Improving Procedures for Production and Maintenance Control Towards Industry 4.0 Implementation

Costa, Rúben D. F. S.; Barbosa, Marta L. S.; Silva, Francisco; Sá, José Carlos; Ferreira, Luı́s Pinto; Pinto, B.

doi:10.1007/978-3-031-09382-1_6

Cited by 2 publications

(3 citation statements)

References 23 publications

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“…However, digital transformation presents new challenges and barriers to the adoption of these technologies, particularly in terms of security and protection, initial investment, trust, research and development, technological barriers, organizational management, human capital, and the lack of financial resources (Costa et al 2023). In this study, the majority of respondents identified the efficiency of production and management systems as the main positive impacts resulting from the adoption of Industry 4.0 tools.…”

Section: Discussionmentioning

confidence: 83%

“…This need for adaptation is transversal across all companies and has led machine manufacturers and suppliers to seek continuous improvement of the equipment they offer on the market (Vieira et al 2022). Costa et al (2023) identified problems on the shop floor due to a need to increase information and control of the production and maintenance processes. With the integration of Industry 4.0 concepts in the organization, it was possible to make the process more profitable for the company, since it was no longer necessary for the heads of the assembly line to regularly stop by to prepare a detailed report of the current status.…”

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Digital Culture, Knowledge, and Commitment to Digital Transformation and Its Impact on the Competitiveness of Portuguese Organizations

Cardoso,

Pereira,

Sá

et al. 2023

Administrative Sciences

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This study aimed to understand the impact of digital culture on companies’ knowledge and constant commitment to digital transformation, as well as its impact on organizations as a whole. Secondly, it aimed to explore the impact of digital technology adoption on organizational performance and competitiveness. Finally, the study investigated the role of knowledge management during digital transformation. A quantitative study was developed using a descriptive design. A questionnaire was developed on pre-test was carried out withon 15 participants and since no doubts or difficulties were detected, it was made available on the internet between January and April 2022. A total of 291 questionnaires were collected and validated. Data were imported from Google Forms for analysis in SPSS, version 25.0, andSmartPLS® 4.0 software. The questionnaire revealed good internal consistency (α = 0.922). Ten of the twelve hypotheses were confirmed, that is, the existence of positive and significant relationships between digital culture (DC) and knowledge of digital transformation (KDT); DC and adoption of digital technologies (ADT); DC and knowledge management (KM); commitment (C) and KDT; C and productivity (P); KDT and ADT; ADT and KM; ADT and P; ADT and C; and P and C. The results of regression analyses showed that the variables that contributed to the model (“competitiveness of organizations”) were productivity, the adoption of digital technologies, commitment to digital technologies, and knowledge management. The variables CD and KDT (Knowledge of digital transformation) presented lower and non-significant values.

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Section: Discussionmentioning

confidence: 83%

Section: Literature Reviewmentioning

confidence: 99%

Digital Culture, Knowledge, and Commitment to Digital Transformation and Its Impact on the Competitiveness of Portuguese Organizations

Cardoso,

Pereira,

Sá

et al. 2023

Administrative Sciences

View full text Add to dashboard Cite

show abstract

“…Therefore, the proposed methodology aims to address this gap by proposing a new rule-based ML framework for improving OEE by experimenting with the automotive industry, which is constantly challenged by strong competitiveness in terms of product quality and process efficiency (Costa et al ., 2022). Specifically, the proposed approach is based on the integration of the analysis of the Six Big Losses and ARs for the detection, classification and prioritization of major anomalies through the Eisenhower Matrix.…”

Section: Introductionmentioning

confidence: 99%

A rule-based machine learning methodology for the proactive improvement of OEE: a real case study

Lucantoni,

Antomarioni,

Ciarapica

et al. 2023

IJQRM

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PurposeThe Overall Equipment Effectiveness (OEE) is considered a standard for measuring equipment productivity in terms of efficiency. Still, Artificial Intelligence solutions are rarely used for analyzing OEE results and identifying corrective actions. Therefore, the approach proposed in this paper aims to provide a new rule-based Machine Learning (ML) framework for OEE enhancement and the selection of improvement actions.Design/methodology/approachAssociation Rules (ARs) are used as a rule-based ML method for extracting knowledge from huge data. First, the dominant loss class is identified and traditional methodologies are used with ARs for anomaly classification and prioritization. Once selected priority anomalies, a detailed analysis is conducted to investigate their influence on the OEE loss factors using ARs and Network Analysis (NA). Then, a Deming Cycle is used as a roadmap for applying the proposed methodology, testing and implementing proactive actions by monitoring the OEE variation.FindingsThe method proposed in this work has also been tested in an automotive company for framework validation and impact measuring. In particular, results highlighted that the rule-based ML methodology for OEE improvement addressed seven anomalies within a year through appropriate proactive actions: on average, each action has ensured an OEE gain of 5.4%.Originality/valueThe originality is related to the dual application of association rules in two different ways for extracting knowledge from the overall OEE. In particular, the co-occurrences of priority anomalies and their impact on asset Availability, Performance and Quality are investigated.

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Improving Procedures for Production and Maintenance Control Towards Industry 4.0 Implementation

Cited by 2 publications

References 23 publications

Digital Culture, Knowledge, and Commitment to Digital Transformation and Its Impact on the Competitiveness of Portuguese Organizations

Digital Culture, Knowledge, and Commitment to Digital Transformation and Its Impact on the Competitiveness of Portuguese Organizations

A rule-based machine learning methodology for the proactive improvement of OEE: a real case study

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