Digitalization of Conventional Rejection Analysis System of MSMEs by using ASP.NET

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ISSN (Print): 2319 - 2526, Volume-2, Issue - 6, 2013 59

Digitalization of Conventional Rejection Analysis System of MSMEs by using ASP.NET

1Ishita M. Thanki, ²Kamal N. Kotecha, ³Jimil M. Shah

1Faculty of Engineering and Technology, Noble Group of Institutions, G.T.U., Gujarat

2 Faculty of Engineering and Technology, Noble Group of Institutions, G.T.U., Gujarat

3 Engineering Consultant, Vadodara, Gujarat

Email : [email protected], [email protected], [email protected]

Abstract- one of the major problems in all Medium Scale manufacturing industries is of Rejection and data collection for the same. This paper gives practical means of facilitating participatory steps taken in productivity enhancement by methodological approach with the emphasis on rejection minimization by first analyzing it and then by taking CAPA(Corrective and Preventive Action). By using ASP.NET and C# Technology we have derived a system in which the company can directly store the feedback of customers into database. By analyzing those feedback data, company can produce the rejection analysis graph. The main focus is to deal with External Rejection.

Index Terms: external rejection, Asp.Net and C#

Technology.

I. INTRODUCTION

In any industry whether it is a small scale or large scale, since ancient times and even in recent days the most prominent problem and fatal problem is the “PROBLEM OF REJECTION”. Rejection means the act or process of rejecting something whether it may be product/raw material/resources in relating to a particular industry/company. Whenever a product for example a car, bike, bearing etc. is manufactured then it is brought into market for sale and due to unpredictable or by means when it gets failed to use by customers or in short rejected due to various defects in the product. This problem is known as the problem of rejection. In other words, even in company due to lack of management or uncertain things when a product is rejected by the company itself and the company recalls their product in large numbers is also called a rejection. [1] But this kind of rejection is included in internal rejection problem. In many large scale industries, when a large number of products get rejected then the company faces a loss.

There are two types of rejections viz. internal rejection and external rejection.

Internal Rejection: Whenever a product is rejected before it is distributed in market and when a fault occurs in the phases of manufacturing process and the product is rejected internally during the final inspection by the company and has no effect to the outside market is said to be Internal Rejection. [7] Examples: When raw materials are rejected during sampling process in the industry. When Laboratory checkup is done in the items selected from small scale industry units. When products are rejected from Assembly and sent to scrap yard directly during final inspection. Here we focus more on external rejection only. [1]

External rejection occurs when the customer rejects the product or the company calls back its product after it’s distributed in the market. [1]

To get this feedback from the customers, Small and Medium Scale Manufacturing industries are using manual system which was full of paper documentation and money wastage. It was very lengthy and time consuming process. Even it was very confusing sometimes. [4]

In this era, Computers are omnipresent. And also there are many platforms and frameworks are available in computers to make such works in a simple way. For Example, ASP.NET and C# to digitalize this work in necessity in industry for betterment of quality of product in time.

II. CONCEPT AND METHODOLOGY

.NET is a framework which provides technologies like ASP.NET for developing web based application and c#

an object oriented programming language in which we can calculate or manipulate our data to produce result.

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So by using such technology and framework we have derived an online feedback system to take valuable feedback from customer for the analysis of external rejection.

By using visual studio software and technologies like Asp.Net and C# we have derived system to fulfill these algorithms.

For developing digital system of analysis of external rejection we have followed agile model. The steps to derive any system using agile model is shown in below figure:

Fig. 1 Agile Model Step 1:

The first thing to develop digital system for external rejection analysis is to understand the organization of working environment of the conventional system in MSME`s. For this we had taken training in one of the MSME’s and observed their conventional methods.

After that step, the first and foremost step was to gather the requirement of the company which we had done in Requirement gathering phase. For this effective communication with the company was done for further upcoming steps.

Step 2:

The architecture of the system was designed according to the requirements of the company. This architecture had plans to build the software which facilitated with working towards the digitalized system from the conventional system. Eventually the outcome was visually designed and shown to the company further development. This would help the company to visualize the digitalized system which was being developed.

Step 3:

The development of the system was done using

languages like C# and .Net. This included several coding methods inclusive of various classes and packages designed especially for each requirement which was covered in the first phase of the agile model. Each and every class was designed in accordance to the requirements.

Step 4:

This phase includes Testing and Feedback from the users. In this stage, first the beta version is submitted to the company for testing and even internal testing was done during this phase. After that the digitalized software was deployed in the company and it was familiarized with the employees to get the feedback regarding the digitalized software which was being developed.

III. DESIGN AND IMPLEMENTATION

Requirements:

Generally in MSME`s, the analysis of external rejection is done by administration on the basis of customer feedback by paper work and documentation. For Example: they have a form of feedback that is sent to clients/customers by courier for their valuable feedback and for improving quality and customer satisfaction level.

By studying the existing rejection analysis process, we gather all requirements that are needed to develop such digital system for external rejection analysis.

Architecture and Design:

After gathering all requirements necessary for the development of the digital system, we can proceed to architecture and design. For that we selected the most feasible technology to develop the system like ASP.Net and C# etc. and designed all diagrams and algorithms to satisfy the requirement of MSME.

ALGORITHMS:

Algorithm for Customers:

1. Customers have to login into their account for giving feedback.

1.1 Must have to enter username and password.

1.2 If username & password both match.

1.3 Then customer is now logged in & can give the feedback.

1.4 Not matched then re-enter username &

password.

2. Customers can view the products of the company.

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3. Customers can view the help page for giving feedback.

4. Customers can give feedback or manage the account.

5. In feedback form, customers have to rate each fields for submitting their feedback & have to enter manufacture code for product.

6. After feedback customer must have to log out from the website.

Algorithm for HR Department:

1. Initially HR people must have to log in into their account.

1.1 Must have to enter username & password.

1.2 If username & password both matched.

1.3 Then HR is going to access their account.

1.4 If not matched re-enter username &

password.

2. Insert/Update/Delete the product.

3. Analyze the feedback by avoiding fake feedbacks on basis of manufacture code.

4. Generating report & charts.

4.1 Generate weekly, monthly & yearly reports based on feedback of customers.

5. Analyze the rejection from the poor ratings of the customers.

6. Forwards the final reports to the management.

7. after completion of Rejection Analysis HR have to log out from the website.

Algorithm for Management:

1. Initially management must have to log in.

1.1 Must have to enter username & password.

1.2 If username & password both matched.

1.3 Then Management is going to access their account.

1.4 If not matched re-enter username &

password.

2. After the Login, management can see all the feedback given by customers globally.

3. Management can see Rejection analysis, reports

& charts calculated by the HR Department.

4. As per the report, management can take steps

towards improvements in quality.

5. After this, management has to log out from the website.

Development:

Here the concept converts the existing paper based rejection analysis system i to digital. To develop such web application, we have used ASP.Net technology to develop the feedback form and C# technology to manipulate and calculate the analysis of rejection.

After developing the feedback form, customers or clients can directly fill that form online so paper work and documentation is eliminated. By using most feasible database system i.e. SQL server, the feedback of worldwide customers can be stored in database directly.

Using these data and valuable feedback, we can easily calculate and analyze the external rejection that is very much easy compare to previous existing method.

Test and Feedback:

In this module, the main task is to deploy the system which is digitalized for calculating external rejection in MSME’s. The beta version is first deployed in the company for testing purpose. Once this takes place, the major task is to figure out the rejection ratio by comparing it to previous year’s rejection analysis data.

Hence to avoid any problems; feedback is taken at regular intervals. Certain kind of amendments was encountered during this task so they were successfully implemented as per company’s suggestion.

Expected Outcome:

The expected outcome of the derived system is to analyze the External rejection and to escalate the customer satisfaction and quality assurance.

The work flow of this system is that from the customer feedback (Online), we calculate the external rejection which involves an algorithm that is used to find the external rejection from the data given by the customer feedback form.

This feedback is filled by the customer online only through a website by which is to be designed for MSME’s via internet.

On basis of data given by customer feedback various pie charts and bar charts would be generated which would then be given as input in the rejection analysis algorithm to analyze the external rejection.

These pie charts and bar charts would be generated dynamically from customer feedback form – weekly, monthly, yearly basis online on my website.

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This model will also help to short list the types of defects and will also check the rating of the product by the given feedback of customers.

After analyzing the rejection corrective and preventive actions are to be taken to avoid the rejection.

From this feedback, the company can easily conclude the lack of quality and take action for the betterment of the product through the relevant department.

Merits over the Conventional System

The derived system helps to provide the feedback of customers in a simple manner.

It saves time and helps to create a positive image in customers’ mind.

It brings to an end to Non Value Added Activities like Paper work and documentation and saves money too.

It helps to take precaution in different kind of quality problems.

It helps to take preventive and corrective actions for the quality assurance in no time.

It simplifies customers’ feedbacks and shorts them out in different criteria for fast improvements.

It leads towards customer satisfaction.

IV. CONCLUSION

In analysis process of External Rejection, the key aspect is to analyze the data from Customer Feedback Form of the company which is done online through a website and resulting in generation of Pie-charts and Bar-charts which include calculation of overall rejection of company based on customer’s rating. After analyzing the whole data, various CAPA can be taken for rejection. In external rejection, we focus on feedback of customers and find whether which department in the company is responsible for rejection i.e. for example:

Designing, Planning etc. Hence we can move towards customer satisfaction and quality assurance. [4]

APPROACH TOWARDS QUALITY

IMPROVEMENTS:-

From these ratings and graphs, company can improve their quality as early as possible. This will increase Statistical Process Control with Process Capability. That will move the company towards SIX SIGMA. [2]

Six Sigma emphasizes the use of facts and data to guide the decision making process. From a statistical view point, Six Sigma has a defect level of 3.4 per million operations [5].

Most of the Small and Medium Scale Companies operate at around 3 Sigma which translates into roughly 67,000 defects per million operations [6].

Achieving Six Sigma at the output of a business process decreases the number of defects to fewer than four per million. Hence with the help of this rejection analysis methodology; this is one of the best try to make a company Six Sigma or move it towards making it a six Sigma company. As the customer satisfactory level will increase; the rejection will be decreased and vice versa.

Here we just give the external rejection analysis; but internal rejection analysis is also effecting in the overall rejection calculation process and making a company Six Sigma.

Most companies today, however, view Six Sigma as a business strategy and methodology for improving process performance in such a way that customer satisfaction is increased and the bottom line is improved [5].

This is one of the best systems to improve customer satisfaction level through customer feedback.

V. FUTURE SCOPE

For Testing and Feedback from the users, first the beta version is submitted to the company. After that the digitalized software was deployed in the company and it was familiarized with the employees to get the feedback regarding the digitalized software which was being developed.

Once this takes place, the major task is to figure out the rejection ratio by comparing it to previous year’s rejection analysis data. Hence to avoid any problems;

feedback is taken at regular intervals. Certain kind of amendments was encountered during this task so they were successfully implemented as per company’s suggestion.

This model is having versatile aspects like feedback collection, form generation, feedback data conversion, short listing of type of defects, ratings for different services provided to customers etc.

It also generates graphs and comparison tables for better visibility.

In future, it will be loaded with other different applications and packages as per the company requirements.

This module will be very much useful in Small and Medium Scale Manufacturing companies especially the vendor companies in an Automobile, Bearing, Chemical and workshop etc. sectors.

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VI. ACKNOWLEDGEMENT

We would like to thank to Austin Engineering Company Limited, Junagadh and its management for their willingness to give us a chance to understand their systems with co-supervise our work and helping us by giving invaluable suggestions on the work. We would also like to heartily thank Mr. Shashikant Thanki , Managing Director of Austin Engineering Company Limited for providing his immense knowledge and inspiring us to build this work and strive ahead for future work in this project. The special guidance of Mr. Hitesh Ajmera was also highly appreciable.

We also owe a sincere gratitude to Management of our respective Institute Noble Group of Institution, Junagadh for their constant encouragement and help in all our endeavors.

VII. REFERENCES

[1] http://en.wikipedia.org/wiki/2009%E2%80%

932011_Toyota_vehicle_recalls.

[2] http://www.businessballs.com/sixsigma.htm [3] http://en.wikipedia.org/wiki/List_of_Six_Sigm

_companies

[4] Austin Engineering Co. Ltd. An ISO 9001:2008

& ISO/TS 16949:2009 Company Village: Patla, Taluka: Bhesan, Junagadh 362030 Gujarat – India http://www.aec-bearings.com

[5] Ronald D. Snee, Roger Wesley Hoerl. (2003) Pearson Education, Inc. Publishing as Financial Times Prentice Hall. Leading Six Sigma: A Step by Step Guide Based on Experience with GE and other Six Sigma Companies. Page No. 4

[6] Achieving Quantum Leaps in Quality and Competitiveness: Implementing the Six Sigma solution in your company .ASQ’s 53rd Annual Quality Congress Proceedings Jerome A.

Blakeslee, Jr. Director PricewaterhouseCoopers Consulting Page No. – 486.

[7] http://www.toledoblade.com/business/

2011/06/10/Toyota-to-Face-Sudden-

Acceleration-Trial-in-2013-Judge-Says.html [8] Professional ASP.NET 4 in C# and VB, WROX

Publication.

[9] Msdn.microsoft.com [10] Statistical Process Control.

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