Inventory Classification Techniques For Effective Store Management At Milma A STUDY ON “INVENTORY CLASSIFICATION TECHNIQUES FOR EFFECTIVE STORE MANAGEMENT AT MILMA, PALAKKAD DAIRY.” MINOR PROJECT REPORT Submitted to UNIVERSITY OF CALICUT In partial fulfillment of the requirement for the award of the degree of MASTER OF BUSINESS ADMINISTRATION Submitted by ABDUL AZEEB P S (REG NO -LCAMMBA001) 3rd Semester MBA (2012-2013) LEAD COLLEGE OF MANANGEMET –DHONI, PALAKKAD Under the guidance of Mr. RAM KRISHNAN. S ASSISTANT PROFESOR LEAD COLLEGE OF MANAGEMENT – DHONI, PALAKKAD LEAD COLLEGE OF MANAGEMENT Page 1
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Inventory Classification Techniques For Effective Store Management At Milma
A STUDY ON
“INVENTORY CLASSIFICATION TECHNIQUES FOR EFFECTIVE
STORE MANAGEMENT AT MILMA, PALAKKAD DAIRY.”
MINOR PROJECT REPORT
Submitted to
UNIVERSITY OF CALICUT
In partial fulfillment of the requirement for the award of the degree of
MASTER OF BUSINESS ADMINISTRATION
Submitted by
ABDUL AZEEB P S
(REG NO -LCAMMBA001)
3rd Semester MBA (2012-2013)
LEAD COLLEGE OF MANANGEMET –DHONI, PALAKKAD
Under the guidance of
Mr. RAM KRISHNAN. S
ASSISTANT PROFESOR
LEAD COLLEGE OF MANAGEMENT – DHONI, PALAKKAD
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Inventory Classification Techniques For Effective Store Management At Milma
CHAPTER 1
INTRODUCTION
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1.1 INTRODUCTION
Stock that a firm keeps to meet its future requirement of production and sales is
called inventory. The basic reason for holding inventory is to keep up the production
activities unhampered. It is neither physically possible nor economically justifiable to wait
for the stock to arrive at the time when they are actually required. Therefore, keeping of
inventory is a must for the efficient working of a business unit. “A STUDY ON
INVENTORY CLASSIFICATON TECHNIQUE FOR EFFECTIVE STORE
MANAGEMENT AT MILMA, PALAKKAD DAIRY” is undertaken in order to know the
inventory controlling techniques for maintaining manufacturing assembly used by the
company and to know inventory performance and position of the company.
This project gives a descriptive outlook of the inventory controlling techniques used in
MILMA, PALAKKAD DAIRY. Presently the company is not using any scientific method of
inventory controlling techniques to manage the inventory. This study mainly aims at
suggesting an inventory controlling technique which will help the company to save its cost
and ensure uninterrupted production. In inventory management, differences between
physical and record inventories continuously plague industry. Methods for reducing these
variations contribute to a reduced risk of stock out, spoilage, and excessive inventory. A
greater understanding of the importance of inventory classification can help solve inventory
management problems as well as increase profitability.
The data collection of this study is done through observation conducted in material and store
department of the company. The collected data’s are analyzed and interpreted by using
simple statistical and analytical tools.
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1.2 ORGANIZATION PROFILE
The Indian dairy industry has made rapid progress since independence .A large number of
modern milk and milk products factories have been established. These organized dairies have
been successfully engaged in the routine commercial production of pasteurized milk and milk
products. India is the world’s largest milk producer that is certified by the international dairy
industry. Dairy is a place where handling of milk and milk products is done and technology
refers to the application of scientific knowledge for practical purpose. Dairy technology has
been defined as that branch of dairy science, which deals with the processing of milk and
manufacture of milk products on an industrial scale. In India, dairying has been practiced as a
rural cottage industry since the remote past. Semi-commercial dairying started with the
establishment of military dairy farms and co-operative milk unions throughout the country
towards the end of the nineteenth century. During the earlier years, each household in those
countries maintained its „family cow‟ or secured milk from its neighbor who supplied those
living closed by. As the urban population increased, fewer households could keep cow for
private use.
Gradually farmers within easy driving distance began delivering milk over
regular routes in the cities. This was the beginning of fluid milk-sheds which surround the
large cities of today. Prior to the 1850s most milk was necessarily produced within a short
distance of the place of consumption because of lack of suitable means of transportation and
refrigeration. The Indian dairy industry has made rapid progress since Independence. A large
number of modern milk plants and products factories have since been established. These
organizes dairies have been successfully engaged in the routine commercial production of
pasteurized bottle milk and various Western and Indian dairy products. With modern
knowledge of the protection of milk during transportation, it became possible to locate dairies
where land was less expensive and crops could be grown more economically. In India, the
market milk technology may be considered to have commenced in 1950, with the functioning
of the Central Dairy of Aarey Milk Colony and milk product technology in 1956with the
establishment of AMUL Dairy, Anand. The industry is still in its infancy and barely10% of
our total milk production .The most valuable resources that a dairy business can have are
reliable and productive workers. Today’s tight labor market means that workers have many
employment choices. Dairy producers need to do all they can to keep their best employees
and attract other excellent workers to their team.
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A Success story on the Dairy scene in India during the sixties was the farmer-
owned AMUL Co-operative in Anand (Kaira District, Gujarat) with is integrated approach to
production, Procurement, Processing and Marketing on Co-operative line. Over the years,
this evolved itself into a model, based on self rule by farmers ensuring maximum returns to
them. This model came to known as ‘ANAND PATTERN’. The efficiency of the Model was
worth replication. Therefore, a dairy programme called “OPERATION FLOOD’ was
launched in 1970 under the aegis of the National Dairy development Board (NDDB). NDDB
functioned as the technical consultants and the erstwhile Indian Dairy Corporation as the
funding agency. The ideology followed by “PERATION FLOOD’ was the remunerative
linking of rural milk producing centers with the urban demand centers so as to build up a
viable diary industry.
Kerala was included in the second phase of ‘Operation Flood’ (OF II 1980-
1987). The eight southern districts from Trivandrum to Trichur were included in the area of
the project which had a total outlay of Rs. 29 Crores. From 1980 KCMMF was involved in
concentrated spearhead team activities, identification of potential milk collection area,
formation of milk Co-operatives and extension activities. MILMA came into its own on 1-4-
1983 when it took over the revenue earning activities of Procurement and Marketing from the
Govt. in April1983. Encouraged by the response of (OF II), the same areas were included in
the third phase of ‘Operation Flood’ (OF III). This phase had an outlay of Rs.18 crores.
The growing popularity of the concept of Co-operativisation Section has
spurred the authorities into exploring new vistas. The uncovered northern areas from
Palakkad to Kasargode were thus brought under the Co-operative umbrella with the inception
of the NORTHE KERALA DAIRY PROJECT. This Project is funded by the Swiss
Development Co-operation through the National Dairy Development Board. The Motto of
Co-operation of “of the people, by the people and for the people” is foundation of the “three
tier system” followed by the Organization. The Power of the Producer members is felt right
from the grass root village Co-operative Society to the Board governing the State level
Federation through this system of functioning. At the village level we have the Village Milk
Co-operative Societies which have the local milk producers as its members. The Village Co-
operatives unite at Regional level to form Regional Co-operative Milk Producers’ Unions.
These Unions later federate at the State level to form State Federation.
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1.3 COMPANY PROFILE
Milma was established in April 1980 by Kerala Co-operative Milk Marketing
Federation (KCMMF). The mission of Milma is ‘Farmer’s Prosperity through consumer
satisfaction’. The objective of Milma is to build up a viable dairy industry in the State and to
provide constant market and stable price to the dairy farmers for their produce. The Malabar
Cooperative Milk Producers’ Union (MCMPU), head quartered at Kozhikode (Calicut) in
Kerala, was started in 1991. It has the 6 Northern Districts of Kerala as its area of operation
and an average milk procurement of 4 lakh litres per day. The Union operates 5 Dairy plants
and 2 Milk Chilling Centers. It has a Milk Products Dairy too. The network of Bulk Milk
Coolers is in fast expansion. Currently a BMC capacity of 2 lakh litres is in place with 75
BMCs installed in the villages. The products comprise Market milk (4 lakh litres per day),
curd (40, 000 Kg /Day), Ghee (150 MT per month), Ice-cream (1500 Litres per day), Peda
(10 MT per month), Butter milk, Milk Lollies, Sterilized flavored milk etc.
MILMA, PALAKKAD DAIRY
Palakkad dairy is one of the three dairies under Malabar Regional Co-operative Milk
producer’s Union(MRCMPU). This dairy was established in 1967 as Palakkad co-operative
milk supply union limited under Madras C-operative society.It is located in kallepully , 5
km away from Palakkad town. In 1983 Kerala Co-operative milk marketing federation.
Malabar Regional Co-operative Milk Producers’ Union (MRCMPU) Limited is a
Union of more than 1000 village level dairy co-operative societies located in the six northern
districts of Kerala State in South India and it is owned by the dairy farmers who are members
of each affiliated society and who live in the area of operation of these societies. The
societies function on the pattern of the societies affiliated to the world famous Anand Milk
Union Ltd. (AMUL) at Anand (Gujarat), India and hence are also known as Anand Pattern
Co-op Societies or “APCOS”. The area of operation of MRCMPU Ltd. comprises of the six
revenue districts of North Kerala, viz Kasaragod, Kannur, Wayanad, Kozhikode,
Malappuram and Palakkad. The Union is affiliated to the state level apex body-Kerala Co-
operative Milk Marketing Federation Ltd (Operating under the trade name MILMA) along
with its sister Unions at Ernakulam and Thiruvananthapuram. The head office of the Union is
located at Peringolam under Kunnamangalam post office near Kozhikode.
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MISSION
“Farmers prosperity through customer satisfaction”.
OBJECTIVES OF MILMA
To channelize marketable surplus from rural areas to urban deficit areas to maximize
returns to the producer and provide quality milk and milk products to the customers.
To carry out activities for promoting production, procurement, processing and
marketing of milk and milk product for economic development of farming
community.
To build up farming community
To provide constant market and suitable price to the dairy farmers for their product.
PRODUCTS
Milma–SmartMilk
Contains 1.5 percent fat and 9.0 percent non-fat solids. Ideal for elderly people since
fat content is low. Can also be used for whitening tea/coffee and for the preparation of milk
based drinks like fruit shakes. Fat will not settle at the top since the milk is homogenized.
Available in 500 ml sachets.
MilmaTonedMilk
Contains 3.0 percent fat and 8.5 percent non-fat solids. Ideal for consumption by children in
the form of milk or in the form of brown beverages like Bournvita. Fat will settle at the top if
Milk is kept still for some time. Available in 500 ml sachets.
HomogenisedTonedMilk
Contains 3.0 percent fat and 8.5 percent non-fat solids. Ideal for whitening tea/coffee and for
the preparation of solid curd. Since the milk is homogenised, whitening capacity is more and
less amount of milk will be sufficient for whitening tea/coffee. The milk will not stick to
vessels on heating and hence washing of used vessels is easier. Fat will not settle at the top
since the milk is homogenised. Available in 500 ml sachets.
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Milma-RichMilk
Contains 4.5 percent fat and 8.5 percent non-fat solids. Ideal for the preparation of payasam
and sweets. Fat will settle at the top if Milk is kept still for some time since the milk is not
homogenised. Available in 500 ml sachets.
SkimmedMilkCurd
Contains 10 percent non-fat solids. Ideal for making curries. Prepared under hygienic
conditions by fully mechanized processes. Cannot be used as starter-curd for converting milk
into curd. Available in 500 ml sachets.
Milma-Sambharam(ButterMilk)
Contains 4.5 percent total solids and natural flavour extracts. Ideal as thirst quencher during
hot season. Prepared under hygienic conditions using fully mechanized processes. Available
in 200 ml sachets.
MilmaGhee
Contains 99.7 percent milk fat. Manufactured by melting fresh cream under hygienic
conditions. Milma ghee has the ideal golden yellow color due to presence of natural carotene
in cow milk. (In contrast, ghee manufactured from buffalo milk is white in color). No
artificial colors or flavors are added in Milma ghee. Natural aroma and flavor of ghee is
retained since ghee is produced directly from fresh cream instead of going in for melting
stored butter
Milma-sipup
Contains the mixture of flavors, color powders, sugar and this mixture is added to the
milk. Flavors used are chocolate, orange, pineapple, pista etc.
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1.4 RESEARCH PROBLEM STATEMENT
Every organization faces problems with regards to the storage of inventory, due to which
certain problems like missed deliveries and lack of adequate materials etc arises. The material
and storage department of MILMA, PALAKKAD DAIRY also face such issues. When
discussion was held with concerned authority due to lack of a scientific method of inventory
controlling technique, the proper maintenance of inventory of assembly parts are difficult. So
the study was conducted with respect to inventory management technique which can be
implemented in maintaining the assembly parts of manufacturing machinery.
1.5 OBJECTIVES OF THE STUDY
1.5.1Primary Objective
To study the inventory controlling technique for assembly parts of machinery in MILMA,
PALAKKAD DAIRY.
1.5.2Secondary Objectives
To determine whether the present system of inventory management and control meet
the requirement of the organization.
To suggest and recommend a new system which could meet most of the inventory
requirement of the organization
1.6 RESEARCH METHODOLOGY
The basic concept of research methodology refers to the way in which companies conduct
their research and how they collect the data they need. Whenever a company or organization
needs to investigate a particular area of their business dealings, they need to adopt the most
suitable research methodology for the job.
The research methodology used here is descriptive research, of which the data analysis and
interpretation is done through pie charts.
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1.6.1 POPULATION TO BE STUDIED
The population to be studied here is the total assembly items ranging around 30 in numbers.
1.6.2 SAMPLING PROCESS
Sampling process used here is convenient sampling,
1.6.3 DATA COLLECTION METHOD
Data collection method is unstructured questioner and unstructured interview with the
officials and data from the records.
1.6.3.1 (A) Primary data
The primary data is collected through observations and unstructured interview with the
officials.
1.6.3.2 (B) Secondary data
The secondary data is from the files, annual reports, journals, text book, internet websites and
other records. Which have already passed through the statistical process are the secondary
data used.
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1.7 SCOPE OF THE STUDY
The overall study can prove or make an outcome which would be helpful in the future for
inventory management of MILMA, PALAKKAD DAIRY. The scientific inventory
management techniques for keeping the assembly parts will always justify the flow of
operations of all the machines without fail. The study makes it easy for the management to
concentrate on the assembly parts which has to be always kept in inventory and which is of
least botheration.
1.8 LIMITATION OF THE STUDY
The primary and major limitation of the study was the time period allotted for the
study which was only 21 days for any research it would have been insufficient, but
still the study has been done to the best of the available time.
The study is related to MILMA, PALAKKAD DAIRY. Only of which no other
population is considered.
The findings and suggestions cannot be generalized due to the presence of trade union
and other things.
The study covered a wide concept hence wide collection and coverage of information
was not easily possible.
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CHAPTER 2
REVIEW OF LITERATURE
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INVENTORY CLASSIFICATION
Every management problem is a decision problem. Decision is an important
task that all organization has to take. The allocation of resource is a common issue to all
organizations. Organizations have to acquire, allocate and control the factors of production
which are necessary for the achievement of the business’s objectives. Inventory management
as one of the key activities of business logistics, has always been a major pre occupation of
the company’s survival and growth.
Hugo, Bandenhorst-weiss and Van Rooyen (2002): The aim of inventory management is to
hold inventories at the lowest possible cost, given the objectives to ensure uninterrupted
supplies for ongoing operations. When making decision on inventory, management has t find
a compromise between the different cost components, such as the cost of supplying
inventory, inventory holding costs and costs resulting from insufficient inventories.
Ballou (2004): “Inventories are stockpiles of raw materials, suppliers, components, work in
process, and finished goods that appear at numerous points throughout a firm’s production
and logistics channel”
Chase, Jacobs and Aquilano( 2004):Inventory is the stock of any item or resource used in
an organization.
Wild (2002): Inventory control is the activity which organizes the availability of items to the
customers. It coordinates the purchasing, manufacturing and distribution functions to meet
the marketing needs. This role includes the supply of current sale items, new products,
consumables, spare parts, obsolescent items and all other supplies. Inventory enables
accompany to support the customer service, logistic or manufacturing activities in situations
where purchasing or manufacturing of the items is not able to satisfy the demand. Lack of
satisfaction could arise either because of the speed of purchasing or manufacturing is too
protracted, or because quantities cannot be provided without stock.
Gordon Carson: "Inventory control is the process whereby the investment in materials and
parts carried in stocks is regulated, within pre-determined limits set in accordance with the
inventory policy established by the management”.
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Richard Pibernik, (2004): In his study “Advanced available-to-promise: Classification,
selected methods and requirements for operations and inventory management” gives the
theoretical framework for the development of models and algorithms supporting order
quantity and due date quoting. At first, alternative generic AATP systems will be identified
on the basis of relevant classification criteria. Based upon this classification, the AATP
planning mechanisms will be detailed for two generic AATP types. On the basis of the
introduced AATP types and the description of selected models we finally derive
requirements, which operations and inventory management have to meet in order to ensure a
successful application of AATP.
Huiskonen (2001): “ The classification of inventory is an essential part of the inventory
management systems, in order to :i) determine the adequate level of managerial attention; ii)
allow the choice of demand forecasting and inventory control methods; and iii) establish
different performance goals at the inventory turnover and service levels between categories.
However, most of the surveyed works use the classification of parts only to choose the
demand forecasting model instead of the inventory control method.”
Zimmerman, (1975): Vilfredo Pareto was an Italian economist who studied wealth and
income. He realized that only 10% of the population held 90% of the wealth. The value of
this realization went unrecognized until the 1930's. In the 30's, the scientific community
applied this principle to inventory management. The similarities between the distribution of
wealth and inventory item value distributions are striking. The value of a small number of
inventory items consume most of the inventory's value, this is the underlying theme of the
ABC principle. Pareto's principle implies that the money saved controlling the lower value
items is available for the management of high value items. Companies which disregard this
simple principle usually encounter a cyclical inventory pattern. This pattern has two
elements: Part 1 – To avert another stock out, management spends a lot of money on
preventive measures. Part 2 – Management’s concern about increased inventory costs sparks
an across the board cost reduction. This cyclical pattern pushes the company into a downward
spiral. To bypass this inventory scenario, managers should categorize inventory into “vital
few” and “trivial many” groups, and concentrate inventory control efforts on the “vital few.”
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Flores and Whybark (1986, 1987):
The traditional ABC classification has generally been based on just one criterion – the annual
dollar usage of the items. However, depending on what part of the organization is concerned;
the criterion of what is most important with respect to inventory items can change .There are
other criteria that represent important considerations for management such as lead time,
obsolescence, availability, substitutability, criticality, reparability, commonality, certainty of
supply, impact of stock-out, inventory cost, number of requests for the item in a year,
scarcity, durability, order size requirement, stock ability, and demand distribution.
Partovi and Anandarajan (2002):
Cohen and Ernst used a statistical technique called cluster analysis to group items across
many dimensions. The main advantage of this approach is that it can accommodate a large
number of combinations of attributes, which are significant for both strategic and operational
reasons. However, this requires substantial data and the use of factor analysis and a clustering
procedure may render this technique impractical in a typical stockroom environment.
Furthermore the clusters themselves must be re-evaluated in order to classify new stock
items. Therefore, there is a chance that previously classified stock may end up being
reclassified differently every time new items are added. This may disturb the inventory
control procedure. In short, their method may pose difficulties for inventory managers.
Partovi & Burton (1993): Proposed a classification method for ABC analysis using the
Analytic Hierarchy Process. In the model, inventory items are ranked based on several
criteria, with weights assigned to each criterion. The three basic steps for this process are (1)
the description of a complex decision problem as a hierarchy, (2) the use of pair-wise
comparisons to estimate the relative weight (importance) of the various elements on each
level of the hierarchy, and (3) the integration of these weights to develop an overall
evaluation of decision alternatives. However, when the number of criteria is increased, the
consistency rate will be very sensitive and reaching a consistent rate will be very difficult.
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Guvenir and Erel (1998): Proposed a method to learn the weight vector along with the cut-
off values for multi-criteria inventory classification. The proposed method called genetic
algorithm for multi-criteria inventory classification (GAMIC) used a genetic algorithm to
learn the weights of criteria along with AB and BC cut-off points from pre-classified items.
Once the criteria weights are obtained, the weighted scores of the items in the inventory are
computed similarly to the approach with AHP. Then the items with scores greater than the
AB cut-off value are classified as class A; those with scores between AB and BC as class B;
and the remaining items are classified as class C. This method had the advantages and
disadvantages of the AHP method. In addition, the classification results, to some extent,
depended on the pre-classified items.
Puente et al. (2002): Presented a fuzzy method of classifying different productive items of a
company. Whereas the rankings obtained using the classical method were based on
information about costs and demand over a period of time in the past. This new method
allowed new fuzzy information about the future to be included, thus allowing stricter control
of the fuzzy ‘A-items’ that resulted from this new classification. The authors, however, only
considered two criteria of demand and cost in their study. The authors’ model was in fact a
bi-criteria rather than a multi-criteria model.
Partovi (2002): Presented an artificial neural network for ABC classification of inventory.
They utilized two learning methods in their approach: back propagation and genetic
algorithm. The reliability of their proposed methods was tested by comparing their
classification ability with two data sets. The methods were compared with the multiple
discriminant analysis technique. Their results showed that both proposed methods had higher
predictive accuracy than discriminant analysis. There was no significant difference between
the two learning methods used to develop the artificial neural network. However, the
application of these methods could become cumbersome for inventory managers.
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Scholz-reiter, Bernd Heger,(2012): Inventory classification based on ABC-XYZ analysis is
of high importance for strategic supply and inventory control. It is common to perform the
analysis with past consumption data. In this context, the purpose of this study is to test
hypothesis that an integration of demand forecasts can improve the performance of item
classification, in particular the performance of ABC-XYZ analysis.
Design/methodology/approach- For the study, real data of an industrial enterprise in the
mechanical engineering sector (focal company) were analyzed and evaluated .Findings – The
study shows that a comprehensive data analysis of the focal company can recommend a
specific implementation of the ABC-XYZ classification. In contrast to the classic method of
making the ABC-XYZ analysis based on consumption data only, the approach developed in
this paper offers considerable advantages. These are quantifiable in respect to an assumed
optimal reference classification. Originality/value- The evaluation of the results is very
promising and applicable to other branches besides mechanical engineering.
Bhattacharya, Arijit sarkar, Bijan, (Aug2007): A distance based multi criteria consensus
framework on the concepts of ideal and negative ideal solutions is presented for the ABC
analysis of inventory items. This article demonstrates a way of classifying inventory items
using the TOPSIS (Technique for order preference by similarity to ideal solution) model. The
methodology has been applied in a pharmaceutical company located in the heart of Kolkata,
India. The technique takes into account various conflicting criteria having incommensurable
units of measurement. Unit costs, lead time, consumption rate, perishability of items and cost
storing of raw materials have been considered for the case study. By using TOPIS, the items
are ranked in categories A, B, and C. The suitability, practicability and effectiveness of the
TOPIS method used in ABC classification have been judged using the analysis of variance
(ANOVA) technique. A simulation model has been used to compare the proposed model with
that of the traditional ABC classification technique.
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Huiskonen and Boyl (2001): The items classification is an essential part of the inventory
management systems, in order to: i)determine the adequate level of managerial attention;
ii)allow the choice of demand forecasting and inventory control methods; and iii)establish
different performance goals at the inventory turnover and service levels between categories.
However, most of the surveyed works use the classification of parts only
to choose the demand forecasting model instead of the inventory control method