Improve Total Production Maintenance with Artificial Intelligence

Mattioli, Juliette; Perico, Paolo; Robic, Pierre-Olivier

doi:10.1109/ai4i49448.2020.00019

Cited by 10 publications

(2 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Modern technologies exhibit huge potential to significantly reduce unplanned downtimes [37]. The overall downtime can be separated into three major phases [38,39]: Failure recognition, failure cause identification, and troubleshooting.…”

Section: Problem Statement and Delimitationmentioning

confidence: 99%

Impediments and Requirements for ICT Technology Adoption in Special Machinery Engineering and Its Impact on Sustainability

Legat,

Schöler,

Kottre

2023

Preprint

View full text Add to dashboard Cite

Special machinery engineering is of great importance to the manufacturing industry and makes a comparatively large contribution to many economies. Digital transformation is already well advanced in many producing industries, and modern ICT technologies such as agents, service orientation, digital twins and artificial intelligence are being used with increasing success. In addition to improving specific product characteristics such as reliability or flexibility, the adoption of modern ICT technologies to ensure sustainability is being intensively discussed. So far, however, there has been little uptake of these technologies in the special machinery industry; sustainability receives little attention. This article examines in detail the reasons for and impediments to the adoption of modern ICT technologies based on a study among special machinery manufacturers. Observations of existing challenges were gathered during daily work, described in detail, and used to derive conclusions about causal barriers. From this, detailed requirements are derived to promote the adoption of modern ICT technologies in the special machinery engineering sector and, ultimately, to bring sustainability more into focus.

show abstract

Section: Problem Statement and Delimitationmentioning

confidence: 99%

Impediments and Requirements for ICT Technology Adoption in Special Machinery Engineering and Its Impact on Sustainability

Legat,

Schöler,

Kottre

2023

Preprint

View full text Add to dashboard Cite

show abstract

“…An overview of key elements of Industry 4.0 researches and several application scenarios [6] highlighted the wide scope of smart manufacturing. Although many authors found that there is a lack of extensive review of Industry 4.0 revolution from different aspects, according to their persistent work nowadays, several articles are available in this topic [7]. A survey on the applications of optimal control to scheduling in production, supply chain, and Industry 4.0 systems [8] focused on maximum principle-based studies.…”

Section: Introductionmentioning

confidence: 99%

The Applicability of Reinforcement Learning Methods in the Development of Industry 4.0 Applications

2021

View full text Add to dashboard Cite

Reinforcement learning (RL) methods can successfully solve complex optimization problems. Our article gives a systematic overview of major types of RL methods, their applications at the field of Industry 4.0 solutions, and it provides methodological guidelines to determine the right approach that can be fitted better to the different problems, and moreover, it can be a point of reference for R&D projects and further researches.

show abstract

Challenges and Requirements for Improving Overall Equipment Effectiveness with Intelligent Manufacturing Technology in Special Machinery Engineering

Legat,

Schöler,

Kottre

2024

Studies in Computational Intelligence

View full text Add to dashboard Cite

Improve Total Production Maintenance with Artificial Intelligence

Cited by 10 publications

References 11 publications

Impediments and Requirements for ICT Technology Adoption in Special Machinery Engineering and Its Impact on Sustainability

Impediments and Requirements for ICT Technology Adoption in Special Machinery Engineering and Its Impact on Sustainability

The Applicability of Reinforcement Learning Methods in the Development of Industry 4.0 Applications

Challenges and Requirements for Improving Overall Equipment Effectiveness with Intelligent Manufacturing Technology in Special Machinery Engineering

Contact Info

Product

Resources

About