The GO0D MAN consortium can take advantage of the collaboration of an External Advisory Board, composed by two members, Prof. Jianjun Shi and Prof. Shozo Takata.
For the plenary meeting in Wien, we had the honour to guest one of them: Professor Jianjun Shi, from Georgia Institute of Technology. He received his B.S. and M.S. in Electrical Engineering at the Beijing Institute of Technology in 1984 and 1987, and his Ph.D. in Mechanical Engineering at the University of Michigan in 1992. He is the Carolyn J. Stewart Chair and Professor at H. Milton Stewart School of Industrial and Systems Engineering and George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology. Professor Shi’s research interests focus on system informatics and control for the design and operational improvements of manufacturing and service systems. He is one of the early pioneers in this field.
Our meeting was a welcome opportunity to listen to Professor Shi’s presentation titled “System Informatics and Control for Multistage Manufacturing Systems”, observing lot of examples in which he applied a model to perform the multistage control.
Let’s discover what Professor Shi presented in details, starting from the definition of a Multistage System, composed by multiple components, stations or stages required to produce a product or service.
Multistage systems are very common in practice and include a variety of modern manufacturing and service systems. In most cases, the quality of the final product or service produced by a multistage system is determined by complex interactions among multiple stages—the quality characteristics at one stage are not only influenced by local variations at that stage, but also by variations propagated from upstream stages.
In the figure below, you can see a schematization for a Multistage System as reported in his work entitled: “Quality control and improvement for multistage systems: A survey”. In particular, you can distinguish xi, and zi that are the process variables and yi that instead is the quality output variable of each stage.
This diagram is the lean representation of what GO0D MAN aims to introduce in production lines, in order to implement a distributed quality control infrastructure in which feedbacks between stages and data exchange are crucial aspects.
Professor Shi also identified three main layers (enhanced in the following figure) in a process: the physical network, the sensor network and the casual network. The casual network is the brain where the decision-making takes place; it receives design data about the process and the product from the manufacturing system network, while system operational data arise from the distributed sensing network.
Professor Shi presentation was very useful to confirm that Multi Manufacturing Process is an emerging research area all over the world, which provides opportunities and challenges, for quality and reliability improvements in data rich environment. This requires multidisciplinary efforts, as Prof. Shi underlined, from domain knowledge, statistics, signal processing, and decision-making.