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Operations > Final Multiple Choice > Flashcards

Final Multiple Choice Flashcards

1
Q

Examples of Projects

A

Project:
unique, one-time operational activity or effort

Examples:
Constructing: houses, factories, shopping malls, athletic stadiums, arenas

Developing military weapons systems, aircrafts, new ships

Launching satellite systems

Constructing oil pipelines, dams, bridges

Developing and implementing new computer systems

Planning concert, football games, or basketball tournaments

Introducing new products into market

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2
Q

Characteristics of Projects

A

non repetitive, one of a kind, subject to high uncertainty, etc.

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3
Q

Key person involved in PM

A

project mgr.

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4
Q

Project team characteristics

A

Cross functional with diff. skills (engg., mktg., HR, prodn., A/c)

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5
Q

What is Work Breakdown structure (WBS)

A

Breakdown project into modules, sub-components, tasks, activities for scheduling / planning; responsibility (job description) assignment - SOW)

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6
Q

• Gantt Chart

A

Graph with a bar representing time for each activity in the project

Provides visual display of project schedule

  • When activities start, finish (activities ahead/ behind schedule)
  • Where extra time is available and which activities can be delayed
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7
Q

Slack definition, Advantage of slack

A

allows resources to be temporarily diverted from activities with slack and used for other activities that might be delayed.

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8
Q

CPM/PERT

A

• Critical path – longest path in the N/W, project cannot be completed in less time than the time reqd. by the critical path, min. completion time of project)

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9
Q

EF=

LS=

A

EF=ES+t;

LS=LF-t

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10
Q

Forward pass

Backward pass

A
  • Forward pass used to calculate earliest start and finish times
  • Backward pass used to calculate latest start and finish times
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11
Q

ES=

LF=

A
  • ES=max of EF of immediate predecessors

* LF=min of LS of immediate successor activities

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12
Q

• For activities on critical path ES=EF and LS=LF & slack = 0

A

o This implies
Activities on critical path cannot be delayed at all. If any activity on critical path delayed, overall project is delayed

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13
Q

Probabilistic activity times can be described by

A

beta distribution

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14
Q

Mean of beta distribution =

A

(a+4m+b)/6

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15
Q

Total project variance =

A

• sum of variances of activities on critical path

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16
Q

• Project crashing definition

A

o Indirect cost increases as project duration increases
o crashing cost increases as project duration is reduced
o optimal project time is the one at min. cost

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17
Q

• Objectives / Role of inventory

A

To meet uncertainty
To provide independence from vendors (supply uncertainty)
To provide independence between stages, thus avoid work stoppages (uncertainty within org.)
To meet seasonal or cyclical demand (demand fluctuations)
To take advantage of price / Qty. discounts
To hedge against future price increases

18
Q

What is ordering cost ?

A

cost incurred each time an order is placed to replenish inventory (paperwork/documentation (POs), shipping & transportation, receiving, inspection, handling, accounting & auditing costs)

As number of orders increases, ordering cost increases

Any cost that increases linearly with the # of orders is ordering cost

Normally expressed as $/order

Annual ordering cost = cost/order x # of orders

19
Q

What is carrying cost ?

A

cost of holding an item in inventory (facility storage - rent, depreciation, power, heat, lighting, refrigeration, security, taxes, insurance, material handling, labor, product deterioration, spoilage, obsolescence, pilferage, opportunity costs)

Greater the inventory, more the carrying costs

Any cost that increases linearly with the # of units carried is carrying cost

Annual inventory carrying cost in USA estimated to be > $30B

Commonly expressed as $/unit/year

Annual carrying cost = cost to carry one unit x average # of items carried

20
Q

Ordering costs react inversely to carrying costs. how

A

As the size of orders increases, fewer orders are required, reducing ordering costs. However, ordering larger amounts results in higher inventory levels and higher carrying costs. In general, as the order size increases, ordering costs decrease and carrying costs increase.

21
Q

Uncertainty is caused due to

A

uncertainty is created by poor quality on the part of the company or its suppliers or both. This can be in the form of variations in delivery times, uncertain production schedules caused by late deliveries, or large numbers of defects that require higher levels of production or service than what should be necessary, large fluctuations in customer demand, or poor forecasts of customer demand.

22
Q

Types of inventory

A

Raw materials
Work-in-process (partially completed products) (WIP)
Finished Goods
Pipeline inventory (Items being transported)
MRO (Maintenance, Repair and Operations) supplies

23
Q

Purpose of inventory management

A

“To meet uncertainty of demand/supply”

24
Q

Dependent demand items ?

A

Demand for items that are used to produce final product (i.e. dependent on other parts, items, or final products)

Ex: Tires, seats, engine, PC parts, etc.

25
Q

Independent demand items?

A

Demand for items used as final products

Ex: Cars, appliances, computers, houses, etc

26
Q

Continuous (fixed-order-quantity) system

A

Inventory level is continuously monitored (so management always knows inventory status)
when inventory on hand decreases to certain predetermined level (called as a reorder point) a fixed amount ordered (to replenish the stock)
The order placed (fixed amount) - minimizes the total inventory costs
This “fixed” amount ordered is called economic order quantity (EOQ)
Use of IT/ technology tools (ex: barcode scanners) to improve speed & accuracy of data entry (ex: POS)
Advantageous for critical items: costly, used for critical, non-substitutable, non-imitable, higher lead time (prone to uncertain supply), high rate of obsolescence items
Disadvantage: costly
Ex: Pearson Packaging Inc., two bin system, checkbooks, re-order cards for office stationery

27
Q

Periodic (fixed-time-period) system

A

Inventory on hand is counted at specific time intervals (ex: weekly or monthly)
After fixed regular intervals, inventory in stock is determined, and order is placed for a variable amount that will bring inventory level back up to a desired level (target inventory level or base stock level)
Advantage:– Little or no record keeping
– Advantageous for less costly items / non critical
Disadvantage: – Less direct control over inventory
– Larger inventory level than continuous system to guard against unexpected stockouts during the fixed periods

Ex: smaller retail / grocery (produce) / convenience stores, drug stores, campus bookstore

28
Q

ABC classification system

A

Method for classifying inventory based on dollar value

Higher the dollar value of inventory, tighter the control
Because they represent such a large %age of the total $ value
Tighter control for class ‘A’ items – continuous inventory monitoring system (low inventory levels & accurate forecasts desired)
‘B’ & ‘C’ items require less stringent inventory control
Class ‘B’ items – periodic inventory management
Class ‘C’ items – simple observation (large inventory OK as carrying costs low)

29
Q

What is EOQ? Where is it used?

A

EOQ is the order size that minimizes the sum of carrying costs and ordering costs

most widely used means for determining how much to order (i.e. optimal order size)

Used in a continuous system

30
Q

• Quantity discounts

A

Qopt’ remains same irrespective of the purchase/discount price (as ‘Qopt’ formula is free of purchase price)

Discount price is associated with a specific order size ‘Q’
‘Q’ may be different from ‘Qopt’

Trade off between higher carrying costs (for discount qty.) and EOQ cost

31
Q

• Reorder point

A

Level of inventory at which a new order is placed

R = dL

where
d = demand rate per period
L = lead time

32
Q

Importance and advantages of accurate forecasting

A

(more stable/uniform production, less inventory needed, less uncertainty, higher quality, more responsiveness, reduced bullwhip effect)

33
Q

Short to medium and long term

A

• Short to medium (daily, weekly, monthly, yearly, up to two years) and long term forecasting (forecasting for more than 2 years)

34
Q

Demand behavior

A

Trend (ex: Flat panel displays, smart phones, GPS, video games, digital mp3 players)
a gradual, long-term up or down movement of demand

Cycle (ex: auto sales, new housing starts)
an up-and-down movement in demand that repeats itself over a lengthy time span (more than a year) (based on economy, cannot be predicted easily – economists predict)

Seasonal pattern (weather/festival related sales – snow blowers, winter sporting goods, lawn mowers, summer apparel, etc.)
an up-and-down movement in demand occurring periodically (in short run); often weather related
Random variations (ex: competitors promotional campaign, local flood)
No pattern, unpredictable
35
Q

Quantitative vs. Qualitative forecasting methods

A

Qualitative
use management judgment, guesswork, expertise, experience, hunches, and opinion to predict future demand
Used when data is scarce / not avl. / not relevant

Quantitative
Time series
statistical techniques that use historical demand data to predict future demand
Used by > 70% firms
Regression
36
Q

Time Series

A

Most popular method - Used by > 70% firms (easy to understand / use)

Makes use of historical data to forecast future demand
Assume that what has occurred in the past will continue to occur in the future

Include
Simple moving average
Weighted moving average
Exponential smoothing

37
Q

Moving Average

A

Simple moving average

Uses past 3 demand values to develop forecast in the next period (by averaging them)

Easy to use, understand, quick, & inexpensive

Useful when demand:
Is stable

Does not display any pronounced dmd. behavior (such as trend / seasonal pattern)

“Mechanical” method that reflects historical data in a consistent way

Drawback: Fails to detect pronounced demand behavior (such as trend or seasonal patterns)

38
Q

Weighted Moving Average

A

weights are assigned to most recent demand data (based on trial and error/experimentation/experience)

Can more closely reflect fluctuations in data

If more recent periods weighted too heavily, forecast might overreact to random fluctuations in demand

If weighted too lightly, forecast might under-react to actual changes in demand behavior

39
Q

Exponential Smoothing

A

More popular and frequently used
Requires minimal data (forecast and actual demand of the current period, smoothing constant)
Easy to understand by management
Good success / accuracy rate when predicting demand behavior (trend, seasonality, etc.)

40
Q

What is adjusted exponential smoothing forecast

A

• exponential smoothed forecast adjusted for trend

Operations (3 decks)

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