Integrated Scheduling of Production and Maintenance for Continuous Plants: Conditional Sequencing and Approximate Modeling of Storage

Abstract

In this study, we present extensions of earlier models for integrated scheduling of optimal production and planned maintenance for continuous and semicontinuous plants to account for different storage requirements. For handling finite storage, we propose approximate modeling of storage (without loss of generality) based on conditional sequencing without considering storage as a separate task. For dedicated storage tanks, when the "total amount to be stored" at an event is within the storage capacity, then we model an approximation of the amount stored. The conditional alignment of consumption and production tasks is extended for handling different storage policies. These features lead to reduction in the number of events. Two different models, based on task-specific and unit-specific timing variables, are proposed for handling finite intermediate storage (FIS), no intermediate storage (NIS), and zero wait (ZW) policies by modifying different constraints in the earlier models. The proposed models are presented for two cases based on the delivery of products and intermediates (1) as and when required and (2) at the end of the time horizon. The concept of planned maintenance is simultaneously incorporated with inventory management and optimal production. The proposed models are solved on different case studies, resulting in fewer events and better computational performance for small to medium scale problems, when compared with the literature model.

Designing synchronizer module in CMMS software based on lean smart maintenance and process mining

“…Other studies have adopted the integrated maintenance and operation approach to creating a model based on operation research to synchronize maintenance with other parts of a company's operations (Beheshti-fakher et al, 2016;Aguirre and Papageorgiou, 2018;Omar and Shaik, 2019;Li et al, 2021). These optimization issues are only applicable to a single business in a particular sector.…”

“…The studies of Beheshti-fakher et al. (2016), Aguirre and Papageorgiou (2018), Omar and Shaik (2019) and Li et al. (2021) suggested an operation research optimization model to combine maintenance and operation processes in order to enhance the overall performance of organizations in a variety of domains and situations.…”

“…An essential element of maintenance management that must be considered is the integration of knowledge, which is a major problem that has a considerable impact on enhancing the overall performance of industrial systems (Ruiz et al, 2013). The studies of Beheshti-fakher et al (2016), Aguirre and Papageorgiou (2018), Omar and Shaik (2019) and Li et al (2021) suggested an operation research optimization model to combine maintenance and operation processes in order to enhance the overall performance of organizations in a variety of domains and situations. Several methods were employed to solve their problem, including genetic algorithms (Ladj et al, 2016), heuristic algorithms (Guiras et al, 2018) and non-linear planning (Khatab et al, 2020).…”