Technical planning parameters for the development of future car models with
reference to the optimal works structure for the manufacture of car bodies
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Abstract
Abstract
The digital factory is a broad computer based concept, which overwhelmingly integrates realworld
facilities into high-level information systems. The objective is to represent key
characteristics of the entire operational base on a common computer platform.
The main pillar of this 'new' concept is simulation modelling, which allows planners to
reproduce reality through easy to use computer software. Simulation attempts to reveal how
existing or ideal systems work or should work and is increasingly applied in managerial
decision making.
This 'new' planning concept draws upon on two equally important inputs for its models:
1. process knowledge
2. technical planning parameters.
Operations expertise in the form of process knowledge and planning parameters, such as
cycle time or availability, directly affect the outcomes of simulation modelling.
Accuracy of both factors is indispensable for making simulation models as realistic as
possible. But this is challenging to accomplish!
The difficulty to acquire profound process knowledge, which often takes years of experience,
is frequently ignored by advocates of the digital factory. Likewise, little attention is paid to the
challenge of retrieving and processing accurate planning parameters to feed into simulation
models.
Accuracy [or rather inaccuracy] is a latent obstacle for simulation and the digital factory as a
whole. Research and industry need to be aware of potential impacts.
Only the correct identification of possible shortfalls will make digital planning a precise and
trusted tool for management and research in the years to come