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- 2012 (10) (remove)
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Keywords
- Information system; automated processes; screwing control; process parameterization (1)
- Intelligent knowledge-based system (1)
- Production Scheme, Knowledge management, Knowledge repository, Environmental impact (1)
- Ramp-up, Knowledge management, Knowledge manager (1)
- Ramp-up; Knowledge management; Knowledge manager (1)
- Robot Farming (1)
- Robot Farming; Ressourceneinsatzplanung; Planungssystem (1)
- automated screwing process control (1)
- data extraction (1)
- process parameterization (1)
Institute
Insbesondere die produzierenden Unternehmen in der Automobilindustrie müssen auf kürzere Produktzyklen und steigende Vielfalt zeitnah und wirtschaftlich reagieren, um langfristigen Unternehmenserfolg zu sichern. Diese Anforderungen können heute verfügbare Systeme oftmals nicht leisten. Die kognitiven Fähigkeiten der Mitarbeiter ermöglichen in der manuellen Montage eine hohe Anpassungsfähigkeit. Erwünschte Produktivitätssteigerungen werden durch Erhöhung des Automatisierungsgrades engestrebt, wobei die Fähigkeiten der Mitarbeiter nur selten genutzt werden und die Anpassungsfähigkeit abnimmt. Zukunftsweisende Montagekonzepte können nur durch entsprechende Zielsetzung und methodische Vorgehensweisen erreicht und umgesetzt werden. Ziel des "Robot Farming" Konzept ist es, die Mitarbeiterproduktivität unter voller Nutzung ihrer kognitiven Fähigkeiten zu steigern. Im Beitrag werden die Vorgehensweise zur Konzeptentwicklung, ausgewählte Bausteine des "Robot Farming" und ein Planungssystem für "Robot Farming" Konzepte in der Montage vorgestellt.
Insbesondere die produzierenden Unternehmen in der Automobilindustrie müssen auf kürzere
Produktlebenszyklen und steigende Vielfalt zeitnah und wirtschaftlich reagieren, um langfristigen
Unternehmenserfolg zu sichern. Diese Anforderungen können heute verfügbare
Systeme oftmals nicht leisten. Die kognitiven Fähigkeiten der Mitarbeiter ermöglichen in der
manuellen Montage eine hohe Anpassungsfähigkeit. Erwünschte Produktivitätssteigerungen
werden durch Erhöhung des Automatisierungsgrades angestrebt, wobei die Fähigkeiten der
Mitarbeiter nur selten genutzt werden und die Anpassungsfähigkeit abnimmt. Zukunftsweisende
Montagekonzepte können nur durch entsprechende Zielsetzung und methodische
Vorgehensweisen erreicht und umgesetzt werden. Ziel des „Robot Farming“ Konzeptes ist
es, die Mitarbeiterproduktivität unter voller Nutzung ihrer kognitiven Fähigkeiten zu steigern.
Im Beitrag werden die Vorgehensweise zur Konzeptentwicklung, ausgewählte Bausteine des
„Robot Farming“ und ein Planungssystem für „Robot Farming“ Konzepte in der Montage vorgestellt.
Sophisticated screwing processes in modern screwing equipment are marked with complex parameter settings of the
screwing operations and with their assessment requirements. To gain the potential for improvement, the screwing processes must be handled using a special strategy. To determine the exact parameters and to achieve improved process quality requires development of analysis tools to diagnose the parameter attributes. Increased requirements in the screwing processes demand operator best fit training procedures. A continuous improvement concept for the process control is required to enhance work quality. An information system with a maturity degree for automated screwing processes is developed. To avoid the technical risks, some mechanisms were developed, which automatically extract the process related data and provide it to operator afterwards. By using the information system, information (process and control data) about the parameterization of the screwing control with standardized correlations and a clear tracing of working steps is provided. In this way the running, modification and optimization of the screwing process can be implemented without errors. The developed information system was evaluated on an experimental platform for screwing process in the research laboratory. Thereby, the functionalities of the platform and their components are described and a validation of the developed system is carried out. The development and assembly of the components is presented. Data interrelations are also described in detail. With the developed information system the correct parameterization of the screwing processes with a degree of maturity of the process parameters were achieved. The evaluation of the maturity degree is made with the help of functional properties of the parameters. Consequently, an obvious minimization of the mistakes and a simple screwing process control is achieved.
The automotive industry is experiencing several limitations due to high mass customization on product side and the consequent evolution of newer ones as well as the expansion of existing production setups. There exist various complexities in planning and control of istributed production setups. This paper addresses issues related to planning using knowledge management approaches in the decentralized manufacturing domain with two distinct cases. The first case relates to the higher level planning methodology to automate experts’ knowledge in production ramp-up whereas the second case relates to optimization of production processes using knowledgebase as an intelligent assistance system for optimization.
The automotive industry is facing challenges due to high mass customization and consequent decentralization of manufacturing systems. Currently, the evaluation and optimization of eco-efficiency of production processes is complicated due to time consuming LCA simulations and inexperience of production planners to make respective decisions. This paper addresses this issue by developing ontology based intelligent assistance system to support planner in environmental assessment of manufacturing of customized production in decentralized manufacturing networks as well as decision making in production planning.
In this approach a knowledge-based system with a parameters quality assessment for automated
screwing processes is developed. To avoid technical risks, it makes sense to develop methods, which
automatically extract the process related data and provide it to operator afterwards. By using the knowledgebased
system, information (process and control data) about the parameterization of the screwing process control
with standardized correlations and tested process steps is provided. In this way the running, modification and
optimization of the screwing process can be implemented without errors. This system was tested on an
experimental platform for screwing process in the research laboratory. Thereby, the functionalities of the
platform and their components are described and a validation of the developed system is carried out. Data
interrelations between different software components are elaborated in detail. The validation of the system is
done using the screwing process test case. The precision in the parameterization is made with help of functional
properties of parameters. Consequently, an obvious minimization of the parameterization errors and a simple
screwing process control are achieved.
The automotive industry is experiencing several limitations due to high mass customization on product side and the consequent evolution of newer ones as well as the expansion of existing production setups. There exist various complexities in planning and control of distributed production setups. This paper addresses issues related to planning using knowledge management approaches in the decentralized manufacturing domain with two distinct cases. The first case relates to the higher level planning methodology to automate experts’ knowledge in production ramp-up whereas the second case relates to optimization of production processes using knowledgebase as an intelligent assistance system for optimization.