Will IoT have influences on your business? Do you see all advantages and possibilities or do you think your business is immune to coming changes? In this article we will raise some questions and hopefully give you some input on how you can utilize already installed software.
Differences between IoT, IIoT and Industry 4.0
We have all heard about the Internet of Things (IoT), which will, and have disrupted many industries. What is then IIoT? IIoT is Industrial Internet of Things, and why is it different than IoT and Industry 4.0? IoT is mainly business to consumer (B2C) marked, but in IIoT we focus on business to business marked, or B2B and machine to machine communication (M2M). We are all aware of it is different. In B2C, standardization is almost non-existing and a lot of companies are struggling to have the marked leading platform for user interface. We know Apple, Amazon and Google fighting for home automation, Fitbit, Garmin and Polar (and a lot of others) fighting for fitness trackers etc. The main message is that if you have several products from different providers, you probably have several apps, one for each provider, and you seldom can utilities your data in other areas. Why is it like that? Because the company which has communication with customers, will have access to customer experiences and able to react much faster on changing trends and will much easier see upcoming markets. In B2B and M2M, we know for sure we will have different platforms, several providers fighting for their platform being marked leader etc. and we know for sure we must have standard interfaces between different providers. So far, nothing new. What about Industry 4.0? Industry 4.0 is coming from the government in Germany and aim to safeguard a sustainable competitive advantage for the German manufacturing base. There are four design principles in Industry 4.0 according to Wikipedia.
- Interoperability: The ability of machines, devices, sensors, and people to connect and communicate with each other via the Internet of Things (IoT) or the Internet of People (IoP).
- Information transparency: The ability of information systems to create a virtual copy of the physical world by enriching digital plant models with sensor data. This requires the aggregation of raw sensor data to higher-value context information.
- Technical assistance: First, the ability of assistance systems to support humans by aggregating and visualizing information comprehensibly for making informed decisions and solving urgent problems on short notice. Second, the ability of cyber physical systems to physically support humans by conducting a range of tasks that are unpleasant, too exhausting, or unsafe for their human co-workers.
- Decentralized decisions: The ability of cyber physical systems to make decisions on their own and to perform their tasks as autonomously as possible. Only in the case of exceptions, interferences, or conflicting goals, are tasks delegated to a higher level.
This is not so far from IIoT theory, but they have different origins and meanings. Either you think about Industry 4.0, or IIoT, you should ask you what will happen in your industry within the next 5 to 10 years.
In some industries, there are huge changes already, disrupting an entire business. Media, telecom, consumer financial services and retail has already been a part of this for a while. Have you noticed all the talk about autonomous cars, cloud computing, robotics, big data, machine learning? Will it involve your business? Almost 100% sure. When? Hard to tell not knowing your business, but for sure it will come in near future. Why? Even if you are in other industries than car industry, internet industry, robotics? If we consider what those changes involves and the opportunities they create, you will be able to decide yourselves, knowing your business better than me. Is this different than historical technical and marked evolution? If we consider evolution, we see a lot of improvements of existing technologies/products. Improvements that are almost the same as the former one. One main characteristic of IIoT is that completely new technologies are developed and made available for other users. As an example, translation of documents into other languages has been a labor-intensive process, but now it’s available as a service through others actors at a much lower cost. This enables companies to translate their web sites, manuals, documents etc. and communicate with other markets much easier and cheaper. Of course, they could have translated documents earlier too, but now it is close to free of charge. This is called disruptive innovation. Criteria for disruptive innovations is that it is radical, and a cheaper technology/product which normally is less accurate or have less quality, but can scale up in a lower cost and is good enough in many cases. As for translation, we know that web based translation services are not (or haven’t been) as good as a native speaking person, but in many cases, they are good enough and easier/cheaper to scale up in size.
Disruptions to come
Autonomous cars are developing a lot of new functionality. Computer vision, odometry, laser lights and to distinguish between different objects are just few of them. You can read about it in Wikipedia. Those new technologies will also be utilized in other industries, creating cheaper, more accurate or better ways to do things. And software algorithms will be available in cloud, giving everyone access to advanced and new technologies. How will that influence your industry? Not sure, but most important is you start thinking about it. Do you have to connect old production equipment to internet, or should you? Maybe the most important learning driver is information, and knowing that, should you collect information from your production? Or is your product more important than your production process? Maybe you should do both. Just a little drawback. You must know what to achieve. Collecting data without knowing your goal, will give you experience in collecting data, but then what?
Why collecting data?
There are at least four main categories for collecting data per “Enterprise IoT, Strategies & Best practices for Connected Products & Services”:
- What is happening? (Descriptive analytics)
- Why did it happen? (Descriptive analytics)
- What is likely to happen? (Prescriptive analytics)
- What should be done to prevent this from happening? (Prescriptive analytics)
If you don’t have experience with IIoT, maybe you should try to collect data to quantify that your process is as you think it is? Sometimes, it’s not. Despite which level you are gaining for, start with a goal which is possible to quantify and which is possible to achieve. Then it is easier to see the benefit and find new projects. Remember descriptive analytics doesn’t require real time data and will be much simpler to collect.
In many industries, we have equipment which is several decades old, not prepared for internet connections, maybe using a proprietary communication protocol. Or we have equipment in harsh environment or without internet connection in reasonable distance? Not all cases are easy, so a natural start is to take the easiest one and the one you will gain most, remembering your solution must be scalable and adaptable to fit other solutions within your company. As a rule, try to convert proprietary data into standard data as early as possible in your process, mainly for using standardized solutions and not requiring specialists further than necessary.
What to do with collected data?
Let’s assume you have connected your project to internet, or at least to your company’s net, and started collecting data in a database. Now what to do, remembering that main goal for collecting information is to take better decisions and learning/optimizing your process? You will find that analysis tools are required to fully benefit from this. In 3DEXPERIENCE, you have a search engine which is capable of handling huge quantities of both structured and unstructured data, namely Exalead CloudView. Exalead CloudView is the world’s third largest search engine, already running inside your 3DEXPERIENCE installation, so you don’t need another standalone installation. Configuration of CloudView follows this process schematics.
Data Sources in the figure is your input data as CAD data, and now your collected data. For the CAD data, the connector is already in place, but for your device/process data, you must create a connector to Exalead. For structured data inside a database, you normally use a database connector. A lot of other connectors are also available. After indexing, you can analyze your data in Exalead PLM Analytics in near real time, or quickly generate views in Exalead Mashup Builder. Should you need help collecting your data, you can utilize Exalead Data collection & data fusion.
Further information on https://www.3ds.com/products-services/exalead/