Lecture+3+ +Principles+of+Sampling

7/31/2019 Lecture+3+ +Principles+of+Sampling

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PRINCIPLESOF

SAMPLING


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I. Definitions

II. Advantages and Disadvantages ofSampling

III. Reasons for SamplingIV. Where Does Sampling Occur?

V. Goals When Sampling

VI. Types of Quality CharacteristicsVII. Selecting the Sample

VIII.Sampling Tools


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A. Lot homogeneous source of itemsfrom the same code

B. Sub lot distinct smaller portion ofa lot a case or pallet

C. Sample a portion of the productunits, or quantity of a commodity,ingredient or supplies from a lot.


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D. Unit smallest quantity beinginspected a representative sample of a freshcommodity, an ingredient or a single package

of food

E. Sampling A method for obtaining

information from a small portion of a lotwhen it is too expensive, time consuming,impossible/preferred to measuring the total

population

(cont.)


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F. Inspection measuring,

examining or testing a sample of

ingredients or product units to

determine if items are acceptable and

meet specifications.


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A. Advantages

1. Economy due to inspecting only part of

each lot

2. Less damage due to handling in

inspection3. Fewer inspectors needed, thereforereduces recruiting and training problems


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4. May use destructive testing

5. Rejections to suppliers or departments

of entire lots provides increased

motivation to meet specifications and

make improvements

(cont.)


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B. Disadvantages

1. Risk of accepting bad lots andrejecting good lots

2. Additional record keepingrequired

(cont.)


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A. To protect producers and consumerby accepting or rejecting product

B. Establish process capability

C. To develop a history of productquality


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D. Feedback for process control (makeappropriate adjustments to control to

minimize variability)

E. To assign quality grades to products to

optimize their economic value

F. Economic, physiological to improve

production process


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A. At the suppliers warehouse

B. As ingredients are received

C. During processing or manufacturing


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D. From product lots stored in your

warehouse

E. From carrier truck

G. From retail markets


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A. Choose random samples

B. Choose samples that represent the population minimize error that will naturally occur due

to the fact that only a portion of the populationis used to estimate population parameters.Representatives samples depend on:

1. Size of lot2. Purpose of control

3. Product variability

4. Regulation


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C. Sample optimal numbers of units at

appropriate times and locations toensure efficiency


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A. Attributes to identify yes/no, go/no go oraccept/reject decisions

B. Variables to identify variations between units measured


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Attributes

Quality characteristics of either a

product or process

Which may be tabulated as either:

-present or absent

-satisfactory or non-satisfactory

- within limit or outside limit


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Variables

- Can be measured and expressed in

increments of inches, mg, degrees, %, etc.

- Can be measured by use of some scales

which can theoretically be divided into

infinite sub-units


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Attributes Vs Variables

- Attribute characteristics are tabulated while

Variables are measured

- Tabulating attributes as the basis for quality

control is generally less expensive than

measuring variables

BUT

- Attributes require many more observations

to obtain the same information than can be

obtained from a small number of

measurements of variables


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A. ATTRIBUTES

as used in quality control

Refers to those quality characteristics that

conform or do not conform to specification.

e.g -broken

-chipped off

- dirty

*defects that may affect safety of product


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B. VARIABLES

based on :sample statistic of average on

standard deviation and the type of

frequency distribution

e.g - thickness of bottles, cans

- weight of bottles, cans- headspace

* will effect fill weight of products.


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A. Non-random sampling bias; disturbproduct acceptance decisions

a. Sampling from same location

b. Selecting only those products that appeardefective (or non defective)

c. Ignoring portions of lot inconvenient tosample

d. Deciding on the pattern of stratificationwith limited knowledge


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B. Random sampling

1. Simple random sample

a. Equal chance of selecting each unit

i. Dice, cards, or numbers out of a hat

ii. Random number table

b. Sample subset = N/n where N = population

size, n = sample size


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2. Systematic random sample

a. Sampling at uniform intervals

b. Number of intervals

i. K = N/n = # product unit in lot / #samples desired

ii. Pick every kth product


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Example :You have 2000 1-gallon containers of ice-

cream and you need 20 samples

K = 2000/20 = 100, or each 100 gallons is asub lot

Therefore, if the first gallon chosen (randomly)off the line was the 14th product from the firstsub lot, then the 14th product from each of the

remaining 19 sub lots must be chosen.


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3. Stratified random sample

Used when the lots are known to come from

different machines, production shifts,operators, etc

4. Composite sampleCombination of two or more random

samples from a uniform flow of solid or

liquid


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5. Skip lot sampling

Used to greatly reduce the amount ofsampling when desired quality isuniform and items are guaranteed as

with ingredients or finished foodsmanufactured the TQM way.


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A. Thief a dipper of probe designed tosample liquids, powders or smallparticulates.

B. Automatic sampler A computer-driven, in-line sampling system for

collecting composite samples from auniform flow of liquids, powder orparticulates.


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C. Rifle or Divider A vibrating,

subdividing sampling system withnumerous sample pockets for use with

a free flowing particulate powder.

(cont.)

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