The IoT and sensor technology are the drivers of digitalization. If industrial companies equip their machines, tools and products with sensors, they can utilize the information they gain to use their resources more cost efficiently and improve customer retention with new services.
Industrial companies should firmly incorporate the Internet of Things and technologies such as sensor technology, data analytics, big data and cloud technology into their digitalization strategies. The IoT operates in a network that encompasses objects, communication, applications and data analytics. Data is made available centrally and thus helps companies to obtain new knowledge. This makes this data an important enabler of new digital business applications. According to Gartner, in 2020 more than half of business processes will be networked via the IoT. Analysts predict specifically that there will be 25 billion networked machines, devices and vehicles – smartphones, tablets and computers not included.
The most important suppliers of data on the IoT are sensors. The topic of sensor technology could receive additional impetus, when there will be a new surge of narrowband solutions onto the market. These solutions will be able to connect any number of devices with little effort, which will then be able to communicate with each other. Cellular network providers predict that there will be 6 billion connections in Europe in the field of narrowband IoT by 2020. Industrial companies that put their faith in sensor technology, and thus in the IoT, will primarily be able to secure two essential competitive advantages: cost savings and stronger customer retention due to new services.
Using resources more cost efficiently with sensor data
An example: If a company equips its machines and tools as well as its products with sensors, it can then centrally analyze and utilize the individual data it receives in combination with one another. For example, sensors provide companies with information about a product, machine or tool’s location, condition and period of use. In the case of forklifts, for instance, empty runs, laden runs and shunting activities can be derived from movement patterns and load conditions using data analytics.
This data can be analyzed according to individual needs. In a subsequent step, companies are then able to access these analyses using mobile solutions. With the help of this sensor data, companies receive, for example, an overview of their utilized capacities and can optimize their own device base and conserve resources accordingly based on this information. This new knowledge supplied by sensors and data analytics thus creates real added value for companies.
In addition to this, sensors are also suited to monitoring the state of medical technology in clinics throughout its life span, for instance, and informing users of maintenance requirements as early as possible. This makes predictive maintenance possible. The same applies to built-in parts and complex machines in other industrial sectors such as vehicle and aircraft construction. This means that companies can provide their customers with an all-round, carefree package and offer them additional services such as the automatic ordering of spare parts and capacity control where needed.
Sensor solutions from a single source
From the production of sensor boards to the backend implementation of solutions, right up to the development of apps – Lufthansa Industry Solutions provides companies using sensors with a solution from one single source. During the integration of sensors into existing IT systems – including the systems of partners and customers – we draw upon our decades of experience as a system integrator. Our performance portfolio includes the analysis of data in cooperation with our in-house experts at the Data Insight Lab. Another important component is data security. When it comes to sensor technology, we also assist companies during the secure, encrypted communication of data from end to end.
IDG Study Predictive Analytics 2018
Please download the study Predictive Analytics 2018 here (in German).
IDG Multi Client Study Real Analytics
Please download the study Real Analytics here (in German).
IDG Study Predictive Analytics 2018 – key findings / whitepaper
Please download the key findings of the study Predictive Analytics 2018 here (in German).