Pharmaceutical Commerce - July/August 2017 - 24

Manufacturing & Packaging
Digital factory transformation beyond serialization compliance
By Evren Ozkaya, Supply Chain Wizard, LLC

"Serialization" is like a new
blockbuster drug for supply chains that
is used in the "treatment" of counterfeiting
or falsifications, while also helping with the
quality and integrity of supply chains. Truly
a game changer. It is already in the works in
more than 40 countries around the world,
and more countries are getting ready to adapt
this new treatment. However, like every great
drug, there are always some side effects, which
you might miss, unless you read the fine print
(i.e., talk to experts or early adaptors). For
serialization, these side effects are not to be
underestimated, as it can make parts of your
supply chain quite miserable, while trying to
improve the others.
Two of the main side effects of serialization
compliance is the loss of efficiency in
packaging operations and warehouse
operations. As manufacturers are getting
ready to comply with the US Drug Supply
Chain Security Act (DSCSA) and the EU
Falsified Medicines Directive (FMD), a few
thousand manufacturers will go through this
painful journey of installing and validating
new serialization (and aggregation) hardware
and software on their packaging lines. An
estimated 10,000+ lines will eventually be
upgraded, and industry surveys suggest that
the majority of these implementations have
not even started yet. As the deadlines for
manufacturers/packagers come before the
3PLs and wholesalers, let us focus on the "side
effect #1": overall equipment effectiveness
(OEE) loss in packaging lines.
As one of the early movers in this field,
Supply Chain Wizard has helped a variety
of manufacturers implement serialization
compliance solutions around the world,
spanning most of the leading packaging line
solution providers. We can conclude that, in
almost all cases, there is an inevitable loss of
OEE. Key questions that the manufacturers
should be asking are:
- Why do we have OEE loss due to
- How much is the expected efficiency
- What can we do about it?

The efficiency losses happen because there
is a set of new equipment being introduced
to the line with additional reject bins. New
reject bins imply more rejects (i.e., reduction
in throughput) and more machines imply
more downtime by default. On top of that,
the complexity of these systems requires
more training, and the human factors
added to the equation are causing even
more stoppages on the line. Typical loss is
around 5-10% of OEE, after the ramp-up
and stabilization of the operations. However,
early on during ramp-up, losses of more than
30% have been observed. In rare instances,
the OEE losses could be mitigated by
introducing some level of automation to the
line, which require additional investments.
The main challenge the industry is facing
is that these levels of efficiency losses could
mean the difference between profitable
and non-profitable businesses, especially
in the contract manufacturing/packaging
world. For all manufacturers, it means direct
negative impact to the bottom line, in terms
of higher cost of goods sold.
Once the manufacturers go through
their own initial line implementations and
resulting efficiency losses, proactive ones
start contemplating pilot projects to improve
OEE levels. Measuring OEE baseline before
any action is taken is a fundamental first step
towards minimizing the losses. The baseline
data collection, however, should be "digital"
in order to be repeatable and sustainable,
instead of being paper based. As the digital
data collection on the line activities ramp
up, the foundation for a "digital factory
transformation" is being put in place.
Serialization compliance solutions are only
putting verified unique serial numbers on
each pack, while an activity we'll call "digital
activity tracking" will start enhancing
the serial number data with operational
data in such a way that will enable the
humble beginnings of a "Digital Factory
Digital Factories are the factories of the
future, whereby every process or activity,
personnel and product is tracked at granular
levels, and such information collected
from the operations is used for generating

Fig. 2. Wireless monitors can gather data for an overall "digital factory" view.
24 Visit our website at July | August 2017

Fig. 1. A serialization program can be the first step toward managing
overall packaging line performance. Credit: SCW

insights (e.g., exceptions, trends, patterns,
projections) and for better data-driven
decisionmaking (e.g., asset replacement,
work order schedules, staffing levels and
more). Over time, these systems will turn
into learning systems, where more data
and insights are used in more automated
decisionmaking, creating a virtuous circle of
continuous improvement. (Fig. 1)
Digital Factory Transformation in 3D
The digital factory of tomorrow will be
in "3D": Data, Dashboards and Decisions,
a three-phased digital transformation
process to enable the promise of smart
manufacturing (what is coming to be
known as Industry 4.0). The 3D journey is
from data to dashboards to decisions, from
more basic and lower-value drivers to more
sophisticated and higher-value drivers.
First, let's better define these three horizons
of transformation:
* Data: Enriched dataset at the level of
unit via unique serial numbers and product
visibility along the supply chain is just the
beginning of a major data transformation.
Internet of Things (IoT) technologies, such as
wireless sensors, provide many opportunities
to enhance datasets collected by traditional
transaction-based systems like ERP, MES and
WMS. Unit level product tracking (status,
location, environmental factors, duration,
carriers, etc.) together with data enrichment
processes to associate commercial data (e.g.,
price, discounts, chargebacks, returns) to
the serial numbers will dramatically increase
supply chain visibility.
* Dashboard: The ability to convert
sets of data into meaningful and actionable
insights through business and management
metrics and visualizations, via rolespecific dashboards. For example, a digital
factory manager would be able to see a live
dashboard of all their production lines with
their status (running, down, idle) and the
analysis of why the lines are not performing
per their target OEE levels for a given time

period. Using these dashboards, business
patterns could be highlighted, and issues
can be addressed faster and more effectively.
Similarly, positive outcomes could be
measured and input conditions could be
replicated at most granular levels (e.g.,
Operator A runs product X on Line 1 on
Mondays more efficiently than any other
* Decisions: Decisionmaking is the
ultimate change in behaviors that impact
operations. Therefore, data and dashboards
are only useful if the management is
changing their actions accordingly. In
the ultimate sense, the decisionmaking
process could also be digitized by the use
of optimization algorithms and machinelear ning systems. For example, the
scheduling of work orders to the packaging
lines with the use of real-time data on
line efficiencies, staff schedules and line
availabilities could bring significant cost
savings due to overtime/waste reduction,
while increasing capacity and throughput.
OEE Tracker in Action: A Case Study in
Factory Digitization
Late in 2015, one of our clients was
faced with the challenge of significant
efficiency loss while upgrading their pilot
bottle-packaging line with serialization/
aggregation technologies-they wanted to
optimize their line efficiency despite these
challenges, as they were concerned with
overall impact to the site after achieving
serialization compliance. (Fig. 2) After
taking some time to understand the unique
nature of the issues, we jointly developed a
solution designed to help optimize the way
they track their operations-digitally; later
we named the solution as "OEE Tracker."
As the pilot project continued over 12
months, expanding into all the packaging
lines at the site, it became clear that the OEE
continued on page 26

By Evren Ozkaya, Ph.D., is founder and
CEO, Supply Chain Wizard, LLC.

Table of Contents for the Digital Edition of Pharmaceutical Commerce - July/August 2017

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Pharmaceutical Commerce - July/August 2017 - Table of Contents
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Pharmaceutical Commerce - July/August 2017 - Cover4