IoT-Based Automatic Non-conformity Detection: A Metalworking SME Use Case

Marques, Maria; Cunha, Adriana; Mohammed, Wael M.; Jardim‐Gonçalves, Ricardo; Agostinho, Carlos

doi:10.1007/978-3-030-13693-2_13

Cited by 2 publications

(1 citation statement)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…NCs in production may be observed from the viewpoints of many different disciplines, including management, economics, environment, technics or technology (Závadská and Závadský 2018). These facts are derived from a modern industrial organisation's goals, reduce production costs and amount of misused raw materials, and increase public awareness of environmental sustainability (Marques et al 2019, Teixeira et al .2020). Giorgetti et al (2017) introduced NCs reporting through the holistic model based on Root Cause Analysis and TRIZ method.…”

Section: Nonconformity Managementmentioning

confidence: 99%

A novel JavaScript MEAN stack approach for real-time nonconformity management in SMEs within Industry 4.0 and Quality 4.0 concepts

Đorđević¹,

Stefanović²,

Cvetić³

et al. 2021

Preprint

View full text Add to dashboard Cite

Nonconformity detection and reporting are evergoing issues in quality management practice and theory. Throughout industrialisation, and consequently, in the Industry 4.0 period, manufacturing organisations strived to reduce nonconformities to the minimum level and reach zero-defect production. Nowadays, it is feasible to overcome this issue by incorporating adequate information and communication technologies and edge devices for nonconformity reporting, and nonconformity classification. These assumptions were a starting point for the research presented in this paper. This paper aims to propose a software solution for nonconformity detection and preventive and corrective actions definition that expands the utilisation of edge devices in compliance with Industry 4.0 and Quality 4.0 paradigms. Presented software solution design is based on JavaScript programming language and its ability to be implemented in all software solution's tiers through interconnected frameworks (MongoDB, Express.js, Angular, and Node.js) in a MEAN stack. The developed solution is implemented in three small and medium enterprises. Initial results show several benefits in increasing nonconformity detection and reporting, increasing employee participation in preventive and corrective actions definition and improved quality management system. The number of corrective and preventive actions was taken based on the assistance of the prediction module. All nonconformities were related to specific sections of ISO 9001:2015 standards so that quality managers and managers in the companies could have insight into the sources of the issues and the foundation for defining different managerial actions. When comparing the newly developed solution and other affordable solutions, it was determined that the new solution has a higher operating velocity if there is a significant increase in the volume of queries towards databases. The paper's main contribution reflects in the software solution's presentation intended for affordable identification and nonconformities massive workload reporting, integrated with other software modules for quality analysis, prediction, and problem-solving. In this way, it is possible to obtain horizontal scalability and richness of the proposed software solution for smart enterprises focused on World Class manufacturing and lean manufacturing. Furthermore, it is possible to achieve a shorter time for nonconformities elimination and better compliance with the ISO 9001: 2015 standard. The presented solution usage contributes to all participants involved in the organisation of production and production itself, through (1) involvement of all employees; (2) digitalisation and improvement of existing nonconformity reporting systems; (3) improvement of nonconformity perception; (4) improved awareness and evaluation of employer's contribution to nonconformity management; (5) making the technology easy to use. The research's novelty lies in presented solution utilisation for real-time nonconformity classification and proactive and corrective measures proposals through communication and prediction modules.

show abstract

Section: Nonconformity Managementmentioning

confidence: 99%