IoT Based Automatic Diagnosis for Continuous Improvement

Rita Martinho, Jéssica Lopes, Diogo Jorge, Luís Caldas de Oliveira, Carlos Henriques and Paulo Peças ()
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Rita Martinho: Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisboa, Portugal
Jéssica Lopes: Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisboa, Portugal
Diogo Jorge: EfficiencyRising, Lda, Erising, 1800-082 Lisboa, Portugal
Luís Caldas de Oliveira: INESC-ID, Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisboa, Portugal
Carlos Henriques: Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisboa, Portugal
Paulo Peças: IDMEC, Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisboa, Portugal

Sustainability, 2022, vol. 14, issue 15, 1-28

Abstract: This work responds to the gap in integrating the Internet-of-Things in Continuous Improvement processes, especially to facilitate diagnosis and problem-solving activities regarding manufacturing workstations. An innovative approach, named Automatic Detailed Diagnosis (ADD), is proposed: a non-intrusive, easy-to-install and use, low-cost and flexible system based on industrial Internet-of-Things platforms and devices. The ADD requirements and architecture were systematized from the Continuous Improvement knowledge field, and with the help of Lean Manufacturing professionals. The developed ADD concept is composed of a network of low-power devices with a variety of sensors. Colored light and vibration sensors are used to monitor equipment status, and Bluetooth low-energy and time-of-flight sensors monitor operators’ movements and tasks. A cloud-based platform receives and stores the collected data. That information is retrieved by an application that builds a detailed report on operator–machine interaction. The ADD prototype was tested in a case study carried out in a mold-making company. The ADD was able to detect time performance with an accuracy between 89% and 96%, involving uptime, micro-stops, and setups. In addition, these states were correlated with the operators’ movements and actions.

Keywords: Internet-of-Things; industrial Internet-of-Things; Lean Manufacturing; Lean & Green 4.0; continuous improvement; Industry 4.0 (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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