Manufacturers have long battled the menace of sudden equipment breakdown, leading to unplanned downtime that hinders productivity, timely deliveries, and painful losses. The ecosystem has consistently experimented with multiple approaches that can help them foresee possibilities of equipment breakdown and prevent them in a timely manner. The initial reactive approach to breakdowns was inefficient, leading to extensive losses and adding unimaginable stress to all the stakeholders. Preventive maintenance came as a precious solution,

1. Empowering Manufacturing
with IoT-Driven Predictive
Maintenance The benefits of transforming from reactive and
preventive maintenance to predictive
maintenance
2018
WeMakeIoT

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Executive Summary
Manufacturers have long battled the menace of sudden equipment breakdown, leading to unplanned
downtime that hinders productivity, timely deliveries, and painful losses. The ecosystem has consistently
experimented with multiple approaches that can help them foresee possibilities of equipment
breakdown and prevent them in a timely manner. The initial reactive approach to breakdowns was
inefficient, leading to extensive losses and adding unimaginable stress to all the stakeholders. Preventive
maintenance came as a precious solution, which helped the manufacturing ecosystem avoid equipment
breakdown. But this cautious approach meant a lot of expenses pinching the already tight budget. This
extravagant approach required an effective replacement and that’s where IoT-driven predictive
maintenance comes in as a lifesaver. With connectivity and smart data analytics as its core USP, IoT
technology effectively collates all critical data gathered from the manufacturing landscape, organizes
equipment-critical information, performs in-depth analyses of the organized data, and delivers precious
equipment-critical data that forecasts potential equipment breakdowns with the cause and solution.
Now, that’s the magic wand that the manufacturing ecosystem has been looking for! So, let’s dig deep
into what IoT-driven predictive maintenance is all about and assess the extensive benefits this
application delivers to the manufacturing landscape.

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Contents
Executive Summary ..................................................................................................................................... 2
Introduction ................................................................................................................................................. 3
Why equipment predictive maintenance is so critical for manufacturing .................................................. 3
Why the initial manual maintenance approach did not work ............................................................. 4
Why the preventive maintenance approach was not too great either ............................................... 4
Data-driven IoT solution to the rescue ................................................................................................ 4
How does IoT-driven predictive maintenance work? .................................................................................. 5
Applications of predictive maintenance ...................................................................................................... 5
Predicting and eliminating equipment breakdowns ............................................................................ 5
Fine-tuning equipment maintenance schedules ................................................................................. 6
Enabling worker safety ........................................................................................................................ 6
Smart management of product quality ............................................................................................... 6
Conclusion: Leveraging IoT for intelligent predictive maintenance ............................................................ 6
About WemakeIoT ....................................................................................................................................... 7
Introduction
Manufacturers have long realized the power of leveraging the benefits that a comprehensive digital
transformation can bring to their landscape. They have also realized that the connectivity and data
capture and processing capabilities of IoT technology form the foundation of this exponential
transformation to achieve Industry 4.0. IoT has proven its mettle across all manufacturing domains, from
delivering worker safety and exponentially improving productivity to streamlining inventory. But one of
its most beneficial applications is predictive maintenance, a boon for this competitive industry that has
been battling the challenges of reining in costs. Predictive maintenance successfully minimizes instances
of sudden equipment breakdowns, thus eliminating a common source of production delays. But why is
the industry so obsessed about predictive maintenance? How does this capability deliver smart solutions
across the manufacturing landscape? Let’s take a look.
Why equipment predictive maintenance is so critical for manufacturing
Sudden equipment failure is on top of the list of pain points for most manufacturers. Studies indicate
that equipment breakdown makes for more than 40% of sudden production downtime. This problem
has many aspects to it. For example, loss in productivity, wasted production hours, and increased
expenditure are not just the only serious repercussions of this complication. Manufacturers spend a

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considerable percentage of their resources and attention on manually determining the cause of the
failure, often failing to zero in on the issue that caused the failure. This problem increasingly happens
during the initial phase of an equipment installation, when the stakeholders are not clear about the
functionality of the equipment, and during the later stages of an equipment’s life where part failures are
a result of its reducing functionality. Both these reasons make maintenance a challenge for most
manufacturers. The need to ensure that critical equipment is available in perfect form, without the risk
of any failures or need for repairs, is an essential determinant of seamless production and high quality
output.
Why the initial manual maintenance approach did not work
One of the initial approaches that manufacturers applied was to use manual tracking of maintenance
schedules and data to identify scope for possible errors, including nonfunctional parts that required
replacement. Interpreting all the data gathered from equipment manually was exhaustive and the initial
response to equipment failure in this mode of approach was primarily reactive in nature. As a result, it
was never really possible to avoid issues and complications entirely, leading to extensive cost of
maintenance and production downtimes.
Why the preventive maintenance approach was not too great either
The solution to this problem was to get into a proactive mode, with preventive maintenance. This
approach involved efficient planning to carry out detailed equipment maintenance to evaluate the
entire equipment to determine any need for repair or replacement. While this approach definitely
helped resolve loss from unexpected downtime, this approach could not avoid downtimes entirely.
Every preventive maintenance schedule meant shutting down the equipment operations and loss in
time and money. In addition, this approach was not economical since it led to a lot of preventive part
replacements even when they were functional. So the industry was on the lookout for a smart solution
that could simplify the equipment maintenance challenge.
Data-driven IoT solution to the rescue
With the advent of smart technology that ushered in Industry 4.0 through a comprehensive digital
transformation, the entire manufacturing ecosystem began to notice the extensive amount of data that
every node of the landscape was generating. But across most industries most of this data was being
ignored. For example, some industries such as the oil and gas were utilizing just about 1% of the total
data generated. Similarly, the current designs of automotives generate humungous amount of data,
most of which do not even see the light of the day, leave alone being available for analytics. The entire
process of capturing all this data, isolating the relevant information, tweaking and analyzing them to
retain just the required information and deriving patterns, forecasts, and other insights from this data
packets seemed quite like an exhaustive exercise. Moreover, by the time the data insights were made
available, it was way beyond the “real-time” requirement of the industry. Such instances of historic
information were not of much use to resolve the current equipment issues.
IoT-driven predictive maintenance came as a perfect solution in this scenario, with the connected
environment and extensive data management abilities of this technology delivering the much-desired
real-time insights for immediate decision making regarding equipment management and possibility of

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equipment failure. Predictive maintenance has hence benefited manufacturing stakeholders to move
from reactive and preventive approaches to taking proactive measures in managing their equipment,
avoiding sudden and unplanned downtime. This approach has also considerably extended equipment
lifetimes, bringing immense operational efficiency into the system. Studies have confirmed that IoT-
driven predictive analytics has indeed arrived into the manufacturing ecosystem with a bang, with a
compound growth rate of about 40% annually, delivering efficiency gains in maintenance to the extent
of about 25%.
How does IoT-driven predictive maintenance work?
IoT devices and sensors present across multiple locations of the equipment across the production prcess
have the ability of capturing select equipment-specific data such as temperature, pressure, vibration, or
humidity. The captured data is compared against preset thresholds and analyzed using cognitive
algorithms to deliver far-reaching and immediate insights that relate to the health of the equipment.
This real-time approach provides manufacturing stakeholders to take smart and timely decisions about
their equipment’s maintenance, repair, and replacement needs well in advance.
The extensive insights also provide them with a critical task level visibility of every minute aspect of their
machines and processes so they can easily and accurately identify and resolve any blocks in the process
or intricate part issues well in advance. The IoT-driven connected environment communicates effectively
across the ecosystem to ensure complete and thorough data capture. IoT platform provide immense
scope for customization and its secure cloud-based functionality provides extensive storage options
without compromising on data safety. Edge computing capabilities in turn reduce data overload across
the system, ensuring that only equipment-relevant data are delivered to stakeholders. With ample
scope for scaling up and expanding operational capabilities including driving mobility-enabled predictive
maintenance, IoT solutions also enable seamless integration with third-party and legacy applications to
simplify smart adoption of the solution across the ecosystem.
Let’s find out a little more about each of the IoT-driven applications of predictive maintenance.
Applications of predictive maintenance
Predicting and eliminating equipment breakdowns
IoT sensors and devices coupled with intelligent technology can deliver state-of-the-art predictive
analytics on equipment maintenance, forecasting and alerting potential challenges before any issue
occurs. This completely eliminates misplaced assumptions about equipment status, providing end-to-
end information about equipment performance and preventing unnecessary machine downtime.
Manufacturers are applying IoT-driven predictive maintenance and the technology’s connectivity to
communicate potential implications of possible equipment breakdowns through automated notification.
For example, aging equipment parts that show indications of failing can be immediately located by
observing their specific properties such as vibration patterns, and faulty parts can be replaced before

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they become the sole cause of equipment breakdown, preventing further increase in expenses and
delays. This also extends the lifetime of equipments, leading to further cost savings.
Fine-tuning equipment maintenance schedules
Predictive maintenance is important for planning maintenance schedules only when they are required,
and not blindly planned on a preventive mode. This helps organize maintenance schedules based on
equipment availability and possibility of breakdown, as per the in-depth insights delivered by IoT
devices. Predictive maintenance promptly delivers detailed analytics of machines and even parts, at a
frequency that can be set based on requirement. The approach can help the manufacturing team’s fine-
tune production schedule and plan their inventory accordingly. This approach can also help trigger self-
maintenance mechanisms based on specific threshold values. This organized approach of planning
maintenance schedules helps minimize costs, increase operational efficiency, reduce time to market,
and optimize availability of assets.
Enabling worker safety
Worker safety is a valuable application of predictive maintenance, when equipment failure can pose a
serious risk to human safety. For instance, increasing pressure, decreasing temperature, or reduced
oxygen levels in a production environment can be hazardous for workers; hence any such sudden
variance in equipment parameters indicate impending breakdowns or serious repercussions, which can
trigger immediate preventive actions.
Smart management of product quality
Ineffective equipment management and unexpected machine breakdown not just causes delays but also
affects the product quality, leading to defective products. For example, faulty parts in a production
environment that delivers high-precision components is completely dependent on maintaining accurate
equipment parameters, especially for components required in the pharma and medical devices verticals.
Smart predictive maintenance can highlight possibility of even minor deviations in equipment
performance, thus eliminating possibility of product quality issues.
Conclusion: Leveraging IoT for intelligent predictive maintenance
IoT-driven predictive maintenance delivers real-time critical insights on equipment performance telling
you when it needs maintenance; analyzes process and equipment blocks in-depth to propose
improvements and deliver warnings about the entire maintenance exercise; and completely eliminates
the need to dive into mounds of data to determine problems with equipment performance. The journey
from manual equipment reviews for possibility of breakdown and maintenance to preventive
maintenance and finally to predictive maintenance has been long and painfully challenging. But with the
power of disruptive technologies such as IoT and digital transformation, the power of a connected
manufacturing ecosystem and data management capabilities have brought confidence to the landscape.
Manufacturing verticals are confident about exponentially enhancing their operational efficiencies
through intelligent management of equipment maintenance through real-time alerts and insights,
forecasts, and pattern-based studies. But the need of the hour is a strong technology partner who can
support you in this critical journey.

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WeMakeIoT is your ideal technology partner who can help you in this IoT-driven journey toward complete
digital transformation. Experience the exponential benefits of IoT's transformative power through connected
enterprise assets, real-time monitoring, end-to-end visibility, and remote management of the entire
manufacturing ecosystem. Make your factory smart with the support of our IoT and data analytic experts who
can deliver to you completely customized manufacturing solutions across all verticals, from food processing to
the automotive industry.
About WemakeIoT
WemakeIoT is your technology expert who empowers you to convert the limitless data generated from
your manufacturing ecosystem into meaningful and directional insights through a smart combination of
intelligent sensors, secure network protocols, and effective data capture and analytics. WemakeIoT
prudently connects your critical enterprise assets to create an intelligent and well-integrated network of
smooth-functioning equipment, well-optimized processes, and efficient people. So, wherever you are in
your journey to Industry 4.0, just let us know what your pain points are and we will deliver the perfect
IoT-enabled solution to conquer all your manufacturing challenges.
For more information, connect with WeMakeIoT today: http://www.wemakeiot.com/discrete-
manufacturing/
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