Dr. Krishnakant Dave
Director academics - Pacific University Udaipur
Mrs. Shrutika Patil
Research scholar - Pacific University Udaipur
Faculty,
Prin. L. N. Welingkar Institute of Management Development and Research
Mumbai, India
Abstract
Manufacturing aims to contribute 25 percent to the
share of India’s GDP by 2020. India plans to be a technology driven
manufacturing hub with many multi- national companies starting to set up the
infrastructure for manufacturing. The Government of India has forwarded a
supporting hand by implementing various initiatives. In the year of 2019 the
government has permitted foreign direct investments of 100 percent in the
sector of contract manufacturing. The Pradhan Mantri Kaushal Vikas Yojna has
facilitated industry oriented skill development to lakhs of prospective
employees. Many hi-tech electronics and communication, luxury brands have
started their operations in India after the availability of the skilled labor.
Industrial corridors, smart cities and integrated supply chains are now trying
to achieve excellence to place India on global manufacturing arena. Catering to
the global market would help India in its exports. Customer orientation is the
key functional aspect of any business. Customers primarily expect five things
from the product like quality, faster delivery, effective cost, variety and
experience with supplier during the lead time. The manufacturing organization
has to strive at its best to ensure customer satisfaction. The research aims to
understand the most crucial operational parameter from the entrepreneurs
perspective that helps them determine the productivity of their manufacturing organization.
Keywords: Operational Parameter, Manufacturing,
Productivity, Entrepreneurs And Quality.
Introduction:
The second industrial revolution embarked between 1870
and 1914 led to life changing innovations like steel, power, moving assemble
lines, telephone, internal combustion engines etc. The revolution connected the
world and made it a smaller place. The second industrial revolution was
predominantly restricted to the western world. With a scattered agricultural
economy, manufacturing soon picked up the pace and became a major economic
contributor in terms of employment, production and catered to the customer
needs (Mokyr, Joel, 1998).The economic situation then led to development of
products and services that became a vital need of the customer. The demand
started to increase exponentially but the supply remained constant. This
situation gave the manufacturers a higher access to the market dynamics. The
manufacturers were often said to control the supply. This left the customers in
a situation where they had no choice but to accept what was put forth by the
manufacturers be it in terms of quality, quantity, variety, cost, speed of
delivery and experience (More, Charles, 2002). There was an unspoken resentment
that lied within customers but with no availability of options the situation
continued to exist the way it was. Seeing the lucrative scope of the market, competitors
started creeping in and dilution of profits began. Slowly and steadily supply
started increasing to cater to the ever growing needs of the customers. The
situation altered soon, supply was now available in excess whereas the demand
for products started to remain as a constant. Organizations now started to
improve their productivity in order to survive the business and earn profits.
The reins of the market were now in the hands of the customer who could be
demanding and decided the fate of the manufacturers. The western world was
getting a taste of customer driven market economies (Mokyr, Joel, 1977).
The era of 1940’s saw another wave of customer
orientation that was evolving in the eastern world. After the World War-II,
Japan was smashed down economically. The Hiroshima and Nagasaki bombings had
destroyed the entire manufacturing hub in Japan. But the country refused to
agree its defeat and took a united decision to rise up from this down trodden
situation. The nation united to a philosophy that if economic situations were
to be improved then employment opportunities had to be improved. Understanding
the skill set possessed by the population , manufacturing seemed to be the
choice of the country. In order to improve the financial state of the country it
was obvious that targeting the global markets and increasing the exports was
the way out to move away from the economic crisis. To move to the global
markets was not an easy task as the global markets were already flooded with
products from the western and Chinese market. Something extra and unique had to
be provided to the customer. One thing had to be kept in the mind that there
was no financial aid that would be available to provide this something extra to
the customers. (Fujita, Masahisa and Tabuchi, Takatoshi, 1997).With significant
leadership the country decided to move ahead. They knew they had to deliver
more with less resources as compared to the western market. Necessity being the
inventor the manufacturing sector started understanding the lacunas of the
western market. They soon learnt that the western market provided a very
limited variety to the customer that created resentment among the customer. The
customers believed this to be conflicting with their personal identity. The
cost for which certain products were offered seemed to be costly. Customers
were subjected to unpredictable waiting periods. The Japanese manufacturers
decided to target these lacunas and converted them into their unique selling
points. Improving productivity now became the chase strategy. (Yamashina,
Hajime, 2000). The research aims to understand the most significant operational
parameter that determines the productivity of the manufacturing organizations.
Literature Review
Productivity all together had a new definition.
Productivity was defined as delivering the best quality product in the shortest
lead time at the most effective cost without compromising the variety that was
to be offered. Resources were limited and wasting them was a blunder. Doing
more with less was the new definition of productivity. The Toyota Production
System formally introduced a production methodology that took the world by
aghast. Till date the Toyota Production system proves to be the most effective
production system. Productivity improvement through their techniques like
identification and elimination of non- value added activities, Quick
Changeovers, Quality Checks at source, Total Productive Maintenance, Kaizen,
Value stream mapping, single piece flow, Just in Time etc are now adopted by
all the successful organizations in the world. The world now looks up to Japan
as the most productive country in terms of its manufacturing strength.
(Drucker, Peter F, 1995)
Being productive demands organizations to constantly
be vigilant. Productivity is an accumulative judgement derived from the
performance of various operational parameters. Focusing on the customer
oriented approach productivity can be derived from the following few
operational parameters:
·
Lead Time
·
Quality
·
Production
Quantity
·
On Time In Full
Delivery
·
Inventory
·
Overall
Equipment Effectiveness
Let us study the impact of each of these operational
parameters on the productivity of manufacturing organizations.
Lead Time:
Online order registration portals have opened up
global markets for organizations. Customers can easily compare the best of the
deals to avail the best offering. Lead time can be described as the time
required to complete a series of operations that includes order registration,
actual production and then the final delivery to the customer. When the order
is actually received by the customer, satisfying his/her expectations, the
duration is termed as lead time. Online portals with an inventory based model
have lured customers with lightning fast deliveries. This has put pressure on
the manufacturing organizations to shorten their lead times as fast as
possible. Lead time provides a competitive edge over the competition but may
involve the use of additional resources to speed up the delivery. Resources
such as additional workforce, better equipment, training, technology may help
organizations deliver in shorter lead time. Lead time tests the operational
performance of the organization as there are many activities that impact the
Lead time. Planning and scheduling often determine the timings when an order
will start processing and when the order will be complete for delivery. Lead
time has three components interlaced one after the other-the first component
being the inbound logistics, the second component being the production and the
third component being the outbound logistics. Production as a component can be
addressed by the organization and improvements related to shortening of the
lead time can be actionable. Inbound and Outbound logistics are often
outsourced and proves to be a difficult area in which the organization can do
anything significant. Lead time is heavily dependent on the material flow in
the organization. When there are a lot of orders pending with the organization
the situation gives rise to accumulation of moving work in progress. The moving
work in progress cumulatively increases the lead time of the new orders
registered in the system. Quality as an operational parameter also impacts the
lead time of the organization. High rate of defects leads to higher rework
which puts a stress on the resources as well the time consumed for production
increases. (Kuhlang, 2011) (Helo, 2004)
Quality:
When long term association with a customer is foreseen
quality is the most uncompromisable factor. Quality is often represented as
adherence to standards, specifications, precision, durability, performance etc.
Organizations often take into consideration the aspect of quality as external
quality delivered in the form of finished goods to the customers. But the game
changer is actually the parameter of internal quality. Quality is often
considered as an investment oriented parameter. It is a myth that quality can
be incorporated into the product only if huge investment in terms of cost are
involved. In fact it is a common myth that the more the number of internal
checks the more the quality incorporated into the product. The Japanese
manufacturing busted this myth by simply delivering quality at six sigma
standards without extravagant expenditure on technology and an increase in the
levels of quality check. The simple philosophy they followed was, that, what
matters the most when it comes to quality is the stage at which it is checked.
If the quality is checked after the production is over, the number of defects
occurring at the end of the process are going to be tremendous. On the other
hand if quality checks are introduced in the beginning itself the defects recognized
in the final stage are few. Early detection leads to prevention is the
underlying philosophy. When quality is checked at the initial stage itself ,
rework being the main cost center of the organization is averted and tremendous
cost savings can occur. Taking elimination of rework as a cost improvement
opportunity too, Pokayoke a mistake proofing technique comes in handy. Quality
as an operational parameter helps organizations achieve customer satisfaction
and create lasting business relationships. Another reason why quality as an
operational parameter is crucial is because it helps in eliminating non value
added costs involved in manufacturing by eliminating the concept of rework that
burdens the resources. (Park, Sung H, 2003) (Deming, W Edwards, 1981)
Production Quantity:
The operational parameter that stands very close to
any entrepreneurs heart is the production quantity. It gives a quick indication
on a daily basis about the state of the organization. Production quantity is
the final defect free output that has been obtained and can be measured on an
hourly, daily, weekly, monthly, annual basis. Production quantity is dependent
on innumerous factors. The availability of quality input material is vital. If
quality material is compromised then a lot of productive time is wasted in
doing the internal check of input, once the input with inferior quality has
been identified a new subprocess of rejecting the material and awaiting the new
material consumes a lot of time and reduces the production quantity. The
involvement of the top management in the production planning and scheduling needs
to be executed by skilled operators to deliver the best output. Any breakdown
in the machine and equipment will lead to reduced availability of the
production time. Contribution of maintenance to production quantities is
significant. An interesting measure of production quantity is, when only the
quantities produced against an order are considered in the quantity. To explain
this further, inter batch changeovers are sometimes quite time consuming. To
avoid the loss of production time organizations produce in big batch sizes
irrespective of orders. This situation technically increases the production
quantity as a whole but creates inventory that has no demand as of now.
Production quantity can often be a misleading figure. Organizations that are
made to stock may have daily targets of production quantities but, creating an
inventory without the demand may lead to investment of working capital that
could cut through the profits. Defects may sometimes too be included in the
count of production quantity and can mislead the entire production system.
Production quantities driven by a registered order and defect eliminated count
are the true count of measuring the production quantity and hence should be
considered as a significant operational parameter. (Wu, YS, 1969) (De Vries,
2014)
On Time in Full Delivery:
Operational Parameters are usually studied in
isolation but with advance developments in the supply chain a new operational
parameter was introduced which was a combination of Lead time and the
Production Quantity. On time in Full Delivery binds together production and
service in a single factor. On time in full delivery is usually expressed in
percentages. All the orders that are fulfilled in a particular time period are
analyzed. Two deciding criteria that are considered in every order is that was
the order completed in totality in terms of the units demanded by the customer.
Has the order been received by the customer in the duration that was demanded
by him/her. If both the criteria are satisfied only then would we say that the
order was completed in On time and in full. The On time in full status of all
the orders are analyzed and a percentage is calculated that, out of all the
orders fulfilled in a particular time how many have been delivered as per the
On time in full criteria. Supply chains today analyze the On time in full
percentage to understand the integrated flow of material and information
throughout the organization. On time in full parameter helps us diagnose that
if the there exists a problem in the production aspect or the delivery aspect
of the organization and effective measures can be taken to improve the on time
in full parameter. On time in full directly impacts the customer satisfaction. Whenever
organizations handle their own logistics it is almost like the organization
runs a supply chain. On time in full delivery acts as a parameter that tracks
the velocity of the supply chain and the production capacity. With an inventory
accumulation in the organization still if the organization is not able to
achieve a good on time in full delivery rate gives it is a clear indication
that the production is not going as per the order management but is being
continued on the preference of convenience over delivery. When the organization
aims to look at operational performance of supply chain as a whole on time in
full delivery is very important. (Ahmad, 2002) (Temponi, 1995)
Inventory:
Financial health of the organization remarkably
depends on the management of the inventory. Different types of businesses
manage inventories in a different ways. Businesses that follow the made to
order model possess very little inventory whereas the made to stock business
model welcomes huge possessions of inventory. If we look into manufacturing of
seasonal goods inventory is accumulated for a restricted period of time and
then for the rest of the period there is no inventory. Traditional management
approach believes inventory to be asset. The modern management approach
contradicts this belief and believes inventory to be a liability. The theory of constraint philosophy of
Goldratt also believes inventory to be liability when it is lying with
organization itself. Inventory can be converted from liability to asset only
when the actual sales of the inventory generates cash to the organization.
(Watson, Kevin J and Blackstone, John H and Gardiner, Stanley C, 2007) The
Toyota production system consists inventory as one of the seven fundamental
wastes that organizations should look forward to eliminate. The Just in Time
manufacturing philosophy considers inventory as a blunder and the possession of
inventory when not needed increases the operational expense of the organization
and sweeps away the profit. Inventory occupies space and requires handling
safety of material which again burdens the organization. The inventory is
classified into three categories , one is the inventory of the raw material,
second is the inventory of the work in progress and the third inventory is that
of the finished goods. Inventory possessed in the form of raw material is still
less harmful. When the inventory is in the form of raw material it has yet not
undergone through any of the process and no additional value added cost is
involved. Inventory in the form of Work in progress is the next dangerous
inventory as working capital has been invested into it but yet returns are to
be awaited. The most dangerous form of inventory is that of the finished goods
because it has consumed all the aworking capital, needs investment in the form
of handling and holding. There are several myths that organizations hold when
it comes to storing excess inventory. One of them is the hope that some urgent
customer order can be fulfilled with the possession of inventory. Sometimes the
availability of labor throughout the year is a problem and pressurizes
organizations to build inventory. Seasonal availability of material, luring
supplier deals, wrong forecasts, incorrect speculations from sales, maintenance
shutdowns, machine breakdowns, planning and scheduling create a havoc in
managing the inventory. (Lieberman, Marvin B and Asaba, Shigeru, 1997)
(Koumanakos, 2008)
Overall Equipment Effectiveness:
Overall equipment effectiveness is an important
parameter for manufacturing organizations that are equipment intensive. The
health status of the machines in an organization directly impacts the
organizations production, maintenance, costs, defect. Overall equipment
effectiveness encompasses three factors
·
Availability
·
Performance
·
Quality
The ideal time available for manufacturing by an
organization can be expressed as the number of working hours. But in reality
these working hours are interrupted with changeovers and unplanned
interruptions like power failure, unavailability of raw material, breakdown
etc. When these losses are subtracted from the ideal working hours we are left
with the actual availability of time. This availability of time is further
subjected to interruptions like reduced speed of operations may be due to
complexity of products or some minor stoppages. When the preceding
interruptions are eliminated from the available time we are left with the
actual operating time where an equipment can actually deliver value added
output. But this operating time is further interrupted with production of
defects that consume the value added operating time. Finally the time when the
machines producing defect free products is known as the fully productive time
of the machine. Overall equipment effectiveness calculates the ratio of the
fully productive time to the ideal working time. An OEE of above 85 percent can
be considered as a gauge to determine the health of the organization. If OEE is
above 85% the organization is good in terms of its operational performance. OEE
is thus considered as an important operational parameter by many manufacturers.(Andersson,
2015) (Muchiri, Peter and Pintelon, Liliane, 2008)
Research Methodology
The research aims to understand the most crucial
operational parameter that determines the“Productivity” for manufacturing
organizations taking into consideration the entrepreneurs perspective. The
primary research involved an exploratory approach by designing a questionnaire
whose respondents were the entrepreneurs of the manufacturing organizations.
The respondents were expected to rank the operational parameters on the basis
of their business acumen and experience. Rank 1 was to be allocated to the most
significant parameter and rank 6 was to be allocated to the least significant
parameter. The operational parameters structured in the questionnaire were
derived from an extensive secondary research from literature like research
papers, articles, news feed. There were 6 operational parameters that were
taken into the construct. The research aimed to understand which amongst the 6
operational parameters is the most significant parameter for a manufacturing
organization. The 6 operational parameters that were taken into consideration
were as follows:
·
Lead Time
·
Quality
·
Production
Quantity
·
On Time In Full
Delivery
·
Inventory
·
Overall
Equipment Effectiveness
The Primary survey was confined to the geographical
area in the district of Mumbai. The population size in manufacturing is 1580
approximately through which a sample size of 100 respondents was obtained using
statistical methods. The sampling techniques used in the primary research were
purposive sampling and quota sampling. The research scholar being a professional consultant could contact the entrepreneurs
through the client based portfolio. Analysis of the data was carried out using
the statistical software of IBM SPSS. Google forms were the medium to circulate
and collect responses from the respondents. As the questionnaire had only one
question which involved ranking hence reliability and validity was ensured by
asking and correcting the questionnaire during the pilot survey. An advanced
multivariate statistical technique known as Friedman’s Rank test was applied to
the coded data that rendered the most significant operational parameter that
impacted the productivity.
Research Objectives:
1.
To study the
operational parameters that determines the productivity of a manufacturing
organization in India.
2.
To identify the
most significant operational parameters that determines productivity of a Small
Medium Enterprise from the entrepreneurs perspective.
The
question that contains the ranking and the operational parameters can be
represented as :
|
Operational
Parameter |
Rank 1 |
Rank 2 |
Rank 3 |
Rank 4 |
Rank 5 |
Rank 6 |
|
[Lead time] |
|
|
|
|
|
|
|
[Quality ] |
|
|
|
|
|
|
|
[Production
Quantity] |
|
|
|
|
|
|
|
[On time - In Full
Delivery ] |
|
|
|
|
|
|
|
[Inventory ] |
|
|
|
|
|
|
|
[OEE - Overall
Equipment Effectiveness] |
|
|
|
|
|
|
The Entrepreneurs were requested to allocate a rank to
every operational parameter and it was made sure that only one parameter could
be allocated to a particular rank.
Research Aim:
To analyze the most significant operational parameters
that determines the productivity of a manufacturing organization.
Hypothesis:
H0 : All the operational parameters determining the
productivity are equally significant from an entrepreneurs perspective
H1 : All the operational parameters determining the
effectiveness are not equally significant from the entrepreneurs perspective
Data Collection and analysis :
The responses gathered from the 100 respondents were
coded in excel and then the statistical software of IBM SPSS was used for
further analysis. The advance multivariate statistical technique of Friedman’s
Rank Test was used for testing the hypothesis. Friedman’s rank Test is a non-
parametric test which is an extension of paired data concept.
Results and Interpretation:
NPAR TESTS
/FRIEDMAN=LEADTIME QUALITY
PRODUCTIONQUANTITY OTIF INVENTORY OEE.
Friedman Test
|
Parameter |
Mean
Rank |
|
Leadtime |
4.41 |
|
Quality |
5.92 |
|
Productionquantity |
3.84 |
|
Otif |
3.17 |
|
Inventory |
2.55 |
|
Oee |
1.11 |
|
Test Statisticsa |
|
|
N |
100 |
|
Chi-Square |
386.389 |
|
df |
5 |
|
Asymp. Sig. |
.000 |
|
a. Friedman Test |
|
The
score distribution of individual parameters is as follows with 6 being the
highest achieved score and 1 being the least achieved score :
|
Score |
Lead time |
Quality |
Production quantity |
On time in full delivery |
OEE |
Inventory |
|
6 |
6 |
94 |
0 |
0 |
0 |
0 |
|
5 |
54 |
4 |
42 |
0 |
0 |
0 |
|
4 |
15 |
2 |
1 |
56 |
25 |
1 |
|
3 |
25 |
0 |
56 |
6 |
13 |
0 |
|
2 |
6 |
0 |
1 |
37 |
54 |
8 |
|
1 |
54 |
0 |
0 |
1 |
8 |
91 |
The
percentage wise contribution of an operational parameter to a score is as
follows:
|
Score |
Lead time |
Quality |
Production quantity |
On time in full delivery |
OEE |
Inventory |
|
6 |
6% |
94% |
0% |
0% |
0% |
0% |
|
5 |
54% |
4% |
42% |
0% |
0% |
0% |
|
4 |
15% |
2% |
1% |
56% |
25% |
1% |
|
3 |
25% |
0% |
56% |
6% |
13% |
0% |
|
2 |
6% |
0% |
1% |
37% |
54% |
8% |
|
1 |
54% |
0% |
0% |
1% |
8% |
91% |
Friedman’s
test is a non-parametric test which is used for testing the differences between
the various groups that are taken into consideration. Mean ranks for each of
the groups is considered and the group with the highest mean rank is the most
significant group. With a sample size of 100 it is observed that the Chi –
Square values are significantly positive. The differences
in the rank have been evaluated statistically at a significance level below
0.000% which is extremely good. This means that the probability of committing
type 1 error is below 0.000%.
As level of significance is below 5.000%, we can
safely reject H0. H0 the null hypothesis states that all the operational
parameters are significantly equal. As we safely reject the null hypothesis we
can conclude that all the operational parameters are not significantly equal.
Conclusion
With the results obtained from the Friedman’s test it
is clear that all the operational parameters are not equally significant. When
productivity is determined from an Entrepreneurs perspective, the most
significant operational parameter that determines the productivity is
“Quality”. Quality is often referred to as the adherence to standards,
specifications, precision, durability, performance etc. and creates long lasting
business relationships with the customer. As per the research, entrepreneurs
observe quality to be the most significant operational parameter that
determines the productivity of their organization.
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