Activity aggregation in model-based AI planning systems

Author(s):  
Graham Winstanley ◽  
Kunito Hoshi

When model-based planning systems are scaled up to deal with full-sized industrial projects, the resulting complexity in the project-specific model and production plan can create serious problems, not only in dealing with such complexity computationally, but also in user-acceptance. In the model-based planning system described in this paper, activities are dynamically generated, inherently at the detailed level of individual physical components. However, it is possible to intelligently group together collections of components which would be common to realistic work packages, and hence schedule on the basis of virtual components existing within an abstraction hierarchy. This paper describes a technique of project planning within an integrated design/planning system, which exploits fundamental knowledge of engineered systems and provides powerful and flexible planning functionality.

2015 ◽  
Vol 60 (16) ◽  
pp. 6213-6226 ◽  
Author(s):  
Brendan Barraclough ◽  
Jonathan G Li ◽  
Sharon Lebron ◽  
Qiyong Fan ◽  
Chihray Liu ◽  
...  

2020 ◽  
Vol 34 (06) ◽  
pp. 9883-9891 ◽  
Author(s):  
Daniel Höller ◽  
Gregor Behnke ◽  
Pascal Bercher ◽  
Susanne Biundo ◽  
Humbert Fiorino ◽  
...  

The research in hierarchical planning has made considerable progress in the last few years. Many recent systems do not rely on hand-tailored advice anymore to find solutions, but are supposed to be domain-independent systems that come with sophisticated solving techniques. In principle, this development would make the comparison between systems easier (because the domains are not tailored to a single system anymore) and – much more important – also the integration into other systems, because the modeling process is less tedious (due to the lack of advice) and there is no (or less) commitment to a certain planning system the model is created for. However, these advantages are destroyed by the lack of a common input language and feature set supported by the different systems. In this paper, we propose an extension to PDDL, the description language used in non-hierarchical planning, to the needs of hierarchical planning systems.


Author(s):  
Elisee Ilunga-Mbuyamba ◽  
Juan Gabriel Avina-Cervantes ◽  
Dirk Lindner ◽  
Felix Arlt ◽  
Jean Fulbert Ituna-Yudonago ◽  
...  

Author(s):  
James A. Stori ◽  
Paul K. Wright

Abstract Within the Integrated Design And Manufacturing Environment (IMADE), operation planning provides a mapping from geometric design primitives to machining operation sequences for manufacturing processes. Operation planning includes tool selection, machining parameter selection, and tool path generation. An object oriented approach to program structure is adopted, whereby features, operations and tools, inherit behaviors and attributes from the appropriate class-hierarchies for the part, the manufacturing operations, and tooling classes. A detailed example is presented illustrating the operation planning search algorithm. Scripts are generated by the individual machining operations for execution on a machine tool. Tooling information is maintained in an object-oriented database through the FAR libraries for Common LISP. Examples of particular process plans show that the inherent trade-offs between specified precision and machining time can be investigated. An Open Architecture Machine Tool (MOSAIC-PM) has been used to machine the parts created by the feature based design and planning system. The novel contributions of this paper relate to the demonstration of “seamless” links between, a) design, b) planning, and c) actual fabrication by milling.


Author(s):  
Christoph Bichlmaier ◽  
Stefan Grunwald

Abstract Competitive products are the key to the success of every company. To resist the pressure of high competition companies must also optimize their processes to an even greater extent. Apart from the direct production departments such as manufacturing and assembly, where the optimization of production processes have been standard practice for decades, the indirect areas such as product development and planning of production systems are now moving increasingly to center-stage. Alongside the requirement for innovation, these areas are expected to keep to schedule and cost restrictions. But the high degree of complexity of the process steps involved and the difficulty of accurately defining them prevent effective process management in these areas. Experience from industry shows that companies desire a lot of support in these areas. The following paper describes an innovative methodology for the flexible planning, monitoring and controlling of highly complex dynamic development processes. This methodology, has already proved successful in pilot projects in different industries such as automobile or electrical tool industry.


2004 ◽  
Vol 18 (2) ◽  
pp. 79-105 ◽  
Author(s):  
Andreas I. Nicolaou

Research indicates that successful adoption of information technology to support business strategy can help organizations gain superior financial performance. The recent wave of enterprise-wide resource planning systems adoptions is a significant commitment of resources and may affect almost all business processes. This study examines the effect of adoption of enterprise systems on a firm's long-term financial performance. A large-scale data identification and collection method compared the financial data of 247 firms adopting enterprise wide systems with a matched control group of firms cross-sectionally and longitudinally before and after adoption. A number of implementation characteristics were also measured and their effects assessed. The results show that firms adopting enterprise systems exhibit higher differential performance only after two years of continued use. Furthermore, controlling for implementation characteristics as vendor choice, implementation goal, modules implemented, and implementation time period, helped explain the financial performance effects of enterprise resource planning system use. These results provide important insights that complement extant research findings and also raise future research issues.


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