Network Design
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 2828
The Logistics Network
The Logistics Network consists of:
Facilities:Vendors, Manufacturing Centers, Warehouse/ Distribution Centers, and Customers.
Materials: Raw materials and finished products that flow between these facilities.
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 2929
Decision Classifications
Strategic Planning: Decisions that involve major capital investments and have a long term effect
1. Determination of the number, location and size of new plants, distribution centers and warehouses
2. Acquisition of new production equipment and the design of working centers within each plant
3. Design of transportation facilities, communications equipment, data processing means, etc.
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 3030
Decision Classifications
Tactical Planning: Effective allocation of manufacturing and distribution resources over a period of several months
1. Work-force size
2. Inventory policies
3. Definition of the distribution channels
4. Selection of transportation and trans-shipment alternatives
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 3131
Decision Classifications
Operational Control: Includes day-to-day operational decisions
1. The assignment of customer orders to individual machines
2. Dispatching, expediting and processing orders
3. Vehicle scheduling
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 3232
Network Design: Key Issues
Pick the optimal number, location, and size of warehouses and/or plantsDetermine optimal sourcing strategy– Which plant/vendor should produce which
product
Determine best distribution channels– Which warehouses should service which
customers
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 3333
Network Design: Key IssuesThe objective is to balance service level against
Production/ purchasing costs
Inventory carrying costs
Facility costs (handling and fixed costs)
Transportation costs
That is, we would like to find a minimal-annual-cost configuration of the distribution network that satisfies product demands at specified customer service levels.
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 3434
Aggregating Customers
Customers located in close proximity are aggregated using a grid network or clustering techniques. All customers within a single cell or a single cluster are replaced by a single customer located at the centroid of the cell or cluster (referred to as a customer zone).
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 3535
Comparing Output
Total Cost:$5,796,000Total Customers: 18,000
Total Cost:$5,793,000Total Customers: 800
Cost Difference < 0.05%
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 3636
Product Grouping
Companies may have hundreds to thousands of individual items in their production line
1. Variations in product models and style
2. Same products are packaged in many sizes
Collecting all data and analyzing it is impractical for so many product groups
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 3737
Within Each Source Group, Aggregate Products by Similar Characteristics
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
0.000 0.010 0.020 0.030 0.040 0.050 0.060 0.070 0.080 0.090 0.100
Volume (pallets per case)
Wei
ght (
lbs
per c
ase)
Rectangles illustrate how to cluster SKU’s.
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 3838
Sample Aggregation Test:Product Aggregation
Total Cost:$104,564,000Total Products: 46
Total Cost:$104,599,000Total Products: 4
Cost Difference: 0.03%
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 3939
A Typical Network Design Model
Several products are produced at several plants.
Each plant has a known production capacity.
There is a known demand for each product at each customer zone.
The demand is satisfied by shipping the products via regional distribution centers.
There may be an upper bound on total throughput at each distribution center.
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 4040
A Typical Location Model
There may be an upper bound on the distance between a distribution center and a market area served by it
A set of potential location sites for the new facilities was identified
Costs:– Set-up costs– Transportation cost is proportional to the distance– Storage and handling costs– Production/supply costs
Inventory Management
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 4242
Inventory
Where do we hold inventory?– Suppliers and manufacturers– Warehouses and distribution centers– Retailers
Types of Inventory– Raw materials– Work-in-process (WIP)– Finished goods
Why do we hold inventory?– Economies of scale– Uncertainty in supply and demand
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 4343
Goals: Reduce Cost, Improve Service
By effectively managing inventory:– Xerox eliminated $700 million inventory from its supply
chain– Wal-Mart became the largest retail company utilizing
efficient inventory management
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 4444
Goals: Reduce Cost, Improve Service
By not managing inventory successfully– In 1994, “IBM continues to struggle with shortages in their
ThinkPad line” (WSJ, Oct 7, 1994)– In 1993, “Liz Claiborne said its unexpected earning decline
is the consequence of higher than anticipated excess inventory” (WSJ, July 15, 1993)
– In 1993, “Dell Computers predicts a loss; Stock plunges. Dell acknowledged that the company was sharply off in its forecast of demand, resulting in inventory write downs” (WSJ, August 1993)
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 4545
Understanding Inventory
The inventory policy is affected by:– Demand Characteristics– Lead Time– Number of Products– Objectives
Service levelMinimize costs
– Cost Structure
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 4646
Cost Structure
Order Costs – Fixed– Variable
Holding Costs– Insurance– Maintenance and Handling– Taxes– Opportunity Costs– Obsolescence
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 4747
Types of inventory
Supplier 1
Supplier 2
Supplier 3
Supplier 4
Plant 1
Plant 2
Distributioncenter 1
Distributioncenter 2
Distributioncenter 3
Customer 1
Customer 2
Customer 3
Customer 4
Supply stage Production stage Distribution stage Consumption stage
•Finished Goods •Shelved Goods •Fixed (Ordering)•Variable•Holding
InsuranceMaintenance and HoldingTaxesOpportunity Obsolescence
Fixed (Ordering)
Inventory CostsCriteria•Raw Materials /
Assembly•Raw Materials /
Assembly•Work-in-Process•Finished Goods
•Demand Pattern•Lead Time•No. of Products•Objectives
Service LevelMinimum Costs
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 4848
Inventory / Production policies
Supplier 1
Supplier 2
Supplier 3
Supplier 4
Plant 1
Plant 2
Distributioncenter 1
Distributioncenter 2
Distributioncenter 3
Customer 1
Customer 2
Customer 3
Customer 4
Supply stage Production stage Distribution stage Consumption stage
Fixed (Ordering)
Postponement
•Make-to-Stock•Make-to-Order
•Consolidation•Cross Docking•Third-party Logistics
•Push•Pull•Push - Pull
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 4949
Factors that Drive Reduction in Inventory
Top management emphasis on inventory reduction (19%)Number of SKUs in the warehouse (10%)Improved forecasting (7%)Use of sophisticated inventory management software (6%)Coordination among supply chain members (6%)Others
Inventory Management: Supply Contracts
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 5151
Supply Contracts
Manufacturer Manufacturer DC Retail DC
Stores
Fixed Production Cost
Variable Production Cost
Selling Price
Salvage Value
Wholesale Price
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 5252
Supply Contracts
Manufacturer Manufacturer DC Retail DC
Stores
Fixed Production Cost
Variable Production Cost
Selling Price
Salvage Value
Wholesale Price
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 5353
Supply Contracts
Manufacturer Manufacturer DC Retail DC
Stores
Fixed Production Cost
Variable Production Cost
Selling Price
Salvage Value
Wholesale Price
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 5454
Supply Contracts: Key Insights
Effective supply contracts allow supply chain partners to replace sequential optimization by global optimizationBuy Back and Revenue Sharing contracts achieve this objective through risk sharing
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 5555
Supply Contracts (Risk Pooling)
Supplier 1
Supplier 2
Supplier 3
Supplier 4
Plant 1
Plant 2
Distributioncenter 1
Distributioncenter 2
Distributioncenter 3
Customer 1
Customer 2
Customer 3
Customer 4
Supply stage Production stage Distribution stage Consumption stage
Fixed (Ordering)
exibility
evenue Sharing
Back Sales Rebate
Quantity Fl
RBuy-
Inventory Management: Managing the Bullwhip Effect
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 5757
The Dynamics of the Supply Chain
Ord
er S
ize
CustomerDemand
CustomerDemand
Retailer OrdersRetailer OrdersDistributor OrdersDistributor Orders
Production PlanProduction Plan
TimeSource: Tom Mc Guffry, Electronic Commerce and Value Chain Management, 1998
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 5858
The Bullwhip Effect and its Impact on the Supply Chain
Consider the order pattern of a single color television model sold by a large electronics manufacturer to one of its accounts, a national retailer.
Order Stream
Huang at el. (1996), Working paper, Philips Lab
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 5959
The Bullwhip Effect and its Impact on the Supply Chain
Point-of-sales Data-Original
POS Data After Removing Promotions
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 6060
The Bullwhip Effect and its Impact on the Supply Chain
POS Data After Removing Promotion & Trend
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 6161
Higher Variability in Orders Placed by Computer Retailer to Manufacturer Than Actual Sales
Lee, H, P. Padmanabhan and S. Wang (1997), Sloan Management Review
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 6262
Increasing Variability of Orders Up the Supply Chain
Lee, H, P. Padmanabhan and S. Wang (1997), Sloan Management Review
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 6363
The Bullwhip Effect:Managerial Insights
Exists, in part, due to the retailer’s need to estimate the mean and variance of demand.The increase in variability is an increasing function of the lead time.The more complicated the demand models and the forecasting techniques, the greater the increase.Centralized demand information can reduce the bullwhip effect, but will not eliminate it.
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 6464
Coping with the Bullwhip Effect in Leading Companies
Reduce Variability and Uncertainty- Point-of-Sales (POS)- Sharing Information- Year-round low pricingReduce Lead Times- Electronic-Data-Interchange (EDI)- Cross DockingAlliance Arrangements– Vendor managed inventory– On-site vendor representatives
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 6565
Distribution Strategies
WarehousingDirect Shipping– No Distribution Centers needed– Lead times reduced– “smaller trucks”– no risk pooling effects
Cross-Docking
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 6666
Supply Chain Integration: Dealing with Conflicting Goals
Lot Size vs. InventoryInventory vs. TransportationLead Time vs. TransportationProduct Variety vs. InventoryCost vs. Customer Service
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 6767
What are the Causes….
Promotional salesVolume and Transportation discountsInflated ordersDemand ForecastLong cycle timesLack of Visibility to demand information
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 6868
Consequences….
Increased safety stockReduced service levelInefficient allocation of resourcesIncreased transportation costs
Inventory Management: e-Business Models
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 7070
The Future is Not What it Used to Be
A new e-Business Model– Reduce cost– Increase Profit– Increase service level– Increase flexibility
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 7171
Reality is Different…..
Amazon (Book)Peapod (Grocery)Dell (Computers)Cisco (Network Management)
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 7272
The e-Business Model
e-Business is a collection of business models and processes motivated by Internet technology, and focusing on improving the extended enterprise performance– e-commerce is part of e-Business– Internet technology is the driver of the business
change– The focus is on the extended enterprise:
Intra-organizational Business to Consumer (B2C)Business to Business (B2B)
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 7373
A new Supply Chain Paradigm
A shift from a Push System...– Production decisions are based on
forecast
…to a Push-Pull System– Parts inventory is replenished based on
forecasts– Assembly is based on accurate customer
demand
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 7474
From Make-to-Stock Model….
Suppliers ConfigurationAssembly
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 7575
Push-Pull Supply Chains
The Supply Chain Time Line
Push-Pull Boundary
PUSH STRATEGY PULL STRATEGY
Low Uncertainty High Uncertainty
CustomersSuppliers
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 7676
….to Assemble-to-Order Model
Suppliers ConfigurationAssembly
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 7777
Business models in the Book Industry
From Push Systems...– Barnes and Noble
...To Pull Systems– Amazon.com, 1996-1999
And, finally to Push-Pull Systems– Amazon.com, 1999-present
7 warehouses, 3M sq. ft.,
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 7878
e-Business in the Retail Industry
Brick-&-Mortar companies establish Virtual retail stores– Wal-Mart, K-Mart, Barnes and Noble
Use a hybrid approach in stocking – High volume/fast moving products for local
storage– Low volume/slow moving products for browsing
and purchase on line
Channel Conflict Issues
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 7979
e-Fulfillment Requires a New Logistics Infrastructure
Traditional Supply Chain e-Supply Chain
Supply Chain Strategy Push Push-Pull
Shipment Type Bulk Parcel
Inventory Flow Unidirectional Bi-directional
Reverse Logistics Simple Highly Complex
Destination Small Number of Stores Highly Dispersed Customers
Lead Times Depends Short
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 8080
Matching Supply Chain Strategies with Products
Pull Push
Pull
Push
IComputer
II
IV III
Demand uncertainty
Delivery costUnit price
L H
H
L
Economies of Scale
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 8181
Locating the Push-Pull Boundary
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 8282
Organizational Skills Needed
RawMaterial Customers
Push Pull
High Uncertainty
Short Cycle Times
Service Level
Responsiveness
Low Uncertainty
Long Lead Times
Cost Minimization
Resource Allocation
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 8383
e-Business Opportunities:
Reduce Facility Costs– Eliminate retail/distributor sitesReduce Inventory Costs– Apply the risk-pooling concept
Centralized stockingPostponement of product differentiation
Use Dynamic Pricing Strategies to Improve Supply Chain Performance
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 8484
e-Business Opportunities:
Supply Chain Visibility– Reduction in the Bullwhip Effect
Reduction in InventoryImproved service levelBetter utilization of Resources
– Improve supply chain performanceProvide key performance measuresIdentify and alert when violations occurAllow planning based on global supply chain data
Design for Logistics
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 8686
Design for LogisticsConcept
Design for Logistics addresses three keycomponents to manage trade-offs between inventory and service levels:
– Economic packaging and transportation.– Concurrent and parallel processing.– Standardization.
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 8787
Economic packaging and transportation
Products that can be packed compactly– are cheaper to transport,– Use up less storage space,– Facilitate cross-docking operations,– Impact handling costs because of lesser
handling needed.
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 8888
Concurrent and Parallel Processing
Modifying the manufacturing processes from sequential and dependent structures to concurrent and parallel processing.– Implement decoupling of manufacturing
processes so as to make them more flexible.Benefits: reduced manufacturing lead time, lower inventory costs through improved forecasting, and reduced safety stock.
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 8989
Standardization
Standardization can lower inventory costs and increase forecast accuracy.Standardization involves introducing concepts of:– Product Modularity
Product assembled in modules allowing flexibility.
– Process ModularityAllows implementing discrete manufacturing operations so that inventory can be stored in partially manufactured form between operations.
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 9090
Approaches to Standardization
Part StandardizationProcess StandardizationProduct StandardizationProcurement Standardization
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 9191
Part Standardization
Commonality among parts.Common parts are introduced among products.Common parts reduce required part inventories due to risk pooling and reduce part costs.
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 9292
Process Standardization
Involves standardizing as much of the process as possible for different products, and then customizing products as late as possible.Manufacturing process starts by making a generic or family product that is later differentiated into a specific end-product.– Also termed as postponement or delayed
product differentiation strategy.Most of the time requires redesigning the process, such as re-sequencing.
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 9393
Product Standardization
A large variety of products may be offered, but only a few kept in inventory.Resort to downward substitution when a product not kept in stock is ordered.– Product is substituted with product
offering a superset of features.
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 9494
Procurement Standardization
Standardizing processing equipment and approaches, even when the product itself is not standardized.– Example: Integrated Circuits.
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 9595
Selecting a Standardization Strategy
IMSE 565, Winter 2003 Instructor: C. Chandra, University of Michigan-Dearborn
Operational Strategies for Standardization
ProcurementStandardization
ProductStandardization
ProcessStandardization
PartStandardization
Product
Modular
Non-Modular
Non-Modular Modular
Process
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 9696
Supplier Integration into New Product Development
Involve suppliers in the design process.Potential benefits:– Reduced Purchased Materials costs– Increase in Purchased Materials quality– Decline in development time and cost– Decline in manufacturing cost– Increase in final product technology levels
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 9797
Spectrum of Supplier Integration
None– Supplier is not involved in design.
Materials and subassemblies are supplied according to customer specification and design.
White Box– Informal consultations between supplier and buyer when
designing products and specifications.Grey Box– Formal supplier integration into the design process.
Formal supplier / buyer teams work on joint development.
Black Box– Supplier independently designs the product according to
requirements given by the buyer.
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 9898
Strategic Planning Process for Supplier Integration
Proposed by the study at Michigan State University (1997):– Determine internal core competencies– Determine current and future new
product developments– Identify external development and
manufacturing needs
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 9999
Keys to Effective Supplier Integration
Select suppliers and build relationships with them.Align objectives with selected suppliers.
Mass Customization
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 101101
Mass CustomizationConcept
Mass customization involves the delivery of a wide variety of customized goods or services quickly and efficiently at low cost.
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 102102
Attributes for Implementing Mass Customization Strategy
Rapid response to customer demands through quick linkages of production modules and processes.Linkages should be costless, that is, add very little cost to processes.Linkages should be seamless so customer service does not suffer.Networks or collections should be formed with little overhead.
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 103103
Techniques to Manage Inventories due to Product Proliferation
Build-to-Order Model utilizing product postponement and push-pull strategiesKeep large inventories at major distribution centersOffer fixed set of options that cover most customer requirements
Module II:Supply Chain Informatics
Theory and Concepts
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 105105
Presentation outline
System and System DesignSupply Chain InformaticsReconfigurable systemsMotivation and general guiding principles of researchProblem solving frameworkAlgorithmic modeling of reconfigurable supply chain – Information support system– Decision modeling system– Decision support systems prototype
Examples of representative research problems
System and System Design
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 107107
System: A Definition
A system may be defined as an assemblage of sub-systems (components, modules, etc.), and agents and mechanisms (people, technology, and resources) designed to perform a set of tasks to satisfy specified functional requirements and constraints.
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 108108
General Systems TheoryBackground
Ludwig von Bertalanffy formulated a new discipline, General System Theory (GST), and defined its subject matter as “formulation and derivation of those principles which are valid for systems in general whatever the nature of the component elements and the relations or forces between them”. GST enunciated the principle of unification of science, and its essence was interdisciplinarity. It produced a new type of scientific knowledge: interdisciplinary knowledge.According to Bertalanffy, there is some element of isomorphism (state of similarity), which allows extension of one scientific discipline to other sciences.
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 109109
Concept of System in GSTUnity, Parts, and Relationship
Unity (‘consistent whole’, ‘complex whole’, ‘wholeness’, ‘synergy’, etc.).Parts (‘elements’, ‘constituents’, ‘components’, etc.).Relationship (‘interrelationship’, ‘interactions’, ‘structure’, and ‘organization’).
Unity
Relationship
Part
Environment
Source: Dubrovsky (2004).
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 110110
Role of System in an Organization
System gives organization a formal structure, a purpose, a goal (s) [objectives], and above all a basis for integration. Such a structure is beneficial for an organization in managing its complexity, integration of its functions, and aligning its product-process-resource structure.System provides the framework that an organization needs for designing and implementing models, methodologies, tools and techniques for aligning its business (es) and improving productivity.
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 111111
How do System and Organization complement each other?
System has a structure (or organization). Organization is a class of system and thus inherits its (system’s) structure.System needs an organization (and its structure) for a formal representation of an enterprise. On the other hand, organization needs a system (and its framework) for formalization.
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 112112
Issues Related to System Design
How should a complex system be designed? – Top-down vs. bottom-up
How should the complex relationships between various components of a system be coordinated and managed?– Modular with process flow interface
How can the stability and controllability of a system be guaranteed? – Satisfying the Design Axioms
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 113113
Domain of System Design
CAs DPs PVsFRs
PhysicalDomain
FunctionalDomain
ProcessDomain
CustomerDomain
Source: Suh, 1998
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 114114
Design Axioms
Axiom 1: The Independence AxiomMaintain the independence of the
Functional Requirements (FRs).
Axiom 2: The Information AxiomMinimize the information content of the
design.
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 115115
Inferences from Design Axioms
Uncoupled Design: When each of the FRs can be satisfied independently by means of one DP. Decoupled Design: When the independence of FRs can be guaranteed, iff the DPs are changed in the proper sequence.Coupled Design: When the design violates the Independence Axiom (or Axiom 1).When several functional requirements must be satisfied, designers must develop designs that are either uncoupled or decoupled.Among all the designs that satisfy the Independence Axiom (or Axiom 1), the design that has the least information content is the best design.
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 116116
Influence of GST on System Design
The biggest influence that GST has had on System Design is in its formalization. For example, system is designed to recognize its whole-part relationship instantiated in its environment (both internaland external). The concept of isomorphism has facilitated system design by recognizing similarity (or commonness) across entities, relationships, and environmental variables. Similarity implicitly recognizes relationships, thereby improving a system’s representation and eventually impacting its performance (quality, reliability etc.).Another useful feature of GST in system design is separating information needs (and associated knowledge) at the domain independent (or generic) level from that of domain dependent (orspecific / problem) level. Such an approach ensures that the system captures both breadth and depth of knowledge. Since the latter is embedded in the former, the captured knowledge has a larger context, thereby ensuring interactions and thus larger relevance. It also ensures that the knowledge does not become redundant.
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 117117
Influence of GST on System Design Some key principles
Unity: All system (and its components) is whole (or unity) depending on the context where they are represented.Commonality: All systems in the universe of systems share common universal characteristics.Isomorphism: Similarity (and therefore commonality) among system components and associated relationships.Reuse: Commonality leads to reuse and eventually standardization, conformity and reliability.Abstraction: Enables managing complexity by abstracting features of system’s components. It also allows representation of relationships such as, whole-part, and generalization-specialization. Polymorphism: Creates classes of systems and reusing them for specialized functions.Encapsulation: Enables encapsulating knowledge and information-hiding on objects (and classes) to create uniqueness of objects (and classes).Independence: Domain independent vs. domain dependent knowledge creation.Inheritance: Enables avoiding information redundancy and information-hiding by clustering information representation where they rightfully belong.
Supply Chain Informatics
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 119119
Concepts
Supply Chain Informatics is the basis for applying Information Science to supply chain problems.The primary thrust of this area is on investigating design and modeling issues in information management of logistics in production networks.Specifically, it applies the concept of Information Economics to managing technology, aided by knowledge from multi-disciplinary topics in seeking solutions for supply chain problems.
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 120120
Motivation
SystemsScience
SystemsEngineering
Management ScienceDecision ScienceIndustrial EngineeringOperations Research
Theory
Application
Tools & Techniques
Explore research in cross- cutting areas
Apply this knowledge to investigating emerging public policy areas / issues
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 121121
Support Integrated Product Life Cycle System
Product-Life-Cycle
Supply Chain Process-Life-Cycle(Plan, Source, Make, Deliver, Return)Suppliers Customers
ERP SystemsPDM Systems
(CAD/CAM/CAE,Expert Systems)
Cyber-Infrastructure(Internet, eBusiness)
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 122122
Enable Co-Design of Product Systems
Logical Systems Design(Designing Inbound/Outbound Logistics)
Physical Systems Design(Designing Product-Process Interface)
Virtual Systems Design(Product Delivery Configuration)
Integrating consumer-supplier interface requirements concurrentlyat design time
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 123123
Reconfigurable Systems
Manufacturing Systems that can be:– Designed, modeled, and
configured according to specific applications flexibly and with agility, and
– Upgraded and reconfigured rather than replaced.
With a reconfigurable system, new products and processes can supposedly be introduced with considerably less expense and ramp-up time.
Reconfigurable supply chain
Supplier 1
Supplier 2
Supplier 3
Supplier 4
Plant 1
Plant 2
Distributioncenter 1
Distributioncenter 2
Distributioncenter 3
Customer 1
Customer 2
Customer 3
Customer 4
Supply stage Production stage Distribution stage Consumption stage
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 124124
Reconfigurable supply chainTriggers
Introduction of new product(s), or upgrade for existing product(s).Introduction of new, or improvement in existing process(es).Allocation of new, or re-allocation of existing resource(s).Selection of new supplier(s), or de-selection of existing ones.Changes in demand patterns for product(s) manufactured.Changes in lead times for product and / or process during its life cycle in the supply chain.Changes in commitments withinand between supply chain members.
IssuesAssessing impacts of one or more of following factors / activities in order to make (economic) decisions to implement reconfigurable systems:
–Flows due to materials, inventory, information, and cash.
–Throughput due to movement of product.
–Capacity utilization.–Costs at various stages of product
development life cycle.–Lead time in product development.–Batch and lot sizing.–Process redesign. –Product development strategies.–Procurement and / or allocation of
resources.–Strategic, tactical, and operational
policies on the supply chain.
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 125125
General guiding principles
Supply chain is a System; hence General System Theory principles can be applied for its study through an inter-disciplinary focus– Managing complexity– Isomorphic frameworks– Formal theoretical
reference models– System research and
design
Application of system design theory principles to develop an axiomatic system design for supply chain– Designing configurable
system architectures through integrating FRs/DPs/PVs, Cs and flows, while maintaining design axioms
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 126126
General guiding principles
Supply chain is an organization system with a set of managerial issues at:
– Technical level– Organizational level– Institutional level
Supply chain knowledge representation is carried out through process modeling of its workflows
– Modeling supply chain workflows
– Capturing and organizing knowledge for workflow management
– Delivering process / problem knowledge to decision modeling tools
System integration comprises integration of information resources and collaboration based on common problems
– Horizontal collaboration vs. hierarchical management
– Shared understanding of common problems and tasks
– Distributed environment for linking diverse information systems
Systematically capturing organization and problem knowledge
– Ontology for supply chain knowledge modeling
– Semantic Web Services for knowledge share and reuse
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 127127
Problem solving
PrinciplesScalability of system(s)Meta modeling of system(s)Coordination withinand between system(s)Information sharing within and between system(s)
Strategies
Developing:
1. Domain independent solution(s) [templates] at the macro level
2. Capability models for application specific domain dependent problems at micro level.
3. Coordination models to integrate models developed in (1) and (2)
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 128128
Taxonomy of supply chain reconfiguration models
S-C STRUCTURAL MODEL Domain IndependentModeling Context
S-C ARCHITECTURE REPRESENTATION MODEL
Domain IndependentMethodological Constructs
S-C WASTE MANAGEMENTMODELS
Domain IndependentProblem-Solving Context
S-C PROBLEM SPECIFICMODELS
Domain DependentProblem-Solving Context
SC Reconfiguration Model Types
• SC System Taxonomy Model
• SC Organization Structure Model• SC Process Model• SC Ontology Model• SC Database Model
• SC Multi Agent Model• SC Agreement Model
• SC Forecast Management Model• SC Inventory Management Model• SC Capacity Planning Model
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 129129
Supply chain modeling system
Supply chainmodelingsystem
Informationsupportsystem
Decisionmodelingsystem
Processmodeling
Knowledge& Agent Modeling
OptimizationSimulationModeling
InformationModeling
Forecasting& Inventory
Management
Information support system provides supply chain information support.
Decision modeling system is used to investigate and solve supplychain management problems.
Modeling overview
Information Support System (ISS)
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 131131
Motivation
Make decision support system effectiveDevelop systematic approaches for information modeling
Use the best breed of available information technologies and resources
Integrate information system with decision modeling system
Support supply chain management activities
Design information systems to meet supply chain management requirements
Integrate processes and activities across the supply chain
Integrate information resources across the supply chain
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 132132
Information support systemScope
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 133133
Information support systemThrust areas
Information modelingSystem taxonomy – standardization of domain structure and content
Problem taxonomy – systematic representation of supply chain managerial issues
Ontology – Organization and problem knowledge conceptualization with formal models
Information system architectureKnowledge intensive information system design
Ontology utilization by information system components in both temporal dimensions (development and run-time)
Knowledge portal and Ontology server design
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 134134
Information modeling framework
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 135135
“System” behind system taxonomy
Input: information, Resources Materials
Output: Designed System, Paradigm, Product, Service
Mechanisms: Control, Action, Performance, Behavior, Program, Management, Strategy, Structure, and Feedback.
Processes: Information flow, Energy flow, Material flow, Transformation, Synthesis, Event.
Objectives: Goals, Means.
Agents: Owner, Role, Actor, and Customer.
Environment: Relevant systems, Dependencies, Constraints, Boundaries.
ProcessesInput Output
ObjectivesEnvironment
MechanismsAgents
Supply chain system taxonomy development objectives• System taxonomy provides standardization of terms and definition, thus ensuring
shared vocabulary across the supply chain system domain.
• System taxonomy also provides unified structure for a formal representation, ensuring that data and knowledge can be represented in a format consumable by supply chain system members’ software applications.
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 136136
Problem taxonomy
Classification of supply chain problems
Classification of problem solving methodologies for supply chain management
Identification of problem requirements
Problem model projection from system taxonomy
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 137137
Ontology modeling
OntologyOntology is a domain or problem knowledge formulated in the formof concepts and relationships with a set of axioms, used in problem reasoning algorithms, and implemented in a common language understandable by software development tools.
Ontology conceptualizationComponents
(1) Data, (2) Axioms (constraints, rules) and (3) Algorithms (problem solving methods)
Stages(1) Business process modeling, (2) problem domain requirements identification, (3) analysis, (4) design, (5) implementation and evaluation
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 138138
ISS Reference Model
Proposition 1. System consists of things (entities) related to each other.Proposition 2. Supply Chain problems can be introduced as a combination of two formalisms, viz., problem object model and problem formal model .Proposition 3. To better serve the needs of problem solving tools and provide reusability of problem models, the information representing their content is captured at different levels of abstractions. Particularly, problem formal model is proposed to have two representation levels: generic and specific.Proposition 4. Relationships in Supply Chain problem domain can be classified into two types: vertical and horizontal. The former is for building domain structure. The latter is for linking outputs of some problems with inputs of others.
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 139139
ISS Reference Model: notations I
Notations related to system taxonomy– System
– Thing symbolizing the elements of a system– Relationships among things of a system defined on T
Notations related to problem taxonomy– Set of thing pertinent to a specific state of the SC
system– Set of relationships pertinent to a specific state of
the SC system among things of a system state defined on
– Problem representation– Vertical representation– Horizontal representation
Notations related to general problem representation– Generic problem model– Attribute– Set of instances of attribute– Variable that can be assigned to attribute for
generic problems– Set of possible values that variable may have– Observation channels for
STR
wT
wR
PRwT
VH
GPiatiAtivv
iatiat
i iati ivv
– Set of possible states of observation channels
Notations related to specific problem representation– Object model– Backdrop
– Set of backdrop states– Specific problem model– Variable that can be assigned to attribute for
specific problems– Set of possible values that variable may have– Observation channel for backdrop – Set of possible states of channels – Observation channel for attributes – Relationship between object system and problem
system– Class instances of S for SC domain (general
representation of )
Notations common for specific and general problem representations
– Relationship between specific and generic systems – Relationship between – Relationship between
iWW iww
Obib
iB ibSP
iv
iV
iat
iviw
ibiW
iwio iat
W
Õ
iW
Ê,i iV VV,j jW WW
iejk
RR
VVww
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 140140
ISS Reference Model: notations II
Notations for Ontology
––– Data model for SC domain
– Ontological commitments. Functions interpreting characteristics into variables
– Set of variables
– Observation channels for defining variables, constraints, and algorithms respectively
– Set of Interpretation functions
– Data model for SC problem
– Constraints on data
– Ontology model
– Set of axioms
– Algorithm or heuristics
– Set of equations
MIV
, ,B B Bc w hJ
MwCOA
HG
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 141141
ISS Reference Model:System Taxonomy
( , R)S T=Thing
System Relationships
( )T I O E A F M P⊆ × × × × × ×
{ }1 2, ,..., nI i i i= { }1 2: _ _ , ,...I i i has properties I I=
{ }( , ) ( , ) : ( , )R I O i o i o I O⊆ ∈ ×Input Output
Thing YThing X
{ }( , ) ( , ) : { }^ { }^R X Y x y y Y x X x y= ∈ = ∀
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 142142
ISS Reference Model: Problem Taxonomy
{ }|wT T w W= ∈ { }|wR R w W= ∈
( , R )w w wS T= { }|wS S w W= ∈
( ), , , Ê,ÕwT Ob GP SP=
Relationship (GP,SP)Object model
Relationship (Ob,SP)General problem Specific problem
({( , ) | },{( , ) | })i i n j j mOb at At i N b B j N= ∈ ∈
({( , ) | },{( , ) | })i i n j j mGP vv VV i N ww WW j N= ∈ ∈
({( , ) | },{( , ) | })i i n j j mSP v V i N w W j N= ∈ ∈
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 143143
ISS Reference Model: Problem Taxonomy
Ê ({( , , ) | },{( , , ) | })i i i n j j j mVV V e i N WW W e j N= ∈ ∈
Õ ({( , , ) | },{( , , ) | })i i i n j j j mAt V o i N B W w j N= ∈ ∈
( )w wRV ,RHwR =Vertical relationships Horizontal relationships
{ }1,3 1 2 1 2( , ) ( , ) : { }^ { }^ | 1, 2w w w w wRV T T x y y T x T x y w w W= ∈ = ∀ ∈
{ }{ }1,2 1 2 1 2( , ) ( , ) : ( , ) | 1, 2w w w w wRH T T x y x y T T w w W= ∈ × ∈
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 144144
ISS Reference Model: Ontology
( , C, H)O M=Data model
Ontology
( B )CC C V= → ∪Constraints Problem solving method
( B )HH H M= → ∪
( , I)w wM S=
( B )w wI V T= → ∪
Observation channels
Ontological commitment
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 145145
System taxonomy building – Upper level
InputInformationRes ourc es
+Input+Materials+Cost+Lead Time+Material Attributes+Requirement
Env ironment+Constraints+Financial+Envorinment1+Organizational behavior+Market
SC Sy s tem Tax onomy
Func tions+Goals1+Means1+Objectives
Mec hanis mManagementRelat ions hip_ ManagementStrategiesStruc ture
+Mechanisms+Decisions
AgentsSCA1
+Members+Agents+GSCA+Role+Management agents+Operational agent
O utputSC_ Produc ts
+Output+SC Services
Proc es s es+Processes+Flows+Transformation+Synthesis
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 146146
System taxonomy building–Mechanisms
Mechanisms
ManagementProduc tioAndMater ialsSalesAndMarketing
+Management+Accounting+HumanResource
Relationship_Management+SC Members Relationships+Open Market Negogiation+Cooperation+Coordination+Colleboration+Relationship Type+Partnership
Strategies+Strategies+Policy+Decision making+Relationship Coordination+Supply+Optimization+Business+Inventory+Manufacturing lots+PRoduction+Distribution
Dec is ions
-Information:int-Trnasportation:int-Location:int-Inventory:int-Supply:int-Production:int
Struc ture+Product+SC Structure+Project+Components
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 147147
Problem Ontology engineering
Supply Chain Model
Process decomposition according to SCOR model
Process type
Process category
Process element
Workflow Conceptual Model
Process models
Process views
IDEF Process models
UML Process models
Ontology Model
Ontologies
Ontology Calculus
SCML
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 148148
Supply chain workflow modeling
Supply Chain Operations Reference (SCOR) modeling technique integrates concepts of business processes, benchmarking, and best practices into a cross-functional framework.
Workflow or process modeling aims to represent processes specified in SCOR third level as a collection of tasks executed by various resources within a SC.
Workflow modeling can be captured by using explicit models: IDEF methods and UML language.
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 149149
Problem classification
Supply Chain
Plan Source Return DeliverMake
Identify, Prioritize, & aggregate Production
Requirements
Select Final Suppliers and
negotiate
Select Final Suppliers and
Negotiate
Schedule Production Activities
Route Shipment and Select Carrier
Forecasting
Schedule Finishing Capacity
Determine Purchase
Requirements for Outsourcing
Plan Production Schedule Production
Schedule Load Capacity
General Production plan
SCO
R P
roce
sses
Task
s an
d A
ctiv
ities
w
ith ID
EF
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 150150
Problem-solving methodology classification
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 151151
Problem model
0..*
1
0..*
1
1..*
1
0..*1
0..*1
0..*1
SteelSupplyChain
Agent
Resource
-NumberofHours:int-ResourceName:int-Shift:int-TotalCapacity:int
ProductionUnit
-Stage:int-PUID:int-PUName:int
Transportation
-TransportationDate:in-TransportationTime:in-TransportationType:in-Destination:int
ResourceAttributes
-Capacity:int-ScheduledRate:int-Yield:int-ProductID:int
Cost
-FixedCost:int-OtherCost:int-TransportationCost
ProductProduction
-ProductionTime:int-SetupTime:int-Resource:int-BreakDownDurationP1:int-BreakDownDurationP2:int-BreakDownDurationType:int-DeffectivenessP1:int-DeffectivenessP2:int-DeffectivenessType:int-BreakDownFrequencyP1:int-BreakDownFrequencyP2:int-BreakDownFrequencyType:i
Product
-ProductType:int-ProductStatus:int-ProductSize:int-ProductID:int-ProductName:int-ProductQuantity:int
Output
Demand
-QuantityAccumulative:in-DemandNet:int-Costomer:int-Period:int
ProductCost
-InventoryHoldingCost:i-ProcessingCost:int-ProductSetupCost:int-ProductCost:int-Period:int
ProductStructure
-Quantity:int-MaterialID:int-ProductID:int
Structure
Mechanism
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 152152
Conceptual framework: Ontology engineering
Scenario narration
Informal knowledge representation
Formal axioms with ontology calculus
Axioms Implementation with a computer language
Axioms classification
Two ontology development specifications are proposed
For knowledge engineers: Situation and predicate calculus
For Software engineers: XML language specification
For each process item (process, task, or activity), ontology or a set of ontologies is designed consisting of three components: (1) model, (2) axioms defining constraints and rules held on data model, and (3) algorithms, which are step-by-step conditional descriptions of process flows.
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 153153
Ontologies
• Ontology calculus is utilized for capturing and representing the dynamics of supply chain processes.
• A supply chain markup language (SCML) for presenting knowledge about SC is being proposed.
( , r )Exist demand p oduct ( , )Less MaxInventory CurrInventory( (( * * ) ) ) ( )Poss do L AVG z STD s Il MakeOrder s Il+ = > ≡ −
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 154154
Supply chain markup language schema
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 155155
Supply chain markup language schema
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 156156
Ontology server
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 157157
Ontology-driven information system components
Semantic WebWeb Services
AgentsOntology serverProcessing logic
and inference engine
Vocabulary and annotation
Semanticsand structure
Distributes DMBS,Repositories,
et setera.
G a t h e r i n g
M a n a g e m e n t
I n t e r f a c e
O n t o l o g y
Management component is implemented through software agents. Interface component is implemented with Semantic Web and Semantic Web services.Ontology component is the library and the ontology server to support their capture, assembly, storage and dissemination.Gathering components is the same as in traditional IS, but with taxonomic links to common ontologies.
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 158158
Inventory model visualization
Modeling overview
Decision Modeling System
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 160160
Decision modeling system
ObjectivesTo develop a framework for
integration of different supply chain configuration models
– To elaborate a comprehensive supply chain configuration methodology
– To improve understanding of issues in SC configuration through analysis of models
– Validation through application
Goal– The ultimate goal is to
establish both robust and flexible supply chain configuration by exploring the problem from different points of view
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 161161
Design principles
Emphasis of common featuresSynergies between modelsData integrityModeling efficiencyReusabilityOpenness
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 162162
Supply chain configuration problem
Backbone for other supply chain management decisionsExisting models have limited scope adequacy– Uncertainty– Dynamic factors– Interactions between
decision making levels– Interactions between
supply chain members
Supply chain configuration problem in the context of an enterprise-wide information systems– Information systems
engineering dimensionData availabilityModeling effort
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 163163
Decision Modeling System
Forecasting
Strategic level optimization
Operational planning
Simulation
Final results
Adjust parameters andconstraints?
YES
Supp
ly c
hain
mod
elin
g da
ta b
ase
Prescriptive supply chain modelingModels use outputs from other models as their input dataModeling parameters and constraints are iteratively updated Modeling data base is used as unified source of information
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 164164
Supply chain configuration process
1. Identify objectives and main constraints; assess impact of expected configuration decisions
2. Gather required data3. Establish a decision making plan (i.e., models
used, situations to be evaluated, acceptance criteria)
4. Pre-selection. Reduce a number of alternatives5. Selection. Establish the configuration6. Sensitivity analysis. Return to step 5, if necessary7. Acceptance of results8. Implement the configuration decisions9. Evaluate the configuration decisions implemented
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 165165
Multiple views
Information systembased on the
common data model
Genericoptimization
model
Stochasticprogramming
modelHybrid model
Simulationmodel
Results
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 167167
Data model
Structures data required for supply chain configurationProvides uniform source of data for different types of models– Reduction of model building efforts– Reduction of errors– Integrity of results
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 168168
Configuration models
Generic MIP modelSimulation model associated with the MIP modelStochastic programming modelHybrid model for modeling impact of dynamic factors
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 169169
Reconfigurable supply chain modeling software prototypeArchitecture
Integration of prominent commercially available tools
Microsoft Excel,Decision modeling
shell
Internet browser,Application controls
LINGO,Optimization
ProModel (orARENA),
Simulation
SAP R/3,Data
management
ARIS,Processmodeling
Together J,Knowledge
analysis CommandsData
Data transferprograms
XML Spy,knowledge
design
Non-automatic link
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 170170
Reconfigurable supply chain modeling software prototype
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 171171
Decision modeling system software template
Modeling steps controls
Example of modeling
results
Handling of modeling
results Input data
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 172172
Some applications analyzed by this researcher
Stamping supply chainInvestments in flexible manufacturing facilitiesAffordable vehicle programHealthcare supply chain
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 173173
Some recent research topics explored by this researcher1. A coordinated supply chain dynamic production planning model
(integrated modeling, operational planning).2. Reconfiguration of multi-stage production systems to support
product customization using generic simulation models (simulation modeling and analysis).
3. Modeling floating supply chains (reconfigurable supply chains, supply chain modeling).
4. Application of multi-steps forecast to restrain the bullwhip effect (bullwhip effect in forecasting, inventory management).
5. Knowledge based lot-sizing (operational planning).6. Relationships among lot-size planning parameters and
environmental settings under stochastic demand (operational planning, forecasting management).
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 174174
Some recent research topics explored in this research
7. Supply chain coordination and information availability (supply chain coordination, information support).
8. Integrated approach to supply chain configuration (integrated modeling, supply chain configuration).
9. Elaborating process models for supply chain reconfiguration (process modeling).
10. Supply chain reconfiguration: Designing information support with system taxonomy principles (taxonomy modeling).
11. Supply chain reconfiguration: Domain and problem-solving ontology construction (ontology modeling).
12. Methodology and architectural framework of multiagent system for supply chain network management (agent modeling).
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 175175
Supply chain design checklistRequirements Definition
– Gather and Synthesize Domain Independent Knowledge
Industry / CompanyProduct
– Make Only General Inferences About the Problem
Identify a few potential problem areas– Select related problem(s)
– For the Selected Problem(s), IdentifyScopeObjectivePerformance MetricsA General Method of Inquiry & Problem-SolvingSchedule
– Write a Formal Document– Review the Document with Project Team
and Industry / Company Sponsors– Obtain Buy-in and Formal Approval of
Project Team and Industry / Company Sponsors
Develop a Design Framework– Clearly outline System -- formulation,
deduction, interpretation and validation issues
Design a System Architecture– Propose a Problem-Solving Hypothesis– Incorporate Design Components -- Structure, Control,
Optimization– Perform Value Analysis for Process, Order and
Information Life-Cycles– Identify Relationships between System Components
through --Process Flow DiagrammingEstablishing Decision-Making HierarchiesDefining Controls
– Create an Integrated Framework withFlows and Decision Modes represented hierarchicallyControls defined within and between system componentsLife-cycles represented within the product and process structures
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 176176
Supply chain design checklist (continued)
Analyze the System in a Specific Domain(Post-Modeling Analysis)– Perform Comparative Analysis
Check system fidelity w.r.t. “As-Is” system environmentCheck system fidelity w.r.t. “To-Be” system environment
– Validate Domain Specificity w.r.t.Performance MetricsBusiness Scenarios
Report Findings of Analysis– Document and report results w.r.t
Requirements Document– Offer problem specific and industry
/ company generic conclusions
Analyze the System in a Specific Domain(Pre-Modeling Analysis)– Develop a System Analysis Methodology
“As-Is” System Analysis– Identify system elements
Identify areas for improvement and approaches consistent with the problemDevelop analysis criteriaEstablish analysis mode
– Conduct Pre-Modeling AnalysisMake specific inferences about the problem
Develop Model to Represent System Analysis
– Model specific to problem domainRepresent design components --structure, control, optimization using problem inferences
Module III:Military Supply Chains
Issues and Perspectives
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 178178
Presentation Outline
Military Supply Chain: BackgroundMilitary Supply Chain: General ProblemMilitary Supply Chain: A Generic ConfigurationCommercial vs. Military Supply ChainsTrends and Paradigms in Military Supply ChainsIssues and Complexities in Military Supply ChainsMilitary Supply Chains TaxonomyPotential Military Supply Chains Configuration?
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 179179
Background
Military supply chains are designed primarily to support military operations– Military operations characterize events with national /
international significanceDuring peace time military consumes resources for preparedness for war time operationsDuring peace time military supply chain is similar to a business supply chain– Both emphasize on minimizing – cost and lead time– Both target improving efficiency in operations– Both strive to adopt best practices
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 180180
Background(continued)
Decision-making for military supply chains– Strategic decisions for war time are taken during
peace time, considering level of threat and force capabilities
Supply levels at various echelonsLogistics goals and policies
– Operational and tactical decisions are taken during war time, considering theatre environment, and specific scenarios
Supplies to commit for theatre deploymentCombat unit’s logistics
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 181181
Background(continued)
Motivation for designing and optimizing military supply chains is planning, implementing, and controlling– Supplies– Resource mobilization– Procuring and Moving ordnance– Maintenance activities– Medical resources
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 182182
Background(continued)
The aim of the Defense Logistics Agency is to provide an integrated defense logistics infrastructure by:– Streamlining the military’s supply chain
system– Harnessing information technology– Cutting costs by adopting practices from
the corporate world
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 183183
General Problem
Design a military supply chain that effectively responds to battlefield needs during a military operation in a specific theatre scenario by optimizingallocation of resources underconstraints of force size and capability, theater environment, enemy size and capability, nature of threat, and doctrine
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 184184
A Generic Configuration
Corps Division Brigade Battalion Company Platoon Squad
Theatre
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 185185
Commercial vs. Military Supply Chains
Military supply chain by and large mimics a consumer goods supply chain– Manufacturers (to make products)– Warehouses (to store products)– Retail stores (general supply units)– Local stores (direct supply units)
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 186186
Commercial vs. Military Supply Chains
Unstable (dynamic)Generally stable (static)Structure
Extensive - complexIntensive – simpleInventory type
Strict – customer-centric, mission critical (war readiness), high reliability (almost 100%)
Relaxed – internal (profit maximization, cost minimization, lead time minimization)
Service Measures
MacroMicroModeling Approach
MassiveSparseFlow
Secondary Primary minimizationCost
Allocation of resourcesDemand, cost, lead timeUncertainty
Short-term, rareLong-term, routineOperation
MilitaryCommercialCriterion
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 187187
Trends and Paradigms
Velocity ManagementTrade mass for velocityJust-in-case vs. Just-in-timeLean operationsFlexible operationsQuick response (maximize response)
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 188188
Issues and Complexities
Massive size and scopeDefined by the term “Mission Critical”Extensive inventories for wide range of products comprising large number of SKU’s across varied classes of supply itemsVast, complex, and unique distribution systemUnique metrics, very different from commercial supply chains
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 189189
Military Supply Chains Taxonomy
Three types of supply chains:– Fast, low volume chain [moves food, medicine,
clothing, etc.]– Slow, large items transport and maintenance
chain [moves weapons system]– Deployment chain [moves large number of
troops and materials]Supply chain characteristics:– Forward pipeline– Reverse pipeline– Lateral pipeline
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 190190
How to contact me?
Charu Chandra, Ph.D.Associate ProfessorIndustrial and Manufacturing Systems Engineering
DepartmentUniversity of Michigan – DearbornEC2230, 4901 Evergreen RoadDearborn, Michigan 48128-1491, USATel: 313-593-5258; Fax: 313-593-3692E-mail: [email protected]: http://www.engin.umd.umich.edu/~charu/
January 11, 2006 Charu Chandra, The University of Michigan-Dearborn, MI
Defense Supply ChainA Logistics Lifecycle Management for TACOM’s Extended Enterprise
A Short Workshop on Developing and Implementing Supply Chain
5th Annual U.S. Army Vetronics Institute Winter Workshop Series U.S. Army, TACOM, Warren, Michigan
January 9-12, 2006
Presenter: Charu Chandra, Ph.D.Associate ProfessorIndustrial and Manufacturing Systems Engineering DepartmentThe University of Michigan-DearbornEngineering Complex 22304901 Evergreen Road, Dearborn, MI 48128-1491Phone: 313-593-5258; Fax: 313-593-3692; E-mail: [email protected]: http://www-personal.engin.umd.umich.edu/~charu/
Industry ExampleFor reference purposes only.
Please do not distribute
January 11, 2006 Charu Chandra, The University of Michigan-Dearborn, MI 3
Food Product Supply ChainBench Markers -- Lead Time, Inventory and Information Sharing
Share Harvest Plans Share Production Plans Share Logistics Plans
Inbound Logistics Operations
Outbound Logistics Marketing Service
RawMaterials
Food Ingredients
Negotiate & commit LTp
Provide INp updates
Share Plan Progress
FinishedGoods
DistributedGoods
Processed Food Packaged Food
Share Plan Progress
Negotiate & commit LTm
Provide INm updates
Share Plan Progress
Negotiate & commit LTo
Provide INo updates
MarketedProduct
Labeled Food
Share Program Progress
Negotiate & commit LTs
Provide INs updates
ServicedProduct
S-C Members Farmer’s Coop ADM Kraft PillsburySara LeeGeneral Mills
Grocery Food
KruegerSmiths
Bid on LTs
Manage INs based on LTs
INm LTm
Bid on LTm
Manage INm Logistics based on LTm
Share Marketing Programs
INs LTs
INo LToINp
LTp
INi LTi
Bid on LTo
Plan Production INo based on LTo
Bid on LTp
Plan Harvesting INp based on LTp
January 11, 2006 Charu Chandra, The University of Michigan-Dearborn, MI 4
Steel Product Supply ChainBench Markers -- Batches, Process & Setup Times, Bottleneck Operations and Information Sharing
S-C Members Iron Ore Mines Mini Mills Distributor
Inbound Logistics Operations Outbound Logistics
RawMaterials
FinishedGoods
Iron Ore Ingot / Fabricated /Finished Steel
SteelProduct
Packaged SteelProduct
INoLTo
INp LTp
INi LTi
Share Plan Progress
Negotiate & commit on Batches and LTo
Provide INo updates
Negotiate & commit LTp
Provide INp updates
Share Plan Progress
Bid on LTp
Plan Ore Mining INp based on LTp
Share Mining Plans
Bid on Batches and LTo
Plan Production Lots, Process and Setup Times for INo based on LTo
Share Production Plans
A Textile Industry Supply Chain Profile
January 11, 2006 Charu Chandra, The University of Michigan-Dearborn, MI 6
Objective of the Supply Chain• Apply the philosophy of Synchronous
manufacturing, which promotes harmony in the entire production processes to achieve goals of the supply chain.
• The attempt is to coordinate all resources in the supply chain, so that they work in harmony or are “synchronized”.
January 11, 2006 Charu Chandra, The University of Michigan-Dearborn, MI 7
GoalsImprove Performance
Financial
• Net Profit
• Return on Investment
• Cash Flow
Operational
• Throughput
• Inventory Levels
• Expenses
January 11, 2006 Charu Chandra, The University of Michigan-Dearborn, MI 8
PrincipleBalance product flow throughout the system
Process Time (A) Process Time (B)
• Rather than balancing capacities, the flow of product through the system should be balanced
January 11, 2006 Charu Chandra, The University of Michigan-Dearborn, MI 9
Understanding the Problem - Key #1Learn about the Product
Fabric & Garment
Labels(Artistic Identification Systems)
Insulation (3M Company)
Knit Cuffs(Green Mountain Knitting)
Zippers (YKK)
Grommets & Washers(Fastener Supply)
Vendors SuppliedPellon
Pocket LiningSleeve Lining
Waist Draw Cord
Other MaterialsNylon Filament Yarn
(DuPont)
Nylon Supplex® Shell (Glenn Raven Mills, Inc)
Lortex, Inc.
Polartec® Body Lining(Malden Mills)
Parka(Cascade West Sportswear, Inc)
Catalog Item(L.L. Bean)
January 11, 2006 Charu Chandra, The University of Michigan-Dearborn, MI 10
Learn about the ProcessProcess Steps for Men’s Nylon Supplex® Parka
January 11, 2006 Charu Chandra, The University of Michigan-Dearborn, MI 11
Decompose ProcessesLevel 0
12 6 8
3 4 5 7
Yarn Processing
Storage atYarn Facility
Cotton Fiber Yarn Packaged Yarn
Yarn Warehouse
Greige Fabric Mill
Storage at Greige Fabric
Mill
10 11 129 13 14 15 16
Supplex FabricRolls
Process Yarn Greige Supples Fabric
Greige Fabric Processing
Transportationof Greige
Fabric
Storage atFinish/Dye Mill
Dyeing/Finishing
1817
Storage atCut/Sew Facility
19
ApparelManufacture
20
Packagingand Shipping
21
RetailDistribution
22 Customer
Storage atRetail Stores
Key: denotes transportation activity denotes storage denotes a process
denotes an end-product
January 11, 2006 Charu Chandra, The University of Michigan-Dearborn, MI 12
Understand Business & Information FlowMarketing Activity
CreateSales Forecast
Customer P.O.AccountForecasts
from Customers
Production PlanningActivity
Historical ProductionPrepare
Production Plan
Inventory Status
Sales Forecast &Customer P.O.
Weekly Updated RM Rolling Forecast& RM PO sent to Texas
Capacity Plan
Production ProcessDesign
Evaluate ProductionProcess
Marketing ActivityDetermine
Reallocation Needsacross Accounts
if Necessary
Production PlanningActivity
Production SchedulingVia Product Wheel
Capacity AllocationRequirements
ProductionSchedule
RM Availability Forecast &RM Shipping Notice from Texas
Prod nPlan
uctio
Plant Operations
Execute Production
Determine the Need for"Break-In" Scheduling
Organization &Management
uctio
A-B-C Priority Configuration
Prod nProcess
Configuration
Financial Data
RM Shipping Invoice
Final CapacityAllocation &Scheduling
GlenTouch
Scheduled"Break-Ins"
Scheduled"Break-Ins"
Fill & Warp Shippedto GT and FFD Respectively
January 11, 2006 Charu Chandra, The University of Michigan-Dearborn, MI 13
DP.7Input
Output
Activity Sequence
DP.2
DP.23 DP.26
Flat Yarn
Produce Polymer via CP Technology(6h)
DP.18
Inspect
Key:End Product
MaterialProcessingStorage
TransportationInspection Set-Up
Pack intoQuads
DP.12 DP.16
Extrude Strip
DP.31
Ship FlatYarn
DP.20
WrapYarn6-8 h
Ship Fill &Warp Yarn
1 day
Store
DP.6
DenierChange
3-8 h
DP.5
ProductionSet-up5-6 h
OverhaulCP Machines
10 days
Delay
DP.28
TOMove
Handling
TO
Unload& Shelve
HMD & AA
DP.3
TOTOTOTODP.13 DP.14
Draw Wind
72 h
DP.29
Store YarnShelve1 day
DP.15 DP.17 DP.19 DP.21
TODP.11
Note: Documentationindicates DP.12 - DP..22requires 6-8 h.
TO
DP.24
DP.10DP.9DP.8
Evaporator ReactorVessel Flasher Finisher
DP.1
DP.22DP.27
Cure Yarn5 days
DP.30
Unshelve& Load
DP.4
Process/Inspection
DP.25
Load
Understand the Activity Flow
January 11, 2006 Charu Chandra, The University of Michigan-Dearborn, MI 14
Understand the Process Flow
InputReceivingDP.1 - DP.2
Polymer ProductionDP.3 - DP.10
Pre-Yarn ProductionDP.11 - DP.16
Inspect & PackageDP.17 - DP.23
Ship & Cure/StoreDP.24 - DP.29
ShippingDP.30 - DP.31 Output
January 11, 2006 Charu Chandra, The University of Michigan-Dearborn, MI 15
Understanding the Problem - Key #2Understand the Manufacturing Diversity
FIBERFIBER
FIBER
TEXTILE
APPAREL
FlexibilityVery Jumbled Flow(Job-Shop)
Less Jumbled Flow(Batching)
Machine-pacedLine Flow
Continuous OutputRigid Flow(Assembly Line) Custom
ProductsLow Volume of Many Products
High Volume of Several Major Products
Low Product-Mix
Pro
cess
Flo
w
Retailer - Non ManufacturingHigh
VolumeLowVery High VolumeCommodity
High
January 11, 2006 Charu Chandra, The University of Michigan-Dearborn, MI 16
Understanding the Problem - Key #3Find out about the Logistics
Cascade West
DuPont
Glen RavenMills
Malden Mills
L.L. Bean ®
Major Population CentersSupply Chain Members
Supply Chain
Retail Distribution
Note: Supply Chain Length is ~ 9,500 highway miles
Polartec ®Supplex ®
Jacket
Yarn
January 11, 2006 Charu Chandra, The University of Michigan-Dearborn, MI 17
Analyzing the Problem - Step #1Breakdown of Productive System
Total Time of Operation for Parka manufacturing under existing system
Total Work Content in Parka manufacturing
Work Content in Parka manufacturingdue todefective -product design,and product orraw materialspecifications
Minimum Work Contentin Parka manufacturing
Total Ineffective Time inParka manufacturing
Work Content in Parka manufacturingdue to inefficient methods, processes, material flow, setup, plant layout, etc.
Contribution of time due to inefficient logistics in Parka manufacturing
Contribution of time due to lack of productivity, unskilled work force, etc. in Parkamanufacturing
Opportunities for problem solving by Methods EngineeringGoal of Methods Engineering
(295 days)
(56 days) (239 days)
DetailedAnalysisRequiredto bring outthese details
Manufacturing Time Line for the Parka Supply-Chain
1st Order WasteI
2nd Order WasteII
3rd Order WasteIII
4th Order WasteIV
Identifying Bottleneck LocationsAnalyzing the Problem - Step #2
WaitTime,Days
0102030405060708090
100
Res
erve
Inve
ntor
y
6.2
Sto
re in
War
ehou
se
5.1
War
ehou
se
Sto
rage
5.7
Rec
eivi
ngS
tora
ge
3.1
War
ehou
se
Sto
rage
3.8
War
ehou
se
Sto
rage
2.5
Rea
dyIn
vent
ory
6.3
Shi
p to
Cut
& S
ew
4.6
Spr
ead
&C
ut F
abric
5.2
Shi
p to
Ret
ail
5.8
Legend1.x Yarn Facility2.x Texturizing3.x Griege Fabric Mill4.x Finish/Dye Mill5.x Cut/Sew Facility6.x Retail
January 11, 2006 Charu Chandra, The University of Michigan-Dearborn, MI 19
Identifying Bottleneck ActivitiesAnalyzing the Problem - Step #3
Activity Breakdown for Supply Chain
0
10
20
30
40
50
60
70D
uPon
t
Gle
nR
aven
Mal
den
Cas
cade
Wes
t
LL B
ean
Supply Chain Member
Num
ber o
f Act
iviti
es
DelaySetupInspectPackageStorageMove/TransportMaterial Process
January 11, 2006 Charu Chandra, The University of Michigan-Dearborn, MI 20
Problem Solving TechniqueConvert Bottleneck Activity to Nonbottleneck Activity
Drum, Buffer, Rope Approach to Synchronization
A B C D E F
Bottleneck (Drum)
Inventorybuffer
(time buffer)Communication
(rope)
Market
January 11, 2006 Charu Chandra, The University of Michigan-Dearborn, MI 21
Organizing Processes Facilitates SynchronizationPipeline CompanyProvideri Provideri+1
ManufacturingReceiving Shipping
Process Flow Model
Activity 1 Activity 2
Activity Flow Model
Task 1 Task 2
Task Flow Model
RawMaterials
FinishedGoods
RawMaterials
WIP WIP
WIP WIP
Customeri
Material Flows Inventories Transformations
January 11, 2006 Charu Chandra, The University of Michigan-Dearborn, MI 22
Information Sharing is Key to Synchronizing
Customer
Marketing
Sales Production Planning
Procurement Production ShippingReceivingVendors
Customer Order,Customer Payment
Order Status,Sales Invoice
Advertising, Catalog StockLevel
Report
ForecastReport
CapacityReport
Surveys
Sales HistoryAggregated Orders
ShippingSchedule
Sales HistoryProcurement
ScheduleProductionSchedule
ShippingInvoice
ShippingInvoice
Purchase Order,Payment Shipping
NoticeShippingNotice
ShippingNotice
January 11, 2006 Charu Chandra, The University of Michigan-Dearborn, MI 23
System Performance Simulation
A D down
SUT
A D down
SUT#
demand
use #
changeu A D down
SUT
A D down
SUTuse #
changeu
Resource 1 Resource 2 Machine 4BottleneckResource
use #
changeu
a
b
V 1 2#
Count
Drum
Rope(Constrained Feedback)
Buffer
January 11, 2006 Charu Chandra, The University of Michigan-Dearborn, MI 24
BenefitsMajor Savings in Production Cycle Time
• Setup time
• Process time
• Queue time
• Wait time
• Idle time
January 11, 2006 Charu Chandra, The University of Michigan-Dearborn, MI 25
BenefitsAll Functions in the Manufacturing Enterprise
• Marketing– discourages holding large amounts of finished goods
inventory• Purchasing
– discourages placing large purchase orders that on the surface appear to take advantage of quantity discounts
• Manufacturing– discourages large work in process and producing earlier
than needed
January 11, 2006 Charu Chandra, The University of Michigan-Dearborn, MI 26
Classification of Supply-Chain Synchronized Models
A B C D E F
Bottleneck (Control)
RawMatl.
Fini-shedGoods
Customer
Push System
Material Flow Information Flow
1
A B C D E F
Bottleneck (Control)
Inventory buffer (time buffer)Rope (Information)
RawMatl.
Fini-shedGoods
Customer
RawMatl. 2 n
Fini-shedGoods
Customer
PullPull
Pull System
Synchronous Flow System
...
January 11, 2006 Charu Chandra, The University of Michigan-Dearborn, MI 27
Comparison of Objectives in Synchronized Models
Time
Met
rics
Utilization
Production Lead Time
(Supply) PushTime
Met
rics
Utilization
Production Lead Time
(Demand) PullTime
Met
rics
Utilization
Production Lead Time
(Push-Pull) Synchronous
Objectives:• Control throughput• Measure WIP Inventory
Objectives:• Control throughput• Control WIP Inventory
Objectives:• Control WIP Inventory• Measure throughput
Source: Dan L. Shunk. Integrated Process Design and Development, 1992. Business One Irwin, Homewood, Illinois.
January 11, 2006 Charu Chandra, The University of Michigan-Dearborn, MI 28
Comparing SynchronousManufacturing to MRP (or the Push philosophy)
• MRP uses backward scheduling
• Synchronous manufacturing uses forward scheduling
January 11, 2006 Charu Chandra, The University of Michigan-Dearborn, MI 29
Comparing Synchronous Manufacturing to JIT
(or the Pull philosophy)
• JIT is limited to repetitive manufacturing
• JIT requires a stable production level
• JIT does not allow very much flexibility in the products produced
January 11, 2006 Charu Chandra, The University of Michigan-Dearborn, MI 30
Comparing Synchronous Manufacturing to JIT
(or the Pull philosophy)
• JIT requires work in process when used with Kanban so that there is "something to pull"
• Vendors need to be located nearby because the system depends on smaller, more frequent deliveries
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 1
Defense Supply ChainA Logistics Lifecycle Management for TACOM’s Extended Enterprise
A Short Workshop on Developing and Implementing Supply Chain
5th Annual U.S. Army Vetronics Institute Winter Workshop Series U.S. Army, TACOM, Warren, Michigan
January 9-12, 2006
Presenter: Charu Chandra, Ph.D.Associate ProfessorIndustrial and Manufacturing Systems Engineering DepartmentThe University of Michigan-DearbornEngineering Complex 22304901 Evergreen Road, Dearborn, MI 48128-1491Phone: 313-593-5258; Fax: 313-593-3692; E-mail: [email protected]: http://www-personal.engin.umd.umich.edu/~charu/
Supply Chain Logistics Configuration and Supportive Information Technology
Examples
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 3
Supply Chain Configuration
Unit P1 Resource R1 Resource R2
Process Pr1
Process Pr2
Process Pr3
Process Pr4
Unit P2 Resource R3 Resource R4
Process Pr1
Process Pr3
Process Pr4
Process Pr5
Product
Process Pr3
Process Pr2
Process Pr5
Process Pr3
Process Pr2
Process Pr5
Process Pr3
Process Pr2
Process Pr5
Time t = t1 Time t = t2
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 4
Supply Chain Network Configuration Examples
Parallel Sequential Distributed
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 5
Product structure
Car Manufacturing Components– Body– Interior– Under Carriage– Power Train
Under Carriage– Wheels– Front and Rear Axles– Front and Rear Shock Absorbers
Body• 14 Preformed Tubes• 5 Exterior Sheets
Interior– Dashboard– Front Seats– Rear Seat
Power Train– Engine– Transmission– Cardan Shaft
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 6
Car Manufacturing Components
Car
Power Train
UnderCarriage
Interior
Body
14 Preformed Tubes5 Exterior Sheets
Dashboard2 Front seats
Rear Seat
2 Front Axles
2 Rear Axles
4 Wheels
2 Front Shock Absorbers
2 Rear Shock Absorbers
Engine
Transmission
Cardan Shaft
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 7
Parallel Distributed Production Model of a Car
Dashboard
Seat Manufacturer
Engine
Shaft / AxlesManufacturer
Transmission
Wheel Manufacturer
Shock AbsorberManufacturer
Interior Assembly
Power Train Assembly
Under Carriage
Forming TubesManufacturer
Exterior SheetManufacturer
Exterior Assembly
Body Assembly
Tier 3 Tier 2 Tier 1 Tier 0
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 8
ExampleAutomotive Supply Chain
Raw Material Suppliers
Tier 2 Suppliers
Tier 1 Suppliers
Manufacturer Dealers Consumers
Product (Materials) Flow
Demand (Information) Flow
Final CarAssembler
Power TrainAssembler
InteriorAssembler
DashboardManufacturer
TransmissionManufacturer
EngineManufacturer
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 9
Supply chain configurations
DashboardManufacturer
SeatManufacturer
EngineManufacturer
ExteriorAssembly
BodyAssembly
Exterior SheetManufacturer
TransmissionManufacturerShaft / Axles
ManufacturerWheel
ManufacturerShock Abs.
ManufacturerForm. Tubes
Manufacturer
EngineManufacturer
ExteriorAssembly
Power TrainAssembly
Exterior SheetManufacturer
TransmissionManufacturer
Under CarriageAssembly
Body / InteriorAssembly
DashboardManufacturer
SeatManufacturer
WheelManufacturer
Shock Abs.Manufacturer
Shaft / AxlesManufacturer
Form. TubesManufacturer
DashboardManufacturer
SeatManufacturer
EngineManufacturer
ExteriorAssembly
BodyAssembly
Exterior SheetManufacturer
TransmissionManufacturer
Shaft / AxlesManufacturer
WheelManufacturer
Shock Abs.Manufacturer
InteriorAssembly
Power TrainAssembly
Under CarriageAssembly
Form. TubesManufacturer
Parallel Distributed Production Model - manufacturing is mainly done in-house and is parallel
Sequential Distributed Production Model - manufacturing mainly is done in-house and sequentially
One-Stage Distributed Production Model -manufacturing is highly outsourced
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 10
Process Data Model for Supply Chain Network Configuration
A process model representation for an automotive SC utilizing a car with four main components Body, Interior, Under Carriage, Power Train, and several constructive elements within these components. In order to manufacture this car, various automotive SC production models may be created; different configurations are being evaluated using experimentation
One-Stage Distributed Production Model
Parallel Distributed Production Model
Sequential Distributed Production Model
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 11
Supply Chain Taxonomy
Customers
Distribution
Information
Finished Product
System L(2)
Taxa
Supply
IT Attributes
Production DistributionSupply
Production Attributes
Production
Production Attributes
Subsystem L(0)
Raw Material Supplier
Dealer’s Attributes
Distribution Attributes
Dealer
DistributionSupply Production
Tier 1 Supplier
Supply Attributes
Distribution AttributesSupply Attributes
Production Attributes Distribution AttributesSupply Attributes
Tier 2 Supplier
System L(0)
Subsystem L(2)
Taxa/Classification
System L(1)
Taxa/Classification
Subsystem
Customer's Attributes
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 12
Taxonomic Representation of Supply Chain Member
Production Attributes
• Work Process Inventory• Product Coordination•SC Membership specific costs
Inventorydination
Supply Attributes
• Component• Product coor
Distribution Attributes
• Finished Product Inventory• Distribution configuration
•Lead Time•Product costs•Holding costs•Transportation costs•Assembly costs per Unit•Assembly costs per Batch•Set up time
Work In Process Inventory
•Lead Time•Customer Demand•Number of Product•Transport. Costs•Product costs•Holding costs•Service level•Delivery Policy•Selling Price
Finished Prod Inventory
•Assembly•Fixed Capacity costs•Operating Time unit•Supplier Integration•Lead time•Batch/lots size•Capacity Utilization•Capacity•Assembly Policy
Product coordination
•Lead Time•Customer Demand•Number/quantity of component•Trans Costs per Unit•Trans Costs per Batch•Product costs•Holding costs•Set up time•Ordering Policy•Buying price
Component Inventory
•Backorder Penalty•Cost of Resources•Costs of resources utilization•Inventory Handling
•Demand Planning
System Components
• Demand Planning
SC Member specific costsInformation
Distribution configuration•Number of warehousing•location•size•space of Product•Transport resources
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 13
Prototypic Implementation of the Supply Chain Object Model
• Utilizes flexible data modeling approach based on the Design of Structured Objects (DESO) architecture.
• Allows modeling any object structure with limited number of relations (tables).
CLASSClass_IDClass_NameClass_Coment
OBJECTObject_IDClass_IDObject_NameObject_Coment
ATTRIBUTEAttribute_IDClass_IDAttribute_NameAttribute_Coment
VALUEValue_IDAttribute_IDObject_IDValue_Value
HISTORICAL_VALUEValue_IDHValue_TimeHValue_Value
1:∞ 1:∞
1:∞1:∞
1:∞
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 14
A Supply Chain Dynamic Constraints NetworkGeneric Object Data Model
Supply Chain
Product
Component Process PU – Product
Production Unit
PU–Product–PU
Resource
Generic Activity
OBJECT
Power Train Manufacturer (PTM)TransmissionPTM - Transmission
OBJECTS
ATTRIBUTE
ProducerProductPriceProduct NameProducer Name
ATTRIBUTES
VALUE
Power Train Manufacturer
Transmission T-234
PTM
Transmission
VALUES
HISTORICAL_VALUE
01.01.01 $1,50002.01.01 $1,52003.01.01 $1,550
HISTORICAL VALUES
CLASS
Production UnitProductPU - Product Relation
CLASSES
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 15
Supply Chain Network Components
OrganizationProduct
Structure Definition
Network structure definition
Flow coordination
Inventory Management
Capacity Management
Manufacturing
Forecasting Control
Common Data Model
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 16
An Enterprise Information Management System
Customer
Marketing
Sales Production Planning
Procurement Production ShippingReceivingVendors
Customer Order,Customer Payment
Order Status,Sales Invoice
Advertising, Catalog
Surveys
Sales HistoryAggregated Orders
StockLevel
Report
ProductionSchedule
ProcurementSchedule
ShippingSchedule
Purchase Order,Payment
ForecastReport
CapacityReport
ShippingInvoice
ShippingInvoice
Sales History
ShippingNotice
ShippingNotice
ShippingNotice
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 17
SAP R/3 Integration Model
R / 3Client / Server
ABAP / 4
SDSales &
DistributionMM
MaterialsManagement
PPProductionPlanning
QMQuality
ManagementPM
PlantMaintenance
HRHuman
Resources
FAFinancial
Accounting
COControlling
AMFixed Asset
Management
PSProjectSystem
WFWorkflow
ISIndustrySolutions
January 11, 2006January 11, 2006 Charu Chandra, University of Michigan - Dearborn 18
Logistics Sub-Modules
• Sales and Distribution• Production Planning• Materials Management• Quality Management• Plant Maintenance• Logistics Information System• Project System• Product Data Management