IoT For OEMs: How Can OEMs Benefit from IoT 

The Internet of Things is a network of linked devices equipped with sensors, software, and communication capabilities. This technology holds the power to revolutionize the way Original Equipment Manufacturers (OEMs) design, manufacture, and support their products. IoT for OEMs enables real-time data collection, analysis, and remote control, paving the way for a new era of intelligent, connected products.

This guide aims to provide OEMs with a comprehensive roadmap for harnessing the potential of IoT. We’ll delve into the specific ways that IoT can transform your products, operations, and customer experience.

What is IoT For OEMs?

IoT adds a layer of digital smarts into the products that OEMs manufacture. This is achieved by adding tiny computers, sensors, and software directly within the equipment itself. This empowers them to gather real-time information about their products, such as how they’re being used, how well they’re performing, and the surrounding conditions. This data can involve a wide range of standards, including temperature, energy consumption, and even wear and tear on components. 

Furthermore, these connected products can then transmit this valuable data over the internet to a central location or other systems, where it can be further analyzed to extract deeper insights. This connectivity also allows for remote adjustments to be made to the products themselves. This could include receiving instructions, software updates, or even having their functions modified remotely.

Key market trends of IoT in manufacturing

Precedence research says that the IoT in the manufacturing market experienced significant expansion in 2022, valued at an estimated USD 202 billion. Projections indicate continued rapid growth, with the market potentially reaching USD 1829.21 billion by 2032. This represents a substantial CAGR of 24.70% during the forecast period (2023-2032).

Several major companies across various sectors are actively leveraging IoT technologies within their manufacturing processes. This includes automotive giants like Ford, GM, and Tesla, aerospace leaders such as Boeing and Lockheed Martin, industrial powerhouses including Siemens, Bosch, and GE, and consumer goods manufacturers like Samsung and Foxconn. IoT is transforming manufacturing through real-time equipment monitoring, predictive maintenance to reduce downtime, increased automation throughout production lines, optimized supply chains, and enhanced quality control measures.

Factors Driving IoT Adoption in the OEM Industry 

The adoption of IoT within the manufacturing sector is accelerating and becoming increasingly crucial for OEMs. Here are the key factors driving this transformation:

Operational Efficiency

In manufacturing, every wasted minute and every unexpected breakdown translates to lost money. IoT puts a spotlight on those issues. Sensors track how machines are running, monitor material usage, and even listen for those subtle changes in a motor that signal a problem’s brewing. Catching issues early means your team can fix them before they cause major headaches.

Data-Driven Decision-Making

OEMs collect data all the time, but IoT takes it to the next level. It’s about real-time insights into how your products are actually used in the field. Which features get heavy use? Are there common pain points for customers? That kind of information is crucial for improving your next product generation and tailoring your support offerings. Forget guesswork; this is about making data-driven decisions.

Enhanced Customer Experience

IoT unlocks incredible potential for customer service. Remote diagnostics, troubleshooting without sending a tech on-site, and over-the-air updates that fix bugs or add features… that’s the kind of responsiveness that builds loyalty. Plus, you can offer usage-based subscriptions – all thanks to the data flowing in from your connected products.

Cost Reduction

Building an IoT solution isn’t as complex or costly as it once was. There are powerful cloud platforms out there that handle the tricky bits, the sensors are getting smaller and cheaper, and the time it takes to see a return on your IoT investment is shrinking.

Competitive Pressure 

The reality is that your competitors are exploring IoT if they are not already using it in some form. Customers are starting to expect connected products and the benefits that come with them. For OEMs, staying at the forefront of innovation is about more than just bragging rights; it’s about staying relevant in a rapidly changing market.

IoT Applications for OEMs

Predictive Maintenance

IoT sensors embedded within equipment continuously collect data on various operating parameters. These can include measurements like temperature, vibration, power consumption, and more. By analyzing this data, OEMs can develop algorithms that detect subtle patterns indicating a potential malfunction. Rather than waiting for breakdowns, OEMs can proactively schedule maintenance or replacement of parts, significantly decreasing the downtime and minimizing the impact on their customers’ operations.

Remote Monitoring & Diagnostics

IoT connectivity empowers OEMs to remotely monitor equipment health, troubleshoot issues, and even perform firmware updates from afar. This capability streamlines support processes and often resolves problems without the need for costly on-site technician visits. The result is faster resolution for the customer and lower support costs for the OEM, fostering a stronger, more trusting relationship.

Data-Driven Product Development

IoT gives OEMs an unprecedented view into how their equipment functions in real production environments. Detailed data on usage patterns, operating conditions, and the causes of common failures becomes a powerful resource for product development teams. This data illuminates opportunities to improve future iterations, making equipment more reliable, efficient, and better tailored to customer needs.

Value-Added Services

OEMs can leverage the steady stream of IoT data to transition from purely selling products to offering ongoing, value-added services. These new revenue streams could include remote equipment monitoring, proactive maintenance alerts, performance optimization recommendations tailored to a client’s environment, and reports that provide actionable insights and business value to the customer.

Increased Supply Chain Visibility

IoT sensors don’t just track finished equipment – they can enable end-to-end visibility throughout the supply chain. OEMs can track the movement of components, gain insights into inventory levels in real time, and proactively identify potential delays or bottlenecks. This data-driven approach allows for better production scheduling, minimizes disruptions due to missing parts, and ultimately ensures that products are delivered on time.

Key components required for IoT in OEMs

Implementing a successful IoT solution within an OEM setting involves more than just picking sensors and connecting things to the internet. Each component needs to be thoughtfully selected and integrated to achieve the project’s specific goals. Let’s break down the essentials:

Sensors & Actuators

Sensors: These devices serve as the foundation for any IoT project, meticulously converting physical phenomena into interpretable data streams. Beyond the common types that measure temperature, vibration, pressure, and flow, there exists a wide array of specialized sensors capable of monitoring everything from air quality to strain on specific components. Matching sensor capabilities to the precise metrics you want to track is crucial.

Actuators: Actuators allow for remote adjustments and direct control of physical components. Their capabilities range from triggering simple on/off actions for valves or switches to orchestrating precise movements with industrial motors. Integrating actuators opens opportunities for automation, proactive maintenance intervention, and dynamic process optimization.

Considerations: Accuracy and precision should align with application requirements. Industrial settings often demand sensors and actuators capable of operating reliably within harsh environments characterized by extreme temperatures, dust, moisture, or vibrations. For battery-powered configurations, power consumption becomes a critical design factor – driving careful hardware selection and efficient firmware development.

Gateways vs. Smart Devices

Smart Devices: In simpler deployments, individual devices may connect directly to cloud-based services, transmitting data and receiving instructions. This streamlined approach works well for scenarios with a limited number of sensors and minimal local processing requirements.

Gateways: These devices act as intermediaries between field-level sensors and actuators and the wider IoT infrastructure. They aggregate and pre-process data locally, reducing the volume (and thereby the cost) of data sent to the cloud. Just as importantly, gateways can translate between different communication protocols, facilitating seamless interaction between devices from various vendors and simplifying system expansion. When real-time decision-making and fast response times are critical, gateways enable a more responsive edge-centric architecture.

Connectivity

Selecting the optimal connectivity technology is key and depends heavily on your unique use case:

• Cellular: Offering wide coverage and ample bandwidth, cellular networks (4G/5G) are well-suited for scenarios demanding high data rates or video transmission. Considerations include increased cost and higher power consumption.
• Wi-Fi: A familiar standard for indoor environments, Wi-Fi provides reasonable speeds and is cost-effective to implement. However, range limitations must be factored into deployment planning.
• LPWAN: Specifically designed for long-range, low-power sensor networks, LPWAN technologies (like LoRaWAN or Sigfox) are ideal for devices communicating infrequent updates. Their extensive coverage and power efficiency make them attractive options for battery-powered sensor deployments.
• Wired: In controlled factory settings, traditional wired connections (Ethernet) still play a role due to their inherent reliability and strong security profile. However, they lack the flexibility of wireless solutions.

Firmware

Security: Treat security as a top priority throughout the development process. Use robust authentication and encryption mechanisms and establish a reliable process for regular over-the-air (OTA) firmware updates to address vulnerabilities promptly.

Power-Efficiency: Especially for battery-powered devices, meticulous firmware optimization can significantly extend operational lifespan. This includes efficient code design, minimizing processor usage, and effectively leveraging low-power sleep modes when possible.

Software

Architecture: Embrace modular software designs that separate data processing, analytics, and user interfaces. This approach facilitates maintainability and enables selective upgrades.

Cloud vs. Edge: Carefully evaluate the tradeoffs between cloud and edge computing models. While the cloud offers scalability and ease of access, processing data locally at the edge can reduce latency and provide greater autonomy, which may be essential for time-critical or remote applications.

Growth: Your software platform must gracefully handle the ever-increasing volume of data generated by your expanding IoT deployment. Plan and choose a solution designed to scale alongside your system requirements.

Telemetry Data Collection in IoT for OEMs

The constant stream of telemetry data generated by IoT devices holds the key to unlocking informed decision-making for OEMs. Understanding the mechanics of how this data is collected is crucial. Let’s examine the various approaches to telemetry data collection, exploring the tradeoffs that influence everything from battery life to the speed of critical alerts.

Push vs. Pull: Choosing the Right Approach

OEMs must decide whether to use a ‘push’ or ‘pull’ model for collecting telemetry data. In a ‘push’ model, devices send data autonomously, either at regular intervals or when a significant event occurs. This is ideal for critical systems with a need for immediate alerts or real-time visibility. The downside is that frequent updates can drain batteries and increase the network load. 

The ‘pull’ model has servers request data from devices periodically, giving finer control over transmission times and potentially reducing power draw for battery-operated devices. However, this approach introduces latency, meaning data may not be entirely up-to-the-minute.

Data Formats: Balancing Efficiency and Simplicity

The format of the telemetry data directly impacts transmission efficiency. Structured text formats (like JSON or XML) are easy for most systems to interpret but can be larger due to their text-based nature. More compact binary formats (like Protocol Buffers) save bandwidth and storage space but require specialized code for encoding and decoding, introducing some complexity.

Optimization Techniques

Getting the most out of your network is crucial. Batching data (grouping readings together before sending) minimizes transmission overhead and is especially useful for stable measurements that change infrequently. Similarly, filtering can significantly reduce data volume by instructing devices only to transmit values that change significantly or fall outside of pre-defined ranges.

Hybrid Approach: Tailoring Data Collection to Needs

Real-world scenarios often demand a flexible strategy. Consider the example of a heavy machinery manufacturer. They could ‘push’ critical vibration readings in real-time for immediate failure detection while opting to ‘pull’ less urgent performance metrics at regular intervals. Routine sensor readings could be batched for efficient transmission, and GPS coordinates could be intelligently filtered only to transmit updates when the equipment has moved significantly.

Data Storage Considerations in IoT for OEMs

The constant influx of IoT data requires OEMs to make strategic decisions regarding where and how to store it. Let’s explore database options, each with its unique advantages, and discuss factors influencing the best fit for your specific needs.

Time Series Databases

Time series databases are a powerful solution for storing and managing the continuous stream of data generated by IoT sensors. Unlike traditional databases, they excel at storing data alongside its timestamp, making it easy to analyze how readings change over time. This capability is crucial for OEMs seeking to:

• Understand equipment performance trends: By visualizing historical data, OEMs can identify gradual changes in performance that might signal the need for preventative maintenance, avoiding costly downtime.
• Troubleshoot issues: Quickly comparing current readings to historical data from a time when things were functioning correctly can pinpoint potential causes of malfunctions, leading to faster resolution times.
• Implement predictive analytics: By analyzing historical data, algorithms can be trained to predict failures before they happen by spotting early warning signs in sensor readings. The subtle vibration patterns might change well ahead of a critical bearing issue, allowing for proactive maintenance and preventing costly breakdowns.

Cloud Databases

Cloud-based databases offer a flexible approach with minimal upfront setup or hardware investment. This leads to quicker deployment times compared to on-premise solutions. As your IoT deployment grows, storage and computing capacity can be seamlessly expanded to accommodate the increasing data volume. In addition, many cloud vendors offer built-in analytics and visualization tools specifically tailored for IoT data. This ease of integration can significantly streamline the time it takes to generate value from your data. However, OEMs should be mindful that very large datasets or the frequent use of analytics services can lead to higher costs with cloud-based solutions.

On-Premise Databases

For projects with a need for precise control over the underlying hardware and database configuration, on-premise solutions offer maximum customization potential. This allows for fine-tuning the database configuration to the exact needs of the project, potentially leading to performance optimizations. In scenarios where OEMs generate massive volumes of data, there’s often a point where the upfront investment in on-premise hardware is offset by long-term cost savings compared to cloud solutions. However, the tradeoff is the increased overhead of managing servers and IT infrastructure in-house.

How to Choose?

The best data storage strategy for an OEM depends on several key factors. Start by considering the volume of data: smaller deployments often favor the simplicity and lower upfront costs of cloud solutions, whereas very large datasets might become more cost-effective when managed on-premise. If minimal latency is crucial for real-time decision-making, an on-premise solution might be necessary. Finally, OEMs should evaluate their analytics needs – often, the built-in tools and potential for machine learning capabilities offered by cloud providers make them an attractive option.

Data Visualization Components in IoT for OEMs

Let’s explore the essential components of effective IoT data visualization, including dashboards, proactive alerts, and intuitive analysis tools.

Dashboards

Dashboards are key to making sense of all the information from your connected equipment. They give you real-time updates on equipment health so you can catch problems early. Plus, dashboards reveal trends over time, helping you notice small performance changes that might signal the need for maintenance before something breaks down. If your equipment moves around, map visualizations make it easy to keep track of everything so you can make the most of your assets.

Alerts

Automated alerts can help OEMs transform how they handle maintenance – shifting from just fixing things when they break to actively preventing issues altogether. You can set up notifications to warn you when sensors detect potential malfunctions, like unusual vibrations or rising temperatures. Alerts can streamline maintenance by actively reminding you when regular checkups are due. These reminders can be based on actual machine usage, improving efficiency. Even quality control gets a boost! Alerts immediately flag when sensor readings fall outside of acceptable ranges, helping you catch and address potential defects early.

Visualization Tools

The best visualization tools are both user-friendly and feature-rich. Look for platforms with drag-and-drop dashboards so your engineers and operators don’t need to be data experts to understand what’s happening. Ideally, these tools should also “play nice” with your other systems, pulling in data from around your business to give you a more complete picture of what’s going on. Advanced features like machine learning take things to the next level, helping you spot potential problems well before they become serious.

Security Considerations For OEM Integration with IoT

 A single compromised device can act as a gateway for attackers, potentially disrupting operations, stealing sensitive data, or even causing damage to equipment. Let’s dive into the methods and best practices for securing your IoT devices and protecting your business.

Device Authentication

Authentication ensures only the devices you trust are allowed to connect to your network. Using certificates for authentication is a strong approach. Each device gets a unique digital ID card (certificate) during manufacturing, proving its identity to your systems. It’s crucial to have a secure process for adding new devices to your network – that’s when they get their certificates, so you want to make sure that process is tightly controlled.

Data Encryption

Encryption disarranges your data, making it unreadable to anyone who shouldn’t see it. You need to protect both data at rest (stored on the device itself) and data in transit (moving across the network). It’s a bit of a balancing act: the stronger the encryption, the more protected your data will be, but strong encryption also takes more processing power, which can be a concern for battery-powered devices.

Security Best Practices

Staying on top of security is an ongoing process. Here’s a checklist of key items to keep in mind:

• Know Your Weaknesses: Stay updated on vulnerabilities in the software your devices use and have a reliable process for pushing out firmware updates to fix those issues.
• Minimize Hacker Entry Points: Disable anything you don’t need on your IoT devices – close those extra doors attackers could try to sneak through. Firewalls and network segmentation help isolate your devices, further limiting an attacker’s ability to cause damage.
• Assume Nothing is Automatically Safe: Don’t inherently trust any device or user connected to your network. Continuously verify identities and make sure no one has more access to your systems than absolutely necessary to do their jobs.

IoT for OEM deployment process

Here’s a breakdown of the key phases when an OEM deploys an IoT solution

Planning & Design

Before deploying any IoT devices, it’s crucial to have a solid plan. Start by specifying your goals: are you aiming to prevent breakdowns, help your customers use the equipment more efficiently, or offer new subscription-based services based on the data? Once you know your goals, you can start selecting the right sensors and figuring out how you’ll connect devices to the internet. Choosing an IoT platform for collecting, visualizing, and analyzing all that data is another essential step in the planning stage.

Development & Integration

This is where your plan turns into reality. You’ll need to create or modify software (firmware) for your devices, making sure they collect the right data and are secure. If you’re adding IoT to existing equipment, this phase is where you’ll install sensors and wireless modules. Next, you’ll set up the cloud systems that will handle the data coming in, as well as any dashboards or analytics tools you want to use.

Deployment & Commissioning

First, make sure the customer’s site is ready – does it have the right network connectivity for your devices? Once that’s good, there’s a secure process for adding devices to your system (you don’t want unauthorized devices accessing your data!) Finally, test everything to ensure data is flowing correctly, dashboards are working, and any alerts you’ve set up are functioning as intended.

Operations & Maintenance

IoT isn’t “set it and forget it.” You’ll want to monitor the health of your devices so you can troubleshoot issues quickly. Prepare a secure system for sending out firmware updates since these often contain security fixes and important new features. Finally, start using the data you are gathering by setting up dashboards to monitor trends and configuring alerts for situations that need attention.

Scaling & Growth

As your IoT solution grows, make sure your systems are designed to handle more customers and devices without slowing down. Your support staff will need to be prepared for new kinds of requests related to the IoT data. Most importantly, use the insights you’re gaining to make your products even better and explore new services you can offer customers based on the data!

Real-life examples of OEMs Using Industrial IoT Adoption 

Let’s dive into real-world examples of OEMs successfully leveraging IIoT to achieve solid results:

Predictive Maintenance

Heavy equipment manufacturers like Komatsu and John Deere use IoT sensors to keep constant tabs on machine health. Algorithms analyze the data to spot subtle signs of trouble, letting technicians schedule maintenance before a breakdown occurs. This means far less downtime for their customers, which is a huge selling point, especially in industries like construction or agriculture.

Maximizing Efficiency

Automakers like Volkswagen and industrial automation giants like Siemens are using IoT to enhance production processes. Data from machines and sensors along the production line reveal how to fine-tune workflows, spot potential bottlenecks, and even reduce energy consumption by optimizing how machines are used.

Remote Support and Asset Tracking

Companies like Caterpillar and Tetra Pak can monitor their equipment from afar thanks to IoT connectivity. Technicians can often diagnose and even fix problems remotely, reducing the need for expensive on-site visits. Plus, with location tracking features, customers have real-time visibility into where their equipment is, preventing theft or unauthorized usage.

New Business Models

Instead of just selling equipment, companies like Kaeser Compressors and Rolls-Royce are tapping into IoT data to change how they do business. Instead of charging a high upfront price for an air compressor, Kaeser lets customers pay based on actual usage. Rolls-Royce takes it a step further: With their “Power-by-the-Hour” model for aircraft engines, airlines only pay for time when the engines are functioning, motivating Rolls-Royce to make incredibly reliable products.

Conclusion

The potential of IoT is enormous, but the technology is constantly evolving. IoT fundamentally shifts how OEMs can operate and deliver value to their customers. From proactive maintenance that minimizes costly downtime to data-driven design improvements that fuel innovation, IoT provides a competitive edge. Enhanced asset tracking streamlines logistics, and the ability to offer new subscription-based services powered by real-time insights creates new revenue streams. The OEMs that reap the greatest rewards will be those who take proactive steps today. By embracing the power of connected devices and data-driven insights, you’ll gain a competitive advantage and position your business for long-term success.

How can Idea Usher help with IoT software development for your OEM?

Idea Usher brings deep expertise in IoT software development to help OEMs achieve their goals. We’ll partner with you to understand your unique objectives and pain points, providing strategic guidance to define the optimal project scope. Our industry-specific experience with OEMs ensures we create solutions that directly deal with the challenges you face. We believe in a long-term partnership approach. Beyond the initial launch, Idea Usher provides ongoing support, adaptation, and feature development as your IoT solution matures alongside your evolving business needs.

Contact Idea Usher today to schedule a consultation and explore how we can help you harness the power of IoT. We’re ready to turn your ideas into reality!

FAQs

How can IoT be used in manufacturing?

IoT in manufacturing connects machines, sensors, and systems across the production floor. This enables real-time equipment monitoring, predictive maintenance to reduce downtime, quality control through automated inspections, improved supply chain visibility, and even the development of new data-driven business models.

What is OEM in IoT?

OEM stands for Original Equipment Manufacturer. In an IoT context, OEMs are the companies that design and manufacture the machines, devices, and sensors that are connected to an IoT solution. Think of them as the providers of the specialized hardware that forms the foundation of many IoT implementations.

What IoT devices are used in the industry?

Industrial settings use a wide variety of IoT devices, including:

• Sensors: Temperature, vibration, pressure, flow, and humidity sensors are used to monitor equipment and environmental conditions.
• Actuators: Motors, valves, and solenoids enable remote control and automation.
• RFID Tags: Used for asset tracking and inventory management.
• Industrial Gateways: Devices that aggregate data from multiple sensors and provide local processing capabilities.

What does IoT stand for in manufacturing?

IoT stands for “Internet of Things” in manufacturing, just like it does in other contexts. The core concept remains the same: connecting physical objects to the internet to gather data and enable new levels of automation, insight, and efficiency.