From a production system perspective, both human and technological capabilities, automation, are important for balance and robustness. Separating and standardizing the balance allocation or relationship between theses two is termed levels of automation (LoA). The purpose of this paper is to investigate the use of Value Stream Mapping to measure levels of automation in production value streams and to discuss suitable types of taxonomies for measuring automation. The results of two case studies show that different LoA models can be used when measuring, but preferable is to separate computerized and mechanized processes. A measurement methodology is also provided based on value stream mapping.

Operation and strategic decision making becomes more complex and dynamic related to the performance of industrial companies. In this light, the choice of a suitable and right automation level becomes critical and is a non-trivial decision making process. The purpose of this paper is to present definitions of manufacturing strategy, operational flexibility and automation levels in manufacturing. Further, this paper discusses linkages between process technology life stages, manufacturing strategy and levels of automation. A framework presenting critical and supportive factors affected by the choice of level of automation both short and long term give the basics for designating responsibilities to different categories of manufacturing managers. The choice of automation levels can be seen from and should be considered within different dimensions: (1) process life cycle stage; (2) fit with manufacturing strategy; and (3) organizational level.

The term Levels of Automation is defined in this paper as the interaction and task division between the human and the machine within a manufacturing system. This paper presents a model for identifying manufacturing parameters to control automation levels. The results show that different parameters are identified as capabilities that affect the level of automation and the output of the system. Conclusion is that the model presented can serve as a way to control and choose the right level of automation by adjusting either input parameters or the level of automation which together with performance measures form a continuous system.