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  • 1.
    Adane, Tigist Fetene
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Machine and Process Technology. KTH.
    Bianchi, Maria Floriana
    KTH, School of Industrial Engineering and Management (ITM).
    Archenti, Andreas
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Machine and Process Technology. KTH, School of Industrial Engineering and Management (ITM), Centres, Design and Management of Manufacturing Systems, DMMS.
    Nicolescu, Mihai
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Machine and Process Technology.
    Performance evaluation of machining strategy for engine-block manufacturing2015In: Performance evaluation of machining strategy for engine-block manufacturing, ISSN 1895-7595, Vol. 15, no 4, p. 81-102Article in journal (Refereed)
    Abstract [en]

    This paper will introduce a novel methodology for the performance evaluation of machining strategies of engine block manufacturing. The manufacturing of engine components is vital to the automotive and vehicle manufacturing industries. Machining is critical processes in the production of these parts. To survive and excel in the competitive manufacturing environment, companies need to improve as well as update their machining processes and evaluate the performance of their machining lines. Moreover, the lines and processes have to be robust in handling different sources of variation over time that include such examples as demand fluctuations, work-piece materials or even any changes in design specifications. A system dynamics modelling and simulation approach has been deployed to develop a methodology that captures how machining system parameters from the machining process are interacted with each other, how these connections drive performance and how new targets affect process and machine tool parameters through time. The developed model could provide an insight of how to select the crucial machining system parameters and to identify the effect of those parameters on the output of the system. In response to such an analysis, this paper provides (offers) a framework to examine machining strategies and has presented model that is useful as a decision support system for the evaluation and selection of machining strategies. Here a system dynamics methodology for modelling is applied to the milling operation and the model is based on an actual case study from the engine-block manufacturing industry.

  • 2.
    Archenti, Andreas
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Centres, Design and Management of Manufacturing Systems, DMMS. KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Nicolescu, Cornel Mihai
    KTH, School of Industrial Engineering and Management (ITM), Centres, Design and Management of Manufacturing Systems, DMMS. KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Evaluation of machining system dynamic stiffness2007In: Swedish Production Symposium: Gothenburg, Sweden, 2007, 2007Conference paper (Refereed)
    Abstract [en]

    Today’s test methods are analysing machine tool specific characteristics but leaves out to a great deal the machining process. In this paper an evaluation method for determining machining system dynamic characteristics is discussed. For machine capability analysis, the overall elastic structure must be considered, i.e., machine tool – fixture – workpiece – toolholder – tool. Regarding dynamic behaviour of machining systems, the stability can only be evaluated through the interaction between the two subsystems, elastic structure and cutting process. In order to analyse the join machining system, stochastic discrete models, ARMA models are used to identify the stability of the join system, elastic structure – machining process.

  • 3.
    Archenti, Andreas
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Centres, Design and Management of Manufacturing Systems, DMMS. KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Nicolescu, Cornel Mihai
    KTH, School of Industrial Engineering and Management (ITM), Centres, Design and Management of Manufacturing Systems, DMMS. KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Evaluation of machining system static stiffness2007In: Swedish Production Symposium: Gothenburg, Sweden, 2007, 2007Conference paper (Refereed)
    Abstract [en]

    The majority of test methods used for determine a machining systems status, are machine tool oriented and do not take into consideration the characteristics of the machining process. In this paper an evaluation method for determining a machining system static characteristics are discussed. The importance of joint stiffness and damping in elastic structures of machine tool is emphasized. In this context the new type of double ball bar (DBB) is described which applies a preload on the structure, thus creating more realistic conditions for accuracy measurements. Also, for machine capability analysis, the overall elastic structure must be considered, i.e., machine tool-fixture-workpiece-tool holder-tool.

  • 4.
    Dencker, Kerstin
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Fasth, Åsa
    Chalmers University of Technology, Division of Production Systems.
    Stahre, Johan
    Chalmers University of Technology, Division of Production Systems.
    Mårtensson, Lena
    KTH, School of Industrial Engineering and Management (ITM), Industrial Economics and Management (Dept.), Industrial Work Science.
    Akillioglu, Hakan
    KTH, School of Industrial Engineering and Management (ITM), Centres, Design and Management of Manufacturing Systems, DMMS.
    Lundholm, Thomas
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Proactive Assembly Systems – realizing the potential of human collaboration with automation2009In: Annual Reviews in Control, ISSN 1367-5788, E-ISSN 1872-9088, Vol. 33, no 2, p. 230-237Article, review/survey (Refereed)
    Abstract [en]

    Manufacturing competitiveness frequently relies on company ability to rapidly reconfigure their assembly systems. This paper introduces assembly system proactivity, a concept based on interrelated levels of automation, human competence, and information handling. Increased and structured human involvement contributes to increased system ability to proactively address predicted and unpredicted events. Correct involvement of human operators will utilize the combined potential of human and technical capabilities, providing cost-efficient assembly system solutions. The ProAct project is developing proactive assembly system models and evaluates proactive, feature-based solutions. Focus is on realising the potential of cost-efficient and semi-automated systems with relevant human involvement, i.e. highly skilled operators who add flexibility and functionality.

  • 5.
    Dencker, Kerstin
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Stahre, J.
    Gröndahl, Peter
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Mårtensson, Lena
    KTH, School of Industrial Engineering and Management (ITM), Industrial Economics and Management (Dept.).
    Lundholm, Thomas
    KTH, School of Industrial Engineering and Management (ITM), Centres, Design and Management of Manufacturing Systems, DMMS.
    Bruch, J.
    Johansson, C.
    Proactive assembly systems-realizing the potential of human collaboration with automation2007In: Cost Effective Automation, International Federation of Automatic Control , 2007, no PART 1, p. 79-84Conference paper (Refereed)
    Abstract [en]

    Manufacturing competitiveness relies on the companies' ability to rapidly reconfigure their assembly systems. This paper introduces assembly system proactivity, a concept based on interrelated levels of human involvement, automation, and information handling. Increased and structured human involvement contributes to increased system ability to proactively address predicted and unpredicted events. Correct involvement of human operators will utilize the fully combined potential of human and technical capabilities, providing cost-efficient assembly system solutions. The ProAct project is developing proactive assembly system models and evaluating proactive, feature-based solutions. Focus is on realizing the potential of cost-efficient and semi-automated systems with relevant human involvement, i.e. highly skilled operators that add flexibility and functionality.

  • 6.
    Maffei, Antonio
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Akillioglu, Hakan
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems. KTH, School of Industrial Engineering and Management (ITM), Centres, Design and Management of Manufacturing Systems, DMMS.
    Lohse, Niels
    Analysis of the Student Perception of the Link between Product and Production System: Towards Effective Strategies to Teach the Holistic Nature of Product Design2014In: International journal of engineering education, ISSN 0949-149X, Vol. 30, no 6, p. 1357-1366Article in journal (Refereed)
    Abstract [en]

    Product design has a huge and widespread impact on the eventual design of the related production processes, such as procurement, manufacturing, assembly, maintenance and recycling, amongst others. Understanding the full the nature of such a complex relationship is a cornerstone in the professional development of any production engineering student and practitioner. Acquiring sophisticated concepts is a long process consisting of acquiring the necessary notions and mentally structuring them through different semantic links in a consistent body of knowledge. This generates a large set of intermediate states between the novice and the expert. Phenomenography focuses on identifying and classifying these perceptions with the aim of identifying the related pattern for good learning. In particular, this phenomenographic analysis focuses on investigating the students' perception of the articulated link between the design of a product and that of the related assembly process. The study is based on courses that exploit the principles of Design for Assembly (DFA) methods to present and detail such a domain. In the first section of the paper, the aforementioned focal issue is fully characterized as a 'Threshold Concept'. The central part of the paper describes five generic levels of understanding of such a matter: from a simple mechanical use of DFA to a more sophisticated correct holistic understanding of all the implications of such a tool. The classification has been inferred through a series of informal, semi-structured interviews with the students. The characterization introduced is finally discussed with the aim of disclosing the pattern of good learning that, in turn, could provide the base for studies aimed at disclosing useful hints for the effective development of the related teaching activities.

  • 7.
    Onori, Mauro
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Neves, Pedro
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Akillioglu, Hakan
    KTH, School of Industrial Engineering and Management (ITM), Centres, Design and Management of Manufacturing Systems, DMMS.
    Hofmann, Andreas
    DEALING WITH THE UNPREDICTABLE: AN EVOLVABLE PRODUCTION CELL2011In: International Symposium on Assembly & Manufacturing / [ed] Prof. Reijo Tuokko, IEEE , 2011Conference paper (Refereed)
    Abstract [en]

    The work presented in this paper intends to clarify how the Evolvable Production Systems (EPS) paradigm has been used to develop a robotic assembly cell based on a fully reconfigurable robot. The work includes some detail of the multiagent architecture based on coalitions of Production modules and how this was successfully used to implement the control architecture for EPS. Finally, it will introduce the issue of unprdictable behaviour as an approach to dealing with dnamic conditions, and how this may be addressed.

  • 8. Vogl, G. W.
    et al.
    Archenti, Andreas
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Machine and Process Technology. KTH, School of Industrial Engineering and Management (ITM), Centres, Design and Management of Manufacturing Systems, DMMS.
    Donmez, M. A.
    Identification of machine tools linear axes performance using on-machine embedded inertia measurement units2017In: Laser Metrology and Machine Performance XII - 12th International Conference and Exhibition on Laser Metrology, Machine Tool, CMM and Robotic Performance, LAMDAMAP 2017, euspen , 2017, p. 65-74Conference paper (Refereed)
    Abstract [en]

    The current trend in manufacturing industry is from mass production towards flexible and adaptive manufacturing systems and cloud manufacturing. Self-learning machines and robot systems can play an essential role in the development of intelligent manufacturing systems and can be deployed to deal with a variety of tasks that can require flexibility and accuracy. However, in order for the machine tool (physical and control system) to deal with the desired task in a cognitive and efficient manner, the system must be "aware" of its capability and,most importantly,its limitations in order to avoid them and adjust itself to the desired task. Thus, characterization of machine tool accuracy and capability is necessary to realize that. In this study,data from a machine-embedded inertial measurement unit (IMU), consisting of accelerometers and rate gyroscopes,was used for identification of changes in linearand angular errormotions due to changes in operational conditionsor component degradation.The IMU-based results were validated against laser-based measurement results,demonstratingthat the IMU-based method is capable of detecting micrometer-level and microradian-level degradation of machine tool linearaxes.Thus, manufacturers could use themethod to efficientlyand robustly diagnose the condition of their machine tool linear axeswith minimal disruptions to production.

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