The Response Surface Methodology Engineering Essay

 

In previous chapter, the working most important of milling machine, machining parameters which affect the surface roughness, chip thickness formation and factors influence surface roughness in milling machine has been discussed. This chapter gives the detailed overview of response surface methodology with its arithmetical background.

Response Surface Methodology (RSM) is a collection of statistical and geometric techniques useful for developing, improving, and optimizing processes [23].The most far-reaching applications of RSM are in the particular situations whas several input variables potentially influence some performance determine or quality characteristic of the process. Thus performance measure or superiority characteristic was called the response. The input variables are sometimes called self-determining variables, and they are subject to the control of the scientist or engineer. The field of response surface methodology consists of the investigational strategy for exploring the space of the process or independent variables, empirical geometric model to develop an appropriate approximating relationship between the yield and the process variables, and optimization methods for ruling the values of the process variables that produce desirable values of the response.

In this thesis, the concentration on the numerical modeling to develop an apposite approximating model between the response y and self-determining variables

In general, the relationship is

………………………………….………. (3.1)

where the form of the accurate response function f is unknown and perhaps very complicated, and e is a term that represent other source of variability not accounted for in f. Usually e includes possessions such as measurement slip-up on the response, background noise, the effect of other variables, and so on. Usually e is treated as a statistical error, often high and mighty it to have a normal

distribution with mean zero and variance s2 . Then

…… (3.2)

The variables in Equation (3.2) are usually called the accepted variables, because they are expressed in the natural units of measurement, such as degrees Celsius, pound per square inch, etc. In much RSM work it is convenient to make over the natural variables to coded variables, which are usually defined to be dimensionless with connote zero and the same standard deviation. In terms of the coded variables, the response function (3.2) will be written as

? = f ) ……………………………………………………(3.3)

Because the form of the true response function f is unknown, we must ballpark it. In fact, successful use of RSM is critically dependent upon the experimenter’s ability to extend a suitable rough calculation for f. usually, a low-order polynomial in some relatively small region of the independent variable space is apposite. In many cases, either a first-order or a second-order reproduction is used. The first-order model was likely to be appropriate when the experimenter is interested in approximating the true response surface over a comparatively small region of the independent variable space in a location where there is little curvature in f. For the glasses case of two independent variables, the first-order model in requisites of the coded variables is

? = ß0 + ß1x1 + ß2x2…………………………………………...…..….. (3.4)

The form of the first-order model in Equation (3.4) is every now and then called a main effects model, because it includes only the main effects of the two variables x1and x2 . If there is an interaction between these variables, it can be added to the model without problems as follows:

? = ß0 + ß1x1 + ß2 x2+ ß12 x1x2……………………………………….. (3.5)

This is the first-order model with communication. Adding the interaction term introduces curvature into the response function. Often the curvature in the accurate response surface is strong enough that the first-order model (even with the interaction term included) is laughable A second-order model will unlikely be required in these situations. For the case of two variables, the second-order model is

? = ß0 + ß1x1 + ß2 x2+ ß11 + ß22 + ß12 x1x2……………………… (3.6)

This model would likely be useful as an rough calculation to the true response surface in a relatively small region. The second-order model is widely second-hand in response surface methodology for several reasons:

The second-order model is very flexible. It can take on a wide variety of well-designed forms, so it will often work well as an rough calculation to the true response surface.

It is easy to educated guess the parameters (the ß’s) in the second-order model. The method of least squares can be used for this purpose.

There is considerable practical experience indicating that second-order models work in good health in solving real response surface problems.

In general, the first-order model is

? = ß0 + ß1x1 + ß2x2+…+ ßkxk…………………………………………(3.7)

and the second-order model is

? = ß0 + + + ………...………..(3.8)

In some frequent situations, approximating polynomials of order greater than two are used. The general motivation for a polynomial approximation for the correct response function f is based on the Taylor series development around the point x10, x20,……….xk0

Finally, let’s note that there is a close connection between RSM and linear regression analysis. For example, consider the model

? = ß0 + ß1x1 + ß2x2+…+ ßkxk +e………………………………….…(3.9)

The ß’s are a set of mysterious parameters. To estimate the values of these parameters, we must collect data on the system we are studying. Because, in wide-ranging, polynomial models are linear functions of the unknown ß’s, we pass on to the technique as linear regression analysis.

RSM is an important branch of experimental design. RSM is a critical equipment in developing new processes and optimizing their performance. The objectives of inferiority improvement, including reduction of variability and improved process and merchandise performance, can often be accomplished directly using RSM. It is well known that deviation in key performance distinctiveness can result in poor process and product quality. During the 1980s [2, 3] considerable attention has given to process superiority, and methodology was developed for using investigational design, specifically for the following:

For designing or developing products and process so that they are robust to component variation.

For minimizing variability in the output response of a product or a progression around a target value.

For designing products and processes so that they are full-bodied to environment conditions.

By robust means that the product or process performs consistently on target and is moderately insensitive to factors that are difficult to control. Professor Genichi Taguchi [24, 25] used the term robust parameter design (RPD) to describe his approach to this imperative problem. Essentially, strong parameter design methodology prefers to reduce process or product variation by choosing levels of controllable factors (or parameters) that make the arrangement insensitive (or robust) to changes in a set of out of control factors that represent most of the source of variability. Taguchi referred to these uncontrollable factor as noise factors. RSM assumes that these noise factors are disobedient in the field, but can be controlled during process development for purposes of a designed conduct test

Considerable attention have been focused on the methodology advocated by Taguchi, and a number of flaws in his approach have been exposed. However, the framework of response surface methodology allows without problems incorporate many useful concepts in his philosophy [23]. There are also two other full-length books on the area under discussion of RSM [26, 27]. In our technical report we are determined mostly on building and optimizing the empirical models and practically do not consider the problems of investigational design.

Most applications of RSM have sequential in nature. At first some ideas are generate with reference to which factors or variables are likely to be important in response surface study. It is usually called a screening experiment. The objective of aspect screening is to reduce the list of contender variables to a relatively few so that subsequent experiments will be more efficient and require fewer runs or tests. The purpose of this phase is the identification of the imperative self-regulating variables.

The experimenter’s objective is to determine if the current settings of the self-determining variables result in a value of the response that is near the optimum. If the modern settings or levels of the self-determining variables are not consistent with optimum performance, then the experimenter must conclude a set of adjustments to the process variables that will move the process toward the optimum. This phase of RSM makes significant use of the first-order model and an optimization technique called the method of steepest gradient (descent).

Phase 2 begins when the process was near the optimum. At this point the experimenter usually wants a model that will accurately approximate the accurate response function within a relatively small region approximately the optimum. Because the true response surface usually exhibit curvature near the optimum, a second-order model (or perhaps some higher-order polynomial) should be used. Once an appropriate reminiscent of model has been obtained, this model may be analyzed to determine the optimum conditions for the process. This in order experimental process is usually perform within some region of the independent variable breathing space called the operability region or experimentation region or region of concentration

Multiple linear regression (MLR) is a method second-hand to model the linear relationship between a dependent variable and one or more autonomous variables. The dependent changeable is sometimes also called the predicted, and the independent variables the predictors. MLR is based on least squares: the representation is fit such that the sum-of-squares of differences of experimental and predicted values is minimized. The relationship between a set of independent variables and the response y is strong-minded by a mathematical model called regression model. When there are additional than two independent variables the regression model is called multiple-regression model. In general, a multiple-regression model with q independent changeable takes the form of

Yi = ß0 + ß1xi1 + ß2xi2 + ……………. + ßqxiq + ei (i = 1, 2, ………, N)

Yi = ß0 + jxij + ei ( j= 1, 2,………,q)

Where n > q. The parameter ßi measures the probable change in response y per unit increase in xi when the other independent variables are held unvarying. The ith observation and jth level of independent variable is denoted by xij. The data organization for the multiple regression model is shown in Table 3.5.

Table 3.1: Data for Multiple-Regression Model

y x1 x2 ….. xq

y1 x11 x12 ….. x1q

y1 x11 x12 ….. x1q

yn xn1 xn2 ….. xnq

Box-Behnken designs has rotatable designs that also fit a full quadratic model but use just three levels of both factor. Design-Expert offers Box-Behnken designs for three to seven factor These designs have need of only two levels, three levels, coded as -1, 0, and +1. Box and Behnken created this design by combine two-level factorial designs with incomplete building block designs. This procedure creates designs with desirable arithmetical properties, but, most importantly, with only a fraction of the experiment needed for a jam-packed three-level factorial. These design offer limited blocking options, apart from for the three-factor version.

Box-Behnken designs necessitate that a lower number of actual experiments be performed, which facilitates probing into probable interactions between the parameters studied .Box- Behnken is composed of a spherical, gyrating design. It consists of a central point and the middle points of the edges of a cube hemmed in on a sphere. It contains three interlocking factorial designs and a central point. In the absent work, the two-level, three-factorial Box-Behnken experimental design is applied to consider process parameters

3.1.5 Analysis of Variance (ANOVA)

The purpose of the statistical analysis of variance (ANOVA) is to consider which design parameter significantly affects the Surface Roughness. Based on the ANOVA, the qualified magnitude of the machining parameters with respect to Surface Roughness is investigated to determine more accurately the best possible combination of the machining parameters.

Analysis of variance (ANOVA) uses the same intangible framework as linear regression. The main difference comes from the nature of the illuminating variables: instead of quantitative, here they are qualitative. In ANOVA, instructive variables are often called factors. If p is the number of factor, the ANOVA model is written as follows:

Yi=ßo + ………………………………………………… (3.1)

Where yi is the value experimental for the dependent variable for observation i, k(i,j) is the index of the grouping of factor j for observation i, and ei is the error of the model. The hypothesis used in ANOVA are identical to those second-hand in linear regression: the errors ei follow the same normal distribution N (0, s) and are independent.

The way the model with this suggestion added is written means that, within the framework of the linear regression model, the y is had the expression of random variables with stand for µi and variance s², where

+ k(I,j),j ……………………………………………...….(3.2)

To use the various tests proposed in the results of linear regression, it is not compulsory to check on second thoughts that the underlying hypotheses have been correctly verified. The normality of the residues can be tartan by analyzing certain charts or by using a normality test. The independence of the residues can be checked by analyze certain charts or by using the Durbin Watson assessment.

Interactions: By interaction was meant an artificial factor (not measured) which reflect the interaction between at least two calculated factors. To make a parallel with linear regression, the interactions are equivalent to the products between the permanent explanatory values although here obtaining interactions requires nothing more than simple multiplication between two variables. However, the information used to represent the interaction between factor A and factor B is A*B. The interactions to be used in the representation can be easily defined in DOE++ software.

Nested effects: When constraints thwart us from crossing every level of one factor with every level of the other factor, nested factor can be used. We say we have a nested effect when smaller number than all levels of one factor occur within each level of the other factor. An example of this might be if we want to study the effects of similar machines and different operators on some output characteristic, but we can't have the operators revolutionize the machines they run. In this case, each operator is not cross with each machine but rather only runs one machine. DOE++ software has an automatic device to find nested factors and one nested reason can be included in the model.

Balanced and unbalanced ANOVA: We talk of balanced ANOVA when for each one factor (and interaction if available) the number of observations within each category is the same. When this is not true, the ANOVA is said to be unbalanced. DOE++ software can handle mutually cases.

Random effects: Random factors can be included in an ANOVA. When some factor are supposed to be accidental, DOE++ software displays the expected mean squares table.

Constraints: During the calculations, each factor was broken down into a sub-matrix containing as many column as there had category in the factor. Typically, this is a full disjunctive table. Nevertheless, the stop working poses a problem: if there are g categories, the rank of this sub-matrix is not g but g-1. This leads to the prerequisite to delete one of the columns of the sub-matrix and possibly to make over the other columns. Several strategies are available depending on the elucidation we want to make afterwards:

a1=0: the parameter for the first grouping is null. This choice allows us force the effect of the first category as a ordinary In this case, the constant of the model is equal to the indicate of the dependent variable for group 1.

an=0: the parameter for the last category is null. This choice allows us force the effect of the last category as a ordinary. In this case, the constant of the model is equal to the mean of the dependent variable for group g.

Sum (ai) = 0: the sum of the parameters is null. This choice forces the unvarying of the model to be equal to the mean of the dependent variable when the ANOVA is balanced.

Sum (ni.ai) = 0: the sum of the parameters is unfounded This choice forces the constant of the model to be equal to the mean of the needy variable even when the ANOVA is unbalanced.

Note: even if the choice of constraint influences the values of the parameters, it have no effect on the predicted values and on the different fitting information.

Multiple Comparisons Tests: One of the main applications of ANOVA is multiple comparison testing whose aim is to confirm if the parameters for the various categories of a factor differ extensively or not. For example, in the case where four treatments are applied to plants, we want to know not only if the treatments have a significant effect, but also if the treatment have dissimilar effects. Numerous tests have been proposed for compare the means of categories. The majority of these tests assume that the sample is more often than not distributed. DOE++ software provides the main tests counting

Summary of the variables selection: Where a collection method has been chosen, DOE++ software displays the selection summing up. For a stepwise selection, the information corresponding to the similar steps are displayed. Where the best model for a number of variables varying from p to q has been selected, the unsurpassed model for each number or variables is display with the analogous statistics and the best model for the decisive factor chosen is displayed in bold.

Observations: The number of explanation used in the calculations. In the formulas shown below, n is the number of observations.

Sum of weights: The sum of the weights of the observations second-hand in the calculations. In the formula shown below, W is the sum of the weights.

DF: The number of degrees of freedom for the preferred model (corresponding to the error part).

R²: The strength of mind coefficient for the model. This coefficient, whose value is between 0 and 1, is only displayed if the constant of the representation has not been fixed by the user. Its value is defined by:

- , where =

The R² is interpret as the proportion of the variability of the dependent variable explained by the model. The nearer R² is to 1, the better is the model. The predicament with the R² is that it does not take into financial credit the number of variables used to fit the model.

Adjusted R²: The adjusted strength of mind coefficient for the model. The adjusted R² can be negative if the R² is near to zero. This coefficient is only calculated if the constant of the reproduction has not been fixed by the user. Its value is defined by:

The adjusted R² is a correction to the R² which takes into description the number of variables used in the model. The analysis of variance table is used to appraise the explanatory power of the explanatory variables. Where the irregular of the model is not set to a given value, the explanatory power is evaluated by compare the fit (as regards least squares) of the final model with the fit of the elementary model including only a constant equal to the mean of the dependent variable. Where the constant of the model is set, the assessment is made with respect to the model for which the dependent variable is equal to the unvarying which has been set.

The predictions and residuals table shows, for each observation, its weight, the value of the qualitative illustrative variable, if there is only one, the observed value of the dependent variable, the model's prediction, the residuals, the self-confidence intervals together with the fitted prediction and Cook's D if the corresponding options have been activate in the dialog sachet. Two types of confidence interval are displayed: a confidence interval in the order of the mean (analogous to the case where the prediction would be made for an infinite number of observations with a set of given values for the illustrative variables) and an interval around the isolated prediction (analogous to the case of an isolated prediction for the values given for the explanatory variables). The second distance is always greater than the first, the random values being larger.

In this chapter, the detailed overview of response surface methodology is presented. The mathematical background of RSM is presented. The various types of RSM methods like, Box-Benken Design, Multiple regression and ANOVA model are described.

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Methodology Is To Describe The Research Procedure Marketing Essay

Research methodology overall includes the research design, data collection method and analysis procedure which are used to explore the insight information from the research problem.

Research methodology helps in carrying out the project report in by analysing the various research findings collected through the data collection methods.

Research design is an important and the vital part of the research. Research design is a comprehensive master plan specifying the procedure for collecting and analyzing the needed information. Research design provides an excellent framework for the research plan of action. The function of the research design is to ensure that the required data is in accordance; research design is a blue print for the research study, which guides research in collecting and analyzing the data.

Here in the project I have used two type of research design.

1. Exploratory Research Design

2. Conclusive Research Design

Exploratory research design helps the researcher in getting the insight information from the research problem. Generally all the marketing research is done with help of this design as it provides sharp focus of the problem under research. Exploratory research lays emphasis on the discovering of ideas and possible insight to get the information needed to carry out the research. This has been used in the research design for project under study.

Conclusive research design is the design, which helps the researcher in studying the research problem in the conclusive form; this helps the researcher in choosing the possible cause of action from various alternatives to make a rational design. Hence this type of research has being used in this research project.

The success of any project or market survey depends heavily on the data collection and analysis. It is necessary that the data collected is a reliable data in order to achieve the research objective. All data sources can be classified into two:

Primary Data

Secondary Data

Primary data is the data, which are fresh and collected for the first time, and are original in character. There are various Primary Data Collection techniques, which have helped in data gathering.

Secondary data are those data, which have been already collected or published for the purpose other than specific research need at hand. This data is simply used up by the researcher for his purpose of collected data and it’s used for the same purpose. The secondary data sources here in this project are:

Websites

Books

The retail store is the place where customers take a decision on the purchase of the products offered by the retailer. The store also influences the perception that customers form in their minds about the store, the products services and staff. Therefore from management’s point of view, operations of the store are a major element of costs. Therefore store becomes a critical asset of the retail business and it is imperative that the operations are managed well to achieve and sustain customer satisfaction and be cost effective.

Managing store operations for a retail business is a challenging task. It requires integration among various functions within the store. When all the functions are performed in an integrated manner then only the store can run smoothly achieving full customer satisfaction.

The retail store becomes of prime importance to the retail organisation, for basically two reasons.

Retail store is the primary source for revenue for the retailer.

It is the point where the customer actually interacts with the retail store and its offering.

The primary responsibility within the environment of a retail store lies with the Store Manager.

Each and every process taking place in the store is defined in the Store Operations Manual. This document lists the tasks which need to be carried out at the store level; it states the responsibility and the time period in which these tasks need to be carried out. This document serves as a guide to efficient store operations.

The task in the store can be broadly classified into following:

Store Administration and Management of the Premises;

Managing Inventory and display;

Managing Receipts;

Customer Service; and

Managing Promotion, Events, Alliances and Partnerships.

Figure: Tasks to be performed at the Store Level

As seen in the figure we can easily observe that each and every task is revolving around Customer Service as it is always at centre stage. Every task is aimed at providing customer an experience which leads to customer delight which is the only way Reliance Fresh can stay ahead of its competitors and still run profitably.

After receiving a service the customer evaluates post purchase and three possible outcomes are:

Actual performance matches expectation, leads to satisfaction.

Performance exceeds expectation and the consumer is Delighted and here customer is excited and does repeat purchases and involves himself into mouth to mouth publicity for the Store. Hence such customers are valuable assets to the company. And the store should always try to gain delighted customers by their unmatchable service. This can help store achieve all its objectives.

Performance below expectations is the situation where customer gets unsatisfied and resorts to negative publicity of the store. This situation has to be avoided at all cost. This can do a very damaging impact on the store image and it becomes a very tough job to get back such a customer.

Managing the operations of a retail store starts by determining how the tasks pertaining to the premises are to be performed.

Now here we can understand how even minute things matter even managing our own premises can contribute heavily towards customer satisfaction.

Some of the tasks which include in management of premises are:

Business hour duration: This is a very crucial decision to be taken by the management which is decided on the basis of target customers. Here the convenience for customer is given due importance. In case of Reliance Fresh being a convenience store located at residential areas where customers start visiting the store as early as 7.00 am. The office going people can come and shop at that time for their daily needs after their morning walk. The same can be the case in the evening when customer wants to shop after their office hours.

Providing flexibility to the opening and closing timings leads to customer convenience and which can help contribute towards reaching customer satisfaction and delight.

Judicial use of Air Conditioners: Air Conditioner provides a congenial environment where we want our customers to stay and spend more time in the store.

This is done basically for two reasons:

Providing customers an experience and comfort while shopping which will definitely help achieve satisfaction.

As the customer spends more time in the store it will definitely have a positive impact on ticket size which means more revenue and profit.

But while using A.C. judicial use is talked as we know that we have to function under certain constraints where we have to minimize the costs also. During lean hours (1.00 P.M to 4.00 P.M) there is no need to run A.C on full capacity and during rush hour (after 6.00 P.M) A.C can be run on full capacity.

Therefore by following the above the store maintains a delicate balance while trying to achieve Customer Delight and escalating costs and hence satisfying both conditions.

Store Layout: The store layout should be planned in such a manner that customer finds enough space for movement. The layout should be in such a systematic manner that customer can easily locate products he/she wants to purchase. At Reliance Fresh a very impressive layout has been put in place where customer easily finds what he wants.

HOME FURNISHING

PROCESSED FOOD

NON-FOOD (Personal Care)

DAIRY

PLASTIC WARES

PROCESSED FOODS

PROCESSED FOOD

STAPLES

PERSONAL CARE

FOOD & BEVERAGES

FOOD & BEVERAGES

FRUITS & VEGETABLES

VEGETABLES

BEVERAGES/DAIRY

Customer Service

TILL

TILL

STAPLES

MOBILES

PROCESSED FOOD

EXIT

Store Administration deals with various aspects like the cleanliness of the store premises, maintenance of the store façade and display, etc. Apart from these it is also responsible for utilizing the store personnel effectively.

Tasks involved in Store Administration which can contribute towards achieving customer delight:

Floor Maintenance: The premises of the store need to be maintained as per standards decided upon by the management.

Floor cleanliness and merchandise arrangement play a very crucial role in creating an image of store in the minds of the target customers. This is crucial when customer tries to evaluate several stores and matches the pricing of products offered with the services provided by the store.

Therefore when a customer tries to compare Reliance Fresh with Fair Price store, Fair Price fails terribly as Reliance Fresh has specially emphasized on its services apart from pricing strategy.

At Fair Price the products are scattered on the floor and customers are also not attended to the level Reliance Fresh does. Hence providing products at cheaper price is not the only factor which customer considers from where to buy.

But Reliance Fresh is using a combination which definitely making it lead is that it is providing all services a convenience store can provide but at better price which is leading to Customer Satisfaction and Delight.

At Reliance Fresh very impressive initiative was taken to maintain its overall store floor maintenance in the name of “Operation Shine” where days were systematically assigned for a particular task and at end of it store performance was evaluated for each store which lead to store maintained and cleaned which gave a very good signal to its customers for its uncompromising take on floor maintenance.

Manpower Planning: The next most important thing that a customer looks after entering the store is how Customer Care Associates (CCA) attend to them, how well a CCA and other staff members at the front end are dressed, educated and competent enough to respond to their queries.

Manpower Planning may include certain functions like:

Shift Planning: A roster is maintained at a Reliance Fresh Store in which the store manager plans and assigns optimum staff to each shift also considering weekdays and weekends.

This is done basically on the basis of footfalls of customer at a particular time. Hence providing for more staff during evening hours when footfalls are high.

The Store Manager also has to intelligently assign work to his staff members according to footfalls as he can assign routine work to supervisor and CCAs at lean hour of the day for work like stock take (Physical Inventory, Stock Indenting etc). He has to push his staff towards attending customers at rush hours ask them to drive sales through their efforts. This helps Reliance Fresh to not only increase sales but gain Customer Satisfaction and Delight.

In charge: For every task in the store a staff member is made incharge of that task so that no confusion is there on the floor and in the store as a whole.

Various tasks like opening of store, indenting of F & V and milk, GRN, stock correction etc. is assigned among supervisors shift wise.

CCAs are assigned bays and responsibility given to them regarding their bay regarding maintenance of Planogram, FIFO, FEFO, proper stacking etc. By doing the above the store can manage display efficiently and ensure the service of the store to an optimal level.

MSRs are assigned to regularly make announcements of schemes offered by the store as it is very crucial as communication helps consumer make decision and push sales. This apart from the task of acting as a member of customer service desk and solving any customer complaints.

The task of allocating the merchandise to the various stores rests with the category manager. At the store the staff manages this inventory. Each and every process is documented at the store level.

Responsibilities with respect to merchandise at the store level involves receiving and inwarding the goods. Once the merchandise is received at the store, the quantity and other details are tallied with the documents accompanying the goods, to detect any discrepancies.

Hand Held Terminal is used at Reliance Fresh stores to directly scan and do the GRN for the products received.

After receiving the goods the real play starts where an MBQ (Maximum Bin Quantity / Maximum display Quantity) is maintained which signifies the maximum quantity the store has to maintain of a particular product. It is done so that optimum level of inventory is maintained so as to optimize cost of holding a product. There is a limitation of the store that excess stock can be put as the space in the store is quiet costly and maximum space has to be utilized for purpose of displaying product to sell.

Excess stock means blocking of valuable resources like money, leads to wastage due to breakage, shrinkage etc leading to direct losses to the company.

A Target Stock quantity is set for each SKU and as it is a reorder level in the MBQ when the Auto Replenishment System automatically indents for the particular product and the product hence is sent by the distribution centre (DC).

This is most critical process as it helps prevent shortages in the store which can lead to customer dissatisfaction and even unwanted excess stock is avoided which spoils the display of store with products lying on the floor.

Hence it is clear that even proper inventory management leads to proper customer satisfaction.

Some important processes followed by Reliance Fresh in inventory management helping them reach optimality in inventory levels and customer satisfaction is:

Physical Verification of Stock: Under this process stocks are physically verified and entered into the SAP. This activity is known as Stock Take.

Any variation with the book stock is recorded. This helps the store to control its shrinkage if the SKUs are physically lesser than the book stock. Similarly excess stock if any is also recorded.

The implication of these variations on planogram display is such that in case of Negative variation i.e. Physical Stock < Book Stock then it leads to shortages of that SKU as Auto Replenishment fails to function as inspite of stock in realty should have triggered the Target Stock but will not as the system shows that there is more stock (Book Stock). This causes great inconvenience to the customers like if a customer comes to purchase a product of daily requirement like Spices and he is not getting it regularly due to such a discrepancy he will definitely get unsatisfied and the store loses sale of that SKU due shortage inspite of demand.

And in case of Positive variation i.e. Physical Stock > Book Stock it creates a different kind of problem where excess stock is sent by the DC and it becomes difficult to manage it as it have to remain scattered all over the floor waiting for the stocks on the bay to get cleared. This also gives negative impression about the store as an ill managed store where products are scattered and there is problem in free movement. This should also be avoided.

Proper recording of Dump and Shrinkage: To maintain proper MBQ it is very important to regularly update dump and shrinkage. This has to be done apart from Stock take which is done once a month or as and when asked by the management.

Push Indenting of Promo article for a particular scheme: During an offer on a product a sudden spurt in demand can be seen which is quite temporary in nature. There it is not advisable to change MBQ as it is more permanent in nature. In case of upward revision of MBQ the product will be delivered in increased quantity even after removal of promo offer. There a temporary increase in indenting is done called Push Indenting. Hence after withdrawal of the scheme the product is delivered on the normal basis.

Revision of MBQ: There is also a process of revising MBQ in case there is a regular increase in demand and the store is maintaining lower MBQ meaning regular shortages. There an upward revision is done.

In case of slow moving goods which the store manger feels is a drag on store performance and is just blocking space he can request for revising the MBQ to lower levels or removing it from the shelf altogether. The product has to be sent back to DC.

DSD Indenting: Direct Store Delivery (DSD) Indenting is done for very fast moving goods like beverages, highly perishable goods like ice-creams and also glass items which highly fragile in nature.

On the part of consumer it helps him to receive products fresh in case of perishables leading to maintainability of high quality standards.

On part of management it reduces cost of holding such perishable and fragile products as the store will receive from the vendor only products which are saleable and meet standards.

Markdown Process: It is process where store manager is authorized to reduce price of saleable quantity F&V, Bakery products or products which are nearing expiry and are expected to become dump if proper step of reducing price is not done.

The objective of this process is to reduce dump at store level and also sell non moving stock of such products.

A very integral part of managing inventory at store level is display it correctly. The best merchandise may remain unsold if it not displayed in a manner that is appealing and convenient for the customer. A very simple example can be illustrated like if rice packets are put on high bays it will become very inconvenient for which mostly female customer do the buying, hence would negatively impact sales.

Display can be considered as a silent salesperson helping to self sell the products. Display is such a critical part in serving customers as it helps avoid confusion and guides customer to make prompt decision.

Various methods are employed to impressively display products are:

Planogram (POG): A planogram is a diagram created from photographs, computer output that illustrates how exactly where every SKU should be placed. It is a visually appealing; represent the manner in which consumer shops (or the manner in which the retailer wants his customer to shop).

End Caps: They are used to display promotional items which helps customer to easily identify schemes and offers on products.

Shelf Edge Labels (SEL): SELs are used to display the prices of the products. At Reliance Fresh, Hand Held Terminal (HHT) is used to give commands for the purpose of printing updated SELs. This makes it quite convenient for the CCAs to promptly change the SELs. A portal is there in place through which the print command is accepted and prints given.

Shelf Talkers: These are used to display promotional schemes on a visually attractive format.

Managing receipts involves defining the manner in which the retailer is going to receive payments for the sales.

At Reliance Fresh the payment is received in the following forms:

Cash

Credit / Debit Card

Sodexho

Accor

All the responsibilities pertaining to Cash management is on Commercial & Accounts (C&A).

The prime responsibility of C&A is Till Management.

He has to ensure proper and smooth running of Tills.

He maintains changes and float cash (Rs.1500) in the till.

He has to ensure that there is no long queues while bill, if at all there is he has to open another till. Almost every CCA is trained to run the billing which is done on Retailix software.

It is a known fact customers are reluctant to shop on places with long queues. There Queue Management is a very important as proper customer service is concerned and helps toward customer satisfaction

The customer service policy adopted by Reliance Fresh is quite impressive and definitely helping it to achieve customer satisfaction and delight.

The customer service policy is put into practice by the store staff primarily by the MSR and then Supervisor on the floor.

This policy doesn’t begin and end at the customer service counter in the retail store. Every staff member is advised to ensure that the customer, who comes in contact with him/her, is comfortable and has a pleasant shopping experience.

An important aspect which affects a customer’s perception of the retail store is the experience that he has while billing the products purchased by him. While a customer may spend hours choosing the product that he like waiting for a long time of payment. Long queues result in disgruntled customers. Reliance Fresh Store operations is geared to handle such a situation. It has provided proper training to each staff to handle cash counters.

Several important steps have been taken by Reliance Fresh to serve its customers better:

Customer Greeting: Every staff member has been asked to make eye to eye contact with customers and greet them on first contact in the store.

PR & Rapport: Staff members are advised to make good personal relations with its customers and make a good rapport.

Proper Attention & Assistance: In case a customer has any query the staff member in contact is supposed to give proper attention and assist him/her with proper solution.

Enrolling in Loyalty program: MSR is expected to make new member in its loyalty program. It helps company to study the customers changing taste and preferences. It also helps Reliance Fresh to regularly communicate to its customers on latest promotions.

On the part of customer feels alighted for being a part of such a program where he is given due attention and also offered loyalty bonus points which can be encashed on a regular basis.

Telecalling: Telecalling is also done from the store by the MSRs to the regular members for informing them about latest promotional offers and schemes.

Home Delivery: This facility has also been introduced to give customers a more customised service.

Scheme Announcements: Regular announcement is done within the store to communicate to its customers about schemes and offers.

Addition of items at store level: Items can be added at the store level if there is a persistent demand of that product. This has to be conveyed to the category team which further does the needful.

Newspaper Insertions: Insertions on weekends about the offers are done to communicate to its customer.

Putting up banners in catchments: Also done to communicate to its customers.

Upselling by Staff members: The staff members’ upsell their products like if a customer has purchased for Rs.700 the staff member communicates about scheme on high value purchase like plate set free on purchase of Rs.999/- which benefits the customer as he/she gets a good offer and as a retailer Reliance Fresh gets an opportunity to increase ticket size as well as win customer loyalty.

Maintenance of Complaint Book: A complaint book has to be maintained at the customer service desk where incase of customer wanting to lodge complaint can do it. This has to be resolved in a specified time.

All of the above plays a major role in creating an atmosphere which leads to a Customer Delight.

Events and promotions are very much a part of the retail marketing scene. In order to enable the success of such an event or a promotion, the store is geared up with prior preparation of such an event.

At Reliance Fresh a KIDS CARNIVAL was organised where blank sheets was given to kids who had to draw painting and submit in a day.

Gifts were distributed to them. This type of events create a bond with its participants and when they are children it becomes more important as we know there importance in decision taken even by their parent.

INTERPRETATION

Percentage

51.72%

3.44%

13.79%

31.03%

Regular Customers were interviewed at Reliance Fresh as they were one who have observed and experienced the services at Reliance Fresh and were in better position to suggest improvement in its Store Operations.

While interviewing it was found that many regular customers were spending more than 50% of their consumption in stores other than Reliance.

INTERPRETATION

Percentage

10%

40%

48%

2%

This signifies the customer profiling on the basis of monthly expenditure.

It shows that most of the customers frequenting the Reliance Fresh Store spend in the range of 5000 – 10000 which may not necessarily be spent at the Reliance store.

INTERPRETATION

Percentage

24.07%

51.85%

24.07%

The above pie chart signifies the preferred schedule of purchase which can help operations plan accordingly.

Most customers prefer weekly purchasing which gives insight to customer behaviour where he/she might prefer offers on weekly basis purchasing.

INTERPRETATION

Percentage

9.61

30.76

21.15

38.46

This is a very important illustration where it shows that only 38.46% of the respondents who are regular visitors of Reliance Fresh Store spend more than 50% in the store.

This shows the scope that Reliance Fresh can how improve on its sales by just giving these customers something better. The revenue can increase manifold by just concentrating on this segment.

INTERPRETATION

Percentage

28

32

30

10

This signifies that of the total monthly spend on Fruits and Vegetables only 10 % of the people were found to be spending more than 75%.

This area can also be improved significantly.

INTERPRETATION

Percentage

12.76%

31.91%

42.55%

12.76%

This illustrates that most of the respondents view Merchandise as the USP of Reliance Fresh Store followed by Freshness and Quality of Products.

INTERPRETATION

Percentage

30.66%

54.66%

8%

6.66%

Here we come to know that most of the visitors of the store concentrated more on Freshness & Quality of products for purchasing while Better Price followed it.

Reliance Fresh should concentrate on the freshness of fruits and vegetables which is considered as of prime importance by the visiting respondents.

Reliance Fresh has a tremendous potential where it can improve its revenue drastically by concentrating on its existing customer base.

As in the research findings it is very clear that even regular customers are still not spending major part of their monthly expense in the Reliance Fresh Store.

Hence this shows that they are expecting more from Reliance Fresh store and here lies a task where Reliance Fresh can improvise on its services to cater to the requirements of its customers.

Reliance Fresh should improve its operations in its Fruits and Vegetable section as it has been seen that people coming just to buy F&V go ahead and buy other products in the store. F&V is the major footfall driver in the Reliance Fresh Store.

Hence high Standards of Freshness and Quality in the F & V section has to be maintained by the Reliance Fresh Store to keep driving customers.

Reliance Fresh has to improve its Store Operations significantly to match customer expectations as the study indicates that most of the customers viewed Freshness and Quality of products as more important than holding large number of merchandise.

This is the area where Reliance Fresh is struggling to make a mark as customer didn’t find Freshness and Quality as a USP of the store as it is projected by the company.

During the course of study it was found that Queuing problem exists at the billing counters which need immediate attention. This problem can be sorted by improving operational efficiency by way of better managing the staff available at the stores.

The data obtained was mostly restricted to respondents who were regular visitors of Reliance Fresh, Model Town II.

Due to shortage of time the study was restricted.

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