More and more businesses are considering enhancing their operations with smart, connected products. The introduction of such products can provide numerous advantages. Customers will benefit from a wide range of enhancements, ranging from improved monitoring of product performance and the external environment to delegating certain stages of production to smart, connected equipment. Simultaneously, vendors of smart, connected products gain new revenue streams and competitive advantage.
Advanced Smart, Connected Products
Smart, connected products differ in maturity levels based on their capabilities: monitoring, control, optimization, and autonomy. These levels should be supported by an IoT architecture.
Monitoring
The first maturity level, monitoring, allows for a deeper look into the operating conditions of connected products, detecting deviations from norms, and issuing alerts. Monitoring provides every party involved with a smart, connected product with a better understanding of how the product is used and suggests which features should be added to the product.
Every party should have the same level of monitoring access. In a service-level agreement, the parties should define such a degree. Monitoring can also be used to test prototypes and identify flaws in machinery and vehicles before they are released to the public.
Control
Intelligent, connected products can be controlled via remote commands or algorithms (implemented in software installed directly on a smart, connected product or in the vendor’s cloud). Both of these options are required even in automated control because control apps may fail to perform the required operations. In such emergency situations, switching to manual control saves users’ assets.
Furthermore, in order to successfully perform its functions as part of the manufacturing processes, a smart, connected product may need to be integrated into a customer’s local systems (for example, SCADA, MES).
Optimization
The combination of monitoring and control capabilities opens up new avenues for optimising manufacturing processes. Sensor-generated big data can then be used to identify discrepancies between expected and actual performance and uncover inefficient processes. Real-time monitoring and product control enable predictive maintenance and remote repair, which reduce downtime and maintenance costs.
Autonomy
The three preceding levels, when combined and tuned to complement one another, enable smart, connected things to act with little or no human intervention. However, this is not true autonomy; such products must be coordinated with other products and systems that a customer uses. Nonetheless, it is a significant step towards a scenario in which the entire factory can work automatically, perform self-testing and maintenance, learn from the environment, and adapt to user preferences.
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