Platform for industrial internet and digital twin focused education, research, and innovation: Ilmatar the overhead crane

Autiosalo, Juuso

doi:10.1109/wf-iot.2018.8355217

Cited by 45 publications

(40 citation statements)

References 11 publications

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“…A rough driving style also increases the risk of accidents. Thus, a system for estimating the usage roughness of an industrial overhead crane, Ilmatar [57] (Figure 7), was developed. The movement of the hook was measured with a three-axis accelerometer (Figure 8), which sent sensor readings constantly to an externally managed IoT platform via MQTT.…”

Section: Usage Roughness Of An Overhead Cranementioning

confidence: 99%

Open Sensor Manager for IIoT

Ala-Laurinaho

Autiosalo

Tammi

2020

JSAN

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Data collection in an industrial environment enables several benefits: processes and machinery can be monitored; the performance can be optimized; and the machinery can be proactively maintained. To collect data from machines or production lines, numerous sensors are required, which necessitates a management system. The management of constrained IoT devices such as sensor nodes is extensively studied. However, the previous studies focused only on the remote software updating or configuration of sensor nodes. This paper presents a holistic Open Sensor Manager (OSEMA), which addresses also generating software for different sensor models based on the configuration. In addition, it offers a user-friendly web interface, as well as a REST API (Representational State Transfer Application Programming Interface) for the management. The manager is built with the Django web framework, and sensor nodes rely on ESP32-based microcontrollers. OSEMA enables secure remote software updates of sensor nodes via encryption and hash-based message authentication code. The collected data can be transmitted using the Hypertext Transfer Protocol (HTTP) and Message Queuing Telemetry Transport (MQTT). The use of OSEMA is demonstrated in an industrial domain with applications estimating the usage roughness of an overhead crane and tracking its location. OSEMA enables retrofitting different sensors to existing machinery and processes, allowing additional data collection.

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Section: Usage Roughness Of An Overhead Cranementioning

confidence: 99%

Open Sensor Manager for IIoT

Ala-Laurinaho

Autiosalo

Tammi

2020

JSAN

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“…The starting point of the project was an Industrial Internet capable crane donated for the purpose of generating new knowledge around the crane as a platform, depicted in Figure 2 and described in [ 21 ]. The academic team started by gathering interesting opportunities from industry partners.…”

Section: The Casementioning

confidence: 99%

Using Low-Cost Sensors to Develop a High Precision Lifting Controller Device for an Overhead Crane—Insights and Hypotheses from Prototyping a Heavy Industrial Internet Project

Sjöman

Autiosalo

Juhanko

et al. 2018

Sensors

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The subject of this study was the product development project creating a new innovative proof-of-concept (POC) prototype device that could control a connected industrial overhead crane in order to perform automatic or semi-automatic high precision lifts within a limited time frame. The development work focused on innovating a new measuring concept, which was parallel to finding suitable sensors for the application. Furthermore, the project resulted in a closed loop control system with Industrial Internet connected sensors and a user interface for factory workers. The prototyping journey is depicted to illustrate the decisions made during the product development project to contribute to both the pragmatic and the process discussion in the field of Industrial Internet. The purpose of this research was to explore and generate hypotheses for how new applications should be developed for heavy industry connected devices. The research question is: what are the implications of applying agile product development methods, such as Wayfaring, to heavy industrial machinery and Industrial Internet -based problems? The methodologies used in this paper, in addition to developing the device, are case study research and hypotheses generated from case studies. The hypotheses generated include that it is also possible to prototype large size connected machinery with low-cost and in a short time, and investment decisions for heavy Industrial Internet products become easier with concrete data from proof-of-concept prototypes by creating knowledge about the investment risk and the value proposition.

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“…In this paper, an overhead crane called Ilmatar [10] is used as an example of an industrial machine for which a digital twin prototype is created following FDTF. Currently, the information of the crane is scattered across several systems that can be used to implement DT features.…”

Section: Introductionmentioning

confidence: 99%