Project work done in just in time JK industries pvt. ltd.

1. A STUDY ON JUST IN TIME
WITH REFERENCE
TO
JAYKAY INNDUSTRIES

2. Report submitted
By
PRASHANT BARLA
Master Of Business Administration
Sec – “C”
Internal Guide :- Ms. Kavitha Rajayogan

3. JUST IN TIME
• JIT is a Japanese management philosophy which has been applied in practice
since the early 1970s in many Japanese manufacturing organizations.
• It was first developed and perfected within the Toyota manufacturing plants by
Taiichi Ohno as a means of meeting consumer demands with minimum delays.
• JIT focus meet the increasing challenges for survival through an approach that
focused on people, plants and systems.
• JIT also focus on standard working, minimizing inventory, just-in-time purchasing,
just-in-time production, just-in-time distribution, just-in-time distribution.
• The main motive is to satisfy customer with best quality in products and service.

5. INDUSTRY PROFILE
• Indian auto components industry has experienced healthy sequential growth over
the last one-and-a-half years.
• The Indian auto-components industry can be broadly classified into the organized
and unorganized sectors.
• The organised sectors caters to original equipment manufacturers (OEMs) and
consists of high-value precision instruments while the unorganized sector
comprises low-valued products.
• Indian auto component industry has expected a turnover of US$ 66 billion in the
financial year 15-16.
• It is expected that this turnover may increase to US$ 115 billion by financial year
20-21.
• The Government of India’s Automotive Mission Plan (AMP) 2006–2018 has come a
long way in ensuring the growth of this sector in the global market.

6. • This turnover is going to increase to double reaching US$145 billion in 2018 due
to focus of government on exports of small cars, multi-utility vehicles and auto
components.
• Amtek Auto Ltd, MRF Ltd, Hero MotoCorp, Suzuki Motor Corp etc. are some
common investors in the Indian auto mobile market.

7. COMPANY PROFILE
• Jay Kay Inndustries was established in the year 2012 at Chennai, Tamil Nadu.
• CEO of the company is Jaganathan Shanmugam.
• Total no. of employee is 105+, company also involved in import and export.
• The company is a Sole Proprietorship (Individual) manufacturing, export import
based firm, involved in the manufacturer of Injection Moulded Components, Mould
Base, Plastic Insert, Plastic Mould, Plastic Injection Moulding Parts and many
more.
• Jay Kay Inndustries is a very wide and robust industry equipped with ultra-modern
machines which help in the organizational operations.
• Organization is divided in various departments which includes manufacturing
department, quality department, warehousing department, packing department,
R&D department, and logistics department.
• These departments are handled by their excellent professionals.

8. • Due to its edge on the market, it has come to reach the following achievement i.e
Easy payment modes, Reasonable prices, Competent and efficient team,
Transparency in dealings.
PRODUCTS
• Moulds
• Mould base
• Plastic Insert
• Plastic injection
• And many more
• Media New Product
• MBBR Media Lathe Machine
• Bio Pac Media
• FAB Media

9. • Like other industries Jay Kay Inndustries also focus on customer need and
demand.
• Jay Kay Inndustires has been awarded for the Best Quality of their products by
whirlpool of India Limited Pondicherry.
• Some of the clients of Jay Kay Inndustries are
VOLTEK POWER SYSTEMS PVT LTD
LUCAS - TVS LIMITED
SUPREME INDUSTRIES
TEXSHINE PLASTICS & HYDRAULICS
BRAKES INDIA PRIVATE LIMITED
SUNDARAM CLAYTON LIMITED

10. OBJECTIVE OF THE STUDY
• There are lot of problems that is being faced by the Jay Kay Inndustries which
includes waste of time, inventory cost, customer satisfaction etc.
• The objective includes
PRIMARY OBJECTIVE
• To study the effectiveness concept of JIT in Jay Kay Industries.
SECONDARY OBJECTIVES
• To reduce the production time in making each moulds through Kanban process &
effectiveness of TPM.
• To analyze whether suppliers Network will give 100% delivery & reduce delivery
time.
• To analyze whether cellular layouts of machines will reduce cycle time.
• To analyze the effectiveness of Standard operations.
• To analyze the effectiveness of 5s plan.

11. REVIEW OF LITERATURE
• VIKAS KUMAR on 2010 at his journal JIT Based Quality Management: Concepts
and Implications in Indian Context stated that quality is important for the survival of
the company through customer satisfaction. He concluded that JIT base quality
manufacturing brings a tremendous positive effect on the company also in the
production.
• Dr. İlhan DALCI on 15th September 2006 at his journal The effect and
implementation of just-in-time system from a cost and management accounting
perspective stated use of JIT production system through adoption of Top and
middle managers commitment, pull method, good relationship with customers,
standard work, clean environment, multi skilled worker, best machines.
• Agrawal, N. on 22nd May 2010 at his journal Just in time techniques in
manufacturing systems stated that JIT implementation is as a pull on the
manufacturing process and system which improves the quality in the customer
demand. Kanban process and CONWIP is one of the key factor.

12. • Ahmad Naufal Bin Adnan on 2013 at his journal Implementation of Just in Time
Production through Kanban System state that the use of Kanban process in JIT
they are able to manufacture and supply the right product, in the right quantity, at
the right place and time.
• Dinesh K. Raut on 2010 his journal JUST-IN-TIME MANUFACTURING stated
about JIT implementation to eliminate all types of wastes from the company by
placing right equipment at right place and overall reduces the waste in time, raw
materials. This is achieved by employee participation, right production on demand,
purchasing survey.

13. RESEARCH METHODOLOGY
Research methodology includes
• DATA COLLECTION
Primary data- Questionnaire
Secondary data - Gantt chart.
• SAMPLING METHOD
simple random sampling(Closed end questions)
• STATISTICAL TOOLS USED FOR ANALYSIS
Percentage analysis method
t-test method.

14. DATA ANALYSIS AND INFERENCE
• Analysis for Pre Kanban and Post Kanban Process Comparison
Average of total time(in minutes) for one week Pre Kanban
Metal Mould
Plastic
Mould MBBR
Mon(29/1/18) 97 57 87
Tue(30/1/18) 90 41 87
Wed(31/1/18) 103 62 83
Thur(1/2/18) 92 60 85
Fri(2/2/18) 122 93 85
Total 504 313 427
Avg. of total 101 63 85
Average of total time(in minutes) for one week Post
Kanban
Metal
Mould Plastic Mould MBBR
Mon(12/1/18) 29 24 27
Tue(13/1/18) 21 21 23
Wed(14/1/18) 21 22 21
Thu(15/2/18) 20 15 17
Fri(16/2/18) 22 19 20
Total 113 101 108
Avg. of total 23 20 22
Comparison of Average Time(in minutes) for Pre Kanban and Post
Kanban
Process Metal Mould Plastic Mould MBBR
Pre Kanban 101 63 85
Post Kanban 23 20 22

15. Pre Kanban Post Kanban
Metal Mould 101 23
Plastic Mould 63 20
MBBR 85 22
0
20
40
60
80
100
120
AverageTime
Comparision of time

16. • Percentage Analysis Chart showing for effectiveness of TPM & Kanban
process satisfaction level
6%
66%
24%
2% 2%
Average Satisfaction level for Kanban & TPM implimentation
Strongly agree Agree Neutral Disagree Strongly Disagree

17. • Percentage Analysis Chart Showing the average views level on suppliers
network & 100% delivery service
39%
38%
16%
5%
2%
Average views level on suppliers network & 100% delivery service
Strongly agree Agree Neutral Disagree Strongly Disagree

18. • Percentage Analysis for showing average views level for cellular layout
concept
9%
50%
36%
5%
Average views level for cellular layout concept
Strongly agree Agree Neutral Disagree

19. • Percentage Analysis Chart showing average view level on 5s Plan
Implementation
44%
30%
13%
11%
2%
average view level on 5s Plan Implementation
Strongly agree Agree Neutral Disagree Strongly Disagree

20. • Percentage Analysis chart showing average view level on Standard
Operation technique.
8%
44%
13%
29%
6%
Average view level on Standard Operation technique
Strongly agree Agree Neutral Disagree Strongly Disagree

21. INDEPENDENT t – Test
• Independent t-test showing the hypothesis of age and Kanban
implementation
Null hypothesis H0 : There is no significant difference between the age and Kanban implementation
Alternate hypothesis H1 : There is a significant difference between the age and Kanban implementation
Since the Sig. (2-Tailed) value is 0.4. This value is greater than .05. Because of this, we can interpret that
there is no statistically significant difference views implementation between the age of 26-30 and age of >35
employees. We can conclude that the employee age between 26-30 and employee >35 highly support that
Kanban Process has reduced the time of production.
Levene's Test for
Equality of
Variances
t-test for Equality of Means
F Sig. t df Sig. (2-
tailed)
Mean
Differenc
e
Std. Error
Differenc
e
95% Confidence
Interval of the
Difference
Lower Upper
Kanban Process
has reduced the
time of
production
Equal variances
assumed .168 .686 .780 25 .443 .250 .320 -.410 .910
Equal variances
not assumed .893 4.669 .415 .250 .280 -.485 .985

22. Independent t-test showing the hypothesis of age and group technology
to improve process time
• Null hypothesis H0 : There is no significant difference between the age group technology to improve process
time.
• Alternate hypothesis H1 : There is a significant difference between the age group technology to improve
process time.
• Since the Sig. (2-Tailed) value is 0.5. This value is greater than .05. Because of this, we can interpret that
there is no statistically significant difference between views on group technology to improve process and the
age of employee 25> and age of employees 26-30. Thus we can conclude that employee age between 25>
and 26- 30 highly support that group technology will improve the process time.
Levene's Test
for Equality of
Variances
t-test for Equality of Means
F Sig. t df Sig. (2-
tailed)
Mean
Difference
Std. Error
Difference
95%
Confidence
Interval of the
Difference
Lower Upper
Group
technology will
improve the
process time
Equal variances
assumed 4.039 .051 .612 44 .543 .130 .213 -.299 .560
Equal variances
not assumed .612 38.671 .544 .130 .213 -.301 .561

23. Independent t-test showing the hypothesis of age and cleanliness for
work area
• Null hypothesis H0 : There is no significant difference between the age cleanliness for work area.
• Alternate hypothesis H1 : There is a significant difference between the age cleanliness for work area.
• Since the Sig. (2-Tailed) value is 0.3. This value is greater than .05. Because of this, we can interpret that
there is no statistically significant difference between views on cleanliness of work area and the age of
employee 25> and age of employees 26-30. Thus we can conclude that employee age between 25> and 26-
30 highly support that there is a need of cleaning for work area, office area and washrooms.
Levene's Test for
Equality of Variances t-test for Equality of Means
F Sig. t df Sig. (2-
tailed)
Mean
Difference
Std. Error
Differenc
e
95% Confidence
Interval of the
Difference
Lower Upper
Is there a need
of cleaning for
the work area,
office area,
washrooms?
Equal variances
assumed 4.390 .042 -1.000 44 .323 -.043 .043 -.131 .044
Equal variances
not assumed -1.000 22.000 .328 -.043 .043 -.134 .047

24. Independent t-test showing the hypothesis of age and giving job
responsibilities
• Null hypothesis H0 : There is no significant difference between the age giving job responsibilities.
• Alternate hypothesis H1 : There is a significant difference between the age giving job responsibilities.
Since the Sig. (2-Tailed) value is 0.02. This value is less than .05. Because of this, we can interpret that
there is a statistically significant difference views on job responsibilities between the age of 25> and age
of 26-30 employees. Since Group Statistics box revealed that the Mean for the age 25> was greater than
the Mean for the age 25 - 30, we can conclude that the employee age below 25 highly support for the
proper job responsibilities compared to employee age between 26-30.
Levene's Test for
Equality of
Variances
t-test for Equality of Means
F Sig. t df Sig. (2-
tailed)
Mean
Differenc
e
Std. Error
Differenc
e
95% Confidence
Interval of the
Difference
Lower Upper
Is there a need
of giving proper
job
responsibilities?
Equal variances
assumed 5.566 .023 2.152 44 .037 .34783 .16162 .02210 .67355
Equal variances
not assumed 2.152 43.630 .037 .34783 .16162 .02202 .67363

25. Independent t-test showing the hypothesis of age and need of training
and discipline
• Null hypothesis H0 : There is no significant difference between the age need of training and discipline.
• Alternate hypothesis H1 : There is a significant difference between the age need of training and
discipline.
Since the Sig. (2-Tailed) value is 0.5. This value is greater than .05. Because of this, we can interpret that
there is no statistically significant difference between views on need of training and discipline and the age
of employee 25> and age of employees 26-30. Thus we can conclude that employee age between 25> and
26- 30 highly support that there is a need of need of training and discipline.
Levene's Test for
Equality of
Variances
t-test for Equality of Means
F Sig. t df Sig. (2-
tailed)
Mean
Difference
Std. Error
Difference
95% Confidence
Interval of the
Difference
Lower Upper
Is there a
need of
Training and
Discipline?
Equal variances
assumed 17.174 .000 1.825 25 .080 .60870 .33357 -.07830 1.29569
Equal variances
not assumed 4.447 22.000 .000 .60870 .13686 .32486 .89253

26. FINDINGS
• It is founded that the average time reduction after implementing Kanban
process in metal mould is from 101 min. to 23 min., in Plastic mould is from
63 min. to 20 min. and in MBBR is from 85 min. to 22 min.
• Overall high number of employee agree with the effectiveness of TPM &
Kanban process satisfaction level i.e. 66%.
• Overall high number of employee strongly agree with the suppliers network
& 100% delivery service i.e. 39%.
• Overall high number of employee agree with cellular layout concept i.e.
50%.
• Overall high number of employee strongly agree with 5s Plan
Implementation i.e. 44%.
• Overall high number of employee agree with Standard Operation technique
i.e. 44%.

27. SUGGESSTION
• A proper management of Human resources in the company will lead to a
proper knowledge management and hence it is recommended.
• Proper cleaning of work area and maintenance of machine need to be done
for better performance in the Jay Kay Inndustries
• A proper implementation of JIT techniques is highly recommended as it will
push Jay Kay Inndustries as a global competitor to many giants of the
industry.
• Proper placing of machines with respect to the process may reduce the over
timing of work among the employees also it will reduce unnecessary/over
production.
• New technologies of work process need to be upgraded among the
employees and in the machines.

28. CONCLUSION
• JIT may help to achieve the drawbacks to the company.
• Kanban process which is implemented as part of JIT had an adverse effect on
reducing time of each process which helped in reducing the overtime and
overproduction in the industry.
• The management has to focus effectively on the proper way of work
techniques to improve productivity and reduce the over time that is coming
due to the negligence of management.
• Company has well educated employees which can bring more productivity to
the organization if they are trained well.

29. THANK YOU