The efficient and effective handling of technical changes in product manufacturing, engineering, and production is seen as an important factor for the long-term success of manufacturing companies. Among the processes associated with manufacturing and production, engineering and manufacturing change management and the identification and involvement of all relevant stakeholders, i.e., departments and employees, play an essential role. Overlooking relevant stakeholders can lead to unforeseen impacts, such as production stops or further necessary changes, and can cause unforseen increased costs. In particular, in large companies, this task is complex and error-prone due to the high number of changes and departments involved, as well as the abundant variety of changes that can take place. Therefore, this contribution introduces an approach for stakeholder identification in technical change management, which allows the automated identification of relevant stakeholders at the beginning of the reactive phases of the change management process. The approach describes all necessary steps from data preparation to the evaluation of the obtained classification models. It is based on a text-classification approach and focuses in particular on the additional integration of expert knowledge to increase model quality. The approach has been successfully applied in cooperation with a German automotive company, and the obtained model quality has been compared to an expert-based classification.
Based on an analysis of research and industrial trends, the paper introduces the basis of a conceptual research framework for an innovative methodology dedicated to design, implement and manage Reconfigurable Manufacturing Systems (RMS). The authors present key challenges extracted from the literature and key industrial needs for RMS, drawn from expert interviews via an industry study. A conceptual framework for reconfigurability management is proposed, which opens several avenues for future research.
Shorter product innovation cycles, high variant products, and demand fluctuation, as well as equipment life cycles and technology life cycles force manufacturing companies to regularly change their manufacturing system. In order to address this challenge, an efficient and structured change management is required. As change causes and factory elements are connected via a complex network of relations and flows, an essential step in change management is the evaluation of considered adjustments with regard to their effects on the current production system. Depending on the context of the application, change impact analysis must process specific inputs and deliver different results. Current approaches, however, each focus only on selected aspects of the versatility of change effects. To address this challenge, this paper presents a modular approach for the individual design of change impact analysis.
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