Change Management through Learning Factories

Dinkelmann, Max; Siegert, Jörg; Bauernhansl, Thomas

doi:10.1007/978-3-319-02054-9_67

Cited by 11 publications

(1 citation statement)

References 9 publications

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“…A Learning Factory offers an approach to representing manufacturing works at an operational level (Barton & Delbridge, 2001), providing a facility dedicated to simulating real production processes and environments according to academic and educational purposes (Tisch, Hertle, Abele, Metternich, & Tenberg, 2015). According to Dinkelmann, Siegert, and Bauernhansl (2014) and Tisch et al (2015), besides educational objectives, a Learning Factory may also be used for research purposes. This structure was chosen because it provided the industrial environment necessary for applying the study proposal and enabled the management of the process variables without disrupting the production.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Influence of Standard Time Variability on the Reliability of the Simulation of Assembly Operations in Manufacturing Systems

Machado

Helleno²,

Oliveira³

et al. 2019

Hum Factors

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Objective: The aim of this article is to analyze the influence of the variability of the standard time in the simulation of the assembly operations of manufacturing systems. Background: Discrete event simulation (DES) has been used to provide efficient analysis during the design of a process or scenario. However, the modeling activities of new configurations face the problem of data availability and reliability when it comes to seeking standard times that are effective in representing the actual process under analysis, especially when the process cannot be monitored. Method: The methods-time measurement (MTM) is used as a source of standard times for simulation. Assembly activities were performed at a Learning Factory facility, which provided the necessary structure for simulating real production processes. Simulation performances using different variability of standard times were analyzed to define the impact of data characteristics. Results: The MTM standard time presented an error of approximately 5%. The definition of the data variability of standard times and the statistical distribution impacts were shown in the simulation results, with errors above 6% being observed, interfering with the model reliability. Conclusion: Based on the study, to increase the adherence of a simulation to represent a real process, it is recommended to use triangular distributions with central values greater than those established via the MTM for the representation of the standard times of new assembly processes or scenarios using DES. Application: The study contributions can be applied in assembly line design, providing a reliable model representing real processes and scenarios.

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