スマート製造は、生産プロセスのすべてのステップを最適化することを目的とした、従来の製造の新たな技術的進化です。センサー 調達、生産、流通、廃棄などのサブセクターにおけるスマート製造ロジスティクスにおいて重要な役割を果たします。
製品の製造ライフサイクルのあらゆる段階でさまざまなセンサーが使用されます。この記事では、スマート製造プロセスのさまざまな段階で使用される最も一般的なセンサーのいくつかを紹介します。
調達、流通、廃棄のスマート追跡
サプライ チェーン ロジスティクス部門は、大量の個々のコンポーネント、パッケージ、およびストレージ デバイスの効率的な管理に大きく依存しています。スマート製造技術は、多種多様なオブジェクトのスマートな追跡を可能にするシステムの導入を先導してきました。
たとえば、ボーイング777航空機には、500社を超えるサプライヤーから提供される300万個を超える個別の部品が含まれています。ボーイング777を効率的に製造するには、倉庫内の各コンポーネントの自動追跡に依存する大規模で正確なデータ セットの支援によってのみ、何百万ものコンポーネントをシームレスに管理できます。To do so, RFID tags and transponders are used as a form of a ‘modern barcode’ that allow for large amounts of components to be tracked throughout the supply chain.
Types of Tracking Tags
RFID tags, or Radio Frequency Identification tags, are low-cost wireless identification devices that can be used to track inventory throughout a supply chain.In smart manufacturing applications, RFID tag readers can be fixed infrastructure that operate at procurement centers such as loading docks.Additionally, RFID readers can be handheld devices.RFID tags can be passively read with these devices up to 10 meters away, allowing for automatic and fast tracking of packages, product reels, or even individual components.
There are two types of RFID tags:
- • Passive, which does not require a power source
- • Active, which does require a power source
Active RFID tags can be sensed at ranges up to 100 meters from the RFID sensor device.Both types can be detected without a line-of-sight and through object and can cost less than 10 cents each.
NFC Tags, which stands for Near Field Communication tags, are a subset of RFID technologies that can store and transmit multiple types of data.They can be used for product authentication applications but are generally not used for product tracing.Rather, NFC tags can be used to validate product information and provide additional product data to smart manufacturing information systems.For more information on the difference between RFID and NFC, be sure to read RFID vs NFC: Difference Between RFID and NFC Explained.
RFID and NFC sensors have become essential to automated product tracing in smart manufacturing technology.They allow for product tracing from the point-of-production to the point-of-use in manufacturing supply chains, as well as from post-production to the point-of-sale and far beyond to a product’s end-of-life.
6 Types of Sensors Used in Production
The breadth of the production sector in smart manufacturing is vast and can be extremely complex.As such, there a wide array of sensors that are used in specialized smart manufacturing systems.These can be seen in bespoke machinery designs, production networks, and even throughout production facilities.Here is a list of some of the most common sensors found throughout production systems:
Temperature Sensors are often used in industries where critical temperatures must be met for proper product application, such as petrochemical, pharmaceutical, food, medical, and raw material manufacturing.For example, consumer-grade aluminum cans often have a food-safe plastic coating on the inside that must be applied at precise temperatures to properly adhere to the aluminum structure.
Hall Effect Sensors are commonly utilized for counting applications, whereby a magnet is fixed to a moving machine component.When that magnet is in the presence of a hall effect sensor, the sensor will detect its presence and provide data to the machine controller.For example, in a rotating bottle labeler, the position of the label spindle can be actively monitored and adjusted based on the magnetic input to the hall effect sensor, allowing for seamless automatic application of labels.
Infrared Sensors are utilized to monitor the infrared output of objects, which can remotely sense temperature data, gas composition analysis, object reflectivity, and surface smoothness.As an example, infrared sensors can be used to monitor gas composition in complex welding applications, such as titanium welding, where the presence of unwanted gases can be catastrophic to the manufacturing process.
Proximity Sensors are used to detect the proximity from the sensor to an object.Proximity sensors are largely used in smart manufacturing applications where machines automate manufacturing action.For example, pick-and-place machines used in electronics manufacturing pick single components from one location and place them in a precise destination.The control system of a pick-and-place machine can contain proximity sensors as a means of informing the tool about how close it is to the component upon ‘picking’ and the destination upon ‘placement’.
Accelerometers can be used in a multitude of smart manufacturing systems such as motor control, anti-theft, tap detection, tilt, object orientation, machine dynamics, and more.For example, the tool head of a 5-axic CNC milling machine will likely contain several accelerometers to ensure exact 3D placement of the tool is achieved during the milling process.
Level Sensors are used to understand fluid levels in fluid distribution and storage containers.In smart manufacturing industries that utilize fluids, the ability to understand the amount of the fluid being utilized can be essential to ensure a process is operating as expected.For example, semiconductor manufacturing facilities utilize hundreds of different fluids ranging from plastic slurries to highly volatile etching solvents.These fluids must be managed in accordance with procedural specifications.Level sensors can be used to understand their rate of use, required disposal quantities, and presence throughout a fluid-containing system.
Smart Manufacturing Sensor in Industry 4.0
Smart sensor technology in manufacturing systems can vary greatly throughout the industry but, regardless of the application, the information they provide is always critically important to the manufacturing process.While smart manufacturing sensors can vary in cost, size, technology, and utilization, sensors play a pivotal role in the transition from traditional manufacturing to smart manufacturing.The data they provide allows for modern control systems and data science to optimize manufacturing processes around the world.