Robust Design for Iot – On the Relevance of Mechanical Design for Robust Sensor Integration in Connected Devicesh.

Abstract

The terms IoT and Industry 4.0 are promising increasingly sophisticated solutions, but the realisation will depend on the inclusion of robust and reliable sensors. If the gathered data is flawed or inaccurate the performance of the whole system will be compromised. By reviewing research on robustness indicators, mechatronics and sensor properties as well as listing mechanical noise factors and providing an electromechanical trade-off example, the paper highlights the importance of considering both mechanical and electrical noise factors and robustness in early development of connected devices.

A Review on Sensor‐Integrating Machine Elements

“…[64] The development of robust measurement procedures, in particular of the devices of measurement used therein, such as SiME and the associated measurement signal processing, represents a subject of current research. [65] Based on the definition of robustness given above, disturbance factors can be differentiated into three categories according to Taguchi et al [63] Disturbances due to external causes (e.g., temperature, vibration), disturbances due to internal causes (e.g., wear, deterioration), and disturbances due to manufacturing or assembly tolerances. In the context of the development of robust measurement procedures, the first two categories are particularly relevant, as they have a time-dependent behavior and occur and vary depending on the context of the use of the system in which the sensory function is to be integrated.…”

“…In the context of the development of robust measurement procedures, the first two categories are particularly relevant, as they have a time-dependent behavior and occur and vary depending on the context of the use of the system in which the sensory function is to be integrated. [65] Furthermore, their temporal behavior is usually not exactly predictable. [66] In order to be able to develop robust measurement procedures, it is first necessary to generate knowledge within the framework of an analysis with regard to occurring disturbance factors and their impact on the measurement procedure and the components used in it.…”

“…The development of robust measurement procedures, in particular of the devices of measurement used therein, such as SiME and the associated measurement signal processing, represents a subject of current research. [ 65 ] Based on the definition of robustness given above, disturbance factors can be differentiated into three categories according to Taguchi et al. [ 63 ] Disturbances due to external causes (e.g., temperature, vibration), disturbances due to internal causes (e.g., wear, deterioration), and disturbances due to manufacturing or assembly tolerances.…”

Barriers for Industrial Sensor Integration Design—An Exploratory Interview Study

“…Depending on the requirements and the novelty of the IoT-application, the sensor performance will be more or less defined by a range of case specific noise factors. However, contributions on the methodical design of sensors are rare and in most cases out-dated, as also highlighted in a review on the importance of mechanical design for sensor systems by Juul-Nyholm et al [19]. Examples include Carr introducing a framework for sensor system noise factors [20] and Ellin and Dolsak [21] as well as Macini et al [22] describing interdisciplinary noise factors for encoders.…”

Perspectives on Robust Design – An Overview of Challenges and Research Areas Across Industry Fields

“…For new design tasks associated with the development of cyber-physical systems that rely on sensor data driven controls of the physical product (Welzbacher et al, 2022), AI / machine learning algorithms to provide contextual intelligence, or the management of design trade-offs in multidisciplinary products, the standard parametric robustness approach will not be sufficient. For example, when considering the question of a sensor variation (Juul-Nyholm et al, 2020), the robustness might for example be affected by its mechanical structure, its hardware, or also the chosen software and filtering solutions. Since all of these domains have their own terminology and understanding, and employ different approaches and tools to address variation and/or robustness in design and real time operation, a more systematic and holistic approach is necessary to carefully align all perspectives across different design phases.…”