Project Presentation@MAHLE Pune

8/2/2019 Project Presentation@MAHLE Pune

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Formulation of Inventory Control strategies for Raw materialstore (RMS) and Finished Goods Store (FGS)

By :-

Sandeep,ANAPGDIE 40,NITIE,Mumbai


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ROAD MAP

Problem statement

Deliverables

Methodology

Analysis of RM

Analysis of FGS

Recommendations

Limitations


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Problem statement

Need: Highly competitive environment

Squeezed profit margins

Essential to maintain the supply chain surplus

Need for efficient inventory management system

Problem Statement :

To set up inventory norms for Raw Materials (RM) and Finished Goods (FG), andmake necessary amendments. The rationale behind this exercise is to ensure a

more accurate control on inventory when the production and schedulingprocesses is initialized.


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Deliverables

Propose Optimum inventory levels and with safety stock for all the child

parts at RMS

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


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Methodology

Understanding Existing Processes

Data Collection

Analysis of Data

Inventory Classification

Devising Safety and Cycle Stock

Formulating Ordering Policies

Simulation

Recommendations


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Analysis of RMS

Inventory classification

ABC analysis of raw materials

HML analysis of raw materials

Inventory Analysis by 9 Matrix Cell approach

Inventory model

Devising Safety Stock for RM

Calculating Cycle Stock for RM

Methodology for allocating ordering policy


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Inventory classification:

ABC Value analysis of raw materials

Consumption dataform jan 10 to Dec

2010

Consumption dataform Jan 10 to Dec2010consumption

value= quantityconsumed x unit cost

Ranking the RMbased on

consumption value

Categorising the RMsbased on decided

cutoffs

Methodology:-

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

setting the inventory control for them is essential

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

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

class C ABC Value analysis accounts for Inventory cost reduction issues


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ABC Volume analysis of raw materials

Methodology:-

For the classification the consumption (Quantity) data from Jan 2010 to Dec 2010 was

used.

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

class C

ABC Volume analysis accounts for Space constraint issues

Consumption dataform jan 10 to Dec

2010

Consumption dataform jan 10 to Dec2010 quantity

consumed

Ranking the RMbased on

consumption

Categorising theRMs based ondecided cutoffs


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HML analysis of raw materials

Methodology:-

Low variabilityitems will be predictable and easier to forecast with accuracy

Medium variabilityitems are relatively predictable but show larger swings

High variabilityitems contain the largest swings in demand and highest risk

Variability classification:-

Low = Std .dev sales/ Average Consumption


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Inventory Analysis by 9 Matrix Cell approach

Segments inventory by value and risk

Enables targeted inventory strategy and policy development

To calculate the inventory for Class A and B with LOW and MEDIUM variability and stock

them effectively.

To filter the C class with items whether they are SLOW MOVING and then stock them based

on the calculated values

Analyze the CLASS A and B with HIGH variability and work on action to improve theconsumption pattern


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Inventory model

The General Periodic order review model :-


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Devising Safety Stock for RM

Safety Stock accounts for

-- Uncertainty in production lead times

-- Unknown customer demand

-- Uncertainty in Supplier lead times

Benefits :-

Allows quick customer service

Avoid lost sales

Avoid Emergency shipments

Good will of customers

Formulae:-

Safety stock (in quantity) = (CSL) x SQRT (D2.LT + lt

2.D2)

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


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Capturing Demand Variability

Capturing Demand:- Historic consumption data from Jan 2010 to Dec 2010 was taken to estimate theaverage consumption 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.

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


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Normalization

Need:- Normalization is done to get a true picture of the consumption variation to calculate

accurate safety stock value.

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

Methodology:- .


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Example

A raw material "O"RING-2557(MTJ P.NO.K1086-101-1640) (1864012557) is taken to

demonstrate the normalization process.

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

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 theconsumption variation for the respective parameter. This is D in the safety stock

formulae.


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Capturing Supply Variability

Procurement dataform jan 2010 -Dec

2010

Lead time assumedbased on location

lead time variationis assumed to be 20

%

lead time= Externallead time+ PO

generation time+QC time

Methodology:-

Lead time is taken based on supplier

locations

Lead time variation is assumed to be 20 %


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Calculating Cycle Stock for RM

Model of periodic review

Cycle stock is equivalent to the lead time of the

respective raw material


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Methodology for allocating ordering policy

The X axis indicates the category in which the RM falls

based on the ABC value analysis

The Y axis is the Volume class of the RM based on the

consumption based ABC Volume analysis

The idea of the above matrix is

-- 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

X ordering policy: Order quantity would be to bring the stock on hand equal to (Cycle stock + 7+

safety stock) number of days. Here order would be generated at the end of every review period

Y ordering policy: Order quantity would be to bring the stock on hand equal to (2 x Cycle stock +

7+ safety stock) number of days. Here order would be not be generated at the end of every review

period


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Methodology for ordering policies

Calculate 7 day demand forrespective RM

IF Y then Freeze itIF X calculate combined

coefficient of variation=cof.Variation consumption+ cof.variation lead time

If combine cof. variation < 50%assign X else Y

IF Y FREEZEIF x then check if cof. variationconsumption


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Analysis of FGS


Classification of finished goods

Variability of Demand vs. Usage Analysis

Stocking methods

Formulating Strategies for stocking

Adherence to planning policies


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Dispatch process

Customer order acceptance by Sales department and approved by Finance department.

Verification the order by checking the inventory

Advance Shipment Notice to customer

Dispatch invoice generated to the Logistics department.

-- Paid freight

-- Customer freight

Generation of L.R.no


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Classification of Finished Goods

Classification is done using 9 matrix cell method and the goods are classified accordingly

CORE ITEMS - Goods with high value (i.e A,B) and Low and Medium variability

NON CORE ITEMS Goods with Low value (i.e C) and Low and Medium variability

VOLATILE Goods with high value (i.e A) and High variability

SLOB Goods with Low value (i.e C) and High variability

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

based on the classification


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Stocking methods

Based on processing Lead time we have 3 ways of stocking options i.e

MTS Make to stock -

ATO Assemble to order -

MTO Make to order -

Order receipt+ pick+ transit +

Receiving time

Order receipt+ assembly + transit

+ Receiving time

Order receipt+ Build+ transit +

Receiving time


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Formulating Strategies for stocking

CORE ITEMS - Safety Stock + MTO+ATO

NON CORE ITEMS No safety stock + Monthly replenishments

VOLATILE No safety stock +MTO+ May require further review

SLOB No safety stock


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Adherence to planning policies

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


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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.


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Limitations

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


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