PriMa: a prescriptive maintenance model for cyber-physical production systems

Abstract

Cyber-physical production systems (CPPS), as an emerging Industry 4.0's technology, trigger a paradigm shift from descriptive to prescriptive maintenance. In particular, maintenance management approaches nowadays are more and more transformed to (semi-) automated knowledge-based decision support systems. This paper is intended to examine existing approaches and challenges towards rethinking maintenance in the context of Industry 4.0 and thus contributes to the literature of production management and planning, by introducing a novel prescriptive maintenance model (PriMa). PriMa is comprising of four layers (i.e. data management, predictive data analytic toolbox, recommender and decision support dashboard as well as an overarching layer for semantic-based learning and reasoning). The integrated approach of PriMa enhances two functional capabilities, namely i) efficiently processing large amount of multi-modal and heterogeneous data collected from multidimensional data sources and ii) effectively generating decision support measures and recommendations for improving and optimising forthcoming maintenance plans correlated with production planning and control (PPC) systems. An industry-oriented proof-of-concept study has been conducted to explore the feasibility of applying PriMa in real production systems by implementing a decision support solution and achieving a significant reduction of downtime. Finally, future research directions in this area are outlined. ARTICLE HISTORY

A smart process controller framework for Industry 4.0 settings

“…The work is focused on the issue of processing massive amounts of real-time data with minimal latency. While Wu et al (2017) propose sampling as a means of reducing the amount of ML processing, our approach is different: we advocate close local monitoring that only Tables 1 and 2. Both Matyas et al (2017) and Ansari et al (2019) propose a circular model with four steps: (1) data acquisition and re-processing; (2) data analysis and simulation; (3) reaction model; (4) prescriptive maintenance decision support. Algabroun et al (2017) propose "maintenance 4.0" framework.…”

Availability Optimization of Two-dimensional Warranty Products Under Imperfect Preventive Maintenance

“…2D warranty system as a type of Cyber physical production systems (CPPS) propels a maintenance mode shift from descriptive to prescriptive maintenance. On this basis, Ansari [16] has developed a type of prescriptive maintenance model based on knowledge and data management, which can effectively generating decision support measures and recommendations in the context of Industry 4.0. Prescriptive maintenance planning is a significant contributor of intelligent and flexible production processes.…”

Marco de referencia para la incorporación de Cobots en líneas de manufactura

“…La posibilidad de tener digitalizado gran parte del proceso de trabajo en las celdas mejorará notablemente la calidad de la información, ya que permitiría el monitoreo y control en tiempo real de las diferentes actividades, tal como se muestra en la Figura 5 (Ansari, Glawar, y Nemeth, 2019).…”