Abstract
Data and information in production systems engineering are the counterpart of material in production. To increase effectiveness and efficiency, waste in data and information flow must be defined in analogy to lean paradigm. For this purpose, the known eight types of waste are transferred to the data and information flow of production systems engineering, considering engineering activities and chain, to achieve overall process optimum. The validation of the defined types of waste using six case studies confirms their applicability and significance in terms of continuous engineering process improvement.
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