wipro.com
Are You Doing Enough to
Plug Revenue Leaks in Your
Manufacturing Process?
wipro.com
A
tiny Adidas factory in Ansbach,
operating parameters to plant manage-
Germany, is currently drawing
ment. These parameters include excep-
the attention of the manufac-
tions, variance and impending failures
turing world. The factory will produce
and are triggered with events, a funda-
about 1 million running shoes for
mental construct of Industry 4.0 and
Adidas in the next few years! . Called a
super factories. Under the MiQ umbrella
“speed factory,” the highly-automated
we have a variety of applications such as
plant is primarily designed for two
Revenue Leak Analyzer and Smart
things: to bring production back home
Non-Conformance Management. The
to Germany and to give Adidas the
Revenue Leak Analyzer has special
capacity to respond faster to market
significance for manufacturing. Manu-
changes with new types of shoes. A
facturing veterans know that revenue
tertiary aim of the speed factory is
leaks even in well-run Lean and Six
even more exciting — to make shoes on
Sigma operations. It does so for many
demand, using robots to turn out
reasons, starting from variances in plant
customized orders within a day.
to plant processes, mismatched labor
If costs can be kept under check, this
customization represents both growth
and margin expansion opportunities
not possible with traditional manufactur-
and non-optimized planning. What
makes this challenge daunting is the fact
that collecting these parameters takes
significant time, doggedness and cost.
ing lines. So, it comes as no surprise that
The Revenue Leak Analyzer differenti-
forward-thinking companies like Adidas
ates itself from other performance
and BMW are striving to deliver extreme
analyzer tools and methods with its
customization using intelligent digitized
ability of decentralized edge analytics
production processes, connected IT
for real-time dynamic performance
and OT systems and Artificial Intelli-
measure at production unit level for
gence (AI) - all of them being key constit-
product operation activities. Hierarchi-
uents of Industry 4.0.
cal computation enables unit-level
For most organizations, replicating this
level of customization-and all the other
cool things-made possible by Industry
4.0 tools and practices will take several
years of perseverance. Should they wait
5 years to put up a super plant and
harvest the benefits of Industry 4.0? We
think there is a faster way to feel and use
performance metrics to be aggregated
at station and plant level for financial
cost,
productivity
provide
and
business
quality,
to
information
in
realtime. This provides an opportunity
for informed decision-making and to
align
manufacturing
strategy
and
accounting systems.
the power of Industry 4.0. We propose
The truth is that transactional process
raising the Manufacturing Intelligence
loss doesn't receive as much attention
Quotient (MiQ) of manufacturing organ-
as it should. This is with good reason: it
izations using Industry 4.0 practices.
represents the lowest level of detail for
MiQ is a philosophy – a way of collating
operating parameters with the sole
purpose of drawing insights, and giving
profitability management and, in the
past, has been difficult to accurately
track the steady trickle and fix it in time.
instant access and control of critical
!
Source: http://www.adidas- group.com/en/media/news-archive/press - releases/2016/adidas-
expands-production-capabilities-speed factory-germany/
2
Does your plant
have Manufacturing Intelligence
Quotient (MiQ)?
It may help to explain this through an
understand the where and the why of
industry example. Imagine a manu-
poor Overall Equipment Effective-
facturer of sophisticated centrifugal
ness (OEE) data that is somewhat akin
compressors for the auto and home
to understanding why the patient’s
markets. The manufacturer has a
temperature has increased! Compa-
target margin of 36% over the life of
nies are waking up to the fact that the
assembly of a compressor. However,
gaps reducing the value of their data
due to production gaps and process
must be bridged. What is becoming
complexities, there is a significant
apparent is the need for granular,
erosion of margins, which go down as
non-siloed and real-time information
low as 25% at the SKU level. The
pertaining to product margins. These
manufacturer is unable to tell in real
organizations are now ready to
time where the problems are.
embark on the next level of maturity
For a large organization, where the
cost of quality could run into anything
In
from $100 to $250 million, moving
compressor manufacturer, first pass
the needle by even 3% to 4% can be
yield that typically hovers between
significant. The good news is that
79% and 83% could improve to 93%
improving MiQ to plug revenue leaks
after the introduction of a suitable
is relatively simpler than launching
MiQ application. The gain is signifi-
the complete line up of Industry 4.0
cant, and is certainly noteworthy
technologies.
when you consider the fact that no
This second level of detailed data has
a second advantage – it can also be
used to provide root cause data to
Injecting MiQ
into your plant
with MiQ and access significant gains.
our
earlier
example
of
the
changes are required to be made to
the bill of material (BOM), plant
equipment or operations manpower.
Manufacturing plants need applica-
has become much easier today to
tions such as the Revenue Leak
create and deploy these applications
Analyzer that capture data with the
using
right granularity, at the right leak
technologies and real-time analytics.
modern
interfaces,
cloud
points (see Figure 1), in real time. It
3
TPM/
Overall
Equipment
Effectiveness
Machine
•
•
•
•
•
Scheduled stops
System disorders
Setup time losses
Change over time
Short stop and
load losses
• Procedural and
organizational losses
• Rate losses
• Loss of quality machine
Manpower
• System failure due
to faults
• Setup and adjustment
• No–load and short
stops
• Decreased velocity
• Quality losses
• Reduced output and
start-up losses
• Vacation, sick leave,
absenteeism
• Overtime
• Planning losses
• Flow losses
(waiting time)
• Quality losses
• Movements
•
•
•
•
•
• Unused energy
consumption during
production
• Unused energy
consumption with
reduced production
Material
Quality
Process
• Losses due to idle and
small stops
• Capacity losses
• Start up losses
• Operating Losses
• Quality losses
• Losses due to molds,
tooling and fixtures
• Loss of volume
• Inventory losses
Energy
First pass yield
Scrap / rejects
Rework
Customer returns
Assembly yield
•
•
•
•
Loss of quality material
Over production
Inventory – FG/RM
Inventory turnover
Figure 1: Possible Revenue Leak Points in Manufacturing
These applications address the prob-
is here that organizations must consid-
lems of aggregated, dated and siloed
er a technology partner that makes
financial information pertaining to
data the center for all strategic and
margin, inventory and profit. They
tactical change.
solve the problem of margin leaks
with near real-time insights through
process mining techniques applied on
a per unit cost basis and relate it to
process gaps. In other words, a Revenue Leak Analyzer captures the event
that causes the leak at an SKU level,
assigns a cost to the event and shows
this in real time. The trick is to make
sure the expertise to implement the
solution at the right points in the
manufacturing process is available. It
What happens after an organization
or a plant has such MiQ applications in
place? Once the applications are
deployed, the insights they deliver
can be further improved. The clues to
improved performance lie in enriching the analytical data by supplementing it with data from other systems
such as PLM and SCADA. However, as
must be clearly apparent, that is a
topic which rightfully deserves a
deeper discussion in the future.
4
Sudhi Bangalore is General Manager and Head of Smart Manufacturing at
About
The Author
Wipro. With over 14 years of experience in industrial engineering and business
operations across industry segments, Sudhi’s responsibilities include strategy,
market growth and P&L management for Smart Manufacturing. He was involved
in the creation of Plant Technology Solutions group and the go-to-market
partnership with a major European company. Prior to this, he headed Wipro’s
Industrial Automation division.
Sudhi holds a Masters in Industrial Engineering from University of Louisville and an
MBA from Kent University. He can be reached at [email protected].
Wipro Limited (NYSE: WIT, BSE: 507685, NSE: WIPRO) is a leading information
About Wipro
technology, consulting and business process services company that delivers
solutions to enable its clients do business better. Wipro delivers winning
business outcomes through its deep industry experience and a 360 degree view
of “Business through Technology.” By combining digital strategy, customer
centric design, advanced analytics and product engineering approach, Wipro
helps its clients create successful and adaptive businesses. A company recognized globally for its comprehensive portfolio of services, strong commitment to
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please visit wipro.com or write to us at [email protected]
5
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