Model-based process planning and control: laser beam welding with CALAS

Author(s):  
Michael J. Dahmen ◽  
B. Fuerst ◽  
Stefan Kaierle ◽  
Ernst-Wolfgang Kreutz ◽  
Reinhart Poprawe ◽  
...  
1981 ◽  
Vol 107 (4) ◽  
pp. 269-279
Author(s):  
Alexander F. Dinsmore ◽  
David Burgoine

Author(s):  
Koji Kimita ◽  
Johannes Matschewsky ◽  
Tomohiko Sakao

Abstract Remanufacturing is a crucial component for our societies to move toward a circular economy. Compared to new manufacturing, the distinctive nature of remanufacturing is found to have high variability, high uncertainty and, thereby, complexity. Therefore, remanufacturers need to be able to adapt to the complexity and to flexibly adjust their processes. Especially, the ability to remanufacturing process planning and control is important. However, few practical methods supporting that are available so far. Therefore, this paper aims to propose a method for designing teams and processes in remanufacturing based on the concept of loosely coupled systems. In the proposed method, Design Structure Matrix (DSM) is applied to identify loosely coupled sub-systems that enable to localize impacts of changes within themselves. These sub-systems are also regarded as cross-functional teams that reduce coordination efforts among line departments and therefore increase the adaptability against uncertainties. As a preliminary validation, the proposed method was applied to a real case of remanufacturing, and then found to be effective for creating teams and processes for remanufacturing process planning and control depending on given uncertainties.


AI Magazine ◽  
2013 ◽  
Vol 34 (3) ◽  
Author(s):  
Lara S. Crawford

A recent trend in intelligent machines and manufacturing has been toward reconfigurable manufacturing systems, which move away from the idea of a fixed factory line executing an unchanging set of operations, and toward the goal of an adaptable factory structure. The logical next challenge in this area is that of on-line reconfigurability. With this capability, machines can reconfigure while running, enable or disable capabilities in real time, and respond quickly to changes in the system or the environment (including faults). We propose an approach to achieving on-line reconfigurability based on a high level of system modularity supported by integrated, model-based planning and control software. Our software capitalizes on many advanced techniques from the artificial intelligence research community, particularly in model-based domain-independent planning and scheduling, heuristic search, and temporal resource reasoning. We describe the implementation of this design in a prototype highly modular, parallel printing system.


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