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Materials for Electronic Products

Electronics supply chain



Where and how were these computers manufactured?

Apple II computerDell notebook computer





A supply chain is a goal oriented network of processes and organizations.

Simplified manufacturing supply chain

Source: National Research Council Staff (2000). Surviving supply chain integration: strategies for small manufacturers. Washington, DC: National Academies Press.




Supply chains transfer two commercially valuable assets:





A supply chain should support strategic goals, such as:
















Electronics manufacturing supply chain in 1990:

Electronics manufacturing supply chain in 1990

Source: Gover, J. & Gwyn, C. (1992). Strengthening the us microelectronics industry by consortia. Albuquerque: Sandia National Laboratories.




Personal computer manufacturing supply chain during 1990s:

Personal computer manufacturing supply chain during 1990s

Source: Dedrick, J., Kraemer, K. (2005). The impacts of it on firm and industry structure: the personal computer industry [Electronic version]. California Management Review, 47(3), 122-142.




Personal computer manufacturing supply chain after 2000:

Personal computer manufacturing supply chain after 2000

Source: Dedrick, J., Kraemer, K. (2005). The impacts of it on firm and industry structure: the personal computer industry [Electronic version]. California Management Review, 47(3), 122-142.




Supply chain operations have different levels of planning integration:





What are specific examples might have a manufacturing supply chain like this?

Serial supply chain




What are specific examples might have a manufacturing supply chain like this?

Distribution supply chain




What are specific examples might have a manufacturing supply chain like this?

Assembly supply chain




Principles for supply chain planning:

  1. The primary purpose of planning is to improve decision making.
  2. Planning is an integration process.
  3. Plan to control and minimize risk, not to completely eliminate risk.
  4. Do not plan if there is insufficient information, little variation or no decision making.
    • More planning is not necessarily more beneficial.
    • Planning is mostly re-planning.
  5. Planning is specific to each organization.
    • There is no one best plan for all organizations.
  6. Planning is not a replacement for operations and strategies.




Principles for supply chain performance:

  1. The output of a supply chain is less than its capacity.
  2. Variability in a supply chain may be buffered by some combination of inventory, capacity and time.
    • The supply chain of a product could be buffer by increasing inventory, adding more capacity or planning more time in the supply chain. Each of those options has a different potential impact on the environment.
    • For example, to handle the higher demand for a product during the holiday season, a company could increase the inventory in its warehouses (option 1) or it could add more production capacity (option 2) by contracting with more suppliers. Option 1 would require more energy and resources (likely a worse impact on the environment) regardless of whether all the inventory is sold or not during the holiday season. Option 2 would have less of an immediate impact on the environment because additional energy and resources would only be used for production when the extra inventory was required for sales.
  3. Flexibility reduces the amount of buffering required in a supply chain.
  4. Impact of flexible buffering is greater near bottlenecks in a supply chain.
  5. Combining sources of variability so that they can share a common buffer reduces the total amount of buffering required to achieve a specific level of supply chain performance.
  6. Stock pooling in a supply chain affects its performance.
    • Stock with higher volume demand should be pooled closer to the end of the supply chain.
    • Stock with higher variability demand should be pooled closer to the start of the supply chain.
    • Stock with higher cost should be pooled closer to the start of the supply chain.
  7. Supply chain performance is reduced due to batch ordering, demand forecasting errors, promotional pricing and gaming behavior by customers.
    • Commonly referred to as the bullwhip effect.
  8. Higher variability of risk between participants in a supply chain reduces its performance.
    • One measure of performance in a supply chain is wasted resources. If a supply chain has a few companies with very strong negotiating power (and less business risk) and many companies with little negotiating power (and more business risk), then the companies with more business risk are more likely to waste resources. Whereas a supply chain that has companies with less differences in business risk will be more likely to cooperate on reducing waste in the supply chain.




The bullwhip effect reflects the volatility that is propagated through a supply chain due to forecasting errors, buffering and gaming behaviour.





A short run is a period of time when at least one input variable is fixed. Otherwise, it is a long run.




The inventory order interface is the location in a supply chain where a unique customer order is fulfilled by stock inventory.

Inventory order interface
Demand models:








Classic models of supply chain operations are based on inventory control.





Material requirements planning (MRP) took advantage of computers to optimize inventory of dependent stock.





Just-in-time (JIT) operations relied on the demand pull in a supply chain to trigger production of a small batch of dependent stock.





Vendor managed inventory (VMI) took advantage of information technology to implement a push model where the manufacturer or supplier controls the inventory at a retailer.





Theory of Constraints (TOC) advocated that supply chains can maximize output by focusing on effective management of the bottlenecks (i.e. constraints).
  1. Identify the constraints.
  2. Identify steps to exploit the constraints.
  3. Subordinate everything else to steps in 2.
  4. Fix the constraints.
  5. Go back to 1 whenever constraints have changed.

TOC strategies raised the importance of supply chain management for integrating all activities in a business.




Fully scheduled operations propose that mathematical optimizations should be applied to all planning decisions.





Trends affecting the design of manufacturing supply chains:

Information technology

Global capital markets

Transportation logistics

Global manufacturing




Economic order quantity (EOQ) is the classical inventory model for stock held on cycle with assumptions of known demand and production lead time. The objective is to select an order quantity that minimizes the marginal annual costs for holding inventory and placing orders.

Economic order quantity


Let D be the steady annual demand for a product and Q be the order size for instant re-stock of inventory.

The average inventory level is:
Q ÷ 2

Let H be the marginal annual cost of holding one unit of inventory. Then, the marginal annual cost for all products is:
H × ( Q ÷ 2 ) = ( H × Q ) ÷ 2


The average order frequency is:
D ÷ Q

Let A be the marginal annual cost of placing one order. Then, the marginal annual cost for all orders is:
A × ( D ÷ Q ) = ( A × D ) ÷ Q


The economic order quantity (EOQ) is the point at which the marginal holding cost equals the marginal ordering costs, which is calculated as:
Economic order quantity


The total annual cost of inventory is the sum of the marginal annual cost for holding inventory and placing orders:
( ( H × Q ) ÷ 2 ) + ( ( A × D ) ÷ Q )

The total annual cost of inventory (TC) is easier to calculate using the EOQ value:
TC = EOQ × H




The annual demand for a product is 2,000. The unit cost of each product is £100 and the storage cost per annum amounts to 20% of stock value. Each order costs £30 for processing. What is the optimal number of orders per year?

From the problem description, A is £30 and D is 2,000.

H is calculated as a percentage of the unit cost:
£100 × 0.20 = £20


The first step of the EOQ calculation is:
2 × £30 × 2,000 = £120,000

then,
£120,000 ÷ £20 = 6,000

and finally,
the square root of 6,000 is approximately 77


Using 77 as the Q value, the optimal number of orders per year is approximately:
2,000 ÷ 77 = 26




On average, 10 products are sold daily and the retailer is open 240 days per year. Each product costs £50 and the holding cost is 24% of the product cost. There is a cost of £9 per order. What is the total annual inventory cost at the optimal inventory level?

From the problem description, A is £9

D is calculated from the daily sales:
10 × 240 = 2,400


H is calculated as a percentage of the unit cost:
£50 × 0.24 = £12


The first step of the EOQ calculation is:
2 × £9 × 2,400 = £43,200

then,
£43,200 ÷ £12 = 3,600

and finally,
the square root of 3,600 is 60


Using 60 as the EOQ value, the total annual inventory cost is:
60 × £12 = £720




Six sigma of quality


Approximately 68% of data values will be within one standard deviation of the average value
68% of data within one standard deviation of the average value



Approximately 95% of data values will be within two standard deviation of the average value
95% of data within two standard deviation of the average value



Approximately 99.73% of data values will be within three standard deviation of the average value (or 2,700 errors per million observations)

Approximately 99.9999998% of data values will be within six standard deviation of the average value (or 2 errors per million observations)
Six sigma of quality




Variability pooling depends on standard deviation of group of items.

standard deviation of
group of N items
= ( square root of N )
× ( standard deviation of a single item )




A manufacturer has 20 retailer customers. Each customer orders a monthly average of 400 products with a standard deviation of 20 products. The manufacturer has committed to a 99.73% service level agreement for order fulfillment. What is the comparative efficiency between having 20 warehouses and 5 warehouses?

A service level agreement for 99.73% requires 3 standard deviations of variable inventory for each warehouse:
400 + ( 3 × 20 ) = 460 products

The base case of 20 warehouses would require the manufacturer to maintain a total monthly inventory level of:
460 × 20 = 9,200 products


The equivalent standard deviation for a group of 4 retailers being serviced by 1 warehouse (5 warehouses total) is:
( square root of 4 ) × ( 20 ) = 2 × 20 = 40 products

A service level agreement for 99.73% requires 3 standard deviations of variable inventory for each warehouse:
( 4 × 400 ) + ( 3 × 40 ) = 1,720 products

The case of 5 warehouses would require the manufacturer to maintain a total monthly inventory level of:
1,720 × 5 = 8,600 products


The efficiency of variability pooling is calculated as:
( 9,200 - 8,600 ) ÷ 9,200 = 600 ÷ 9,200 = 6.5% efficiency




Variability of risk


Variability of risk between a manufacturer and a retailer customer can be reduced with a risk sharing contract such as product buy back:

The probability that a retailer customer will order enough to meet sales demand is expressed as a ratio:
( (retail price) − (wholesale price) ) ÷ ( (retail price) − (buy back price) )


The optimal ratio is obtained by setting wholesale price to the cost of manufacturing and the buy back price to zero:
( (retail price) − (manufacturing price) ) ÷ ( retail price )


The buy back price is calculated using the optimal ratio:
retail price − ( ((retail price) − (wholesale price)) ÷ (optimal ratio) )




The cost to manufacture one product is £20. The manufacturer sells at a wholesale price of £50 and its retail price is £100. What is the buy back price for optimal risk sharing between the manufacturer and the retailer customer?

The optimal ratio is calculated as:
( 100 − 20 ) ÷ 100 = 80 ÷ 100 = 80%


When the buy back price is £30, the ratio is low and would cause the retailer to keep inventory below the optimal quantity:
( 100 − 50 ) ÷ ( 100 − 30 ) = 50 ÷ 70 = 71%


When the buy back price is £40, the ratio is high and would cause the retailer to keep inventory above the optimal quantity:
( 100 − 50 ) ÷ ( 100 − 40 ) = 50 ÷ 60 = 83%


When the buy back price is £35, the ratio is low, but closer to optimal:
( 100 − 50 ) ÷ ( 100 − 35 ) = 50 ÷ 65 = 77%


When the buy back price is £37.50, the ratio is optimal:
( 100 − 50 ) ÷ ( 100 − 37.50 ) = 50 ÷ 62.50 = 80%


Which is the same as using the formula above:
£100 − ( (£100 − £50) ÷ 0.8 ) = £100 − ( £50 ÷ 0.8 ) = £100 − £62.50 = £37.50