Upload
sandeep-anantha
View
98
Download
6
Embed Size (px)
Citation preview
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
National Institute of Industrial Engineering, Mumbai Page | 3
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
National Institute of Industrial Engineering, Mumbai Page | 4
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
National Institute of Industrial Engineering, Mumbai Page | 5
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.
National Institute of Industrial Engineering, Mumbai Page | 6
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
National Institute of Industrial Engineering, Mumbai Page | 7
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
National Institute of Industrial Engineering, Mumbai Page | 8
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
National Institute of Industrial Engineering, Mumbai Page | 9
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
National Institute of Industrial Engineering, Mumbai Page | 10
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.
National Institute of Industrial Engineering, Mumbai Page | 11
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.
National Institute of Industrial Engineering, Mumbai Page | 12
MAHLE Filter Systems (India) Limited:-
Structure & background : Manufacturing Plants
Joint Venture in April 2005
National Institute of Industrial Engineering, Mumbai Page | 13
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 :-
National Institute of Industrial Engineering, Mumbai Page | 14
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
National Institute of Industrial Engineering, Mumbai Page | 15
Product Types: Filters
Sales Data (in Million USD )
National Institute of Industrial Engineering, Mumbai Page | 16
MAJOR PRODUCTS AND CUSTOMERS PER REGION
National Institute of Industrial Engineering, Mumbai Page | 17
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.
National Institute of Industrial Engineering, Mumbai Page | 18
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
National Institute of Industrial Engineering, Mumbai Page | 19
Understanding present process
“As is” process :-
National Institute of Industrial Engineering, Mumbai Page | 20
“TO be” process:-
National Institute of Industrial Engineering, Mumbai Page | 21
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
National Institute of Industrial Engineering, Mumbai Page | 22
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
National Institute of Industrial Engineering, Mumbai Page | 23
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
National Institute of Industrial Engineering, Mumbai Page | 24
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
National Institute of Industrial Engineering, Mumbai Page | 25
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
National Institute of Industrial Engineering, Mumbai Page | 26
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…
National Institute of Industrial Engineering, Mumbai Page | 27
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
National Institute of Industrial Engineering, Mumbai Page | 28
Devising Safety & Cycle Stock:-
The General Periodic order review model
National Institute of Industrial Engineering, Mumbai Page | 29
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
National Institute of Industrial Engineering, Mumbai Page | 30
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.
National Institute of Industrial Engineering, Mumbai Page | 31
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.
National Institute of Industrial Engineering, Mumbai Page | 32
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
National Institute of Industrial Engineering, Mumbai Page | 33
Methodology:- .
Excel sheet:-
National Institute of Industrial Engineering, Mumbai Page | 34
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
National Institute of Industrial Engineering, Mumbai Page | 35
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 :-
National Institute of Industrial Engineering, Mumbai Page | 36
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
National Institute of Industrial Engineering, Mumbai Page | 37
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
National Institute of Industrial Engineering, Mumbai Page | 38
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.
National Institute of Industrial Engineering, Mumbai Page | 39
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.
National Institute of Industrial Engineering, Mumbai Page | 40
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
National Institute of Industrial Engineering, Mumbai Page | 41
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
National Institute of Industrial Engineering, Mumbai Page | 42
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 :-
National Institute of Industrial Engineering, Mumbai Page | 43
National Institute of Industrial Engineering, Mumbai Page | 44
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
National Institute of Industrial Engineering, Mumbai Page | 45
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
National Institute of Industrial Engineering, Mumbai Page | 46
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.
National Institute of Industrial Engineering, Mumbai Page | 47
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