new seven management tools

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Total quality management

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New Seven Management Tools

Matrix Data Analysis Diagram

Introduction

In addition to seven Statistical tool

7 Management Tools

Quality Improvementused for

Committee of J.U.S.E. - 1972 Aim was to develop more QC techniques with

design approach Work in conjunction with original Basic Seven

Tools

New set of methods (N7) - 1977

Relation Between New Seven Q.C. Tools and Basic Seven Tools

FACTS

Data

Numerical Data Verbal Data

Organize

The Seven New Tools

Information

The Basic Seven Tools

•Generate Ideas•Formulate plans

•Analytical approach

Define problem after collecting numerical data

Define problem before collecting numerical data

Source: Nayatani, Y., The Seven New QC Tools (Tokyo, Japan, 3A Corporation, 1984)

The Seven Management Tools and their Purposes

Management Tools Purpose

Affinity diagram For Synthesizing ,classifying, Organizing, Indefinite ideas

Relationship diagram For Isolating Cause and Effect Relationship

Tree Diagram For Deploying general concepts into details

Decision Tree For identifying Alternatives

Arrow Diagram For Planning

Matrix Diagram For correlating in a Logical Form, In order to evaluate, Select and decide

Matrix Data Analysis For Quantifying relationships

Matrix Data Analysis Diagram

Matrix data analysis diagram ≡ Matrix diagram

Difference The Numerical Data is used instead of Symbols

Only Tool

uses Numerical Data Produces

Numerical Results

It is a Shaped Matrix

Uses Pair Wise Comparison to In order To choose Best Options

MDAC……

When do we use it?

To present Numerical data about two sets of factors in a matrix form and analyze it to get numerical Output

Tool is used in “Principal Component Analysis”(Where only two characteristics can be studied

at a time)

• Tool is Advantageous in studying

1.Parameters of Production

2.Analyzing Market Information

3. New product planning and so on..

How do we construct it?

Decide 2 Factors (Whose relations are to be analyzed)

Check No Of Individual Items (In two Factor)

Prepare a Matrix

Enter Numerical Data in the Matrix

Analyze The Final Result

Constructing a Prioritization Grid Source: Foster, S., Managing

Quality (Upper Saddle River, NJ: Prentice Hall, 2001)

Determine your goal, your alternatives, and criteria for decision

Place selection in order of importance

Sum individual ratings to establish overall ranking (Divide by number of options for average ranking)

Apply percentage weight to each option (all

weights should add up to 1)

Rank order each option with respect to criterion (Average the rankings and apply a completed

ranking) Multiply weight by associated rank in

Matrix (in example, 4 is best, 1 is worst) Result is Importance Score

Add up Importance Scores for each option

See completed the diagram

Rank order the alternatives according to importance

Criteria Customer Acceptance StrengthImportance Sum

Score Option Ranking (most important) Cost Reliability (least important)

Options

Design A

Percentage weight .40 .30 .20 .10

Rank 4 3 3 1

Importance score 1.6 .90 .60 .10 3.2 1 (tie)

Design B

Percentage weight .30 .40 .10 .20

Rank 3 4 1 2

Importance score .90 1.6 .10 .40 3.0 2

Design C

Percentage weight .25 .25 .25 .25

Rank 1 2 4 3

Importance score .25 .50 1 .75 2.5 3

Design D

Percentage weight 0.3 .10 .20 .40

Rank 3 1 3 4

Importance score .90 .10 .60 1.6 3.2 1 (tie)

Sum of weights 1.25 1.05 .75 .95

Average weight .31 .26 .19 .24

Criterion Ranking 1 2 4 3

Example

• For example, a washing powder may have different characteristics achieving 'softness' and 'stain removal' in garments made of acrylic, polyester, wool and various fiber mixtures.

• If similar affects are found in a group of fibers, then changing the powder ingredients may affect the whole group in a similar way.

• The Matrix Data Analysis Chart (or MDAC) helps classify items by identifying two major characteristics common to all items and then plotting each item as a point on a standard x-y chart.

• This makes it easier to see how the individual items relate both to the characteristics and to one another, thus:

Some other Examples

• It would be useful to be able to compare many characteristics together, such as the density, color, texture, strength, etc. of cement mixtures

?Queries

Thank You

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