An intelligent maintenance planning framework prototype for production systems

2017 ◽  
Author(s):  
Simon Kranzer ◽  
Dorian Prill ◽  
Davood Aghajanpour ◽  
Robert Merz ◽  
Rafaela Strasser ◽  
...  
Keyword(s):  
Production Systems ◽  
Maintenance Planning ◽  
Intelligent Maintenance ◽  
Planning Framework

scholarly journals A Systematic Approach to Intelligent Maintenance of Production Systems with a Framework for Embedded Implementation

2013 ◽  
Vol 46 (7) ◽  
pp. 23-28 ◽  
Author(s):  
Edzel R. Lapira ◽  
Behrad Bagheri ◽  
Wenyu Zhao ◽  
Jay Lee ◽  
Renato VB Henriques ◽  
...  
Keyword(s):  
Systematic Approach ◽  
Production Systems ◽  
Intelligent Maintenance ◽  
Embedded Implementation

scholarly journals Automation of Predictive Maintenance Using Internet of Things (IoT) Technology at University-Based O&M Project

2021 ◽  
Vol 11 (7) ◽  
pp. 332-336
Author(s):  
James Ryan Fernandez ◽  
◽  
Yogi Tri Prasetyo ◽  
Satria Fadil Persada ◽  
A. A. N. Perwira Redi
Keyword(s):  
Internet Of Things ◽  
Mobile Applications ◽  
Performance Indicator ◽  
Predictive Maintenance ◽  
Fault Prediction ◽  
Maintenance Cost ◽  
Maintenance Planning ◽  
Significant Deterioration ◽  
Sustainable Operations ◽  
Planning Framework

Predictive Maintenance can be defined as a type of advanced maintenance that detects the onset of system degradation allowing causal stressors to be eliminated or controlled prior to any significant deterioration in component physical state. Thru Internet of Things (IoT) Technology, automation, and implementation of Predictive Maintenance are possible. The purpose of this study is to propose the implementation of Predictive Maintenance using IpT Technology at University-based Operation & Maintenance Project that aims to transform the current Key Performance Indicator (KPI) of PM to CM Ratio from 80:20 to 90:10. Six Sigma DMAIC Methodology and Data-Driven Predictive Maintenance Planning Framework were utilized as the methodology of this research. Research’s results show that KPI, 90:10 (PM to CM Ratio) is achievable and maintenance cost can significantly reduce from 25% to 30%. Other valuable benefits are return of investment (10X), elimination of breakdown (70 - 75%), reduction in downtime (35% - 45%) and increase of production (20% - 25%). The proposed concept can be utilized in other industries to achieve high customer satisfaction percentages, sustainable operations, fault prediction, and online monitoring using PC or mobile applications.

scholarly journals Integrated production and maintenance planning in cyber-physical production systems

Procedia CIRP ◽  
2019 ◽  
Vol 79 ◽  
pp. 534-539 ◽  
Author(s):  
Martin Schreiber ◽  
Kilian Vernickel ◽  
Christoph Richter ◽  
Gunther Reinhart
Keyword(s):  
Production Systems ◽  
Maintenance Planning ◽  
Integrated Production ◽  
Cyber Physical Production Systems

scholarly journals Integrated Production and Maintenance Planning for Cyber-physical Production Systems

Procedia CIRP ◽  
2018 ◽  
Vol 72 ◽  
pp. 934-939 ◽  
Author(s):  
M. Schreiber ◽  
J. Klöber-Koch ◽  
C. Richter ◽  
G. Reinhart
Keyword(s):  
Production Systems ◽  
Maintenance Planning ◽  
Integrated Production ◽  
Cyber Physical Production Systems

Simulation-Based Analysis of Intelligent Maintenance Systems and Spare Parts Supply Chains Integration

2019 ◽  
Vol 28 (1) ◽  
pp. 31-42 ◽  
Author(s):  
Enzo M. Frazzon ◽  
Tulio H. Holtz ◽  
Lucas S. Silva ◽  
Matheus C. Pires
Keyword(s):  
Supply Chains ◽  
Production Systems ◽  
Cost Effective ◽  
Spare Part ◽  
Spare Parts ◽  
Safety Stocks ◽  
Intelligent Maintenance ◽  
Simulation Based ◽  
Maintenance Systems ◽  
The Right

Abstract Production systems are composed of increasingly complex components with unique specifications. Therefore, since holding safety stocks of each component would be prohibitive, maintenance activities rely on the proper delivery of spare parts, making it available at the right time and place. Equipments monitored by sensors as well as the transmission of sensors data to the spare part supply chain represent an interesting venue for dealing with this contemporaneous industrial challenge. In this direction, this paper applies a simulation model derived from a real world scenario to analyze the performance of the collaboration between condition-based maintenance – also known as intelligent maintenance systems – and spare parts supply chains, in comparison with existing maintenance approaches. Obtained results substantiate the potential of monitoring, treating and transmitting equipment condition data to ensure cost-effective maintenance and production systems availability.

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