IOT solution approach for Industrial problems. It explains more about problem and solution space.

1. IoT| Product Plan 2021
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Problem Statement
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1. What is the customer problem you are trying to solve? Please elaborate the pain point faced by the
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customer.
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The main challenges and drivers for manufacturing firms are shorter time to market, to increase flexibility and
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higher innovation speed, which will boost efficiency. Factories therefore have to become more interconnected
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internally in order to take advantage of new technologies and adapt to changes within the industry.
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a) Machine operator don’t have real time feedback on machine wear down. It makes him unaware of possible
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breakdown.
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b) Possible breakdown means loss to the productivity of the company and loss in revenue. In case Equipment
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breaks > production halts > he waits for the maintenance person to come fix it.
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c) Operators have been practicing a time-based approach to equipment maintenance. The primary factor in
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planning any maintenance routine was simply the age of the machinery. The older the equipment, the
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more frequent the maintenance procedures would be. For that operator schedules downtime at a
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somewhat arbitrary interval > Operator waits for the maintenance person to remove what may be
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perfectly good parts and replace them with new ones, sacrificing money and production time along the
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way.
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d) In something broken inside of machine, the operator has no idea unless he removes any protective
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shielding. For new operator joins, old operator needs to explain with removes any protective shielding.
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e) In the manufacturing vertical, it isn’t uncommon for there to be a disconnect between workers on the
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production floor and executives and analysts who are assumed to operate separately in their ‘ivory
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towers’. This may mean your business could be missing out on valuable information as well as reducing
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your employees’ investment in its success.
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Persona Role KPI Pain points
Manufacturing
operator
Set up the production equipment and
supplies before executing the job orders.
Operate equipment safely and effectively
for production processing.
Quality
Performance
Safety
Often under pressure and stress
Lack of knowledge
Lack of support when incident
occurs
Lack of information for reporting
Plant manager Watch over and organize daily operations
of manufacturing plants.
Oversee employees, production
and efficiency to make sure
plant is running smoothly,
quickly, efficiently, and safely
Overall
equipment
effectiveness
Budget
Safety
Innovation
Productivity
Lack of skilled operator
Collaborative interaction
Vendor relationships
Frequent changes in plan
User-friendly access to
information
Maintenance
engineer/
Technician
Assure optimization of the maintenance
organization structure
Analyze repetitive equipment failures.
Estimate maintenance costs and
evaluation of alternatives.
Assess needs for equipment replacements
and establish replacement programs
when due.
Overall
equipment
effectiveness
Budget
Alternative
Diagnostic takes too long
because of various systems.
Missing spare parts.
Administration & analysis leads
to longer downtime.
Time-consuming process to find
supporting information.
Always on call as he is senior
person.
Maintenance
manager
Ensure facilities, layout, and machinery
run at maximum efficiency and output.
Preventive maintenance, managing
breakdowns of mechanical
Budget
Complete-
to-do
Limited time to perform
maintenance tasks
Pressure on costs

2. IoT| Product Plan 2021
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budgetary/cost reporting
Executive Look for production improvement.
Look for optimize cost.
Look for safety of employee.
Never wants to refuse order.
Look for improve speed of operation
Revenue
Cost
Safety
Order
Downtime
Don’t want to downtime when it
needs more production.
Schedule maintenance are
increase cost.
Getting stress, when listen
machine breakdown.
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2. Why do you think this problem exists?
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Currently as technology advanced and competition grows, there is a demand to have competitive
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advantage, increase revenue, reduce cost. Traditional automation is excellent at repetitive tasks but has
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difficulty adapting to new or unforeseen circumstances. It is difficult a device early in a workflow could
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inform other machines down the line about errors or upcoming changes, helping them adapt.
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Adding to that a worldwide study from ARC group states that only 18% of equipment fails due to its age.
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The remaining 82% of failures occur randomly. Such findings show that an age-based approach to
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maintenance is not cost effective.
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To avoid ineffective maintenance routines and the high costs that accompany them, manufacturers can
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use Industrial IoT and data science to their advantage
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3. How big is the problem? Can you extrapolate the market size (TAM, SAM)?
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Aberdeen Research reveal 82% of companies experienced unscheduled shutdowns in the past three years.
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Those shutdowns come at a high price. Aberdeen estimates unplanned downtime can:
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a) cost an industrial plant up to $260,000 an hour
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b) last an average of 4 hours
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c) Tangible costs: lost production, lost capacity, lower cost of holding inventory, decrease the labor cost per
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unit
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d) Intangible costs: Responsiveness on addressing downtime than customer service , downtime can cause
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a lot of stress and less time for Innovation
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Internet-of-Things (IoT) market in manufacturing was valued at USD 175.3 billion in 2020 and is expected to
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reach USD 399.08 billion by 2026 and grow at a CAGR of 14.76%.
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4. Why do you think this problem needs to be solved?
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The downtime means loss to the company and it is a crime in Industry 4.0. Predictive analytics is available
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to monitor a tool that can be used to alert teams when high-productivity components, such as pumps,
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fans, and motors, signify they might fail. Condition-based monitoring is when machine learning models
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look for a specific set of conditions that indicate a machine failure may occur. So instead of make
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downtime uncontrollable, we can aim for perfect downtime where operator are able to focus their efforts
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on each individual problem according to the strength of its impact on daily operations without impacting
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the productivity.
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3. IoT| Product Plan 2021
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1st was when mechanization and steam power changed the whole concept of manufacturing.
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2nd revolution happened when mass-production assembly lines and electrical energy took place and enabled
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a giant step in production efficiency.
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3rd revolution brought automation, computers, and robots to production.
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4th
industry 4.0 manufacturing concepts of the future should gain benefits from new sensing technologies, big
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data, cloud computing, artificial intelligence, adaptive robots, smart valves, and autonomous smart control
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applications for bringing maximum added value in smart processes of the next generation to make increase
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production efficiency, reduce waste, decrease manufacturing costs.
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Solution
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1. Which part of the problem (pain point) will you address and solve?
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a) Reduce downtime of repair
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b) Reduction in machine failure
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c) Reduction in maintenance cost
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d) Increase the service life of parts and fix before it damages any other parts
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e) Visibility across plant ecosystem (Operator/Manager/Executive)
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we are looking to address the machine issue, which is going to solve the problem a) to d) and for e) we can do
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once we have enough data to share across ecosystem or we can share the data to existing Dashboard in the
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organization.
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2. What do you think the ideal solution looks like and can you describe a customer experience?
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5 Layers of the IoT Technology Stack used for predictive maintenance.
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We have problem statement for design the solution for 10meter long machine in food processing unit.
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So, I am taking assumption on machine capability and around ecosystem.
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Layer 1 – Device Hardware
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Devices act as the interface between the physical and digital worlds. We can consider for brownfield
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solution where the device that connects to the machine.
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Small devices like smartwatches, we may only have physical space for a System on a Chip (SoC). For more
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demanding solutions, we may need an embedded computer like Raspberry Pi, Arduino, or BeagleBone
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4. IoT| Product Plan 2021
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board. For critical computing needs, we may need advanced industrial computers like compact RIO or PXI.
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All these solutions have different requirements around cost, size, battery life, etc
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For 10meter long manufacturing machine for food processing, we might look for below sensor.
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Thermography, which analyzes equipment while in operation to examine areas that are generating
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excess heat.
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Vibration analysis, which can pinpoint issues with extreme accuracy and even specify the source of
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abnormal vibration.
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Moisture analysis, which utilizes humidity sensors to monitor the water content in hydraulic and
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lubrication oils.
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Acoustic monitoring, which analyzes and translates the acoustics and noises generated by electrical and
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mechanical equipment with moving parts to check for unusual noise.
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Layer 2 – Device software
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The device software is the component that turns the device hardware into a “smart device.” Device
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software allows us to implement communication with the Cloud or other local devices. We can perform
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real-time analytics, data acquisition from our device’s sensors, and even control.
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Building hardware is expensive, and it takes a lot longer than software. So instead of building our device
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for a narrow and specific purpose, it’ better to use generic hardware that can be customized by our device
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software to give us more flexibility down the road using software-defined hardware.
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For 10meter long manufacturing machine for food processing, we might look for below software layer.
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Device Operating System: We will be taking frequent samples to measure temperature / vibration/
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moisture/noise. This produces an enormous amount of data. But we don’t need to send all that data to
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the Cloud—just the data that indicates there’s a problem and act. We can choose Edge OS.
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Device Applications: Device applications run on top of the Edge OS and provide the specific functionality
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for our IoT solution.
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Layer 3 – Communications
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Our device will exchange information with the rest of the world. Selecting the right communication
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mechanisms is a critical part of our IoT product strategy. It will determine not only how we get data in and
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out from the Cloud (for example, using Wi-Fi, WAN, LAN, 4G, 5G, LoRA, etc.), but also, how we communicate
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with third-party devices in the same building.
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For 10meter long manufacturing machine for food processing, we might look for below software layer.
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For us machine usually situated in a smart building with other machine, to communicate with each other
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using the BACnet protocol across local network. More data you transmit, the more it costs.
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Layer 4 – Cloud Platform
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It is the backend of IOT solution. For Cloud we need three elements.
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Data Collection and Management: Collect the data from the smart device.
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Analytics: Its ability to crunch data, find patterns, perform forecasts, integrate machine learning to to find
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insights from our data to makes our solution valuable.
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Cloud APIs: Exposing API to interact with outside eco-system.
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For 10meter long manufacturing machine for food processing, we might look for below Cloud platform.
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For our machine, the data from one machine might not seem like a lot. But over the years, it will add up.
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We more machine, then we need to allow for flexible storage and processing of this data.
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5. IoT| Product Plan 2021
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Cloud analytics might need to process incoming data in real-time to detect trends and be able to make
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predictions of when the machine will need service. Also need to open an API to surface this information
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to ours/other application layer.
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Layer 5 – Cloud Applications
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End-user applications are the part of the system that our customers will see and interact with. These
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applications will most likely be web-based, and depending on our user needs, we might need separate
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apps for desktop, mobile, and even wearables. We can have customer facing and Internal apps. For
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Internal apps, we need to revisit the user and see there needs, so that we can share the data accordingly.
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For 10meter long manufacturing machine for food processing, we might look for below Cloud aplication.
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For our machine monitor, one possible application would be a web app used by machine operators
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working in a central control room. This app displays information and trends of machine that they manage
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and alerts them when a particular machine needs service. The operator can get this information in real-
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time and dispatch the maintenance team to perform preventive maintenance, avoiding costly repairs and
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service interruptions.
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3. What does the proof of concept (POC) look like?
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A low-risk proof of concept is the best way to introduce IoT to company, we make sure experiment with a
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solution in our environment, collect data, and evaluate performance from a set timeline on a set budget.
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We set the goal and determine whether the technology is operating, capturing data, and automating
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actions in its intended design.
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4. How will you capture user feedback to improve features?
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We can talk to each job role described in problem section and get feedback for improvement. We can ask
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if they have any improvement in their KPI.
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