A method is presented for the model-based redesign of enterprises. It consists of two main steps, the initialization step and the optimization step. During the initialization step, the processes are modelled and analy...
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A method is presented for the model-based redesign of enterprises. It consists of two main steps, the initialization step and the optimization step. During the initialization step, the processes are modelled and analysed. During the optimization step, the optimal configuration is found for the possible modifications of the processes. Emphasis is placed on the process analysis. The proposed approach is based on activity chains which describe the set of activities needed for the achievement of a given gear, and their execution order necessary to guarantee a low processing time. An algorithm is presented for filtering such activity chains from an enterprise model. It is based on graph theory and corresponds to the solution of an optimization problem, whereby the sum of weights of ail edges belonging to the solution graph should be maximized under some given constraints. Because of the high complexity of the problem, some complexity-reducing measures are presented, measures that arise from the earlier problem analysis.
Strong international competition forces enterprises to reduce organizational overhead and cost. Today's industrial practices allow, in general, only the selection of whole planning and control systems for CIM (e.g...
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Strong international competition forces enterprises to reduce organizational overhead and cost. Today's industrial practices allow, in general, only the selection of whole planning and control systems for CIM (e.g., CAD systems, PP&C systems,...). These systems can be adapted only in a limited range to the user requirements. With the introduction of executable enterprise models to the industrial environment, it is expected that it will be possible to design tailored CIM systems built of standardized software modules which will lead to higher complexity of the planning process for software systems. Thus, today's planning and selection approaches will face more and more problems. In order to master the increasing complexity of the planning of software systems for enterprises, new planning methods and tools are required. An integrated approach to software system planning and selection based on CIMOSA enterprise models was developed. The underlying idea of the approach is the conversion of the planning problem into an equivalent constraint satisfaction problem. The conversion process can be accomplished fully automatically.
One of the many features needed to support the activities of autonomous systems is the ability to plan motion. This enables robots to move in their environment securely and to accomplish given tasks. Unfortunately, th...
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One of the many features needed to support the activities of autonomous systems is the ability to plan motion. This enables robots to move in their environment securely and to accomplish given tasks. Unfortunately, the control loop comprising sensing, planning, and acting has not yet been closed for robots in dynamic environments. One reason involves the long execution times of the motion planning component. A solution for this problem is offered by the use of highly parallel computation. Thus, an important task is the parallelization of existing motion planning algorithms for robots so that they are suitable for highly parallel computation. In several cases, completely new algorithms have to be designed, so that a parallelization is feasible. In this survey, we review recent approaches to motion planning using parallel computation. As a classification scheme, we use the structure given by the different approaches to the robot's motion planning. For each approach, the available parallel processing methods are discussed. Each approach is assigned a unique class. Finally, for each research work referenced, a list of keywords is given.
A concept for the intelligent control of subsystems of a flexible assembly cell is presented. Unknown or uncertain data about the real world may lead towards failure during an assembly task. Therefore, a fault toleran...
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The use of manipulator systems with many degrees of freedoms is essential to expand the field of potential applications. This paper presents a distributed approach for executing task-level programs for cooperating man...
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The use of manipulator systems with many degrees of freedoms is essential to expand the field of potential applications. This paper presents a distributed approach for executing task-level programs for cooperating manipulators or one-arm systems with many degrees of freedom. At task level, only the movement of the objects to be manipulated is specified. The according manipulator motions are then calculated by assigning local intelligence to each joint. The local intelligence enables the joint agents to calculate in parallel their appropriate movements to make the end effector reach the desired position. During execution, each joint evaluates sensor data to compensate for execution errors, to react on unexpected obstacles and to provide the manipulator coordination. Therefore, a distributed fuzzy rule base has been developed. As this local evaluation may lead to non-optimal overall behavior of the manipulator, the joint agents communicate to provide global suboptimality.
In this article, the development of an action-based process model is described which was especially tailored to the needs of modelling and simulating multifinger hands. The research has been concerned with a descripti...
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In this article, the development of an action-based process model is described which was especially tailored to the needs of modelling and simulating multifinger hands. The research has been concerned with a description technique using constraints for modelling the working environment and with the design of an appropriate process model for simulating complex movements of manipulation objects with multifinger hands. The paper presents the results of an object-oriented approach to the proposed model and consists of two parts: a constraint net that describes the connections and relations between cell components (robots, grippers, objects) in the working environment and a propagation algorithm that computes the new locations regarding the modifications and logical dependencies.
The rise of Industry 4.0 has revolutionized manufacturing by integrating real-time data analysis, artificial intelligence (AI), automation, and interconnected systems, enabling adaptive and resilient smart factories. ...
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ISBN:
(数字)9798331538606
ISBN:
(纸本)9798331538613
The rise of Industry 4.0 has revolutionized manufacturing by integrating real-time data analysis, artificial intelligence (AI), automation, and interconnected systems, enabling adaptive and resilient smart factories. Autonomous Mobile Robots (AMRs), with their advanced mobility and navigation capabilities, are a pillar of this transformation. However, their deployment in job shop environments adds complexity to the already challenging Job Shop Scheduling Problem (JSSP), expanding it to include task allocation, robot scheduling, and travel time optimization, creating a multi-faceted, non-deterministic polynomial-time hardness (NP-hard) problem. Traditional approaches such as heuristics, meta-heuristics, and mixed integer linear programming (MILP) are commonly used. Recent AI advancements, particularly large language models (LLM), have shown potential in addressing these scheduling challenges due to significant improvements in reasoning and decision-making from textual data. This paper examines the application of LLM to tackle scheduling complexities in smart job shops with mobile robots. Guided by tailored prompts inserted manually, LLM are employed to generate scheduling solutions, being these compared to an heuristic-based method. The results indicate that LLM currently have limitations in solving complex combinatorial problems, such as task scheduling with mobile robots. Due to issues with consistency and repeatability, they are not yet reliable enough for practical implementation in industrial environments. However, they offer a promising foundation for augmenting traditional approaches in the future.
Model-based diagnosis of industrial applications (i.e., complex systems) has to face a lot of problems inherent in complexity. Most applications involve thousands of components and are dynamic. The approach outlined i...
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A mobile robot that navigates in an unknown or changing environment needs to maintain a dynamic model of its environment in order to update existing knowledge about the world. This paper addresses the problem of how t...
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A mobile robot that navigates in an unknown or changing environment needs to maintain a dynamic model of its environment in order to update existing knowledge about the world. This paper addresses the problem of how to update a local model of the perceivable environment of a mobile robot and how to produce a description of newly perceived obstacles. A new hybrid concept is presented which combines the advantages of parameter- and grid-based modelling techniques. By introducing local grids that only cover areas where new obstacles are expected, the complexity of the map building process is significantly reduced. Local grids can be used in dynamic environment which was not possible with earlier grid-modelling approaches. The information, grids are constructed from, is provided by ultrasonic range sensors and an active stereo-vision system, Fusing information of both sensor systems is advantageous, especially due to their complementary error characteristics concerning range and angular resolution.
A method for planning motions of robot arms is presented which considers not only the collision-avoidance but also robot's dynamic aspects. Based on the concept of configuration space, robot motions are planned at...
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