redesign of company

7/27/2019 Redesign of Company

http://slidepdf.com/reader/full/redesign-of-company 1/34

DOME of 34 ME4042/10/03

ME4042 - PRODUCTION AND OPERATIONS MANAGEMENT

INDUSTRY RELATED PROJECT

FINAL REPORT

PRODUCTION PLANNING AND PROCESS RE-DESIGN

AT PATHMA DISTRIBUTERS – TEXTILE WEAVING

INDEX NO NAME

100219F S.Jeyatharsini

100235B T.Kankeyan

100433F Y.Rameshkanna

100449J R.Ratheesan

100503V S.Seran

GROUP NO 10

DATE OF SUBMISSION 23/09/2013



DOME of 34 ME4042/10/03

PROJECT TITLE

Production Planning and Process Re-design at Pathma Distributers - Textile Weaving at Ja-Ela

BACKGROUND

Company Profile

Pathma Distributers – Textile weaving is situated at B-9, Industrial Estate, Ekala, Ja-Ela, Sri Lanka.

Annual Sales Amount: US$5 – 10 Million

Total No. of Staff: 11 – 50 People

No. of R&D Staff: 5 – 10 People

No. of Engineers: Fewer than 5 People

Business Type: Manufacturer

Main Export Markets: Southeast Asia

No of machines: 28

Production efficiency: 90 %

OBJECTIVES

The objective of the project is to improve the efficiency of the production and optimize the

resources available through production planning and processes re-design.

SCOPE

Our planned and Solutions/Improvement suggested areas;

Material flow from one machine to the other

Process flow

Plant Layout

New processes adoption

Automation of Processes

Quality control

Inventory management

Demand and Sales Forecast

By analysing and studying we have produced solutions for the operations for mentioned areas in

order to achieve the project objectives.



DOME of 34 ME4042/10/03

METHODOLOGY

We had visited the weaving plant and analysed the production flow and the processes. We had got

information regarding the whole process. We had got to know about the available resources for

production. We had collected all the information required produce the required production planning

and redesign.

The following activities have been carried out for this project.

1. Contacted the director and get his approval to visit the place

2. Visited the firm and find out the process and collected the details.

3. Gathered information from director and staffs.

4. Studied about Production Planning in Books and Internet

5. Visited the plant whenever required

6. Checking with the viability of the solutions

7. Communicating the viable solutions with the owner of Pathma Distributers – Textile

weaving

8. Working on the improvements and amendments, he suggests

9. Ensuring the satisfaction of the owner with the final proposal

PROCESSES OF THE COMPANY

1. Introduction

In the textile industry in Sri Lanka is growing continuously so the company need to improve the

quality and quantity of the products. This industry has been developed following both vertical

integration, particularly among spinning and weaving firms, and horizontal integration, promoted

by the idea that a full line of textile products is necessary for effective marketing.

Process Flow Diagram

FIBRES

Natural/

Man-made

YARN

Ginning

Carding

Combing

Spinning

Dyeing

FABRIC

Weaving or

Knitting

Bleaching

Dyeing

Finishing

FINISHED

PRODUCT

Clothing

Homefurnishings

Industry



DOME of 34 ME4042/10/03

The main process that they are using is weaving. It consists of crossing a yarn, called the weft yarn,

with several thousands of yarns composing the warp. Starching is a procedure that comprises

synthesis and special treatment of some warps. Warp making is the arrangement of the warp yarns

in parallel on a roll. Each yarn is taken from a bobbin which is put on a bobbin stand. Production

planning algorithms for each phase are required. For example, the weaving process is characterized

by long planning horizons and relatively slows speed of machines, very long setup times, very large

production batches, and mixed order and stock-based production. On the contrary, the warp making

process is characterized by short planning horizons and high speed of machines, short setup times,

small production batches and only orders-based production. The above phases pose the most

complex production scheduling problems.

Most textile companies are ageing while the technology changes rapidly. These companies own

machines of different ages and production characteristics, such as processing speed, changeover

possibilities and facilities. In their company they use some traditional machinery, traditional

processes and some conventional materials so; we prefer some new machines and some new

materials to improve their business. The competitive companies in Sri Lanka introduce new

machines and techniques to overcome their

These are the machines that they are using currently in their process

1. V-Bed

2. Power loom

3. Air jet weaving machine4. Water jet weaving machine

5. 4-truck single jersey circular knitting

Some of the Advance technological machine that we are going to suggest

1. Jacquard circular knitting

2. 4- interlock circular

3. Rib circular

4. Collar cuff v-bed auto knit

5. Tricot warp

6. New towel making weaving machine

Types of clothes of the company produce

1. Cotton

2. Polyester

3. Wool

4. Polyester

5. Silk



DOME of 34 ME4042/10/03

New types of clothes

1. Blending fabric

2. Modern types of synthetic materials.

They are producing cotton, polyester, denim materials and some time they make school uniform

material (special contracts not regularly). They didn’t produce much variety of cloths, just doing the

traditional ways. This is in the mass and continuous production range. They have to introduce some

new techniques and some more projects.

PRODUCTION

RESOURCES FOR PRODUCTIONS

1. Human resources

2. Raw material

3. Transport

4. Time

5. Machines

Nowadays the textile industry in Sri Lanka has been facing many problems because they lost their

main market in European countries due to the elimination of the GSP. So they don’t need to

increase their capacity of the production. To control the demand they need to get some outsource

(sub contracting). Increase the labour is not a proper way so they need to make some additional

shifts from their labours. They didn’t have too much of order so the stocking back ordering and the

overtime is not needed in this situation so if they increase their production they have to make the

above things correctly.

Our plan has to be some special consideration

1. Meet the customer due dates comfortably

2. Minimized idle time

3. Must a feasible and cheaper option

So they have a good production planning but if they increase their facilities they have to make their

above planning.



DOME of 34 ME4042/10/03

FACILITIES OF THE COMPANY

Facility Location

Location of the company should be located near to the place where the raw materials are taken and

also near to the stores where the customers purchase the final product. This will reduce the transport

cost and the time consumption to finish the process. Most of the Raw materials which are used for

the process are imported from India as it’s cheaper to them than purchasing here in Sri Lanka. The

Raw Materials are also purchased from the Sri Lankan markets sometimes when there is a delay in

importing. The company is located in Colombo - 01 now which is near to the Colombo Harbour and

in a specific distance from Kattunayaka Airport. Big quantity of the raw materials is taken from the

Colombo Harbour. Small quantity and is delivered from Kattunayaka and only if the Ship transport

is unavailable and if an urgent delivery of Raw materials is required. So the Current Location of the

company is better in this way. Most of the stores are located in Colombo - 01 which is near the

company.

Facility Layout

Facility layout and design is an important component of a business's overall operations, both in

terms of maximizing the effectiveness of the production process and meeting the needs of

employees. The basic objective of layout is to ensure a smooth flow of work, material, and

information through a system. The basic meaning of facility is the space in which a business's

activities take place. The layout and design of that space impact greatly how the work is done — the

flow of work, materials, and information through the system. The key to good facility layout and

design is the integration of the needs of people (personnel and customers), materials (raw, finishes,

and in process), and machinery in such a way that they create a single, well-functioning system.

The company we analysed is a yarning company where the machines over there are Loom

Machines, Drum Winding Machines, and Pirn Winding Machines. There is also a place where themeasurements and cuttings take place for the final product (Clothe).

A1-A18 and B1-B4 – Loom machines (numbers are given according to present machine numbers)

B5, B6, B7 – Pirn-winding machine

B8, B9, B10 – Drum winding machine

EN – Entrance

MA – Measuring area



DOME of 34 ME4042/10/03

The weights were given, considering the importance of the relationship between the particular

regions. Following are some examples in choosing the relationships.

E.g.:-

There are objects deals with the external environment. Those are Drum winding machines (B8, B9,

and B10), measuring area (MA) and Pirn-winding machines (B5, B6, and B7). So, these objectsshould be situated close to the entrance (EN). The interaction between the external environment and

these particular objects are frequent. So the closeness to the entrance is highly required.

There is only one labourer who has knowledge in repairing and maintaining these machines. And

there are some machines which breakdowns frequently (A5, A6, A13, A17, B3, B9) and which

should be under this labourer’s supervision. The company’s layout also has been made out in this

way already.

Departments

D1 : A1-A9

D2 : A10-A18

D3 : B1-B8

D4 : EN

D5 : MA

Shown below is the ―From-To Table‖ by giving the weights to the interactions between the

machines and working areas which is obtained from the details we got from the Company.

Flow diagram is given below,



DOME of 34 ME4042/10/03

Value Closeness Rating

A Absolutely Necessary 6

E Especially Important 5

I Important 4

O Ordinary Closeness 3

U Unimportant 2

X Undesirable 1

Activity Diagram

The current Layout is already a better layout which only needs some modifications on it to be a

better and efficient Layout to make the process is easy and efficient.

INVENTORY



DOME of 34 ME4042/10/03

A

company

should be

nibble

and fast

enough to

fulfil

customers

demands

to sustain

in the

market.

For an effective business it is important to maintain the inventory small as possible to use the

money tied up in inventory in an effective way. If we could maintain the inventory in a reasonable

level we can invest the unnecessary capitals which are struck in the inventory for new product

development, expanded marketing and sales, acquisitions, modernization, re-engineering,

expansion, debt reduction, and many others. So it is highly recommended to design the inventory.

Our inventory includes

Raw material: natural and synthetic fibers in rolled form, tools for different weaving

techniques, dies, indirect materials used to process raw materials.

Work-In-Process: Wrapped strings on shuttle, Wrapped threads on a wheel

Finished Goods: garments

Inventory control is important in whole operation. Inventory must be well managed to maximize

profits. Uncontrolled inventories are inefficient and costly. Old goods and damaged goods often

have to be discarded to keep the inventory producible, recover the holding costs and save the space

too. Inventories that have too many products in one category often result in a surplus of hard-to-sell

items that result in deep discounting. Such discounts can often eliminate profit on the item. It is

necessary to maintain enough inventories to meet demand prevent product aging and avoid under-

performing products in the industry.

The reasons for inventory control

Helps balance the stock as to value, size, colour, style, and price line in proportion to

demand or sales trends.

Help plan the winners as well as move slow sellers



DOME of 34 ME4042/10/03

Helps secure the best rate of stock turnover for each item

Helps reduce expenses and markdowns.

Helps maintain a business reputation for always having new, fresh merchandise in wanted

sizes and colours.

In some cases, inventory is so bloated that a high percentage of it will become obsolete before it is

sold. These may include poor forecasting, inadequate order/product specifications, ineffective

production scheduling, poor quality, bottlenecks, long cycle times, product and process problems,

and/or inappropriate performance metrics, to name a few. And these problems can compound

themselves.

Long lead times lead to a requirement to forecast, and long-range forecasts are by nature inaccurate.

When actual customer demand is not what was forecasted, unsold inventory quickly accumulates in

expensive piles, while expensive expediting is used to produce the needed products that are in shortsupply. Salable throughput decreases while customer service goes down.

Every decision affects the inventory size. When designing inventory theses expenses should be

considered to make it profitable.

Holding costs

Setup costs

Ordering costs

Shortage costs

Holding costs includes the costs for storage facilities, handling, insurance, taxes, pilferage, breakage

and opportunity costs for capital. It is needed to keep the holding costs in a moderate level to

maintain the inventory level and to avoid frequent replenishments.

Data

76m width fabric

Holding cost = 1.50Rs/meter

Ordering cost = 35Rs/meter

Cost of a unit fabric = 100 Rs/m

68m width fabric





DOME of 34 ME4042/10/03

Cost of a unit fabric = 90Rs/meter

49m width fabric



Cost of a unit fabric = 85Rs/meter

Lead time = 7days

All productions are supplied as rolls. But depending on transportation and economical factors the

quantity of a specific roll varies from other roll. So we used the least unit to standardize all

calculations.

EOQ model

It is a mathematical tool for determining the order quantity that minimizes the costs of ordering and

holding inventory. This model assumes that the demand equation faced by the firm is linear. In

other words, the rate of demand is constant or at least nearly constant.

The goal is to minimize total inventory cost. Inventory costs are made up of Holding and ordering

cost. Holding cost include the cost of financing the inventory along with the cost of physically

maintaining the inventory. These costs are usually expressed as a percentage of the value of the

inventory. Ordering cost include the cost associated with actually placing the order. These include a

labour cost as well as a material and overhead cost. The equation for total inventory cost is

developed as follows:

Assumptions of Basic EOQ Model (Assumed these for companies):

Demand is known with certainty

Demand is relatively constant over time

No shortages are allowed

Lead time for the receipt of orders is constant

The order quantity is received all at once



DOME of 34 ME4042/10/03

Total annual cost = Annual purchase cost + annual ordering cost + Annual holding cost

TC – Total cost

D – Demand

C – Cost/Unit

Q – Quantity

S – Setup cost

R – Reorder point

L – Lead time

H – Annual holding cost



DOME of 34 ME4042/10/03

76m width 68m width 49m width

2011 2012 2011 2012 2011 2012

Annual Demand 66175 62441.67 63316.67 52364.28 37383.33 34658.33

Total cost 6620136 6246727 5711394 4715062 3179389 2947722

Re-order level 1269.11 1197.511 1214.292 1004.246 716.9406 664.6803

Q (opt) 1745 1695.6 1663.2 1497.4 1204.5 1155.7



DOME of 34 ME4042/10/03



DOME of 34 ME4042/10/03

Fixed order quantity model needs a constant known demand. In actual case demand varies with

time. In our case also seasonal changes affects majorly the demand. Consumer needs for the

garments changes with seasonal changes. So demand for weaved materials is not actually constant.

So it is must to maintain safety stocks to overcome stock outs in peak demand times. With the

previous time data it is possible to forecast the demand for seasons and it is advised to maintain

safety stocks. For fixed quantity model orders are replenished when the inventory level drops to a

certain level, danger of stock out in this model ours only during lead time. In this case we planned

to maintain a 90% probability for not stocking out.

Fixed time period models

It is an inventory control method where orders are periodically placed, but the order quantity is

different every time, and is also called Fixed Period Deficit Ordering System. The method has the

following features:

An order is periodically placed.

The order quantity is different every time.

Even relatively large fluctuations in demand can be handled properly.

Even seasonal variation can be handled modestly.

The inventory volume can be reduced compared with ordering point system.

A-group items are usually best for this method.

Longer lead time is acceptable.

Longer time for paperwork is needed.

In fixed time period system inventory is counted only at particular time. This system needs higher

level of stock than fixed order quantity model. In a fixed time period system reorders are placed at

the time of review T and the safety stock

̅( )

The weaving mill we went is a supplier of the fabric wanted for garments. So the seasonal changes

and other factors won’t affect much of their business. But still there are some impacts due to

weather changes and other environmental facts. For example in the rainy season demand for cotton

fabric is lower than normal level. So they need to think about these factors to make the business



DOME of 34 ME4042/10/03

much profitable. But from the past data we could find that they reduce the production of the fabrics

which are not suitable for the ongoing season. But we recommend that from past data it is better to

produce more fabrics which are suitable for the specific seasons. As it is a fabric factory they need

to consider fashions changes and all aesthetics. And here again they need to think about the holding

costs. When planning the inventory again we have to think about both the two cases mentioned

above. Fixed order method and fixed period methods. Both have their own advantages and

disadvantages. For the fixed period method we need to maintain the inventory with the large

quantity. Thus that increases the holding costs and effects in profit too. And in this model it is

possible to run out of stock as replenishment done in certain intervals. So there is a possibility to

face critical situation for supply without stocks. And Pathma traders have some prefixed supplies.

So their orders are fixed somehow. So we prefer fixed order method to control the inventory.

SOLUTION FOR IMPROPER SALES FORECASTING

The company faces many problems, but the main reason for the profit loss which the company face

is Improper Sales Forecast. We are planning to give a detailed solution for the above problem.

Simple methods of Sales Forecasting are not enough to forecast their Sales. Detail calculations are

shown below. So some extra effect they have to put forecast their sales. In this case we try some

new techniques to forecast and try to match the demand approximately.



DOME of 34 ME4042/10/03

Demand and Forecast for 49m width yarn

Year MonthDemand for

49m

Simple Moving Average Weighted Moving Average Exponential Smoothing

Three

months

Seven

months

Three

months

Five

monthsα = 0.3 α = 0.5 α = 0.7

2011

January 47300

February 28900 47300 47300 47300

March 34400 41780 38100 34420

April 50300 36867 34685 39566 36250 78301

May 39800 37867 42320 42786 43275 58700

June 48200 41500 42140 40460 41890 41538 78302

July 51400 46100 45995 42520 43783 44869 57231

August 50700 46467 42900 48700 46415 46068 48134 78303

September 16900 50100 43386 50535 48700 47458 49417 58981

October 35600 39667 41671 32215 39235 38290 33159 78304

November 17800 34400 41843 32255 37575 37483 34379 48411

December 27300 23433 37200 23005 30365 31578 26090 26983

2012

January 28600 23433 37200 23005 30365 30295 26695 27205

February 32700 27325 34563 26410 27755 29786 27647 28182

March 16800 26600 32625 29235 27550 30660 30174 78306

April 19300 26033 28300 23340 25165 26502 23487 35252

May 21500 22933 24375 20560 22600 24342 21393 78307

June 49400 19200 24950 20135 22400 23489 21447 38542

July 36500 30067 26675 36515 29845 31262 35423 78308

August 42800 35800 29257 38120 32175 32834 35962 49042September 46700 42900 31286 41900 37000 35824 39381 78309

October 51200 42000 33286 44000 41570 39087 43040 56183

November 50900 46900 38200 48590 46010 42721 47120 78310

December 19500 49600 42714 50360 47480 45174 49010 59123

P.S: Weight for three months weighted moving average 1st

– 0.15, 2nd

– 0.3 & 3rd

– 0.55 and weights for five months weighted moving average 1st

–

0.1, 2nd

– 0.15, 3rd

– 0.2, 4th

– 0.25 & 5th

– 0.3



DOME of 34 ME4042/10/03

Demand and forecast for 68m yarn


68m


Three

months

Seven

months

Three

months

Five

monthsα = 0.3 α = 0.5 α = 0.7

2011

January 65400

February 71300 65400 65400 65400

March 69400 67170 68350 69530

April 65300 68700 69370 67839 68875 78301

May 70800 68667 67430 67077 67088 69200

June 47400 68500 68940 68680 68194 68944 78302

July 38500 61167 57105 62520 61956 58172 56671August 70400 52233 61157 46015 54295 54919 48336 78303

September 68900 52100 61871 57380 57375 59563 59368 72771

October 64300 59267 61529 64790 60160 62364 64134 78304

November 58800 67867 60800 66595 61110 62945 64217 68501

December 69300 64000 59871 61965 61905 61702 61508 61710

2012 January 69400 64000 59871 61965 61905 63981 65404 67023

February 36000 65450 60875 65455 65755 65607 67402 68687

March 45800 58375 59450 49440 56445 56725 51701 78306

April 76000 50400 60363 46400 51870 53447 48751 55552

May 56700 52600 61063 60940 57740 60213 62375 78307

June 78600 59500 59538 60855 57510 59159 59538 63182

July 67900 70433 61325 71640 63425 64991 69069 78308

August 75400 67733 61486 69430 67340 65864 68484 71022

September 65600 73967 62343 73630 71420 68725 71942 78309

October 78400 69633 66571 68885 69570 67787 68771 69413

November 46800 73133 71229 74110 73045 70971 73586 78310

December 52700 63600 67057 59100 64860 63720 60193 56253


– 0.15, 2nd

– 0.3 & 3rd


–

0.1, 2nd

– 0.15, 3rd

– 0.2, 4th

– 0.25 & 5th

– 0.3



DOME of 34 ME4042/10/03

Demand and forecast for 76m yarn


76m


Three

months

Seven

months

Three

monthsFive months α = 0.3 α = 0.5 α = 0.7

2011

January 78300

February 56000 78300 78300 78300

March 36800 71610 67150 62690

April 78900 57033 48785 61167 51975 78301

May 6780057233 62835 66487 65438 78720June 56400 61167 66480 63655 66881 66619 78302

July 76400 67700 63195 60770 63737 61509 62971

August 68300 66867 64371 69110 66095 67536 68955 78303

September 42600 67033 62943 68945 68930 67765 68627 71301

October 75300 62433 61029 55380 60375 60215 55614 78304

November 78300 62067 66529 64440 64000 64741 65457 76201

December 79000 65400 66443 72045 68720 68809 71878 77670

2012

January 69400 65400 66443 72045 68720 71866 75439 78601

February 36000 75500 68213 72955 68675 71126 72420 72160

March 45800 65675 65663 52365 59365 60588 54210 78306

April 76000 50400 61838 46400 55895 56152 50005 55552

May 56700 52600 62800 60940 59690 62106 63002 78307

June 78600 59500 64563 60855 57510 60484 59851 63182

July 67900 70433 64975 71640 63425 65919 69226 78308August 75400 67733 61486 69430 67340 66513 68563 71022

September 65600 73967 62343 73630 71420 69179 71981 78309

October 78400 69633 66571 68885 69570 68106 68791 69413

November 46800 73133 71229 74110 73045 71194 73595 78310

December 52700 63600 67057 59100 64860 63876 60198 56253


– 0.15, 2nd

– 0.3 & 3rd


–

0.1, 2nd

– 0.15, 3rd

– 0.2, 4th

– 0.25 & 5th

– 0.3



DOME of 34 ME4042/10/03

10000

20000

30000

40000

50000

60000

0 2 4 6 8 10 12

Demand for 49m

2011

2012



DOME of 34 ME4042/10/03

30000

40000

50000

60000

70000

80000

0 2 4 6 8 10 12

Demand for 68m

2011

2012



DOME of 34 ME4042/10/03

30000

40000

50000

60000

70000

80000

0 2 4 6 8 10 12

Demand for 76 m

2011

2012



DOME of 34 ME4042/10/03

10000

20000

30000

40000

50000

60000

0 5 10 15 20 25

Demand and Forecast for 49m

Demand for 49m

Linear (Demand for 49m)

Expon. (Demand for 49m)

5 per. Mov. Avg. (Demand for 49m)




DOME of 34 ME4042/10/03

30000

40000

50000

60000

70000

80000

0 5 10 15 20 25


Demand for 68m







DOME of 34 ME4042/10/03

30000

40000

50000

60000

70000

80000

0 5 10 15 20 25


Demand for 76m







DOME of 34 ME4042/10/03

Acceptable forecast using Adjusted Exponential Smoothing. Fewer variations with actual Demand


49m

Exponential Smoothing T T r r eennd d Adjusted Exponential Smoothing

α = 0.3 ββ == 00..66

2011

January 47300 78300 0

February 28900 63480 -8892 54588

March 34400 54756 -8791 45965

April 50300 53419 -4319 49101

May 39800 49333 -4179 45155

June 48200 48993 -1876 47118

July 51400 49715 -317 49398

August 50700 50011 50 50061

September 16900 40078 -5940 34138

October 35600 38734 -3182 35552

November 17800 32454 -5041 27413

December 27300 30908 -2944 27964

2012

January 28600 30215 -1593 28622

February 32700 30961 -190 30771

March 16800 26713 -2625 24088

April 19300 24489 -2384 22105

May 21500 23592 -1492 22100

June 49400 31335 4049 35383

July 36500 32884 2549 35433

August 42800 35859 2805 38663

September 46700 39111 3073 42184October 51200 42738 3405 46143

November 50900 45187 2831 48018

December 19500 37481 -3491 33989



DOME of 34 ME4042/10/03

15000

25000

35000

45000

55000

0 5 10 15 20 25

Demand and Forecast 49m

Demand for 49m

Adjusted Exponential Smoothing



DOME of 34 ME4042/10/03


68m

Exponential Smoothing TTrreenndd Adjusted Exponential Smoothing

α = 0.3 ββ == 00..66

2011

January 65400 78300 0

February 71300 76200 -1260 74940

March 69400 74160 -1728 72432

April 65300 71502 -2286 69216

May 70800 71291 -1041 70251

June 47400 64124 -4717 59407

July 38500 56437 -6499 49938

August 70400 60626 -86 60540

September 68900 63108 1455 64563October 64300 63466 797 64262

November 58800 62066 -521 61545

December 69300 64236 1094 65330

2012

January 69400 65785 1367 67152

February 36000 56850 -4815 52035

March 45800 53535 -3915 49620

April 76000 60274 2478 62752

May 56700 59202 348 59550

June 78600 65021 3631 68652

July 67900 65885 1970 67855

August 75400 68740 2501 71240

September 65600 67798 435 68233

October 78400 70978 2083 73061

November 46800 63725 -3519 60206

December 52700 60417 -3392 57025



DOME of 34 ME4042/10/03

30000

40000

50000

60000

70000

80000

0 5 10 15 20 25


Demand for 68m




DOME of 34 ME4042/10/03


76m

Exponential Smoothing T T r r eennd d Adjusted Exponential Smoothing

α = 0.3 ββ == 00..66

2011

January 78300 78300 0

February 56000 71610 -4014 67596

March 36800 61167 -7871 53296

April 78900 66487 43 66530

May 67800 66881 254 67135

June 56400 63737 -1785 61952

July 76400 67536 1565 69101

August 68300 67765 764 68529September 42600 60215 -4224 55991

October 75300 64741 1026 65766

November 78300 68809 2851 71659

December 79000 71866 2975 74841

2012

January 69400 71126 746 71872

February 36000 60588 -6024 54564

March 45800 56152 -5072 51080

April 76000 62106 1544 63650

May 56700 60484 -356 60129

June 78600 65919 3119 69038

July 67900 66513 1604 68117

August 75400 69179 2241 71421

September 65600 68106 252 68358

October 78400 71194 1954 73148

November 46800 63876 -3609 60266

December 52700 60523 -3455 57068



DOME of 34 ME4042/10/03

30000

40000

50000

60000

70000

80000

0 2 4 6 8 10 12 14 16 18 20 22 24


Demand for 76m




DOME of 34 ME4042/10/03

Annex 1

Machine Details

Machine

Index Imported from

Area required

for the machine

Average

Production Rate

1 A1

China 1.9 m x 1.5 m 160m / day

2 A2

3 A3

4 A4

5 A5

6 A6

7 A7

8 A8

9 A9

10 A10

11 A11

12 A12

13 A13

14 A14

15 A15

16 A16

17 A17

18 A18

19 B1

India 2.1 m x 1.8 m 130m / day

20 B2

21 B3

22 B4

23 B5

24 B6

25 B7

26 B8

27 B9

28 B10



DOME of 34 ME4042/10/03

Annex 2

Maximum Production Rate

Sales of 2011 & 2012

Demand for 76m width,

Width Day or 15 hrs Month

76m 3192m 79800m

68m 2856m 71400m

49m 2058m 51450m

Months of 2011 Demand (m)

January 78300

February 56000

March 36800

April 78900

May 67800

June 56400

July 76400

August 68300

September 42600

October 75300

November 78300

December 79000


January 69400

February 36000

March 45800

April 76000

May 56700

June 78600

July 67900

August 75400

September 65600

October 78400

November 46800

December 52700






January 65400

February 71300

March 69400

April 65300

May 70800

June 47400

July 38500

August 70400

September 68900October 64300

November 58800

December 69300


January 71000

February 39500

March 48500

April 64300

May 62700

June 63800

July 36800

August 26800

September 69300October 64900

November 58700

December 56400


January 47300

February 28900

March 34400

April 50300

May 39800

June 48200

July 51400

August 50700

September 16900

October 35600

November 17800

December 27300


January 28600

February 32700

March 16800

April 19300

May 21500

June 49400

July 36500

August 42800

September 46700

October 51200

November 50900

December 19500

redesign of company

Documents