Supply Chain Management Concepts

OEM 2001

Joe Geunes

Supply Chain Management and Analysis

What is Supply Chain Management (SCM)? What is the difference (if any) between SCM and Business

Logistics Management? Supply Chain Definition (G.C. Stevens, 1989): “. . . a connected

series of activities which is concerned with planning, coordinating and controlling materials, parts, and finished goods from supplier to customer. It is concerned with two distinct flows (material and information) through the organization.”

The Basic Problem: Get the right amounts of the right products to the right markets at the right time in the most economical way.

Key Supply Chain Activities

Customer Service Standards– Cooperate with marketing to:

Determine customer needs and wants for logistics customer service Determine customer response to service Set customer service levels

Transportation– Mode and transport service selection– Freight consolidation– Carrier routing– Vehicle scheduling– Equipment selection– Claims processing– Rate auditing

Key Supply Chain Activities

Inventory management– Raw materials and finished goods stocking policies– Short-term sales forecasting– Product mix at stocking points– Number, size, and location of stocking points– Just-in-time, push, and pull strategies

Information flows and order processing– Sales order-inventory interface procedures– Order information transmittal methods– Ordering rules

Key Supply Chain Support Activities

Warehousing– Space determination– Stock layout and dock design– Warehouse configuration– Stock placement

Materials handling– Equipment selection– Equipment replacement policies– Order-picking procedures– Stock storage and retrieval

Key Supply Chain Support Activities

Purchasing– Supply source selection– Purchase timing– Purchase quantities

Protective package design for – Handling– Storage– Protection from loss and damage

Cooperate with production/operations to– Specify aggregate quantities– Sequence and time production output

Key Supply Chain Support Activities

Information maintenance– Information collection, storage, and manipulation– Data analysis– Control procedures

We can’t forget additional factors related to product design for manufacture and distribution, i.e., the constraints that product characteristics place on ease of manufacture and distribution. Another important issue is product mix from a marketing standpoint, i.e., which products the chain will carry.

Logistics Strategy and Planning

Three objectives of logistics strategy:– Cost reduction (variable costs)– Capital reduction (investment, fixed costs)– Service Improvement (may be at odds with the above two

objectives). Major Logistics Planning Areas:

– Customer service goals (customer requirements/costs of providing service)

– Facility location strategy (assign markets to plants to minimize distribution costs)

– Inventory decisions (push, pull, location of stocks)– Transport strategy (modes, shipment sizes, routing, scheduling)

Considerations in Formulating Strategy

Demand (volume, dispersion, predictability) Customer service requirements (customer

expectations and competition) Product characteristics (density, value, risk) Logistics costs (based on above three

factors) Pricing policy (does the customer price

include delivery charge?)

Typical Supply Chain Strategies

Postponement – Delay product differentiation until as late as possible in the production process

– HP printers that serve different countries used to be produced as separate products, but now the same product uses an external power pack that is packed in the box depending on the destination

– Benetton delays dying of fabrics until after the sweater is produced and demand is realized).

– Postponement usually involves products with a highly modular architecture (e.g., Gateway and Dell computers).

Typical Strategies:

Consolidation –if the market demands several products made by the manufacturer, consolidating them into one warehouse will make it more economical to send frequent consolidated shipments of full truckloads to the market.

Mass Customization –a modular product architecture helps enable mass customization, which is the ability to mass produce goods that can quickly and easily be customized to individual specifications (as in the Gateway and Dell computer examples).

JIT/VMI - Just-in-time and vendor managed inventory strategies to smooth flow of goods and increase response time of suppliers.

Product Characteristics

Product life cycle 80-20 rule Individual characteristics:

– Weight-Bulk ratio (ration of weight to volume, density; e.g. cotton vs. steel)

– Value-Weight ration (coal vs. jewelry)– Substitutability (customer’s reaction when not in

stock)– Risk characteristics (perishability, flammability, ease

of being stolen)

Customer Service Elements

– Pretransaction elements: Written policies System flexibility Clarity of procedures Technical help

– Transaction elements Backorder policies Order cycle time (lead time) Product substitution Complexity of transaction (convenience)

Customer Service Elements

Post-transaction elements– Installation, warranty, repairs; Claims, complaints; Packaging;

Temporary replacement during repair Courtesy, Reliability and integrity Willingness to respond to customer wants and needs

(with new or better products) Clarity of communications to customer Integrated information systems A monopolistic company must also adhere to these

guidelines in case competition strikes in the future (e.g. AT&T, cable, utility companies)

Customer Service Aspects of Logistics:

Order cycle time: time between placing order and receiving product

– Order transmittal– Order processing and assembly– Additional stock acquisition time (if out of stock)– Delivery time

• “On the average it is approximately six times more expensive to develop a new customer than it is to keep a current customer. Thus, from a financial point of view, resources invested in customer service activities provide a substantially higher return than resources invested in promotion and other customer development activities.”

– P.S. Bender, Design and Operation of Customer Service Systems, 1976.

Cost vs. Service Models

Customer Service Level

Revenue (sales)

Profit

Logistics costs

Transport Fundamentals

Transport involves equipment (trucks, planes, trains, boats, pipeline), people (drivers, loaders & unloaders), and decisions (routing, timing, quantities, equipment size, transport mode). In underdeveloped countries we often find it necessary to locate production close to both markets and resources, while in countries with developed distribution systems people can live in places far from production and resources.

When deciding the transport mode for a given product there are several things to consider:

Mode price Transit time and variability (reliability) Potential for loss or damage

Single-mode Service Choices and Issues

– Rail (long distance, heavy goods, slow mover) – Carload (CL) vs. less-than-carload (LCL per hundredweight cwt.)

avg. length of haul = 720 miles avg. speed = 22 mph Larger cars can carry around 83 tons

– Truck (Smaller goods than rail, medium time duration) avg. 646 miles for truckload (TL), 274 miles for less-than-

truckload (LTL) More than ½ shipments are less than 10,000 lbs. Trucks can go door-to-door as opposed to planes and trains Can hold 30-50,000 lbs. depending on the product density avg. 35-45 mph

Single-mode Service Choices and Issues

Air (Smallest size goods, quick transport)– avg. 545-585 mph– avg. distance of 1,300 miles– Low variability in lead time– Requires transport to and from airport

Water (Extremely slow, large goods, international trade)– avg. speed on Mississippi = 5 – 9 mph– avg. distance 500 miles on rivers, 550 miles on Great Lakes, 1775 miles

coast lines– Up to 40,000 tons

Pipeline (limited product line, liquids, gases)– 3 – 4 mph (89,000 gallons per hour in a 1ft diameter pipe)– Highly reliable– Low product losses

Transport Cost Characteristics

– Fixed costs: Terminal facilities Transport equipment Carrier administration Roadway acquisition and maintenance

– Variable costs: Fuel Labor Equipment maintenance Handling, pickup, and delivery

Transport Cost Characteristics

Rail– High fixed costs, low variable costs– High volumes result in lower per unit (variable) costs

Highway– Lower fixed costs (don’t need to own or maintain roads)– Higher unit costs than rail due to lower capacity per truck– Terminal expenses and line-haul expenses

Water– High terminal (port) costs and high equipment costs (both fixed)– Very low unit costs

Air– Substantial fixed costs– Variable costs depend highly on distance traveled

Pipeline– Highest proportion of fixed cost of any mode due to pipeline ownership and

maintenance and extremely low variable costs

Transportation Rate Structures

– Volume-based rates (based on weight)– Distance-based rates– Typically some combination of both of the above– Important that rates are consistent and relatively

simple– Simplest rate – US Mail first class letter rate– Typical rate charts based on distance and weight – Freight “class” also very important – the class of an

item depends on its density and bulkiness

Vehicle Routing:

– Separate single origin and destination: Once we have selected a transport mode and have

goods that need to go from point A to point B, we must decide how to route a vehicle (or vehicles) from point A to point B.

Given a map of all of our route choices between A and B we can create a network representing these choices The problem then reduces to the problem of finding the shortest path in the network from point A to B.

This is a well solved problem that can use Dijkstra’s Algorithm for quick solution of small to medium (several thousand nodes) sized problems.

Multiple Origin and Destination Points

– Suppose we have multiple sources and multiple destinations, that each destination requires some integer number of truckloads, and that none of the sources have capacity restrictions. In this case we can simply apply the transportation method of linear programming to determine the assignment of sources to destinations.

Sources Destinations

Transportation Problem Formulation:

– Minimize

– Subject to:

c xij ijj Ji I

x s i I

x d j J

x i I j J

ijj J

i

iji I

j

ij

,

,

, 0 ,

Coincident Origin and Destination: The TSP

If a vehicle must deliver to more than two customers, we must decide the order in which we will visit those customers so as to minimize the total cost of making the delivery.

We first suppose that any time that we make a delivery to customers we are able to make use of only a single vehicle, i.e., that vehicle capacity of our only truck is never an issue.

In this case, we need to dispatch a single vehicle from our depot to n - 1 customers, with the vehicle returning to the depot following its final delivery.

This is the well-known Traveling Salesman Problem (TSP). The TSP has been well studied and solved for problem instances involving thousands of nodes. We can formulate the TSP as follows:

TSP Formulation

– Minimize

– Subject to:

c xij ijj Ji I

x i I

x j J

x U U N

x i I j J

ijj J

iji I

iji j E U

ij

1

1

1

,

,

,

{0,1}, ( , ) ( )

,

TSP Formulation

In the TSP formulation if we remove the third constraint set we have the simple assignment problem, which can be easily solved.

The addition of the third constraint set, commonly called subtour elimination constraints, makes this a very difficult problem to solve.

Questions about the TSP

Given a problem with n nodes, how many distinct feasible tours exist?

How many arcs will the network have? How many xij variables will we have? How could we quantify the number of subtour

elimination constraints? The complexity of the TSP has led to several

heuristic or approximate methods for finding good feasible solutions. The simplest solution we might think of is that of the nearest neighbor.

6 City TSP Network

Illustration of subtours

TSP Heuristics

A second heuristic, known as the sweep heuristic, will perform much better in the ‘worst case’ then the nearest neighbor.

The sweep heuristic basically attempts to make an outer loop around the nodes.

Draw a straight line emanating from the depot with a length r which is at least as great in length as the maximum straight-line distance from the depot to any customer (the direction of the line is not important).

Visualize the line as sweeping either clockwise or counter-clockwise through a circle of radius r. Each time the radius line intersects a customer location we make that customer the next customer on the route.

Single Depot, Multiple Destinations, Vehicle Capacities

– When the depot contains many vehicles and vehicle capacity constraints come into play, the problem becomes even more complex.

– If each customer has enough demand to receive a full truckload the problem is easy and we simply use the shortest path to get the single truck to each customer. Otherwise, we must decide which customers will receive deliveries from the same truck, and then we must decide how to route the trucks to the customers on the route.

– We will look at a mixed-integer programming formulation of the Vehicle Routing Problem (VRP).

Illustration of VRP

(Outlier)

Depot

50

76

39

112

88

2912344

5890

77

89

57

115124

59 176

65

98 125Truck Capacity = 250What is the minimum # of trucks we would need? Maximum?

The Vehicle Routing Problem (VRP)

The Vehicle routing problem (VRP) generalizes the TSP since we have a set of K capacity constrained (homogeneous) vehicles at a depot, each of which must visit a subset of the n - 1 customers exactly once and return to the depot.

No two vehicles may visit the same customer. This means that each vehicle must complete a Hamiltonian tour (a Hamiltonian tour is a feasible TSP solution).

The objective is to determine the minimum travel cost required to serve each customer. Let A denote the set of pairs of cities, and let k index trucks, each with capacity u. Assume that customer i has demand equal to di.

VRP Heuristics

– Given the difficulties in solving the TSP problem, we cannot expect to have great success solving VRP problems without some sort of heuristic approaches. We can use several guiding principles in developing these heuristics. (Note that the above formulation does not consider additional practical restrictions such as limits on driver time, time window delivery restrictions, or return of goods from customers to the depot.)

VRP Heuristic Principles

1. Try to assign customers in close proximity to the same truck. 2. Assign customers in close proximity (not on the same truck)

to the same delivery day (to better manage capacity usage). 3. Build routes beginning with the farthest delivery and cluster

around this delivery first. 4. Routes should form a “teardrop” pattern (similar to sweep

heuristic for TSP). 5. Allocate largest vehicles to routes before small vehicles. 6. Plan pickups during deliveries, not after all deliveries have

been made. 7. Outliers are candidates for alternate means of transport. 8. Avoid time windows if possible.

VRP Sweep Heuristic

Note that the sweep method, when applied to the VRP, will have a slightly different interpretation. That is, we can only add a delivery location to a route as long as it does not exceed the vehicle capacity. So we can only continue to assign deliveries to a route as long as the vehicle capacity is not exceeded. Then we need to start assigning deliveries to a new truck.

Sweep Heuristic

(Outlier)

Depot

50

76

39

112

88

2912344

5890

77

89

57

115

124

59 176

65

98 125Truck Capacity = 250

Start Sweep

Facility Location Decisions

Classifying location decisions– Driving force (critical factor - traffic, labor rates,

emergency facilities, obnoxious facilities)– Number of facilities– Discrete vs. continuous choices– Data aggregation– Time Horizon

Facility Location

Rent Curve - The rent of land is a decreasing function of the distance to the market

Weight gaining vs. weight losing industries– Weight losing should locate close to raw materials– Weight gaining should locate close to market

Tapered (concave) transportation costs– The derivative of total transportation cost is non-increasing

with the distance to the market (holds for inbound and outbound costs)

– Optimal solution will always locate either at raw materials or at market (extreme point solution)

Single Facility Location Model

This model assumes a known set, I, of source and demand points, each with known demand volumes, Vi, and transportation rates, Ri.

The objective is to locate the facility at the point that minimizes total transportation cost, TC:

– Let di denote the distance from the facility to demand point i.

– Min

– subject to:

– The decision variables are the coordinates of the facility– Xi, Yi denote the coordinates of demand point i.

i i ii I

TC V R d

2 2( ) ( )i i id X X Y Y

and ,X Y

Single Facility Location Model

Differentiating TC w.r.t. and setting the result equal to zero gives the ‘center of gravity’:

and X Y

i i i

ii

i i

ii

i i i

ii

i i

ii

V R Xd

XV R

d

V RYd

YV R

d

Single Facility Location Model

This continuous problem is often called the Weber problem

These problems are restrictive because they assume continuity of location and straight-line distances

Also, only variable distance related costs are considered

General Facility Location Model

The general facility location problem considers the simultaneous location of a number of facilities

Notation:– I - Set of customers, indexed by i.– J - Set of facilities, indexed by j.– di - demand of customer i.– cij - cost of transporting a unit from facility j to customer i.– Fj - fixed cost of creating facility j.– xij - variable for flow from facility j to customer i.– Yj - binary variable that equals 1 if we create facility j, 0

otherwise– sj - capacity of facility j.

Uncapacitated Facility Location Model Formulation

Minimize

subject to:

,

, ,

0, {0,1}, ,

j j ij ijj i j

ij ij

ij i j

ij j

F Y c x

x d i I

x d Y i I j J

x Y i I j J

Capacitated Facility Location Model Formulation

Minimize

subject to:

,

,

min{ , } , ,

j j ij ijj i j

ij ij

ij ji

ij j i j

F Y c x

x d i I

x s j J

x s d Y i I j J

0, {0,1}, ,ij jx Y i I j J

Supply Chain Design Model

The objective of this model is to determine the warehouse and plant configuration that minimizes total costs for production and distribution of multiple products.

Based on Geoffrion and Graves, 1974, “Multicommodity distribution system design by Benders decomposition,” Management Science, v20, n5. (see Tech. Suppl., Ch. 13)

Notation:– i - index for commodities– j - index for plants– k - index for warehouses– l - index for customer zones

Supply Chain Design Model

Notation (continued):– Sij - production capacity for commodity i at plant j.– Dil - demand for commodity i in customer zone l.– - min and max total throughput for warehouse k.– fk - fixed part of annual costs for owning and operating warehouse k.– vk - variable unit cost of throughput for warehouse k.– Cijkl - average unit cost of producing, handling, and shipping

commodity i from plant j through warehouse k to customer zone l.– Xijkl - amount of commodity i flowing from plant j through warehouse

k to customer zone l.– ykl - binary variable = 1 if warehouse k serves customer zone l, 0

otherwise– zk - binary variable = 1 if warehouse k is open, 0 otherwise.

, k kV V

Supply Chain Design Model Formulation

Minimize

subject to:

,

,

ijkl ijkl k k k il klijkl k l i

ijkl il klj

ijkl ijkl

k

C X f z v D y

X D y ikl

X S ij

y

= 1,

0, {0,1}, {0,1}

lk

k il kl kl i

ijkl kl k

l

V D y V k

X y z ijkl

Network Planning

Network planning refers to assessing or reassessing the configuration of facilities, commodities, and flows currently used to satisfy demand

Network planning data checklist:– List of all products– Customer, stocking point, and source point locations– Demand by customer location– Transportation rates– Transit times, order transmittal times, and order fill rates– Warehouse rates and costs– Purchasing/production costs– Shipment sizes by product– Inventory levels by location, by product, control methods– Order patterns by frequency, size, season, content– Order processing costs and where they are incurred

Network Planning

Data Checklist (continued):– Capital cost– Customer service goals– Available equipment and facilities and their capacities– Current distribution patterns (flows)

Note that many of these are decision variables Accumulating these data usually results in improvements by

uncovering anomalies We must decide our network design strategy:

– Specify minimum service levels– Specify shortage costs and minimize cost– Levels of acceptable aggregation of demand– Optimization vs. heuristic methods– Which areas require the most accuracy and attention?

The Role of Information Systems in Network Planning

The past five years have seen an explosion in customized installations and implementations of supply chain and total resource planning software packages

These packages, such as SAP and PeopleSoft, integrate all of the elements on the previous network planning data checklist

– These packages integrate human resources, accounting, finance, production (push and pull capable), marketing, and distribution (DRP) systems

– The common name for such systems is ERP (Enterprise Resource Planning), although several companies have systems dedicated to supply chain (production and distribution) planning and scheduling

The goal of ERP systems is to have one integrated place for all vital corporate data.

Many of the jobs in IE consulting these days focus on implementation and customization of these systems for manufacturing and service firms.