final) sandeep

A Project Repot on

“Formulation of Inventory Control strategies for Raw material store (RMS) and

Finished Goods Store (FGS)”

Undertaken at

In partial fulfillment of Summer Internship of

PGDIE (Post Graduate Diploma in Industrial Engineering)

By:

Sandeep, ANA

PGDIE class of 2012

Roll No: 01

Under the guidance of:

Dr.Dinesh Seth Mr. Sandeep Rane

Associate Professor, Commercial Head,

NITIE, Mumbai MAHLE Filters India, Pune

National Institute of Industrial Engineering

Vihar Lake Mumbai-400087

National Institute of Industrial Engineering, Mumbai Page | 2

ACKNOWLEDGEMENTS

“Too often we are so preoccupied with the destination, we forget the guiding light.”

-Anonymous

I take this opportunity to extend my sincere thanks to NITIE, Mumbai and

MAHLE Filter Systems (India) Limited ,group Company of ANAND Group for

offering a unique platform to earn exposure and garner knowledge in the field of

Supply Chain Management.

First of all, I extend my heartfelt gratitude to my project guide Mr.

Sandeep Rane, Commercial Head Mahle, pune for having made my summer training

a great learning experience by his constant guidance, encouragement and extreme

support.

I also take immense pleasure in extending my thanks to my Summer

Project Internal Guide Mr. Dinesh Seth, Professor, NITIE for providing valuable

insights during the project.

I am extremely thankful to Mr. Vivek Tandon, Plant Head, Mahle

Filters, Pune for spending their valuable time in giving me invaluable guidance and

support. Their devotion to analysis and serious attitude toward management has given

me great encouragement and inspiration to accomplish this project.

Last but not the least I would like to express my profound gratitude

to each and every employee of the organization who contributed in their own ways in

successful completion of this project.

Sandeep, ANA

PGDIE Class of 2012

NITIE, Mumbai

TABLE OF CONTENTS


Topic Page no

1. Executive Summary 5

2. About the Company

ANAND Group

MAHLE GmbH

Profile

Infrastructure

Test Facilities

Structure and Back ground

Product Types

Major products and Customers per region

7

3. Need of the project 17

4. Objectives of the project 18

5. Understanding present processes

AS IS analysis

TO be analysis

19

6. Devising inventory procedures for Raw materials

Inventory classification

ABC analysis of raw materials

HML analysis of raw materials

9 Matrix Cell approach

Summary of Inventory classification

Devising safety stock and Cycle stock

The periodic order review

Understanding Cycle stock and safety stock

Capturing demand

Capturing demand variation

Capturing Lead time

Capturing Lead time variation

Calculating safety stock

Calculating cycle stock

21


Topic Page no

7. Consolidated analysis of Finished goods store

Present process

Classification

Procedure flow chart

Adherence to planning policies

42

8. Recommendations 45

9. Limitations 45

10. Academic contributions 46

11. Bibliography 47


EXECUTIVE SUMMARY

In line with ANAND GROUP‘s aspiration to be India's premier

Automotive Company, recognized for its world-class quality and enduring consumer

trust, MAHLE Filter Systems(India) Limited is meant to constantly improve &

optimize the supply chain to remain competitive.

The objective of the project is to develop inventory control

procedures for Raw Materials (RM and Finished Goods (FG) to reduce the inventory

by using 9-cell matrix (an excel model) in correspondence of MAHLE standards. With

the help of 9-cell matrix we have to do the inventory classification and then have to

focus on the class with the maximum valuation (i.e. A class). The rationale behind this

exercise is to ensure a more accurate set of input data when automation of the

production and scheduling processes is initialized. The deliverables of the project are

inventory norms ensuring an optimized level of safety stocks of RM and FG inventory

at various echelons of the supply chain & consequently savings in terms of losses due

to storage of excess material, expiry of unused materials etc.

Deliverables:

To design an inventory control system which can

Reduce & control the inventory to optimum level

Give purchase order (P.O.) data

Order point

Order quantity

Safety stock for individual items

Weekly inventory tracking

Methodology:

The inventory calculations will be made in an excel worksheets and the

model will be made compatible with the output of the existing software so that the

daily stocks can be evaluated easily. The following procedure will be adopted:

Identifying items for inventory reduction

Initially all the Raw materials and finished products with cost contributing

value are identified. After this, identification of actual raw material items and finished

goods are done with classification is done the help of ABC (Pareto) analysis (both

quantity and value), HML classification. With this 9 matrix cell is constructed

accordingly facilitating which are the items when controlled properly will give

maximum benefits in terms of cost reduction.


Understanding the operations

Developing a model for inventory control

Here actual production plan from PPC (Production Planning and Control)

department was broken down to monthly item requirement so complete store issuances

of components are collected from stores for past 12 months i.e Jan‘10 to Dec‘10.

Collect the data for manufacturing and transit lead times for each part to use fixed

period review system, and replenishment stock concept to calculate inventory levels

(minimum stock levels, transit inventory and maximum inventory).

To classify the stocks on the basis of consumption (ABC analysis) and

variability (Low, Medium and High) and define material strategy inventory model

was developed for monthly opening inventory , weekly consumption, weekly ending

inventory , P.O. data ,weekly inventory tracking and demand vs. production variation

tracking etc.

Simulation and testing

Excel model was simulated for certain items. Various scenarios were

generated for demand fluctuation and the model was tested for absorbing those

fluctuations. To get the system working on real time basis with current software once

all the above are confirmed and approved.

Key Words: Inventory control, Safety Stock, ABC analysis, LMH (Low, Medium

High) Classification.

Understanding Materials and Usage

Procurement FGS

Understanding Manufacturing

Process Constraints

Understanding the products

Air Filters Oil Filters Fuel Filters


About the Company - ANAND GROUP

Vision

To become a most preferred global source for world-class quality automotive parts

system by the year 2010.

Mission

The mission statement of Anand ‗U‘ is „To champion and accelerate learning by

providing world-class technical and managerial solutions and act as the hub for

transfer of learning throughout the Group’. The focus is therefore two-fold: provide

solutions that are directly relevant to the business units and also help in the horizontal

replication of learning.

Profile

Anand is a leading manufacturer of automotive components and systems in India.

With a sales turnover of $550 million, it has the widest range of auto Components,

supplied to virtually every vehicle and engine producer in the country. In 1961, Mr.

Deep C Anand, Chairman of Anand Automotive Systems, founded the Group‘s

flagship company - Gabriel India in Mumbai for the manufacture of shock Absorbers.

Today, Anand comprises 18 companies spread in nine states of the country. It has also

built up a sizeable export market, currently about 20% of the total sales of existing

products, targeted to reach 30% in the next few years. Employing over 6000 people,

Anand has 700 professionally qualified Professionals. It invests two per cent of its

sales every year on training and development programs, conducted by its in-house

technical and management institute – Anand 'U'.

Anand ‗U‘ is set up as a Corporate University to cover the needs of Anand.

Essentially, there were five broad forces that led to the setting-up of Anand „U‟:

The emergence of a flat, flexible organization

The need for ‗knowledge workers‘ rather than ‗blue-collared workers‘

The shortened shelf life of knowledge

The new focus on lifetime employability, rather than lifetime employment

A fundamental shift in the global education marketplace

These broad trends point to a new key vehicle for creating a sustained competitive

advantage – the Group‘s commitment to employee education and development.

Anand Group of Companies:-

Anand Automotive Limited


Behr India Limited

Chang Yun India Limited

CY Myutec Automotive India Private Limited

Faurecia Emission Control Technologies

Federal-Mogul Bearings India Limited

Gabriel India Limited

Haldex India Limited

Henkel Teroson India Limited

MAHLE Filter Systems India Limited

Mando India Limited

Perfect Circle India Limited

Spicer India Limited

Takata India Pvt Limited

Valeo Friction Materials India Limited

Victor Gaskets India Limited

Camfil Farr Air Filtration India Limited

Degrémont Limited

SUJAN Luxury Hotels

Joint Ventures

Dana Corporation, USA

ArvinMeritor Inc, USA

Federal-Mogul, USA

Henkel, Germany

CY Myutec, Korea

Behr, Germany

Mando, Korea

Valeo, France

Haldex, Sweden

Degrémont, France

Mahle, Germany


Anand Initiatives

Women Empowerment

Anand has set itself a target of 30% women employees. Currently the figure stands at

14% but some of the more recently established companies and facilities of the Group

have close to 50% women.

Concept of Operating Engineers

The concept of employing Operating Engineers (OEs) at Anand first emerged in 1994.

In view of the changing and competitive business environment, which demanded

world-class quality products, the Group realized the need for a 'knowledge workforce'.

Knowledge workers have the ability to learn and grasp things faster and apply the

same at their workplace. This facilitates self-managed, team-based working as the

knowledge worker also has a better attitude towards quality work by virtue of his/her

education and training.

Integration of Managers with International Partners Anand believes in and is committed to develop global managers through integration of

its people with its Strategic International Partners. In keeping with this belief, Anand

has an ongoing program, wherein 26 Anand managers are currently on secondment

overseas for stints ranging between 3 – 36 months.

Corporate Governance

Another recent initiative taken by Anand is the induction of professionals as additional

independent directors on the boards of its various companies as well as in Advisory

capacities. The objective is to promote good corporate governance, enhance

shareholder value, drive Anand - with its eighteen companies - as a single entity and at

the same time give a thrust to double its turnover to Rs 40 billion in the next five

years.

Exports

Anand's Business Philosophy stipulates 30% of its total sales turnover for exports to

World markets. The Group has been exporting established products like Shock

Absorbers, Engine Bearings, Filters, Piston Rings and Gaskets for several years and in

Piston Rings and Filters, has achieved an export of 30% of its turnover. Overseas

customers of Anand include reputed companies in Europe, USA and Asia Pacific.Two

of Anand Companies – Gabriel India and Purolator India have an ‗Export House‘

status, bestowed by the Government of India.

Source: http://www.anandgroupindia.com/profile.html


MAHLE

Mahle GmbH is one of the 30 largest automotive suppliers

worldwide. As the leading manufacturer of components and systems for combustion

engines and its periphery, the Mahle Group is among the top three systems suppliers

worldwide for piston systems, cylinder components, valve train systems, air

management systems, and liquid management systems. As a leading global

development partner for the automotive and engine industry, MAHLE offers unique

systems competence in the internal combustion engine and engine peripherals. With

its two business units Engine Systems and Components and Filtration and Engine

Peripherals, the MAHLE Group thus ranks among the top three systems suppliers

worldwide for piston systems, cylinder components, as well as valve train, air

management, and liquid management systems. Almost all automobile and engine

manufacturers around the world are customers of MAHLE.

For more than 90 years, MAHLE has played a decisive role in

promoting the development of automotive and engine technology, setting standards

time and again. Driven by performance—every MAHLE employee demonstrates

surpassing enthusiasm for performance, precision, and perfection.

MAHLE has a local presence in all major world markets.

More than 47,000 employees work at over 100 production plants and eight research

and development centers in Stuttgart, Northampton, Detroit (Farmington Hills, Novi),

Tokyo (Kawagoe, Okegawa), Shanghai, and São Paulo (Jundiaí). Around the world,

approximately 3,000 development engineers and technicians are working on forward-

looking concepts, products, and systems for the ongoing development of vehicle

power trains.

The Industry business unit bundles the MAHLE Group's

industrial activities. These include the areas of large engines, industrial filtration, as

well as cooling and air-conditioning systems for railway and special vehicles, buses,

ships, construction and agricultural machinery, the aerospace industry, and stationary

large engines for power generation. The Aftermarket business unit serves the

independent spare parts market with MAHLE products in OE quality.

In 2010, the MAHLE Group achieved sales of approximately

EUR 5.3 billion (USD 7 billion), positioning the company among the top 30

automotive suppliers worldwide.


The product lines of Mahle in details:

Piston systems: Aluminum pistons for gasoline and diesel engines, articulated and

steel pistons for commercial vehicle engines, piston assemblies and complete

power-cell- modules.

Cylinder components: Piston rings, piston pins, connecting rods, cylinder liners,

bearings and bushings for combustion engines and other automotive applications,

piston inserts.

Valve train systems: Machined and assembled cylinder heads and engine blocks

as well as assembled complete engines, precision sintered parts and turbocharger

parts. Complete valve train systems and their components.

Air management systems: Complete air intake systems, air filter elements,

crankcase ventilation systems, cylinder head and engine covers, cabin air filters,

actuators, blowby heating, EGR- modules and mechatronic components.

Liquid management systems: Oil filter modules, oil and fuel spin-on filters, fuel

filter modules, fuel pressure regulators, inline fuel filters, carbon canister modules,

heat exchangers for engines and transmissions, hydraulic oil filters, air driers.

The profit centers of Mahle in detail:

Aftermarket: Products for engine service and rebuilding from the complete Mahle

product range.

Small engine components: Cylinder assemblies, cylinder heads, pistons, and

filters for small engines of handheld power equipment, motorcycles, and power

sports vehicles.

Large engine components: Pistons and engine components for gas, diesel, heavy-

oil, and multi-fuel engines for marine applications and energy production.

Motorsports: Development and production of high-quality engine components

for motorsports.

Industrial filtration: Fluid filtration, fluid separation, oil mist separation, process

filtration, and dedusting in general, industries, ship maintenance, for large engines,

in industrial vehicles, and process technology.

Mahle Test Systems: Vehicle and component testing, pressure/vacuum based

leak testing, vehicle end-of-line testing, web based reporting, data loggers,

assembly plant testing equipment.


MAHLE Filter Systems (India) Limited:-

Structure & background : Manufacturing Plants

Joint Venture in April 2005


Profile of locations – Pune, Maharashtra

Established in 1969

Headcount -144

Estate area – 51965 sqm

Production area – 3888 sqm

Infrastructure

• Powder Paint line

• Assembly lines

• PU

• Assembly lines Air Liquid assemblies

• Carbon canister manufacturing line

Test Facilites :-


Structure & background: Salient Features

Main Product groups - Air & Liquid filtration.

India‘s largest manufacturer / exporter of Oil, Fuel, Air & Hydraulic filters to

Automotive, Railways & Aviation industries.

Principal supplier of filters to both - OE & replacement markets, with a sizeable

presence in overseas markets as well.

All existing 3 Plants are certified for:

Quality Management System: TS 16949.

Environment Management System: ISO14001

Occupational Health and Safety Management System OHSAS18001

Special Lines:-

Aft Mkt

40%

OE

40%

Exports

20%

Pune Plant: PU Element Line Mould

Transfer Oven

Pune Plant: Spin On Filter Line With

Pre-Treatment and Electro-static / Liquid

Painting


Product Types: Filters

Sales Data (in Million USD )


MAJOR PRODUCTS AND CUSTOMERS PER REGION


Need of the project

The Automotive industry in India is one of the largest in the world

and one of the fastest growing globally. India manufactures over 17.5 million vehicles

(including 2 wheeled and 4 wheeled) and exports about 2.33 million every year. It is

the world's second largest manufacturer of motorcycles, with annual sales exceeding

8.5 million in 2009. India's passenger car and commercial vehicle manufacturing

industry is the seventh largest in the world, with an annual production of more than 3.7

million units in 2010. According to recent reports, India is set to overtake Brazil to

become the sixth largest passenger vehicle producer in the world, growing 16-18 per

cent to sell around three million units in the course of 2011-12. In 2009, India emerged

as Asia's fourth largest exporter of passenger cars, behind Japan, South Korea, and

Thailand.

In such competitive environment when the profit margins are

being squeezed it is very essential to maintain the supply chain surplus. One of the

various contributors to the supply chain surplus is an efficient inventory management

system at various echelons of the chain. So the project directly addresses the level of

inventory at various levels. The inventory levels should be optimized to reduce the on

hand inventory while at the same time the customer service level should be maintained

which is highly critical.

So it is very essential to MAHLE maintain a high service

level and at the same time streamline the inventory to increase the supply chain

surplus and profitability which in turn is the objective of the project.


Objectives of the project

Project Title: - Inventory Control at Raw Material Store (RMS) and Finished Goods

Store (FGS)

Objective: - To set up inventory norms for Raw Materials (RM) and Finished Goods

(FG), and make necessary amendments. The rationale behind this exercise is to ensure

a more accurate control on inventory when the production and scheduling processes is

initialized.

Project Deliverables and Business Impact:-

Propose Optimum inventory levels for child parts

Setting of inventory control norms ensuring optimized levels of RM and FG

inventory at various echelons of the entire Supply Chain

Savings in terms of losses owing to storage of excess material


Understanding present process

“As is” process :-


“TO be” process:-


Devising inventory procedures for Raw materials

Inventory Classification

The count of raw materials used in MAHLE is close to 2500 and before we

proceed to setting the inventory control for them it is essential that we classify the

inventory based on certain parameters. The objective of classification is to firstly

group items with similar characteristics together, secondly to manage the inventory

based on the classification and to devise ordering frequency and quantity for each

category. ABC method of classification is one very popular method for inventory

classification based on Pareto‘s principle of distribution. Pareto rule stated that the

chunk of wealth of any nation is with a small percentage of people. In terms of

inventory management it will translates that the maximum value of the inventory is

occupied by a few items. Hence controlling the cost of few items will contribute to the

effective control of a large amount of costs. The ABC analysis categorizes the

inventory in to 3 classes namely:

Class A: Occupies 70 to 80 % of the total inventory value and contributes only

10 to 20 % of the physical inventory. Are expensive &Very strict control should

be placed on them. Exact service levels & other parameters must be determined

to accurately calculate safety stock in order to reduce unnecessary inventory

holding costs. Cooperation with vendors and strategic sourcing should be

employed to reduce lead time variations to reduce risk .Review frequency can

be increased to give increased flexibility and reduced on hand inventory.

Class B: Occupies 15 to 20% of the total inventory value and contributes 20 to

40 % of the physical inventory. Moderate control should be used. The approach

should be to allow some deviation from the optimal EOQ and safety stock

levels so as to reduce the operation costs

Class C: Occupies 5 to 10 % of the total inventory value and contributes 40 to

70 % of the physical inventory. It is economic to hold these items in quantities

large enough to make the possibility of stock-out negligible. The general

concept is to ensure that low cost items will not cause an expensive production

or service system to stop


ABC analysis of RM

ABC analysis was performed on the raw material inventory. For the

classification the consumption data from Jan 2010 to Dec 2010 was used. The ABC

was done to categorize the raw materials based on the value of their consumption. The

cut offs taken was 80% of value for A class , 15 % value for class B and 5% for class

C.

Methodology:

Excel sheet:-

Consumption data form jan 10 to Dec 2010

Consumption data form jan 10 to Dec 2010consumption value= quantity consumed x

unit cost

Ranking the RM based on consumption value

Categorising the RMs based on decided cutoffs


HML classification:-

Analysis was performed on the raw material inventory. For the classification the

consumption data from Jan 2010 to Dec 2010 was used.

The lower the standard deviation from the average usage, the lower the risk of

maintaining levels of inventory

The higher the variation the less predictability of demand and therefore the

higher the risk to ordering and maintaining inventory

Grouping items based on variability helps the inventory manager identify items

which can or cannot be easily forecasted:

Low variability items will be predictable and easier to forecast with accuracy

Medium variability items are relatively predictable but show larger swings

High variability items contain the largest swings in demand and highest risk

Variability classification:-

Low = Std .dev sales/ Average Consumption<= 1.0 0r 100% of average usage

Medium = Std .dev sales/ Average Consumption <= 2.0 0r 100 - 200% of

average usage

High = Std .dev sales/ Average Consumption >=2.0 0r greater than 200% of

average usage

Methodology:-

Consumption data form jan 10

to Dec 2010

Average and Std Dev is calculated

Calculating Variability

=st.dev/Average

Categorising the RMs based on

decided cutoffs


Excel sheet:-

ABC Volume:-

ABC analysis was performed on the raw material inventory. For the

classification the consumption data from Jan 2010 to Dec 2010 was used. The ABC

was done to categorize the raw materials based on the Volume of their consumption.

The ABC was done plant wise. The cut offs taken was 80% of value for A class , 15 %

value for class B and 5% for class C.

CONFIDENTIAL


Methodology:-

Excel sheet:-

Consumption data form jan 10 to Dec

2010

Consumption data form jan 10 to Dec

2010 quantity consumed

Ranking the RM based on

consumption

Categorising the RMs based on decided

cutoffs

CONFIDENTIAL


9 - Cell Matrix approach: -

When you consider every combination of ABC and LMH or(ABC volume) in a cell

matrix is called 9 Matrix cell approach. The purpose of classification is to identify the

problem areas more effectively.

Benefits of the 9-cell Matrix:

_ Segments inventory by value and risk

– Value classification used to prioritize

– Monthly demand volatility captures inventory risk

_ Enables targeted inventory strategy and policy development

– Where should focus be placed?

– What are the drivers and constraints of each cell or group?

– What are the optimal management strategies and processes?

_ Monthly reporting can be performed at level appropriate for audience:

– Overall for non-operations corporate view

– By initials, replenishment and excess for operations review

– By division for item management planning and control

Risks of disregarding classification:

• Many companies failed to apply the right production and inventory strategy to

products, because they disregard stock classification. This occurs because:

a. No stock classification is reviewed as frequently as required.

b. Key system data is not up to date e.g. current stock level, lead-times, ROP (re

order points), safety stocks…


c. Wrong beliefs on definition of best sellers are driving the wrong ―gutfeel‖

parameters

d. Inconsistent policies and practices are applied to individual items

The strategies for Inventory Control will be:

1. To calculate the inventory for Class ‗A‘ and ‗B‘ with ‗LOW‘ and ‗MEDIUM‘

variability and stock them effectively.

2. To filter the ‗C‘ class with items whether they are SLOW MOVING and then stock

them based on the calculated values

3. Analyze the CLASS ‗A‘ and ‗B‘ with ‗HIGH‘ variability and work on action to

improve the consumption pattern

Summary – Inventory Classification:

Step 1: Items are separated into RM, FG (based on the ―product category‖).

Step 2: ABC classification based on dollar value of annual usage to ensure that

majority of time and effort is dedicated to manage critical items

– A: Items that represent top 80% of total usage value

– B: Items that represent next 15% of total usage value

– C: Items that represent remaining 5% of total usage value

Step 3: LMH classification based on demand variability of annual usage

– L: Items with a demand variance of less than or equal to 1

– M: Items with a demand variance is greater than 1 and less than or equal to 2

– H: Items with a demand variance of greater than 2

Step 4: ABC classification based on Consumption Quantity of annual usage to ensure

that majority of Space and effort is dedicated to manage critical items

– A: Items that represent top 80% of total usage value

– B: Items that represent next 15% of total usage value

– C: Items that represent remaining 5% of total usage value


Devising Safety & Cycle Stock:-

The General Periodic order review model


The base stock or target inventory level or order up to level for periodic review policy

is : ( Lead time + Review period) x demand + safety stock

Cycle stock = Lead time

Safety stock (in quantity) = Normal inverse (CSL) x SQRT (σD2.LT + σlt

2.D

2)

D= Demand LT=Lead time σ= Standard deviation (variation)

Hence we see that the cycle stock depends on the Lead time while safety stock

depends upon service level, consumption & its variation, lead time and its variation.

Stock Management

Understanding Cycle Stock and Safety Stock:

In most manufacturing organizations, inventory managers face an ongoing dilemma


Hence to calculate the safety stock these parameter needs to be captured

Capturing demand:-

The historic consumption data from Jan 2010 to Dec 2010 was

taken to estimate the average consumption/demand parameter for each item. For this

the Daily production file is taken from production department. Then the daily

consumption data was summed up to get monthly consumption for each raw material

each month from Jan to Dec. The average monthly consumption was calculated from

this data. This corresponds to the parameter D in the safety stock formulae.


Excel sheet:-

Capturing demand variation:

The variations in consumption/demand will be due to many factors like:

Growth in the volumes of production as market shares increase

Economic batch sizes based production schedule

Deviations for proposed production schedule

Seasonality

Other causes

So all these variations need to be captured and normalized to get a true picture of the

consumption variation to calculate accurate safety stock value.

The above can be explained the case of a raw material "O"RING-2557(MTJ

P.NO.K1086-101-1640) (1864012557) to demonstrate the normalization process.


If the standard deviation of this un normalized consumption is taken it will give a high

value and consequently a high value of safety stock which in turn will have a high

value impact in terms of A items.

Hence we follow the normalization as follows:

Firstly a linear best fit trend line is calculated based on method of least squares.

(Shown as red line in above figure). Least square method ensures that the distance of

the trend line form all the points are the minimum. Now the deviation of each point is

calculated from the trend line. The Root mean square of the deviation of all points

from the trend line gives the consumption variation for the respective parameter. This

is σD in the safety stock formulae.

This was done for all raw materials using this methodology:

0

500

1000

1500

2000

2500

3000

JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC

CONSUMPTION VARIATION

0

500

1000

1500

2000

2500

3000

JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC

CONSUMPTION VARIATION

CONS – VARAITION

CHANGE


Methodology:- .

Excel sheet:-


Capturing the Lead time and its variation:-

Lead time consists of external lead time and internal lead time. The external lead time

includes the manufacturing time of the vendor and the time in transit. While the

internal lead time consists of the purchase order generation time and the quality testing

time.

The external lead time was calculated by taking the time between the release of a purchase

order and the Goods Receipt date. Now the above data consists of many deliveries against

the same purchase order this is known as staggered deliveries. So this data can‘t be used

directly and we need to filter out the staggered delivery data points hence only the first

delivery against a purchase is considered and remaining points are filtered.

As SAP is not available the lead time is taken based upon the location

of vendor and Lead time variations are assumed to be 20%.

Methodology:-

Procurement data form jan 2010 -Dec

2010

Lead time assumed based on location

lead time variation is assumed to be 20 %

lead time= External lead time+ PO

generation time+ QC time


Calculation of Safety stock:-

Cycle stock = Lead time

Safety stock (in quantity) = Normal inverse (CSL) x SQRT (σD2.LT + σlt

2.D

2)

D= Demand LT=Lead time σ= Standard deviation (variation)

For example:-

Example "O"RING-2557(MTJ P.NO.K1086-101-1640) (1864012557)

Average monthly consumption= 1582.666667 NOs/month

Std. Dev. Of consumption = 405.088696 NOs/month

Lead time = 7 days = 7/30 = 0.233 month

Std. Dev. Of lead time =0.20 months

SS= 1.64 x SQRT (0.233 x 405.088 ^2 + 0.20^2 x 1582.66 ^2) = 917.36 NOs/ month

SS in days = 917.3645542 / 1582.666667 = 0.579632month

= 0.579632 x 30 =17.38897 days

Customer Service Level :-


Excel sheet:-

Calculating Cycle stock:-

From the model of periodic review it is seen that Cycle stock is equivalent to the

lead time of the respective raw material. Hence cycle stock is estimated from the lead

time table.

CONFIDENTIAL


Ordering policies for Raw materials :-

Present ordering policies:-

Present Ordering policy is done at month end of every month

with the help of Order Book which contains customer name and filter code which is

called as production schedule in terms of quantity comes as a rolling plan for the

current month (CM). Based on these estimated production volumes the on hand

inventory is checked to ascertain how many days of inventory is covered by the stock

on hand and on order.(The forecasted production volumes is assumed would be

linearly consumed to convert the number of days of stock into quantity terms.)

For each filter they use corresponding Bill of Material

(BOM) and calculate the Child part quantity required for the entire month‘s plan.

Flow Diagram:-

PPC Schedule

Calculate child part

req

Checking of On hand

inventory

Purchase order

generation


Alternative ordering policies:-

a. In the ideal periodic review model the stock on hand is always below the base

stock or the target inventory level or the order up to level. This means that

ideally at the end of every review period orders would be generated for all the

Raw materials. This is not feasible with 300 raw materials with the present

resources. Hence to overcome the above shortcoming there can be two ordering

policies:

The X ordering policy: here the order quantity would be to bring the stock on hand

equal to (Cycle stock + 7(Review period) + safety stock) number of days. Here order

would be generated at the end of every review period

The Y ordering policy: here the order quantity would be to bring the stock on hand

equal to (2 x Cycle stock + 7(Review period)+ + safety stock) number of days. Here

order would be not be generated at the end of every review period

The X ordering policy will have a lower on hand inventory compared to Y ordering

policy as shown in the figure:

Hence the ordering policy is assigned to a raw material based on the respective raw

materials Value class, volume class and coefficient of variation. A generalized format

for allocation of ordering can be summarized as the following VALUE vs VOLUME

matrix.


The X axis indicates the category in which the RM falls based on the ABC analysis

done previously (On consumption value). The Y axis is the Volume class of the RM

based on the consumption based ABC analysis done earlier. The idea of the above

matrix is that for a raw material having high value in terms of cost it would ideal to

carry less average inventory to reduce our working capital. Similarly for items having

a high volume value again carrying low average inventory would mean lesser

warehousing space required. Similarly items with low value and volume class can be

stocked up in higher quantities as it would not have a high cost or space impact. So

based on the raw materials categorization the ordering policy is assigned. However we

cannot directly assign the ordering policies based on the above matrix since carrying

lower on hand inventory means higher risk of a stock out , hence form the past

consumption the coefficient of variation & lead time is calculated and if they are

below a acceptable value the ordering policy is assigned.


Methodology for allocating ordering policy :-

Let review period be – 7 days

Calculate 7 day demand for

respective RM

IF x then check if cof. variation

consumption <80% and cof. of

variation LT<80%

IF Y FREEZE

If combine cof. variation < 50%

assign X else Y

IF X calculate combined

coefficient of variation=cof.

Variation consumption+cof.

variation lead time

IF Y then Freeze it

IF YES assign X IF YES assign Y


Initially calculate the 7 day average demand for the respective raw

material. Now initially the ordering policy is assigned according to the value volume

matrix. The RMs falling under X ordering policy require stringent assessment as the X

ordering poses a higher risk in terms of a stock out. Hence initially the past behavior

of the raw materials variation pattern is checked using the coefficient of variation

(standard deviation ÷ average x 100) is used. The combined coefficient of variation is

the sum of coefficients of variation of consumption and lead time. If the value is less

than 50 % indicated that the consumption Variation is acceptable. However there

might be a case where in a RM shows a very little Variation in consumption but high

degree of variation in lead time but still the combined variation is bellow acceptable

limits. To negate such instances a further check is made individually on the coefficient

of variation of consumption and lead time respectively. The items which satisfy the

entire above criterion are allocated the X ordering policy.

This was done on all raw materials:

CONFIDENTIAL


Consolidated analysis of finished goods:-

Present Process :-

In finished goods store the dispatch is done according to the

customer order acceptance given by sales department and approved by finance

department. Then FGS will verify the order by checking the inventory in the store and

after completing Advance Shipment Notice is sent to the customer, Dispatch invoice is

given to the logistics department.

Classification:-

In this policy the finished goods are classified using 9 matrix cell method and

categorized according to usage and Variability of demand. They are classified into

CORE ITEMS

NON CORE ITEMS

VOLATILE

SLOB

After classifying the products decision is taken on stock inventory control of the

material based on the classification

For example:-

A,B class and L,M class products are high valued and high variable materials so

decision is taken to keep safety stock and the inventory should be in such a way that

Make to Stock and Assemble to Order can be implemented.

Below you can see the detail flow diagram of the process:

PROCEDURE FLOW CHART :-


Excel Sheet:

Adherence to planning policies & procedures helps lower productions costs and

minimizes inventory levels:

Setting clear policy on order planning and adhering to it can minimize the costs

of expedited shipments and can minimize risks to stock outs

Because of capacity planning, MAHLE will need to work with suppliers to

provide visibility to the order forecast

Demand through lead time is determined using MRP

Actual reorder quantities may vary due to supplier/manufacturing lot/batch

sizes, order modifiers, and anticipated/forecasted demand

Accurate lead times are crucial to determining the amount of inventory you will

have to order. Inaccuracies can lead to overages or shortages in inventory orders

Confidential


Recommendations:

Integration with advanced radio-frequency and bar coding technologies.

Complete back-office integration with Order Entry, Inventory Control, and

Purchase Orders modules.

Scalability to accommodate future business growth.

Real-time inventory updates.

Hand-held interface.

Advanced reporting capability.

Support for multiple picking methods.

Compliance labeling and ASNs.

Automated inventory receipt and assisted put-away.

Limitations

• The calculations have been done using the average demands from historical data.

• In case of order quantities for raw materials and packing materials the optimal truck

loading conditions have not been considered


Academic contributions

Basically this project was related to ―Inventory Management‖.

Basic inventory classification methods were used in the project

Safety stock calculation concept was applied diligently.

Periodic review model is used to control.

Concept of MTO, MTS, and ATO are used.

Excel model with numerous formulae was developed to control and examine

Inventory in the system.


Bibliography

J. R. Tony Arnold, Introduction to materials management, fifth edition,2007

James H. Greene American, Production and inventory control society,

Production and inventory control ,McGraw-Hill, January 1996

Essentials of inventory management , Max Muller

www.inventorymanagement.com

www.inventorymanagementreview.org

www.inventoryops.com

Mapedia.org

Wiley ,Excel VBA programming for dummies

Wikipedia.org

SCMOPS.com

final) sandeep

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