How Industrial IoT (IIoT) is Empowering Discrete Manufacturing – Real life Examples and Concrete Tips

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IoT is the technology and strategy of connecting machines, devices and sensors to the internet, gathering and analysing data, generating smart insights and building automated processes. The bottom line is that loT makes it easier for humans by making processes more efficient.

It’s very easy to understand how a smart AC can help us optimize our indoor temperature, or how a smart camera can help us identify who’s at the door (the kids are back from school? The housekeeper? A thief maybe?).

But some use cases are harder to digest than others. Like advanced cases of IIoT at the service of manufacturing or specifically, discrete manufacturing.

The potential of IoT

IoT has completely changed the business sector, and that’s before getting into specific industries, such as discrete manufacturing.  For example, let’s say that you work in the water services industry, and you are operating ‘stupid’ machines, such as water meters. Dedicated team members must (physically) visit each meter periodically, let’s say once a month, to gather needed data for billing or for any other purposes.

If you have millions of water meters, you will need to employ thousands (!!) of workers to deal with it. Yes, this was the reality of most players until recently, but now things are starting to change.  

If you can somehow manage to connect all these ‘stupid’, simple hardware based machines to the internet (connected cloud), and automatically collect, organize and analyse relevant data, your operation will look completely different (and I am not even talking about optimization yet… I am just talking logistics).     

That is basically the idea behind making simple hardware smart and connected via IoT related sensors, technologies and softwares.

The potential of IIoT

IIoT, or industrial IoT, is built on the same notion implemented in an industrial manufacturing environment.

The hidden potential of IIoT goes way beyond collecting data and making smart predictions.

Don’t get me wrong, analysing data and predictive analytics are major components of any decent IIoT implementation, but there’s more to it, which justifies the term ‘Industry 4.0’  and the ‘industrial revolution’ that everybody talks about.

Advanced IIoT solutions go way beyond just connecting factories, machines and sensors to the internet and automatically collecting data.

These solutions are moving past plain IoT towards providing AI based optimization recommendations that cover the entire production process.

In other words, selected smart IIoT solutions collect data, send alerts AND provide actionable insights based on the data, that help humans make optimized decisions, less mistakes, and maintain quality while supporting much bigger production scales.

Now, that’s a revolution.

Benchmarks and predictions:

The numbers are indicating that IIoT will keep transforming manufacturing:

IDC’s Manufacturing Predictions 2018 report  predicts that “by 2020, 60% of the G2000 [top] manufacturers will rely on digital platforms that enhance their investments in ecosystems and experiences and support as much as 30% of their overall revenue.”

BCG predicts that discrete manufacturing will show a 3 million euro growth on spending in IoT by 2020 (starting 2015), and along with additional manufacturing industries, will account for 50% of overall IoT spending.

In our IIoT Survey (done in partnership with SME) we asked top manufacturing C level executives about expected growth due to digitalization, and almost all respondents (93%) mentioned that they expect single or double digit growth over the next three years.

It is always nice to have some numbers to back up one’s claim, but at the end of the day, nothing helps us understand the potential and necessity of IIoT more than some real life examples.  

So I’ve gathered some of the most relevant ones (in my eyes) here.

I am also using this opportunity to spill the beans and share best practices that can help you leverage IIoT for your discrete factory.   

Airbus – Scaling production

A joint venture between Airbus and its Chinese partners led to the creation of Harbin Hafei Airbus Composite Manufacturing Centre (HHACMC), responsible for manufacturing and assembly of composites of certain Airbus aircraft parts (carbon fiber rudders, elevators, belly fairings for A350 XWB and also rudders for A320).

The challenge

Relying on paperwork (‘travel document’), and manually calculating and recording ETL (Exposure Time Left) led HHACMC to an inefficient utilization of materials, caused multiple manual errors that resulted in re-work and scrap, drove to blindness (lack of real-time visibility) and left no record of the impact on quality.

With the increase in demand for the relevant Airbus aircrafts, issues became more severe.

The site team fell short, not being able to meet the capacity required or to meet the deadlines. In other words: This Airbus site had a hard time scaling.

How did the IIoT solution help?

Plataine’s IIoT software solution continuously collects factory floor data, analyzes it and raises alerts such as material units that are close-to or exceeded expiration date and exposure time, tools that require maintenance, and more. By tracking parts, material and tools using Plataine’s software, Airbus can accurately monitor items’ movement on the production floor. ‘In & out of freezer’ times are automatically calculated by Plataine’s software, including material expiration date and exposure time. Additionally, Plataine’s

solution optimized the Cutting & Kitting processes while considering all relevant production elements such as customer orders and inventory on hand. This automation and optimization increased throughput and enabled staff to optimize material selection and minimize waste.

Key takeaways:

IIoT enhances scaling capabilities.  

Read the full Airbus case study

GE Aviation – Machines tracking

GE Aviation is a world-leading provider of commercial, military and general aviation jet and turboprop engines, components, as well as avionics, electrical power and mechanical systems for aircraft.

The challenge

GE Aviation suffered from lack of visibility over kits and tools that triggered inefficiencies and material waste.

Manual tracking of the kits’ locations, expiration date (bond by date) and exposure time resulted in late processing, excessive lab testing and in some cases disqualification and scrap.

Errors in expiration date (bond by date) and exposure time calculations led to quality issues and excessive lab testing.

GE faced a burning need to find an advanced solution for materials, assets and tools tracking.

How did an IIoT solution help?

In addition to Plataine’s Material & Asset tracking solution, GE Aviation wanted to track their tools as well. GE decided to use this opportunity and leverage an implemented IIoT solution to optimize maintenance efforts and prevent production delays.

Plataine’s solution provided GE aviation the ability to optimize their tools and track their duty cycles to utilize predictive maintenance.

That allowed GE Aviation to move their maintenance efforts from time based maintenance (for the sake of this explanation, let’s say every 3 months) to duty cycle based maintenance (sending tools to service based on the number of actual autoclave duty cycles), that lead to improved OEE (Overall Equipment Effectiveness).

In addition, the ability to track tools enabled GE Aviation to quickly locate them when needed for the next tool layup operation and hence prevent production delays.

Key takeaways:

With IIoT a manufacturer can track not only materials and assets, but also tools. Besides tracking, a related optimization layer that provides actionable insights can be added to optimize tool maintenance cycles and improve its availability.  

Renault Sport Formula One Team – Agility and Response Time

The challenge

Renault Sport Formula One utilized Plataine’s IIoT solution to automate production processes and meet ‘time to market’ goals and deadlines.

Most components in a Formula One car have a limited service life due to working in extreme conditions of high loads, heat and vibrations. Components are often replaced before the end of their service life.

With just a week between races, the composites department at Renault Sport Formula One Team worked hard to manufacture composites in as short a response time as possible, sometimes within just a few days or hours. It was very challenging.  

How did the IIoT solution help?

Using Plataine’s Material & Asset tracking IIoT solution to control inventory, avoid waste and reduce risk of error allowed Renault Formula One composites team to respond quickly and efficiently to rush orders, a joint need of many manufacturers.

Automatically tracking time sensitive material expiration dates, exposure time and creating ready-to-cut cutting programs enabled Renault Formula One to dramatically reduce response time and improve quality.

Key takeaways:

IIoT can dramatically reduce time to market – applicable to factories handling rush orders.

Stark Aerospace

STARK Aerospace is a global aerospace defense contractor located in Columbus, Mississippi.

The challenge

Stark has expanded its manufacturing facilities to allow production of several new product lines. The team used to extensively rely on paperwork and manual processes to manage its operations.

The inevitable result was characterized by an inefficient utilization of material, human errors causing rework and scrap, lack of real-time visibility, and no digital record of the impact on quality.

Stark knew that their existing manual and paper-based practices limit their ability to scale-up production and stand in their way to becoming fully digital or ‘audit-ready’ at all times.

How did the IIoT solution help?

Before answering that, here’s another question: Whether or not Tier 2, ‘less than huge’, manufacturers can enjoy the benefits from IIoT solution implementations and gain quick ROI?  

The short answer is yes. As cloud solutions can be as flexible and scalable as needed, manufacturers of different scale can leverage smart factory features that match their specific needs and no more.

Besides, implementation can be even easier in these cases. Stark completed the implementation in just 2 weeks.

By implementing Plataine’s Material & Asset Tracking IIoT solution, and deploying the solution in a 2 week period of time, STARK minimized material waste and increased production capacity while maintaining quality and meeting deadlines.

The bits and bytes:

RFID tags were attached to each moving asset such as raw material rolls, kits, parts and layup tools. They were used to automatically track and collect real-time data about asset locations and status (sensitive material expiration dates, out-times until parts are cured). The result: Creating full part genealogy, traceability and auditability of the Digital Thread.

Today, Spark production managers receive constant updates on asset locations, sensitive material expiration dates and out-times (until parts are cured).  

Key takeaways:

Manufacturers and sites of different size and scale can leverage IIoT and increase capacity to meet growing demand.

The Boing use case is already a popular case that you may have heard of before, as it is already widely shared online.

Boeing revolutionized the aviation industry by using IoT and used it to build an ultra successful value chain collaboration.

As describes it: “Boeing and its Tapestry Solutions subsidiary have aggressively deployed IoT technology to drive efficiency throughout factories and supply chains. The company is also steadily increasing the volumes of connected sensors embedded into its planes.” Chris Chadwick, chief executive of Boeing Defense, Space and Security, commented on its supply chain collaboration, saying: “Out of the $6 billion [in cutting], probably 66 percent of that will come out of the supply chain, maybe more.”

Key takeaways:

How to leverage IIoT in support supply chain collaboration to scale up production while all along widely reducing costs.

Siemens – Full Automation

Siemens’ Electronics Manufacturing Plant in Germany claimed to be 75% fully automated, which is aligned with their automation vision: “Production is (now) largely automated. Machines and computers handle 75 percent of the value chain on their own; the rest of the work is done by people. Only at the beginning of the manufacturing process is anything touched by human hands, when an employee places the initial component (a bare circuit board) on a production line. From that point on, everything runs automatically. What’s notable here is that Simatic units control the production of Simatic units. About 1,000 such controls are used during production, from the beginning of the manufacturing process to the point of dispatch.”

Key takeaway:

Machines aren’t (yet) making humans redundant. They’d rather help them reach the needed scale and stay profitable.

Aspiring to become fully automated and taking a holistic approach when it comes to implementing IIoT is what helps companies stay competitive and profitable.


Nothing can help us deeply understand the potential of IIoT, and the clear benefits and savings it brings along, more than exploring real use cases and generating valuable takeaways. I can think of many more use cases on top of what I already shared, but I think that the ones above are enough to make a point.

I invite you to book a demo of Plataine and explore some more use cases.

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