OM GroupA9 Project

8/8/2019 OM GroupA9 Project

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LAUNCHING OF A PRODUCT: STARLINE WASHING

MACHINEDETERGENT-FREE

DOESNT NEED

WATER

WORKS ONBATTERY POWER

IRONS your

clothes too!!

A PROJECT ON:


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FEATURES

Strong Iron Programme (SIP)

Flexibility in Placement

Teflon Coating

Detergent-Free

Cost-Saving

Environment-Friendly Appliance

Doesn't Need Water


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INTRODUCTION

Consumers look for one or more of these features in a washing machine:

1. Power efficiency

2. Less detergent requirement

3. Less water requirement

4. Less space occupying

5. Attractive aesthetics

Consumers are also likely to go for a power stabilizer along with the

washing machine.

The issue that a consumer is faced with is that all these features do not

come together in a single washing machine.

Starline Washing Machine brings to you all these features packed in a

single unit along with all other regular features.

6. Clothes drying facility

7. Ironing of clothes

8. Quick wash

9. Auto timer

10.Alarm


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FEATURES


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THE STAGES OF DESIGN

Preliminary Design

Evaluation & Improve

Prototype & Final

Design

Market Testing

Ramp Up

Screening

Concept Generation


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DESIGN FOR MANUFACTURING


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PRODUCTION

RAW MATERIALS:

Sheet steel coated with zinc: for rust resistance

Stainless steel: for spin tub

Plastic: for outer wash tub Aluminum: for the transmission

Hoses

Controls timers & switches

Motors Cables, LCD Display

Battery

Heat Chamber & Suction Box

Other electronic components


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PRODUCTION

MANUFACTURING PROCESS:

Sequence of steps involved in the manufacturing process:

Fabrication (making parts)

Sub-assembling (putting parts together to make

components)

Assembling (putting the components together to form

the final product)

Testing

Packaging

Shipping


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LOCATION

Power supply

Transport

Water

Labour

Land

Raw materials

Housing welfare/education


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CHOOSING A SITECHOOSING A SITE

BRIDGEMANS DIMENSIONAL ANALYSIS:

It helps in computing the relative merits (or cost

ratios) for each of the cost items, giving each of theratios an appropriate weightage by means of the power

(index) to which it is raised and multiplying these

weighted ratios in order to come up with a

comprehensive figure on the relative merit of the twoalternative sites. Choosing a location becomes easier.


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ILLUSTRATION:

S. No Factors Site A Site B Weights

1 Building & EquipmentCosts (Rs.)

50,00,000 40,00,000 4

2 Taxes per year (Rs.) 50,000 50,000 2

3 Power Cost per Year 1,00,000 1,20,000 3

4 Community Attitude 5 4 1

5 Product Quality as a

function of worker skill

12 11 5

6 Flexibility to adopt to

changed situation

4 4 3

Figures in the above table are hypothetical; used only for illustration


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Preference Merit Ratio (R)

= Preference for location A / Preference for location B

Conditions:

If R1, choose location B

If R=1, choose location A or B

R= (5000000)4X (50000)2 X (100000)3X (5)1 X (12)5X (4)3(4000000)4X (50000)2 X (120000)3X (4)1 X (11)5X (4)3

= 2.72

Since R>1, Location B will be chosen


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PRODUCT LAYOUTPRODUCT LAYOUT

Assembly

TestingPackagingShipping

Sub AssemblyFabrication

Product layout is best suited for this kind of

manufacturing process as:

Output: Product

layouts

can

generate

a

largev

olume

ofproductsinashorttime.

Cost: Unitcostislowasaresultofthehigh volume.

Utilization: Thereisahighdegreeoflabourand

equipment

utilization


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THE ASSEMBLY LINE LAYOUT THE ASSEMBLY LINE LAYOUT


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FACTORY LAYOUTFACTORY LAYOUT


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F O R E C A S T I N GF O R E C A S T I N G

Demand forecasting & Production system

Information on most recent

demand

Demand forecast

for Operation

Planning thesystem,

Product design,

Process design,

Eqpt. Investment

Capacity planning

Scheduling,

Aggregate

planning,

Operations

scheduling.

Controlling thesystem,

Production

control, Inventorycontrol,

Cost control.

Output: Washing

Machines


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F O R E C A S T I N GF O R E C A S T I N G

Month

Forecasted

Demand

(F)

Actual

Demand

(A)

Forecast

Error

(A-F)

Absolute

Deviation

|A-F|

Sum of

Absolute

Deviation

Mean

Absolute

Deviation

Running

Sum of

Forecast

Error

Tracking

Signal

1 1000 950 -50 50 50 50 -50 -1

2 1000 1070 70 70 120 60 20 0.33

3 1000 1100 100 100 220 73.33 120 1.64

4 1000 960 -40 40 260 65 80 1.23

5 1000 1090 90 90 350 70 170 2.43

6 1000 1050 50 50 400 66.67 220 3.30

Figures in the above table are hypothetical; used only for illustration

ILLUSTRATION:


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STEPS FOR THE FORECASTSTEPS FOR THE FORECAST

1. Objective of the forecast:QuantityofWashing Machines

tobeproduced

2. Items to be forecasted:UnitsofWashingmachinethe

marketdemands

3. Determine the time-horizon of the forecast : short,

mediumorlong-term

4. Forecasting models: Nominalgrouptechnique,market

surveyetc

5. Gather data needed to make the forecast6. Validate the forecasting model

7. Make the forecast

8. Implement the results: Produceandsupplytheforecasted

no.ofunits


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C A P A C I T Y P L A N N I N GC A P A C I T Y P L A N N I N G

Capacity planning is the analysis of how many

washing machines we are capable of producing versus

what our expected demand will be.

CAPACITY PLANNING STRATEGIES:

Long-term

Short-term

Medium-term


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QU A L I T Y M A N A G E M E N T QU A L I T Y M A N A G E M E N T

Pr ct lity ill s r y c c tr ti g t

f ll i g i si s:

Perf r ce

Feat res

eliability

f r ance

Durability Serviceability

est etics

Perceived Quality


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PROMOTIONSPROMOTIONS

Attractive introductory offers

Washing machine sales rise with the onset of monsoon. So the

product will be launched a few weeks before the season while the

promotions in both print and electronic media will start with the

production of first machine to create curiosity. Emails will be sent out to the target segment notifying about the

washing machine and feedback will be requested.

Large banners, posters and hoardings at prime locations.

Decorative body stickers will be given out to customers to match

the products look with the interiors of their homes.

Customer response awards scheme will be launched. Customers

who send maximum number of suggestions for improvement of

the product in any given month will be rewarded.

Incentives and contracts with retailers and distributors


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C O M P A R I S O NC O M P A R I S O N


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C O M P A R I S O NC O M P A R I S O N


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A CK N O W L E DGE M E N T A CK N O W L E DGE M E N T

We wish to express our sincere thanks to:

Mr. Subrata Kar faculty, Globsyn Business School

for giving us the opportunity to work on this

project. This has given us the insight of how

Operations Management is applicable to the

launching of new products in real world.


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OM GroupA9 Project

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