A multi-event combination maintenance model based on event correlation

Abstract

Due to the complexity of large production systems, maintenance events are diverse, simultaneous and dynamic. Appropriate maintenance management of complex large production systems can guarantee high availability and save maintenance costs. However, current maintenance decision-making methods mainly focus on the maintenance events of single-components and series connection multi-components; little research pays attention to the combination maintenance of different maintenance events. Therefore, this paper proposes a multi-event combination maintenance model based on event correlation. First, the maintenance downtime and cost of three types of maintenance events under different maintenance beginning times and degrees are analysed. Then, shared maintenance downtime and cost models are established by maintenance event correlations. In addition, a multi-event combination maintenance model is constructed to achieve the goal of the highest availability and the lowest cost rate in both the decision-making cycle and the remaining life. Moreover, a particle swarm optimization algorithm based on interval segmentation for model solving is designed. Finally, a numerical example is presented to illustrate the model.

Modularizing Maintenance for Improved Production Impact Clarification

“…The physical state of the equipment is also important to maintenance performance measurements such as breakdown severity, mean time to repair, system complexity (Azadivar and Shu, 1999), and equipment age (Raouf, 1993). The process structure and an understanding of the dependencies is also important when implementing more knowledge intensive approaches such as predictive maintenance (van Horenbeek and Pintelon, 2013) or maintenance clustering (Cui and Li, 2006;Dekker et al, 1997;Do et al, 2015;Guo et al, 2018;Hu and Zhang, 2014;Nzukam et al, 2017;Wildeman et al, 1997). Equipment data can be stored in the CMMS, but can also be supported through documentation in the form of drawings or CAD models.…”

“…Another way to optimize maintenance is to group the actions taken. The grouping of maintenance can minimize the resources required and the production impact by taking advantage of the dependencies there are across maintenance actions (Dekker et al, 1997;Guo et al, 2018;Nzukam et al, 2017). This section introduces studies on maintenance data and maintenance in the dimensions proposed by : physical, action, and process, as well as the use of data to describe and document these dimensions.…”

Standardising Maintenance Jobs to Improve Grouping Decision Making

“…As seen from literature, criteria can be operations that describe the actions to be taken along with practical information about the job such as the type of job, the location, the required materials and so forth (Assaf and Shanthikumar, 1987;Dekker et al, 1997;Guo et al, 2018;Hu and Zhang, 2014;Li et al, 2018;Nzukam et al, 2017;Van et al, 2013). Before starting the process of standardisation it is…”