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The scheduling of complex manufacturing systems requires the integration of production, inventory, and maintenance to obtain a robustness control and per-formance. In this context, this paper proposes a data-driven simulation-based op-timization approach for production scheduling to optimize job shop sequencing decisions considering inventory availability and machine breakdowns. The ap-proach consists in the implementation of a combination of genetic algorithm with discrete-event simulation model aiming to optimize the selection sets of dispatch-ing rules for groups of machines in the job shop to improve the manufacturing system performance. The approach was evaluated in a machining process, part of a job system of a Brazilian industry of the dental and medical sector, achieving better performance for the average lead time with the improvement of 10.27% compared to the current strategy of the company.
Scheduling Workforce In Decentrally Controlled Production Systems: A Literature Review
Chair of Logistics Engineering, Institute of Material Handling and Industrial Engineering, TU Dresden, Germany
Decentral production control plays a crucial role within the paradigm of Industry 4.0. Due to fast and flexible decisions on allocation and sequencing, there is no baseline schedule in advance. Moreover, the fourth industrial revolution modifies the organizational structures in the area of human resources, too. Despite changed tasks, the human is still a key factor with a coordinating, controlling and directing function—but without knowing the exact time of requirement. The workers are not available 24 hours a day but are provided individually via personnel schedules. Creating a personnel schedule for the changed tasks without an overall baseline schedule becomes a crux of efficient staff deployment in the vision of Industry 4.0. This article presents the current state of this research aspect and derives a challenge for future research.
Maintenance 4.0: A literature review and SWOT analysis
1Production Engineering Graduate Program, Federal University of Santa Catarina, Florianopolis, SC 88040-900, Brazil; 2Department of Mechanical Engineering, Federal University of Santa Catarina, Florianopolis, SC 88040-900, Brazil
Maintenance 4.0 (M4.0) is described as an innovative and optimized maintenance strategy, integrating existing practices with technologies from Industry 4.0. These technologies have been impacting and transforming several production processes and also maintenance management. It is possible to extract increasingly accurate data about the assets through sensors and other technologies in real-time. However, companies still struggle during the Maintenance 4.0 implementation, becoming an open field for research. Based on this, we developed a consistent literature review, followed by a SWOT analysis (strengths, weaknesses, opportunities, and threats) of Maintenance 4.0 implementation. The synthesis of the results was divided into bibliometric, thematic, and SWOT analyses. The bibliometric analysis showed the continuous growth of the theme in recent years. In the content analysis, the perspectives were grouped into (i) conceptual, theoretical studies, (ii) empirical studies/applications. In the SWOT analysis, we demonstrated the main strengths to achieve the benefits of implementing Maintenance 4.0. The weaknesses and threats identified may challenge some organizations. The implications of this study are in the organization of a comprehensive body of knowledge on Maintenance 4.0. From a practical point of view, it is hoped that this research can be used as a guideline, providing decision support to maintenance managers.