Sensors in electronics manufacturing: Production with all senses

Sensors along the production chain

• Logistics
  Load handling, localization, environmental detection - navigating automated guided vehicles (AGVs) through factories requires a range of sensors. In the premium segment, 3D lidar with time-of-flight cameras provides distance information as well as a wealth of other data that holds the promise of additional functions beyond collision avoidance.
  Data fusion of less powerful sensors can also perform logistical tasks. For example, acoustic sensors and frequency analysis can be used to detect wear and tear on vehicles. If the maintenance status is derived from this, the result is predictive maintenance. In this case, less expensive sensors are purchased at a higher cost in the form of software or AI algorithms.
• Quality Control
  Close-mashed, efficient quality control ensures consistently high product quality and transparency in industrial production processes. Automated image processing (machine vision) is an important component. It is based on industrial cameras with digital sensors, special optics and software. Special algorithms extract and analyze data from the images, increasingly using deep learning. Application scenarios range from the identification of specific workpieces to process or quality control.
• Condition Monitoring, Predictive Maintenance
  Predictive maintenance programs are among the most successful scenarios in smart factories. Sensors on equipment and machines continuously record a wide range of physical parameters such as vibration, temperature, magnetic field, sound pressure, current, etc., which are then evaluated by independently learning predictive models. This allows components to be replaced proactively before failures occur.
• Process control
  Whether it is levels, speeds, distances, or temperatures, sensors determine the status of machines and transmit it to the PLC (programmable logic controller), which uses it to automatically control processes via actuators. Further processing of the data supports troubleshooting, process analysis, condition monitoring, and energy management.
• Human-Robot Collaboration (HRC)
  Due to the high demands on human safety, robots are usually limited in performance and power. Effective HRC requires 3D safety sensors, such as high-resolution radar or LiDAR (Light Detection and Ranging), to monitor the entire collaboration space and dynamically adjust the robot's speed and direction of movement.
• After Sales
  Sensors on customers' machines and equipment open up new data-based business models in the form of innovative billing mechanisms such as pay-per-use, product-as-a-service (PaaS), machine-as-a-service (MaaS), or service offerings such as predictive maintenance. The latter significantly reduces downtime and maintenance costs for the plant operator. The manufacturer benefits from additional revenue and improved customer retention. What applies to the machines and systems in the manufacturer's own production thus opens up new business areas for the customer.