IoT is Today!

IoT, some call it industrie4.0, has brought a new breath in the whole industrial production process by allowing the physical and digital world to merge together. This will result in increasing productivity, efficiency, reduction of production costs...and many other positive effects even though there are tough non-technical challenges ahead (change old habits & mindsets, new skill requirements and also greater competition).

Facts: The requirements in industrial production are becoming more sophisticated.

1. The necessity to have products that precisely meet expectations which are becoming more and more sharpened
2. Companies have to deal with new competitors (see the impact of Google's announcement of driverless cars has already on the old car industry!)

Hence companies need to merge the fields of systems engineering, computer and economics to achieve the level of efficiency and quality desired.

The potential :

• The number of Internet users worldwide is estimated at nearly 3 billions today
• Some experts estimate that in 2020, the number of connected devices could exceed 50 billion
• 11.1 USD trillion per year in 2025: this is the global economic impact of IoT applications
• Numerous analysts and experts expect 50 percent of this materializing in industry.
• Today, most of IoT data are not used, e.g only 1 percent of data from an oil rig with 30,000 sensors is examined. The data that are used today are mostly for anomaly detection and control, not optimization and prediction, which provide the greatest value.

Network connectivity: the key factor

Today, the network is the determining factor in IoT. The role is so important that we note the very rapid improvements regarding the quality and network performance. These improvements in network coupled with big data tools and intelligence applications are drivers for hyper connectivity in industry.
Example: End-to-end digital engineering in every manufacturing facility where machinery is a unit of a set of connected devices. Continuously performed measurements and data analysis allow to

• anticipate maintenance issues before machines break. Advantage: workflow interruptions are minimized.

• identify factors that will improve efficiency and throughput.

 5 levels of connectivity

1. Shop floor to top floor – intra company vertical integration:
   The first level of integration is to connect business systems to shop floor systems. Generally, systems on the top shop floor are separated from the the business systems. Shop floor systems are standalone and unique to each factory or line requirements. the rampant proliferation of localised deployments has led to disparate but dedicated systems for manufacturing planning, execution, process control, and tracking and tracing for each plant.
2. Machine-to-Machine – Autonomous machines (M2M)
   The main idea is to use machines which are able to self-diagnose and self-correct by changing parameters to meet overall objectives. This leads to use of sensors in machines and production lines. Depending on the level of performance desired, the number of sensors can drastically increase. A typical example is a downstream machine which has detected a problem and needs to slow down can request the upstream machine to decrease its speed in order to slow down the line.
3. eCommerce Integration - Direct integration of online configurations
   This concerns the customer design-oriented companies that offer customers the possibility to deeply configure and customize their product ordered online. The need here is to install an automated remote management system for customization whose input is the verbal command from the client and the output is the robot arms that manufacture the product.
4. Manufacturing collaboration – visibility – genealogy – quality – direct replenishment
   The main objective is communication in real time between different stakeholders in industrial production. These are among other suppliers, design partners, Original Equipment Manufacturers (OEMs) and customers who interact with each other ensuring that stakeholders interests are met. A classic example is the case where the supplier and the contract manufacturer communicate with the shop floor and business systems. In this case, machines on the shop floor can send replenishment signals directly the suppliers. Then, machines in the contract manufactures location can constantly update the OEM according the status of production orders and the fitting with the schedules.
5. Machine Cloud – Predictive Maintenance – Predictive Quality
   Without manually impacting on performance machines, the idea is to remotely manage the sites and reduce the presence of owners, operator or manufacturer hands on machines during operation. This shows advantages regarding performances on preventive and proactive maintenance. Another aspect of IoT is related to data collected from sensors and telemetry which can be merge with business data in order to make decision regarding the business model needed to follow up.

Conclusion

Nowadays it is no longer right to say that IoT is still in development: It already enters its maturing phase. Indeed IoT in industry has already reached a high penetration rate.

Still, we are far from imagining all solutions IoT can bring to the industry.

 And a few final remarks

1. IoT or industrie4.0 are just "words" and what´s behind is still often seen as something "theoretical", especially as many discussions are focussing on "IT".
2. It becomes more tangible when discussing "USE CASES" and the business case behind.

What we need are "entrance uses cases" and energy efficiency can play a major role here. When you start thinking of the different levels of connectivity as mentioned above, you might be able to easier understand what IoT can deliver. And once you have started, it becomes much easier to also elaborate on its further potential.

To be continued...

_{Sources:
http://www.mckinsey.com/insights/business_technology/the_internet_of_thi...
http://www.iaasiaonline.com/index.php/issues-insights/item/168-industry-...}