Modeling and Performance Diagnostics of Composite Work Cells With Gantries

In this paper, the performance of a typical composite work cell structure that includes multiple machines and a material handling gantry is studied. A mathematic model is established to analyze the performance of such gantry systems. Due to the unique features of the gantry system, cycle time and waiting time of the gantry and machines are discussed and formulated based on two basic scenarios. To measure the impact of disruption events, permanent production loss is evaluated by using the sensor data collected from plant floors. Data-driven diagnostic methods are developed to identify the bottleneck machine and to evaluate permanent production loss attribution of each machine. The results provide a solid base to efficiently and effectively improve the performance of a composite work system. Performance diagnostics of gantry systems provides a theoretical and practical basis for production improvement. A gantry system for composite lay-up processes is used for numerical simulation case studies, by which the performance diagnostic methodologies and improvements are demonstrated. Note to Practitioners—Accurate performance diagnostics and effective improvement methods are critical to manufacturing operation and management. Most existing efforts are devoted to analyzing the performance of a whole production line rather than considering the complexity of each station/work cell in the line. This paper zooms into a composite work cell with a material handling gantry and focuses on the performance diagnostics of the lay-up station in a composite work center. The methods presented in this paper can be extended and applied to other manufacturing work cells comprising the similar gantry structure. We build a mathematical model to analyze the characteristics of the gantry system such as gantry cycle and waiting time. The evaluation of system production loss, which directly adopts sensor data from the factory floors, provides a quantitative tool for production engineers to monitor and control the system in real-time operation. In addition, the performance diagnostic methods based on production loss attribution and bottleneck identification are developed to guide the decision makers to improve the production system under different resource conditions. The methods are developed based on a work cell with only one gantry under a fixed gantry moving sequence. In the future research, we will extend the study to the systems with more gantries and more complex gantry moving policies.