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Towards Adaptive Management Systems in Manufacturing: An Agent-Supported Approach
IFOR Events
Seminar:
'Optimization & Applications'
(see information & program)
Feb 20 - May 28, 2012
IFOR Mitteilungen
This booklet informs about ongoing projects and future events at the IFOR and appears once at the end of the year.
| Author | Jens Henoch |
| Abstract |
Owing to changing customer demands and expectations, a shift from build-to-forecast to build-to-order production for competitive reasons often becomes necessary in manufacturing. Management systems as a vital part of manufacturing systems have to master these new requirements, i.e. management systems have to cope with complexity and uncertainty. The motivation for this study is based on the observation that a rigid centralized approach to manufacturing planning and control is no longer appropriate. Therefore, this dissertation promotes an agent-based approach as a means of supporting operationally human-centered management systems towards an adaptive and flexible conduct, nowadays essential in manufacturing. The core of this thesis presents a modeling and simulation framework integrating concepts of the fields of management cybernetics, production logistics management, artificial intelligence, and object-oriented concurrent programming. As such, the work is at the crossroads of these fields. The framework features three modeling levels. The resulting models can be verified separately utilizing simulation. Physical layout considerations-such as the selection of machines to be utilized-are mapped on the physical level. Operational issues are addressed at the logical level, meaning that instructions are given on how to operate a physical system. Organizational structures and task responsibilities regarding the operations are modeled on the management level. The organizations being mapped on the management level of this framework are multi-agent systems providing means for management systems in their striving to improve their adaptiveness to the situational conditionalities of the shop-floor. In order to effectively support management systems, multi-agent systems must follow the structural guidelines as proposed by cybernetics. Operationalized, the framework supports recursively structured multi-agent systems, in which the behaviors of planning, scheduling and execution can be found in every multi-agent system. Thus, a behavior determines an agent's entire action repertoire, denoted also as capabilities. The advanced level of adaptive conduct as a source for building eigen-variety is supported in a way that agents feature multiple levels of adaptation. Owing to the multi-level adaptation process, robustness can be gained by attenuating uncertainty. In order to maintain the system's cohesion, the adjustment of agents' variety is brought about by the introduction of constraint blocks to be respected by them. The information base of agents is embodied by their knowledge bases and internal models. Additionally, a distinction has been made between decision-related agents (management agents) and decision-supporting agents (service agents). Multi-agent systems containing management agents are being developed on the management level and are subject to performance assessments regarding their organizational structure. The primary reason for the introduction of the management level is not the analysis of algorithmic competence, but rather to examine its utilization by decision-making agents. The conceptual development of agents is technically backed up by an implementation based on an active object approach, which grants agents communication and process autonomy. The conceptual separation of the three modeling levels is technically supported as well. However, agents must interfere on the logical level. Proxies as special types of service agents can encapsulate objects on the logical level. As a result, the proxies are able to redirect the information flow to managerial agents, which was originally connecting the objects on the logical level. Thus, these agents are, among other things, able to allocate resources differently than originally planned. |
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