Examination of the new machine's implementation in a software company

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dc.contributor.advisorMatkó, Andrea Emese
dc.contributor.authorShaukat, Samee
dc.contributor.departmentDE--Műszaki Kar
dc.date.accessioned2025-01-30T15:06:48Z
dc.date.available2025-01-30T15:06:48Z
dc.date.created2024-11-20
dc.description.abstractThis thesis explores the application, maintenance, and evaluation of laser cutting and bending technologies in the industrial sector. Through a combination of interviews, case studies, and machine performance data analysis, it identifies challenges like software integration issues, maintenance practices, and workforce training needs. Key Performance Indicators (KPIs) such as OEE, MTBF, and MTTR were analyzed to evaluate the impact of different maintenance strategies on machine performance. The findings highlight the superiority of predictive maintenance in reducing downtime and enhancing reliability compared to preventive approaches, particularly for SMEs facing integration and training challenges. Recommendations include adopting predictive maintenance, improving workforce training, and optimizing software systems.
dc.description.courseMechanical Engineeringen
dc.description.degreeBSc/BA
dc.format.extent48
dc.identifier.urihttps://hdl.handle.net/2437/386240
dc.language.isoen
dc.rights.accessHozzáférhető a 2022 decemberi felsőoktatási törvénymódosítás értelmében.
dc.subjectBending Machines
dc.subjectCutting Machines
dc.subjectsoftware company
dc.subject.dspaceEngineering Sciences
dc.titleExamination of the new machine's implementation in a software company
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Theses (Department of Mechanical Engineering)