Details
Original language | English |
---|---|
Pages (from-to) | 393-398 |
Number of pages | 6 |
Journal | Procedia CIRP |
Volume | 107 |
Early online date | 26 May 2022 |
Publication status | Published - 2022 |
Abstract
Since the beginning of global networking, the environment of production systems has been considered a turbulent zone, in which the unpredictability of economic, technical and political trends characterizes a phase of sudden and high speed of change. These changes can lead to disturbances in factory operation resulting in economic losses. Therefore, each change requires time to adapt to reach and maintain a certain performance level. One element of a factory are the employees working on production processes, maintenance or further support functions. Employee specific learning behavior of production tasks is already investigated in detail and describes the constantly increasing performance based on a learning process. To reach a certain level of productivity, employees require a specific timeframe. The duration of the timeframe depends on further factors e.g. task complexity or individual learning ability. Learning behavior is similar to the adaption of factories to change events, which is why it offers a basis for describing the proven concept of changeability. Therefore, the goal of this paper is to relate the characteristics of learning curves to changeability of factories in order to develop a framework for assessing the impact of change. The framework contains starting points for influencing the learning process in terms of its speed or necessity, as well as for estimating the point in time at which a factory is ready for change again. For this purpose, possible influencing factors such as resilience or transformability, and the significance of production logistic key figures are examined in a more detailed analysis.
Keywords
- Change management, Changeability, Factory planning, Learning behaviour
ASJC Scopus subject areas
- Engineering(all)
- Control and Systems Engineering
- Engineering(all)
- Industrial and Manufacturing Engineering
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In: Procedia CIRP, Vol. 107, 2022, p. 393-398.
Research output: Contribution to journal › Conference article › Research › peer review
}
TY - JOUR
T1 - Framework for assessing the impact of change on a factory by adapting learning behavior models
AU - Hingst, Lennart
AU - Ast, Jonas Martin
AU - Nyhuis, Peter
PY - 2022
Y1 - 2022
N2 - Since the beginning of global networking, the environment of production systems has been considered a turbulent zone, in which the unpredictability of economic, technical and political trends characterizes a phase of sudden and high speed of change. These changes can lead to disturbances in factory operation resulting in economic losses. Therefore, each change requires time to adapt to reach and maintain a certain performance level. One element of a factory are the employees working on production processes, maintenance or further support functions. Employee specific learning behavior of production tasks is already investigated in detail and describes the constantly increasing performance based on a learning process. To reach a certain level of productivity, employees require a specific timeframe. The duration of the timeframe depends on further factors e.g. task complexity or individual learning ability. Learning behavior is similar to the adaption of factories to change events, which is why it offers a basis for describing the proven concept of changeability. Therefore, the goal of this paper is to relate the characteristics of learning curves to changeability of factories in order to develop a framework for assessing the impact of change. The framework contains starting points for influencing the learning process in terms of its speed or necessity, as well as for estimating the point in time at which a factory is ready for change again. For this purpose, possible influencing factors such as resilience or transformability, and the significance of production logistic key figures are examined in a more detailed analysis.
AB - Since the beginning of global networking, the environment of production systems has been considered a turbulent zone, in which the unpredictability of economic, technical and political trends characterizes a phase of sudden and high speed of change. These changes can lead to disturbances in factory operation resulting in economic losses. Therefore, each change requires time to adapt to reach and maintain a certain performance level. One element of a factory are the employees working on production processes, maintenance or further support functions. Employee specific learning behavior of production tasks is already investigated in detail and describes the constantly increasing performance based on a learning process. To reach a certain level of productivity, employees require a specific timeframe. The duration of the timeframe depends on further factors e.g. task complexity or individual learning ability. Learning behavior is similar to the adaption of factories to change events, which is why it offers a basis for describing the proven concept of changeability. Therefore, the goal of this paper is to relate the characteristics of learning curves to changeability of factories in order to develop a framework for assessing the impact of change. The framework contains starting points for influencing the learning process in terms of its speed or necessity, as well as for estimating the point in time at which a factory is ready for change again. For this purpose, possible influencing factors such as resilience or transformability, and the significance of production logistic key figures are examined in a more detailed analysis.
KW - Change management
KW - Changeability
KW - Factory planning
KW - Learning behaviour
UR - http://www.scopus.com/inward/record.url?scp=85132262640&partnerID=8YFLogxK
U2 - 10.1016/j.procir.2022.04.064
DO - 10.1016/j.procir.2022.04.064
M3 - Conference article
VL - 107
SP - 393
EP - 398
JO - Procedia CIRP
JF - Procedia CIRP
SN - 2212-8271
ER -