Industry 4.0 means smart machines: more automation, the merger of the physical and digital worlds (IIoT), a move away from central industrial controls to a more distributed system with smart machines defining and controlling processes and lastly the use of digital twins, data models, etc… This all leads to an increased customisation of products rendering them more fit for purpose and therefore more efficient. 

Edge computing (EC) represents a major shift in computing. Mainframes of the 50’s were followed by client/servers of the 70’s, and succeeded, more recently, by cloud computing. EC is expected to be as disruptive as the above major shifts. In manufacturing, billions of devices are getting connected. According to IDC research, in 3 years, near 50% of IoT data will be stored & processed & actioned at the edge. 6+ billion devices will be connected to EC applications. Cloud infrastructure will come under pressure. Network latency, cost of bandwidth, cost of data storage, security can all be reduced using EC. 

EC means that instead of sending all data collected by IoT sensors directly to the cloud, EC processes data “at the edge”, within the network so that only relevant data is sent. Computing closer to the source, means improved data management, reliable and cheaper connectivity and better security for IIoT applications. Less long-distance client/server communications entails reduced bandwidth use. 

Some of the advantages of EC for IIoT are:

• Faster response: data storage and computation is local. No back and forth to the cloud needed.
• Reliable even with unreliable connectivity: Many remote assets are in regions with weak internet. EC can store & process data locally, ensuring no data loss in the event of temporary or frequent internet failure.
• Enhanced security: EC avoids the need for large quantities of data being transferred from sensor to cloud. Data is filtered locally and only important information is transmitted to the cloud which enhances security.  Lastly, sensitive information doesn’t need to pass through a network!
• Reduced costs:  Lower costs due to reduced bandwidth, less data storage, and computations. EC performs much of the computations locally, allowing IoT users to decide what to run locally and what in the cloud. All reducing the final cost of the IIoT project.
• Legacy and modern devices: EC devices can liaise between legacy and recent assets. Legacy machines can therefore connect to modern machines or benefit from IoT solutions, providing immediate benefits.

Ultimately, not all smart devices will utilize cloud computing. In a growing number of IIoT cases, the return trip to the cloud can and should be avoided. That is at the core of EC. While EC will not replace Cloud computing – the latter has advantage such as computational power, more storage, potential for predictive and machine learning, AI, etc… , EC is a complement for an overall approach to IIoT.  IMBU believes that the two should be combined. 

We see EC used increasingly in manufacturing (enhanced automation, precision engineering, fault finding, etc..),  after market services (predictive maintenance, condition based monitoring, ), transportation (EVs, mass urban transit, etc…), health care (health-monitoring wearables: Fitbits, glucose monitoring, EKG, to fast data processing for remote patient monitoring, inpatient care, etc…), smart agriculture (monitoring soil conditions, weather, temperature with EC particularly suitable for remote locations), energy (safety monitoring of O&G utilities, rigs, solar panels, etc…), retail (EC’s potential is huge – think of Amazon’s cashierless store), financial services, logistics, etc, etc…

To conclude, data generation will skyrocket. For manufacturers this is unavoidable progress as centralized computing has its limits. EC is a complement and at an early stage but the potential is there and in specific cases, the value of EC will be game changing! IMBU offers a “one stop shop” for OEMs wishing to enter this area, from inception to the finished product, based on 10 years of IIoT experience. Feel free to contact IMBU for a free diagnosis of your IIoT potential solutions.

IIoT will allow you to  get secure access to machines you manufactured while they operate at your clients’ sites. IMBU specializes in IIoT by transforming raw data into immediately actionable information. IMBU allows you to have remote secure access, edge computing, cloud based data logging, trending, machine specific dashboards, web-based access and many more IIoT features such as receiving email and other alarms. IMBU also offers semi-online solutions where operators/mechanics interface with an analytics node using their phone and a dedicated app.

What is white label IIoT?

White label IIoT allows you to sell a digital product created by IMBU under your brand name. This enables you to add to your current offering without spending time developing the product/service yourself. 
White label value proposition
Traditionally white label involves charging more for your white labelled services or products than what you are paying your white label supplier. It is a faster solution, it saves time and money because you can take advantage of someone else’s accumulated expertise. 
IIoT is however a money maker in many more ways. While IIoT can be charged for and create a direct return, it will, in addition, spin off knowledge of your machines as used by the customer enriching your understanding of your own product, it transforms you from A.N.Other supplier to your client’s partner through increased knowledge of machines in their working environment, it enhances your brand through increased reliability and much more. 

Why IMBU?

IMBU’s founders background is both IT (with a focus on controls) and Industrial “after market services”. The latter entailed the sale and service of turbines, gas engines, gas compressors, controls, ignition, filtration, etc… and was sold to US investors in 2020 – see www.quorex.ch and www.msikaz.com. Some 10 years ago, IMBU realised that to arrive at good and practical IoT systems, one needs to straddle and understand both the industrial mechanical world and the IT world. This understanding is at the origin of IMBU’s IIoT activity today (see www.imbu.nl). 

Why outsource your IIoT project?
Building an IIoT platform to your requirements means starting from scratch, spending time and money and reaching an uncertain result in an uncertain time. Main reasons for this are (1) it is not your field, (2) you will move slowly (initially) in a fast moving area, (3) you may re-invent existing available solutions, (4) you will not match resources and expertise of existing specialists that are focused in this area. 

Some advantages of IMBU’s white label IIoT:

Time to market: The first advantage of using white labeling is to broaden your services and do it fast. 
Cost control: By outsourcing services to IMBU as a white label IIoT provider, you avoid hiring in-house developers full-time & can budget the project with a good degree of certainty. 
Project management savings: By outsourcing the complete IIoT project to one supplier, you do not have to coordinate hard and software providers. IMBU is a “one stop IIoT shop”. 
Keep IP Control: Outsourcing a white label IIoT project to IMBU, lets you keep control of IP. You can always move to another supplier or take it back in house. No hostage taking.
Quality of your IIoT: A white labelled IMBU solution equals a complete product developed by IMBU from start to finished product. 
Improve your Service: IIoT allows efficient & quality after market service, reduced downtime, improved operational efficiency, better understanding of machine operation in situ & much more.
Improve your Brand’s Image: most clients ignore IMBU’s involvement & assume your company is delivering quality up to date digital services, enhancing a forward looking company image. 

What we are getting at is “what we take for granted today is likely to change tomorrow”. Elon Musk redefined what we may expect from cars by taking away the segregation between mechanics, electrics, electronics, software, and the internet. Albeit a bit more slowly, the industry is now following. Where industrial gas engine manufacturers used to see ignition as a buy-in item, nowadays companies like Caterpillar, MTU, and Waukesha supply engines with integrated electronics. A first step in the right direction, unfortunately still short of coming up with a well thought out, online analytics strategy.

At IMBU, it is our deep conviction that driven, driving, and even static industrial equipment will get smarter and smarter. OEMs of industrial equipment often have a detailed understanding of performance optimization & failure mechanisms of the equipment they manufacture. They often are frustrated that assets, once supplied to end-users,  often don’t perform at the level they are designed for. Online intelligence allows, both end-user and OEM to get in sync, empowering the OEM’s with new models of efficient support to the end-user and helping the OEM to achieve a better understanding of how their machines are used and abused in real-life.

We see in practice, that notwithstanding the initial enthusiasm of the OEM to embrace smart machine programs, it can wilt after the initial development excitement. This can be due to a variety of reasons – introduction can be harder than initially expected, early customer response is less enthusiastic than hoped for, etc…  This can sometimes be misperceived as a confirmation that ‘this is not for us’, we need to focus on what we are good at, forget about the online analytics, we have done without for decades, it is too fancy anyway, etc… What is going wrong here?

We started this blog by illustrating some large progressive movements in car design and industrial equipment offerings. As indicated above, we believe that driving, driven and other industrial equipment will move in the same “smart” direction – the benefits are just too large to ignore. Working closely with several OEMs, we have seen however that industrial IoT programs can initially be slow in generating revenue and value. This is illustrated by a graphic we include in any pitch we make to an OEM. The total surface of the 4 x slices of the inverted pyramid, each represent ‘value creation’, starting from the ground up.

At the narrow pyramid’s point, the surface is small and generates no direct (economic) value. This is where we define the IoT set-up, select sensor principles, work out analytics in order to find issues with machine condition and performance, typical for the selected machines. We study working principles, discuss the robustness of the set-up, do first field-trials, etc. This is exciting but also dangerous. In this phase, it is easy to lose OEM focus and enthusiasm (we all have been spoiled in our personal lives with rapidly developing electronics and software and expect the same from industrial assets). In addition. It is sometimes difficult to find end-user(s) willing to pay for the set-up, which may mean free trials. The pointed small base of the pyramid is however the indispensable layer that must be put in first. It is the base for everything that is to be built on top. In addition, this pointed layer needs to be balanced exactly right. Wrong choices here will have the pyramid tipping over later-on.

The second value-layer is where the OEM has an IoT product/service which can be sold against payment, monthly subscription, or other. The OEM may now be able to run the program for a small profit or break-even but direct revenues won’t be exciting… yet! This is where OEMs learn to scale-up the service, fine-tune functionalities, and better serve both end-user and OEM. Giga- and terabytes start to flow in, revealing that the data offers a base for previously unexpected yet very valuable insights in the OEM’s machinery performance at customers’ sites (one OEM found out that their pumps are often operated with pulsation induced cavitation which so far went unnoticed by the end-user but did decrease the life of certain components, another found that compressor-valves in end-user applications can often be optimized in order to dramatically increase valve-life). This is where recognition of the scope for improvements and optimization starts in reality. 

The third value-layer is larger and is when things finally start to get exciting! This is where the OEM sees that the industrial IoT ecosystem, created and built over 12-24 months, enables re-thinking how products and services can be combined into new models. An example is (insurance type) monthly fees, whereby the end-user no longer takes the performance risk but buys this off by paying a fee to the OEM. The latter is now so well in tune with its customer’s asset operations that the OEM can accept said risks and is able to leverage this deeper understanding across machine design and field performance, all gained at end-users.

The fourth and largest value-layer is where industrial IoT is no longer something the OEM does as an addition but IoT becomes an integral part of any of the products the OEM sells. No longer is IoT driven by a few product champions inside the company but its value is now embraced by all in the company and fully integrated into company products and services. This is where the OEM’s identity starts to change.

Two examples of companies that went all the way to this fourth layer: Tesla and GE.

GE is an example of failure after burning through billions of USD. In our view, because GE put in a large IoT infrastructure top-down but omitted to smartly integrate sensors into their assets, develop smart analytics and start by gathering deep insights ‘at the edge’. In our opinion, successful industrial IoT projects are characterized by top-down and bottom-up parallel approaches.

Tesla is a more successful example in redefining what users can and should expect from cars. Tesla remains in direct contact with end-users, learning about car utilization and performance, and upgrades car firmware as a result. Tesla has also shown that IoT enables an OEM to use a more direct route to market, without a costly distribution network, remaining in charge by staying fully in touch with end-users. While the end result is for the future to tell, it is an impressive disruptive model, now being copied by many larger players.

We believe the inverted pyramid is a pointer for what industrial OEMs should strive for!