Industry 4.0 would not be possible without intelligent sensors

The Information Age for industry is just getting off the ground. The limitless exchange of manufacturing, product and logistics data means it is now possible to make better decisions and experience complete transparency across all levels of the value chain. At the start of the process chain, this world of greater resource efficiency depends largely on the equipment that supplies this data: the intelligent sensors. It is absolutely essential for sensor technology to be intelligent, rugged and reliable when it comes to dealing with challenges such as the safe interaction between people and machines, high levels of variance and controlling fluctuations in demand at short notice.

Sensors provide the senses for machines. The feedback they provide is what makes intelligent machines possible in the first place. Sensor intelligence focuses on one aspect of sensor technology: equipping machines with the ability to see, recognise and communicate intelligently. Intelligent sensors contribute the ability to classify and interpret information. This is characterised by intelligent signal processing, which derives the truly relevant information from large quantities of data and makes it available to various levels. This is why — in addition to the primary control system for machines and systems — information is provided for monitoring production systems and making it possible to detect faults. Transparency of the processes and material flows produces additional potential for optimisation. Processes are becoming more efficient and cost-effective and are increasing competitiveness.

Examining the four challenges throughout the production levels — ‘quality control’ at the sensor and drive level, ‘flexible automation’ at the machine level, ‘safety’ at the production level and ‘track and trace’ at the corporate level — makes it clear that we as a driver of technology in Industry 4.0 are already capable of presenting and implementing solutions.

Flexible automation requires variable basic conditions. Manufacturing plants have to be flexible and adapt to what the individual customer wants. Due to high product diversity, even as the part batch sizes continue to decrease, intelligent components (smart sensors) have to be capable of adjusting and controlling themselves.

The essential driver for the area of safety is the interaction of people and machines, while taking into account workplace ergonomics and safety. The central questions here are what role people are to play in production of the future, and how can sensors support and keep them safe in that role?

Vertical integration — that is the keyword for track and trace. Traceability of products during complex manufacturing and logistics processes is a priority for this integration. Logistics for production and transport merge until delivery is made to the customer, requiring the flow of goods to be transparent so that decisions can be made more quickly.

Increasing quality requirements and the desire for resource efficiency necessitate autonomous fault detection through comprehensive product and production data. In the area of quality control, goods in the production process and supply chain must be reliably and uniquely identified so that they can support efficient automated control.

Flexible automation: customising goods in the packaging process

Using a packaging machine as an example shows how an automatic batch change without manual intervention — by using intelligent components with automated control — generates higher product diversity with a general increase in productivity. Maximum productivity with product variation down to a batch size of 1 is a central goal of the Industry 4.0 concept.

As an example: final packaging of prepackaged batches with bottle sizes of 0.5 L and 1.5 L capable of being packaged on one system by means of detection from smart sensors with automatic format changeover. The sensors detect the product changeover and tell the control system that the system has to readjust, so that the right box can be set up, the bottles can be fed in and the box can be labelled and transported away. The changeover steps are listed on a monitor while the machine adjusts. The system keeps running automatically and does not have to be put back into operation manually. If the sensors detect an incorrect placement when measuring the length of the product, they notify the control system. The product is sorted out without the system coming to a stop. In addition, the sensors provide data for proactive maintenance, such as monitoring the system for fine particles to automatically implement measures that safeguard the packaging process.

Intelligent, communicative sensors are what make Industry 4.0 possible in the first place. Smart sensor solutions — the use of state-of-the-art sensor technologies in combination with complete integration into the control level — focuses heavily on decentralising certain automation functions to the sensor. This takes some of the load off the control system and increases the productivity of machines.

Safety: robot protection using laser scanners

Sensor intelligence is a prerequisite for safe interaction between people and machines in the era of Industry 4.0. Safe laser scanners reliably monitor the hazardous area of stationary or mobile machines and systems, such as welding robots or automated guided systems. Protection of people is the top priority here. If a person enters the area, the dangerous movement must be stopped safely. On established systems people are protected but production is stopped.

In the future, smart sensors in the context of Industry 4.0 will be used not only to ensure the safety of people, but also to implement ever-increasing production specifications.

The digitally switching protective fields currently in use are being replaced with flexible ones, which are automatically calculated during highly dynamic movements and adjusted corresponding to the hazardous areas of the robot. The compact systems use an integrated swivel mirror as an optical radar to scan their surroundings in two dimensions and measure distances according to the time-of-flight measurement principle. This results in freely definable safety zones.

Quality control: reliable data acquisition and tracking

The future holds continued increases in the speed that packages are transported. The distances between the packages are becoming smaller. This means checking the quality of products is even more important. To accomplish this, the package data is scanned on the conveyor belt and read into the software. The packages are identified and compared. Is the package damaged? Is the code complete? Are the weight and volume the same? Is there a pile-up of packages, or is a package possibly even missing? Automatic fault detection is made possible by comprehensive product and production data. The data is completely synchronised in seconds. Defects can be tracked by all centres, and it is possible to trace where the weak point is. In addition, quality defects can be identified and resolved in the process. Since the speeds on the conveyor belts are further increased, maximum productivity is ensured — not just within a location, but also globally.

The example of an intralogistics process shows how increasing quality requirements and the desire for resource efficiency can be implemented in the context of Industry 4.0. The sensors detect changes to the object and enable seamless data acquisition. The software solution analyses the process data and implements actions. The combination of a variety of data and the analysis software is an important prerequisite for Industry 4.0 and the issue of sustainability. Goods in the production process and the supply chain must be reliably and uniquely identified so that these can support efficient automated control. From an individual package on a conveyor belt to a complete overview of millions of packages transported every day — there must be a convenient way to call up and analyse the status of all acquired data.

Smart sensors acquire and communicate this data. However, users do not experience true added value until this data can be used as a basis for improving business processes. This data offers extensive opportunities but also presents the significant challenge of preparing it in a way that allows companies to make the right decisions. This is the cornerstone of Industry 4.0: the seamless flow of data and information from the sensor to the control system and back.

From sensor to sensor intelligence

The increasing speed in the computing power of state-of-the-art chips enables remote processing of substantially larger amounts of data and capabilities like the associated use of complex mathematical methods. This is resulting in completely new dimensions for the scope, accuracy and ruggedness of measurements. Sensor solutions measuring in multiple dimensions, such as camera systems and laser scanners, would also be impossible without this development due to their high data volume.

The computing power enables even more intelligent sensors, but they do not turn into sensor intelligence until equipped with the right software and application knowledge. The intelligent linking of application knowledge with the flexibility of state-of-the-art software architectures enables the next development stage for sensors. This is characterised by the possibility of sensors that can perform more extensive analysis, automatically adapt to changes, communicate in the network and remotely solve complex tasks within a larger manufacturing network. In other words, the sensor links to the machine, system, factory and the entire value-creation chain, and provides for transparency in production. As a result, it provides the entry point into the world of Industry 4.0. For all virtual worlds, however, sensor intelligence remains one thing above all — part of a sensor. Even the cloud and apps need to have a physical basis in the real industrial environment, namely, a rugged and reliable piece of hardware.