FG Automatisierungstechnik
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- Intelligent Production Control, Knowledge Driven System, Human Machine Interface, Dynamic Navigation, Technology Data Catalogue, Ontology, Mass Customization (1)
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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.
Elicitation of Requirements for a Knowledge Management Concept in Decentralized Production Planning
(2013)
The planning in manufacturing system is becoming
complicated day by day due to the expanding networks and shortage
of skilled people to manage change. Consequently, faster lead time
and rising demands for eco-efficient evaluation of manufacturing
products and processes need exploitation of new and intelligent
knowledge management concepts for manufacturing planning. This
paper highlights motivation for incorporation of new features in the
manufacturing planning system. Furthermore, it elaborates
requirements for the development of intelligent knowledge
management concept to support planning related decisions.
Afterwards, the derived concept is presented in this paper considering
two case studies. The first case study is concerned with the
automotive ramp-up planning. The second case study specifies
requirements for knowledge management system to support decisions
in eco-efficient evaluation of manufacturing products and processes.
The automotive industry is distinguished by regionalization and mass customization of products. As a consequence, the diversity of products will increase and the lot sizes will decrease. Thus more product types have to be handled along the process chain and common production paradigms will fail. Hence, Rapid Manufacturing (RM) will be used for manufacturing small individual lot sizes. Nevertheless, new solution for joining and assembling these components are needed. The state of the art production control solutions exhibit several disadvantages while responding mass customization. A comprehensive and real time intelligent production control and monitoring system can overcome these limitations which will be the totality of intelligent production control and will be based on intelligent soft computing algorithms and smart intelligent peripheral devices. The concept is based on three interlinked main modules: a technology data catalogue (TDC) to access, share, process and structure relevant engineering data, an automated scheduling processor (ASP) based on graph theory to get an optimized and adaptable work plan using feature technology and a central programmable automation controller (PAC) for real-time sensor/actor communication. The processes will be controlled through PAC and influenced by humans through scalable human machine interfaces. The PAC and its supported software’s widespread functionality for real time applications and compatibility and flexibility with the conventional programming languages will enable in developing customized palette of functions and tools for scalable level of control solutions. It will have a widespread accessibility as it will influence the execution of robot programs after pre-processing the data coming from various peripheral devices and calculating new robot paths by segmentation of detected curves and paths corresponding to the process planning information via one interface. The human machine communication will be based on the ontological approach as a natural language interaction system for filtering and translating into machine command. The entire concept will be demonstrated in a laboratory set-up with distinct machining, assembly and joining processes and will be experimentally validated in European research and development projects.
The optimization processes in production planning often encounter problems due to unavailability of skilled workers in the concerned production departments since the decisions made in uncertain situations rely mainly on the knowledge possessed by the relevant planners. This paper further presents and elaborates the unified web-based knowledge based decision support system concept to automate and reuse implicit knowledge generated during interaction with the dedicated software tools as well as during interaction with real hardware setups in an industrial environment. The unified concept has been devised considering two pilot cases i.e. decision making on eco-efficient decentralized production schemes for manufacturing customized products and decision support for solving problems in ramp-up management process. This paper further discusses the development issues concerning web-based knowledge based decision support system to demonstrate the unified concept. The software modules from both pilot cases are validated considering two pilot cases.
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.
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.
This paper focuses on the systematic methodology for
incorporating intelligence and development methodology for
knowledge acquisition system in an automated manufacturing
environment. The intelligence is incorporated in the shape of
technology data catalogue that contains the knowledge about
production system as a whole. The knowledge acquisition system is
implemented in the form of a multiuser scalable interface into remote
human machine interface devices (e.g. Personal Digital Assistants)
with a purpose of extracting concrete and precise information and
knowledge about manufacturing systems and processes in highly
automated manufacturing environment. The extraction of precise
knowledge as well as organized access to the knowledge will
facilitates the operators, technicians and engineers for making faster,
safer and simpler on-process modifications and parameters
optimization.
Produktionswissenschaft sowie Technologie- und Innovationsforschung sind sehr dynamische Gebiete. Sie setzen sich mit den Forderungen nach robusten und wandlungsfähigen Produktionssystemen sowie innovativen Technologien auseinander, schaffen theoretische Modelle und praxistaugliche Instrumente zur Entscheidungsunterstützung in einem dynamischen, internationalen und zunehmend vernetzten Umfeld. Das Buch beinhaltet Beiträge namhafter Autoren, gibt einen Überblick zum aktuellen Forschungsstand und würdigt als Festschrift für Professor Dieter Specht dessen interdisziplinär angelegtes wissenschaftliches Wirken. Der Band versammelt unter anderen Beiträge von Daniel Baier, Klaus Bellmann, Ulrich Berger, Udo Buscher, Jörg M. Elsenbach, Wolf Fichtner, Joachim Fischer, Jürgen Gausemeier, Georg Gemünden, Torsten J. Gerpott, Horst Geschka, Uwe Götze, Diana Grosse, Andreas Größler, Evi Hartmann, Hans H. Hinterhuber, Christopher Jahns, Bernd Kaluza, Joachim Käschel, Wolfgang Kersten, Klaus-Peter Kistner, Bernd Kortschak, Herbert Kotzab, Rudolf O. Large, Peter Lethmathe, Peter Loos, Horst Meier, Barbara Mikus, Peter Milling, Magdalena Mißler-Behr, Martin G. Möhrle, Theodor Nebl, Joachim Reese, Bernd Rieper, Gerhard Schewe, Hans-Horst Schröder, Günther Seliger, Marion Steven, Oliver Thomas, Meike Tilebein, Bernd Viehweger, Kai-Ingo Voigt, Marion A. Weissenberger-Eibl, Horst Wildemann, Herwig Winkler, Stephan Zelewski.
The manufacturing industry is distinguished by regionalization and individualization of products accompaniedby varying customer demands, faster time to market, short innovation cycles and product life cycles. Theintroduction of new materials, new processes as well as struggle to achieve economic and efficient use ofresources has raised complexities to achieve quick and optimal configuration in manufacturing systems. Toresolve the complexities, the reconfiguration at different levels in the manufacturing system is presented byusing three distinct examples. The first example refers to reconfigurable joining cell design for versatile joiningof automotive subassemblies. Second example refers to strategy for quick reconfiguration of robots for precisemachining applications. The third example elaborates fast calibration of monitoring system in joiningprocesses to enable fast reconfiguration of sensors in commissioning as well as in the maintenance.
A Multilevel Reconfiguration Concept to Enable Versatile Production in Distributed Manufacturing
(2011)
The manufacturing industry is confronting challenges due to high diversity of product variants,reduced product life cycles,short innovation cycles, faster time to market as well as strictenvironmental regulations. These challenges have persuaded manufacturers to exploit conceptsrelated to open innovation, distributed manufacturing, modular and scalable production systemdesign and eco-efficient production. This paper aims at providing a short review of state of the art inreconfiguration of distributed production systems and focuses on new strategies to resolvecomplexities that arise subsequently. In this regard, a reconfiguration concept based on newstrategic objectives has been proposed to enable customized production. The approach will beimplemented and validated in the collaborative projects.