@inproceedings{ZipterZuernBerger, author = {Zipter, Volker and Z{\"u}rn, Michael and Berger, Ulrich}, title = {Optimierte Ressourceneinsatzplanung f{\"u}r „Robot Farming" Konzepte in der Montage - „Robot Farming" Systeme optimal konfigurieren}, series = {Automation 2012, 13. Branchentreff der Mess- und Automatisierungstechnik, Kongresshaus Baden-Baden, 13. und 14. Juni 2012}, booktitle = {Automation 2012, 13. Branchentreff der Mess- und Automatisierungstechnik, Kongresshaus Baden-Baden, 13. und 14. Juni 2012}, publisher = {VDI Verlag}, address = {D{\"u}sseldorf}, isbn = {978-3-18-092171-6}, pages = {291 -- 296}, abstract = {Insbesondere die produzierenden Unternehmen in der Automobilindustrie m{\"u}ssen auf k{\"u}rzere Produktlebenszyklen und steigende Vielfalt zeitnah und wirtschaftlich reagieren, um langfristigen Unternehmenserfolg zu sichern. Diese Anforderungen k{\"o}nnen heute verf{\"u}gbare Systeme oftmals nicht leisten. Die kognitiven F{\"a}higkeiten der Mitarbeiter erm{\"o}glichen in der manuellen Montage eine hohe Anpassungsf{\"a}higkeit. Erw{\"u}nschte Produktivit{\"a}tssteigerungen werden durch Erh{\"o}hung des Automatisierungsgrades angestrebt, wobei die F{\"a}higkeiten der Mitarbeiter nur selten genutzt werden und die Anpassungsf{\"a}higkeit abnimmt. Zukunftsweisende Montagekonzepte k{\"o}nnen nur durch entsprechende Zielsetzung und methodische Vorgehensweisen erreicht und umgesetzt werden. Ziel des „Robot Farming" Konzeptes ist es, die Mitarbeiterproduktivit{\"a}t unter voller Nutzung ihrer kognitiven F{\"a}higkeiten zu steigern. Im Beitrag werden die Vorgehensweise zur Konzeptentwicklung, ausgew{\"a}hlte Bausteine des „Robot Farming" und ein Planungssystem f{\"u}r „Robot Farming" Konzepte in der Montage vorgestellt.}, language = {de} } @inproceedings{LebedynskaBerger, author = {Lebedynska, Yuliya and Berger, Ulrich}, title = {Intelligent Knowledge-based System for the Automated Screwing Process Control}, series = {AIKED 2012, 11th WSEAS International Conference on Artificial Intelligence, Knowledge Engineering and Data Bases}, booktitle = {AIKED 2012, 11th WSEAS International Conference on Artificial Intelligence, Knowledge Engineering and Data Bases}, editor = {Rudas, Imre J. and Zaharim, Azami and Sopian, Kamaruzzaman and Strouhal, Jiri}, publisher = {WSEAS Press}, isbn = {978-1-61804-068-8}, pages = {175 -- 180}, abstract = {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.}, language = {en} } @inproceedings{LebedynskaBerger, author = {Lebedynska, Yuliya and Berger, Ulrich}, title = {Development of an Information system with Maturity Degree Management for Automated Screwing Processes}, series = {IADIS International Conference Information Systems 2012}, booktitle = {IADIS International Conference Information Systems 2012}, editor = {Nunes, Miguel Baptista and Isa{\´i}as, Pedro and Powell, Philip}, publisher = {IADIS Press}, isbn = {978-972-8939-68-7}, pages = {49 -- 56}, abstract = {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.}, language = {en} } @inproceedings{MinhasJuzekBerger, author = {Minhas, Sarfraz Ul-Haque and Juzek, Christian and Berger, Ulrich}, title = {Ontology based Intelligent Assistant System to support Manufacturing activities in a Distributed Manufacturing Environment}, series = {45th CIRP Conference on Manufacturing Systems 2012, Athens, Greece, 16 - 18 May 2012}, booktitle = {45th CIRP Conference on Manufacturing Systems 2012, Athens, Greece, 16 - 18 May 2012}, publisher = {Curran}, address = {Red Hook, NY}, isbn = {978-1-62748-512-8}, pages = {215 -- 220}, abstract = {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.}, language = {en} } @inproceedings{MinhasJuzekBergeretal., author = {Minhas, Sarfraz Ul-Haque and Juzek, Christian and Berger, Ulrich and Lehmann, Christian}, title = {Development of Intelligent Decision Support System Based on Unified Concept for Distributed Manufacturing Planning}, series = {7th IFAC Conference on Manufacturing Modelling, Management, and Control}, booktitle = {7th IFAC Conference on Manufacturing Modelling, Management, and Control}, editor = {Bakhtadze, Natalia and Chernyshov, Kirill and Dolgui, Alexandre and Lototsky, Vladimir}, doi = {10.3182/20130619-3-RU-3018.00351}, pages = {454 -- 459}, abstract = {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.}, language = {en} } @inproceedings{MinhasBerger, author = {Minhas, Sarfraz Ul-Haque and Berger, Ulrich}, title = {Development of Intelligent Assistance System to Support Eco-efficient Planning}, series = {KEOD 2012 - Proceedings of the International Conference on Knowledge Engineering and Ontology Development, Barcelona, Spain, 4 - 7 October, 2012}, booktitle = {KEOD 2012 - Proceedings of the International Conference on Knowledge Engineering and Ontology Development, Barcelona, Spain, 4 - 7 October, 2012}, editor = {Filipe, Joaquim and Dietz, Jan L. G.}, isbn = {978-989-8565-30-3}, pages = {331 -- 334}, abstract = {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.}, language = {en} } @incollection{MinhasKretzschmannVargasetal., author = {Minhas, Sarfraz Ul-Haque and Kretzschmann, Ralf and Vargas, Veronica and Berger, Ulrich}, title = {An approach for the real time intelligent production control to fulfill mass customization requirements}, series = {Mass Customization Services}, booktitle = {Mass Customization Services}, editor = {Edwards, Kasper and Blecker, Thorsten and Salvador, Fabrizio and Hvam, Lars and Friedrich, Gerhard}, publisher = {Vesterkopi Copenhagen Denmark}, address = {Copenhagen, Denmark}, isbn = {978-87-90-855-12-3}, pages = {86 -- 101}, abstract = {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.}, language = {en} } @misc{MinhasJuzekBerger, author = {Minhas, Sarfraz Ul-Haque and Juzek, Christian and Berger, Ulrich}, title = {Ontology Based Intelligent Assistance System to Support Manufacturing Activities in a Distributed Manufacturing Environment}, series = {Procedia CIRP}, volume = {1}, journal = {Procedia CIRP}, number = {3}, editor = {Chryssolouris, George and Mourtzis, Dimitris}, issn = {2212-8271}, doi = {10.1016/j.procir.2012.07.038}, pages = {215 -- 220}, abstract = {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.}, language = {en} } @misc{MinhasJuzekBerger, author = {Minhas, Sarfraz Ul-Haque and Juzek, Christian and Berger, Ulrich}, title = {Elicitation of Requirements for a Knowledge Management Concept in Decentralized Production Planning}, series = {Special Journal Issue of World Academy of Science, Engineering and Technology}, volume = {2012}, journal = {Special Journal Issue of World Academy of Science, Engineering and Technology}, number = {81}, issn = {2010-3778}, pages = {617 -- 626}, abstract = {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.}, language = {en} } @inproceedings{LehmannOlofssonNilssonetal., author = {Lehmann, Christian and Olofsson, Bj{\"o}rn and Nilsson, Klas and Halbauer, Marcel and Haage, Mathias and Robertsson, Anders and S{\"o}rnmo, Olof and Berger, Ulrich}, title = {Robot Joint Modeling and Parameter Identification Using the Clamping Method}, series = {Proceedings of 7th IFAC Conference on Manufacturing Modelling, Management and Control (MIM)}, booktitle = {Proceedings of 7th IFAC Conference on Manufacturing Modelling, Management and Control (MIM)}, isbn = {978-3-902823-35-9}, pages = {813 -- 818}, language = {en} }