Data Fusion for Adaptive Control in Manufacturing: Impact on Engineering Information Models

Abstract

Abstract This paper addresses the impact of data fusion on engineering and manufacturing information systems. Data fusion is the integration and analysis of data from multiple sensors to develop a more accurate understanding of a situation and determine how to respond to it. (Sensor fusion, a related term, has a somewhat different, more implementation oriented focus. The difference between these two concepts is addressed specifically in Section 1.) Although data fusion can be applied in many situations, this paper focuses on its application to manufacturing and how it changes some of the more traditional, less adaptive information models that support the design and manufacturing functions. Data fusion requires changes, primarily extensions, to these traditional information models. Engineering models normally address geometry, features, and performance characteristics of a part, while manufacturing models address machine tool characteristics and how they interact with the workpiece and operations scheduling. For data fusion and adaptive control, these models must include the dynamic behavior and interactions between the workpiece and the machine tool. In addition, these models must specify how these dynamic behaviors can be seen and interpreted by various types of sensors (e.g. temperature, pressure, and vibration). On a broader level it must also consider how the machine tools and robots interact within a work cell or production line. The paper consists of four parts. The first section explains what data fusion is and its impact on manufacturing. The second section describes what an information system architecture is and explains the natural language-based information modeling methodology used by this research project. The third section identifies the major design and manufacturing functions, reviews the information models required to support them, and then shows how these models must be extended to support data fusion. The fourth section discusses the future directions of this work.