Production/maintenance control of multiple-product manufacturing system

Mifdal, Lahcen; Hajej, Zied; Dellagi, Sofiène

doi:10.1109/icocs.2014.7060904

Cited by 3 publications

(1 citation statement)

References 13 publications

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“…Joint maintenance and production control can improve overall production costs and efficiency (Rasay et al ., 2018; Kang and Subramaniam, 2018). Maintenance and production planning are interdependent as the degradation of the production system is dependent on the production rate (Hajej et al ., 2014) and maintenance times may interfere with production (Ao et al ., 2019). Insufficiently integrated planning for maintenance and production can pose a major problem for maintenance management systems (De Felice et al ., 2014; Bokrantz et al ., 2020).…”

Section: Opportunities For Internal Integration Supported By Data-dri...mentioning

confidence: 99%

Data-driven decision-making in maintenance management and coordination throughout the asset life cycle: an empirical study

Hinrichs,

Prifti,

Schneegass

2023

JQME

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PurposeWith production systems become more digitized, data-driven maintenance decisions can improve the performance of production systems. While manufacturers are introducing predictive maintenance and maintenance reporting to increase maintenance operation efficiency, operational data may also be used to improve maintenance management. Research on the value of data-driven decision support to foster increased internal integration of maintenance with related functions is less explored. This paper explores the potential for further development of solutions for cross-functional responsibilities that maintenance shares with production and logistics through data-driven approaches.Design/methodology/approachFifteen maintenance experts were interviewed in semi-structured interviews. The interview questions were derived based on topics identified through a structured literature analysis of 126 papers.FindingsThe main findings show that data-driven decision-making can support maintenance, asset, production and material planning to coordinate and collaborate on cross-functional responsibilities. While solutions for maintenance planning and scheduling have been explored for various operational conditions, collaborative solutions for maintenance, production and logistics offer the potential for further development. Enablers for data-driven collaboration are the internal synchronization and central definition of goals, harmonization of information systems and information visualization for decision-making.Originality/valueThis paper outlines future research directions for data-driven decision-making in maintenance management as well as the practical requirements for implementation.

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Section: Opportunities For Internal Integration Supported By Data-dri...mentioning

confidence: 99%

Data-driven decision-making in maintenance management and coordination throughout the asset life cycle: an empirical study

Hinrichs,

Prifti,

Schneegass

2023

JQME

View full text Add to dashboard Cite

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A Systematic Literature Review of Virtual and Augmented Reality Applications for Maintenance in Manufacturing

Buettner

Breitenbach

Wannenwetsch

et al. 2022

2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC)

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Production and Maintenance Planning for a Deteriorating System with Operation-Dependent Defectives

et al. 2018

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This paper provides new insights to the area of sustainable manufacturing systems at analyzing the novel paradigm of integrated production logistics, quality, and maintenance design. For this purpose, we investigate the optimal production and repair/major maintenance switching strategy of an unreliable deteriorating manufacturing system. The effects of the deterioration process are mainly observed on the failure intensity and on the quality of the parts produced, where the rate of defectives depends on the production rate. When unplanned failures occur, either a minimal repair or a major maintenance could be conducted. The integration of availability and quality deterioration led us to propose a new stochastic dynamic programming model where optimality conditions are derived through the Hamilton-Jacobi-Bellman equations. The model defined the joint production and repair/major maintenance switching strategies minimizing the total cost over an infinite planning horizon. In the results, the influence of the deterioration process were evident in both the production and maintenances control parameters. A numerical example and an extensive sensitivity analysis were conducted to illustrate the usefulness of the results. Finally, the proposed control policy was compared with alternative strategies based on common assumptions of the literature in order to illustrate its efficiency.

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Production/maintenance control of multiple-product manufacturing system

Cited by 3 publications

References 13 publications

Data-driven decision-making in maintenance management and coordination throughout the asset life cycle: an empirical study

Data-driven decision-making in maintenance management and coordination throughout the asset life cycle: an empirical study

A Systematic Literature Review of Virtual and Augmented Reality Applications for Maintenance in Manufacturing

Production and Maintenance Planning for a Deteriorating System with Operation-Dependent Defectives

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