erp system at ppic

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ERP system at PPIC. Presented by Waleed Rawhi Ahmed Tomeh Mohamad shtaiwy Siham Abu Rabie. Covered Topics. Project overview. ERP Requirements. Current State Analysis. - Internal processes. - Sales system. - Inventory system. Suggested improvements. - Future sales system. - PowerPoint PPT Presentation

TRANSCRIPT

ERP system at PPIC

Presented byWaleed RawhiAhmed Tomeh

Mohamad shtaiwySiham Abu Rabie

Covered Topics

• Project overview.• ERP Requirements.• Current State Analysis.• - Internal processes.• - Sales system.• - Inventory system.

• Suggested improvements.• - Future sales system.• - Future inventory system.

• Recommendations.

• What is ERP?• Project Objectives.• Project Methodology.

Project Over View

What is ERP ?

ERP Modules

Planning

Purchasing

Inventory

SalesMarketing

Financial

HR

commercial software package that promises the seamless integration of all the information flowing through the company–financial,

accounting, human resources, supply chain and customer information”

Benefits of ERP

Integration of a single source of data

A real-time system

Common data definition

Reduced operating costs

Improved internal communication

Foundation for future improvement

Increased productivity

Project Objectives

• Study the current state systems in the company.

• Evaluate current systems and assess them.

• Construct a new systems that the company should have.

• Improve the information flow by 30%.

Methodology

Evaluate current systems.

Construct new systems

Evaluate new systems.

Coding new systems.

• Sales functions.• Inventory functions.• Production functions.

ERP Requirements

Sales Functions

Sales inquiry handling

Margin control

Quotations

Sales Pricing control

Items Prices

Discounts.

Sales contract handling

Long term agreements

with customers

Contracts for new customers

Sales order control

Commissions

Manage sales order, cost

order.

Customer returns.

Sales invoicing

Billing functions

Accounts control

The main system isForecasting system

• Which it is the key in planning issues.

We will discuss later on this presentation

Inventory Functions

Barcode Picking

Groups / Kits / BOM Product List Track stock

levels

Inter Store Stock

TransfersPrice Matrix

Price Movement

Tracking

Stock Adjustments

Supplier Price and Code

Listing

Production functions

Material Planning

Shop floor management

Traceability

Plant maintenance

Labor & material costing

Work center scheduling

• Internal processes.• Sales analysis.• Inventory analysis

Current state analysis

Sales processes

The arrival of an order from the customer

Ensure the availability of stock.

Make Production order.

Feedback from the stores when the order is complete.

Production Processes

Production request

received from inventories.

Production order is

issued.Raw materials

arrival.Production scheduling

Production start.Quality control

approval

Delivery of finished products

to storesDaily reports

Financial manager approval on

accounting system

Inventory Processes

Receipt of raw materials.

Receipt of final product and under processing items

Delivery of raw materials and materials under processing to the production department .

Sales current state analysis

Sales Analysis Methodology

Sales data collection

Products ABC classifications

Forecasting models tests.

Choose the suitable forecasting system.

Three Types of products

• Preforms ( PET )

• Pipes.

• Bottles.

Data Collection for Preforms• Preform Sales at 2012

Data collection for Pipes• Pipes Sales

Data collection for bottles

• Bottles sales

ABC Classification for preforms

AB4 - 30 - Blue

AB2 - 33 - Blue

AB2 - 30 -

Trans.

AB4 - 33 - Blue

AB2 - 30 - Blue

AB4 - 30 -

Trans.

Trans. - 33

AB2 - 15.5

Trans.

AB4 - 15.5 - Trans.

Trans. - 51

Trans. - 23

DB7 - 30 -

Trans.

Trans. - 18

Blue - 18

Trans. - 80

Trans. - 47

DB7 - 33 - Blue

Blue - 47

0102030405060708090

100

Preform Classification

B C

A

A

DescriptionTotal number of

parts

Percentage of

items in the sales

Cumulative usage

value

Percentage of

annual sales value

Cumulative of

annual sales value

A 4 %22 %22 %82 %82

B 4 %22 %44 %13 %95

C 10 %56 %100 %5 %100

Total 18 %100 %100

ABC Classification for Pipes

DescriptionTotal number of

parts

Percentage of

items in the sales

Cumulative usage

value

Percentage of

annual sales value

Cumulative of

annual sales value

A 16 %25 %25 %80 %80

B 16 %25 %50 %15 %95

C 31 %50 %100 %5 100%

Total 63 %100 100%

ABC Classification for bottles

Twissted off - 1.5

L

Trans. - 1.5 L

Trans. - 1 L

Trans. - .5 L

Blue - 1.5 L

Trans. - 1 L - Jar

0102030405060708090

100

Bottles Classification

AB

C

DescriptionTotal number of

parts

Percentage of

items in the sales

Cumulative usage

value

Percentage of

annual sales

value

Cumulative of

annual sales value

A 1 %17 %17 70% %70

B 1 %17 %34 %29 %99

C 4 %66 %100 %1 %100

Total 6 %100 %100

Forecasting systems

• For the current forecasting system we found that there is no accurate forecasting system.

- The company forecasts its sales by the last quantity produced in the last year.

• Which means that all over the forecasted year the quantity remains the same.

Pipes Forecasting ( moving average )

Index

C1

73645546372819101

90000

80000

70000

60000

50000

40000

30000

20000

10000

0

Moving AverageLength 3

Accuracy MeasuresMAPE 81MAD 16327MSD 387347401

Variable

Forecasts95.0% PI

ActualFits

Moving Average for pipe

Pipes Forecasting ( Single Exponential smoothing )

Index

C1

73645546372819101

100000

80000

60000

40000

20000

0

Smoothing ConstantAlpha 0.0985075

Accuracy MeasuresMAPE 78MAD 18372MSD 475925999

Variable

Forecasts95.0% PI

ActualFits

single Exponential Smoothing

Pipes Forecasting ( Naïve forecasting)

0

10000

20000

30000

40000

50000

60000

70000

80000

90000

100000

Actual

Native forecast -ing

Pipes Forecasting

0

10000

20000

30000

40000

50000

60000

70000

80000

90000

100000

ActualNative forecast -ing3 Moving AverageExpenensial smoothing

Date Method of forecast Standard Error Accuracy measure

14 months

From 1/1/2012

To 28/2/2013

Naïve Method _______

Moving Averages 109288.5535MAPE 81

MAD 16327

Exponential Smoothing 179996.6564MAPE 78

MAD 18372

Preform Forecasting ( Moving Average)

Index

C2

73645546372819101

120000

100000

80000

60000

40000

20000

0

-20000

-40000

Moving AverageLength 3

Accuracy MeasuresMAPE 130MAD 20890MSD 751059074

Variable

Forecasts95.0% PI

ActualFits

Moving Average for preform

Preform Forecasting ( Single exponential smoothing)

Index

C2

73645546372819101

125000

100000

75000

50000

25000

0

-25000

-50000

Smoothing ConstantAlpha 0.0766089

Accuracy MeasuresMAPE 140MAD 27394MSD 1082991809

Variable

Forecasts95.0% PI

ActualFits

Single Exponential Smoothing for preform

Preform forecasting

020000400006000080000

100000120000140000160000180000200000220000240000260000

Exponensial

3 Moving Average

Actual

Date Method of forecast Standard Error Accuracy measure

14 months

From 1/1/2012

To 28/2/2013

Naïve Method _______

Moving Averages 109288.5535MAPE 81

MAD 16327

Exponential Smoothing 179996.6564MAPE 78

MAD 18372

Bottles Forecasting (Moving Average )

Index

C3

73645546372819101

150000

100000

50000

0

-50000

-100000

Moving AverageLength 3

Accuracy MeasuresMAPE 26393MAD 24791MSD 1881885206

Variable

Forecasts95.0% PI

ActualFits

Moving Average for Bottel

Bottles Forecasting (Single exponential smoothing)

Index

C3

73645546372819101

125000

100000

75000

50000

25000

0

-25000

-50000

Smoothing ConstantAlpha 0.0455059

Accuracy MeasuresMAPE 5822MAD 16286MSD 1082742561

Variable

Forecasts95.0% PI

ActualFits

Single Exponential Smoothing

Bottles forecasting

12-Jan23-Ja

n3-Fe

b14-Fe

b25-Fe

b8-M

ar

19-Mar

30-Mar

10-Apr

21-Apr2-M

ay

13-May

24-May

4-Jun15-Ju

n26-Ju

n7-Ju

l18-Ju

l29-Ju

l9-A

ug

20-Aug

31-Aug

11-Sep22-Se

p3-O

ct

14-Oct

25-Oct5-N

ov

16-Nov

27-Nov8-D

ec0

20000

40000

60000

80000

100000

120000

140000

160000

180000

Exponensial3 Moving AverageActual

Date Method of forecast Standard Error Accuracy measure

14 months

From 1/1/2012

To 28/2/2013

Naïve Method _______

Moving Averages 235611MAPE 26393

MAD 2479

Exponential Smoothing 350221.7MAPE 5822

MAD 16286

Inventory current state analysis

Inventory analysis methodology

Inventory data collection

Inventory ABC classifications

Inventory model

Implement the model

Three types of inventories

• Raw material inventory.• - Pipes raw material.• - PEX raw material.• - Poly ethylene raw material.

• Finished goods inventory.

• Commercial inventory.

Pipes Raw Material inventory ABC classification

Description Category Cum % of Total Usage

Poly Ethylene RM A 74.59310897

HDPE RM( مجروش ) B 86.52154129

PEX RM B 94.59420105

Black color C 96.42562021

Calcium Carbonate RM C 97.50423181

25برابيش mmتدكيك C 98.49766113

White Catalyst C 98.8875339

Yellow ink solvent C 99.26539379

32برابيش mmتدكيك C 99.53877796

Yellow ink C 99.79359677

Printer cleaner C 100

PEX raw material Classification

Poly Eth

elen RM

HDPE RM( ش

جرو( م

PEX RM

Black c

olour

Calcium Carb

onite Rm

ش را3ب3ي

ب3

25

mmدكيك

ت3

White Cata

lest

Yellow in

k solve

nt

ش را3ب3ي

ب3

32

mmدكيك

ت3

Yellow in

k

Printer

clean

er 0

10

20

30

40

50

60

70

80

90

100

PEX RM Cummulative %

Preform Raw material ABC classification

PET RM Alto Blue -2 Alto Blue -4 Ultra Pure Dasani Blue -793

94

95

96

97

98

99

100

Preform Commulative %

Description Category Cum % of Total Usage

PET RM A 95.67305

Alto Blue -2 B 97.21377

Alto Blue -4 C 98.68748

Ultra-Pure C 99.57653

Dasani Blue -7 C 100

ABC Classification for Poly Ethylene finished product

Description Category Cum % of Total Usage

L.D.B.E Hieden 0509 A 57.24233068

RONFLIX PIPE B99.63213558

Prog RM C99.81606779

118 RM C100

PalPipe 50mm-16 C100

L.D.B.E Hieden 0509 RONFLIX PIPE Prog RM 118 RM PalPipe 50mm-160

102030405060708090

100

Poly Ethylene FP Commulative %

Commercial Pipes Classification

E.F ELbow 20 E.F Reducer 160-110 E.F TEE 63MM SDR11 PN16 TEE90 MM e.f tapping tee 110/32 Te ( Injected) 160mm0

20

40

60

80

100

120

Poly Ethylene Connecters Cumm %

ABC Classification for Poly Propylene connectors commercial.

TRNS 25- 3/4 Male

TRNX 32-1 FE

Elbow 90-25

Elbow 40-90

TRNS 25- 3/4 Female

Elbow 90-32

TRNS 20-1/2 Male

Elbow 90 FE

25 -3/4

Elbow 90

Male 32 -3/4

REDU 50-32

REDU 40-32

REDU 40-25

REDU 40-20

TEE 40-25-40

Elbow 90-63

0

10

20

30

40

50

60

70

80

90

100

Ply Prob. Prices commercial%

ABC Classification for Agriculture connectors commercial

Coupling 75*75

Small Pipe

cleaner

Large Pipe

cleaner

End Cap 20

End Cap 63

End Cap 25 mm

Coupling 32*32

Elbow 20 -1/2

Rec.

Outside head 1/32

End Cap 32

Head Cap 20 -

1/2

Coupling 63*63

0

10

20

30

40

50

60

70

80

90

100

Agricurture Connecters Comm %

ABC Classification of Irrigation Pipes.

Coupling 75*75

Small Pipe cleaner

Large Pipe cleaner

End Cap 20

End Cap 63

End Cap 25 mm

Coupling 32*32

Elbow 20 -1/2 Rec.

Outside head 1/32

End Cap 32

Head Cap 20 -1/2

Coupling 63*63

0

10

20

30

40

50

60

70

80

90

100

Agricurture Connecters Comm%

ABC Classification for Packaging and Filling Inventories

Preform car-ton

40*38*60

Nilon Roll Preform

Carton Layers 1200*1000*

70

Carton Layers 1200*1000

Nilon 107*95 Plaster 132 m Wood Ballet Kargal Ballets Nilon Roll 0

10

20

30

40

50

60

70

80

90

100

Packaging & Filling Comm %

Suggested Improvements• Electronic pick slip report for the

warehouse/ transportation

Suggested Improvements

• ERP system contains two modules , the first one concern with sales.

• The second one concern with inventory.

ERP Sales Module

ERP Inventory Module

Recommendations

Thank you For listening

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