data/documentation/FAS-Simulator.bib

@article{CURRENNT,
  author  = {Felix Weninger},
  title   = {Introducing CURRENNT: The Munich Open-Source CUDA RecurREnt Neural Network Toolkit},
  journal = {Journal of Machine Learning Research},
  year    = {2015},
  volume  = {16},
  pages   = {547-551},
  url     = {http://jmlr.org/papers/v16/weninger15a.html}
}

@misc{CURRENNTFORK,
  added-at = {2016-07-23},
  author = {Tero Keski-Valkama},
  title = {A fork of {CURRENNT} to make it run against the latest {CUDA} toolkit},
  url = {https://github.com/keskival/currennt}
  year = 2016
}
@misc{FASSimulator,
  added-at = {2016-07-23},
  title = {Flexible assembly simulation: {FAS Simulator}},
  author = {Tero Keski-Valkama},
  url = {https://github.com/keskival/FAS-Simulator}
  year = 2016
}
@article{LSTM,
    author = {Sepp Hochreiter and Jürgen Schmidhuber},
    title = {Long short-term memory},
    journal = {Neural Computation 9(8)},
    pages = {1735-1780},
    year = 1997,
    howpublished = "\url{http://deeplearning.cs.cmu.edu/pdfs/Hochreiter97_lstm.pdf}"
}
@misc{IndustryHack,
  added-at = {2016-07-23},
  author = {Tero Keski-Valkama},
  title = "Cybercom Team Won the \#{IndustryHack} \#{HackTheFactory} \@{Fastems} - {Summary}",
  url = {https://www.linkedin.com/pulse/cybercom-team-won-industryhack-hackthefactory-fastems-keski-valkama}
  year = 2015
}
@article{langer2011self,
  title={Self Learning Anomaly Detection for Embedded Safety Critical Systems},
  author={Langer, Falk and Bertulies, Karsten and Hoffmann, F},
  journal={Schriftenreihe des Instituts f{\"u}r Angewandte Informatik, Automatisierungstechnik am Karlsruher Institut f{\"u}r Technologie. KIT Scientific Publishing},
  pages={31--45},
  year={2011}
}
@article{gers2000learning,
  title={Learning to forget: Continual prediction with LSTM},
  author={Gers, Felix A and Schmidhuber, J{\"u}rgen and Cummins, Fred},
  journal={Neural computation},
  volume={12},
  number={10},
  pages={2451--2471},
  year={2000},
  publisher={MIT Press}
}
@article{gers2003learning,
  title={Learning precise timing with LSTM recurrent networks},
  author={Gers, Felix A and Schraudolph, Nicol N and Schmidhuber, J{\"u}rgen},
  journal={The Journal of Machine Learning Research},
  volume={3},
  pages={115--143},
  year={2003},
  publisher={JMLR. org}
}
@article{giulio,
  author = {Giulio Rosati and Maurizio Faccio and Christian Finetto and Andrea Carli},
  title = {Modelling and optimization of fully flexible assembly systems (F-FAS)},
  journal = {Assembly Automation},
  volume = {33},
  number = {2},
  pages = {165-174},
  year = {2013},
  doi = {10.1108/01445151311306690},
  URL = { 
        http://dx.doi.org/10.1108/01445151311306690
  },
  eprint = { 
        http://dx.doi.org/10.1108/01445151311306690
  },
  abstract = { Purpose – The paper aims to address the modelling and optimization of fully flexible assembly systems (F-FAS), a new concept in flexible automation recently introduced by the authors.Design/methodology/approach – The paper presents a mathematical model of the F‐FAS, which makes it possible to predict its efficiency, throughput and unit direct production costs, correlating such values with system and production variables. The mathematical model proposed in the paper was derived from experimental and simulation data, which were analysed for a wide range of different productions and system settings.Findings – Correlation analysis revealed that there are three main determinants of the efficiency of the F‐FAS: the number of components (types of parts) used to assemble the models (production variable); the average complexity of the models to be assembled (production variable); the ratio of the average perimeter of components (production variable) over a significant dimension of the working plane (system variable). Such parameters makes it possible to estimate the maximum attainable efficiency of the F‐FAS, and to calculate the optimal setting of the feeder which makes it possible to obtain such efficiency during the execution of the whole production order.Originality/value – The model presented in the paper makes it possible to quantify in advance the real potential of the F‐FAS, according to the characteristics of the production mix and type of components to be assembled. By using the methodologies presented in the paper, one can first evaluate the convenience of the F‐FAS approach with respect to traditional FAS technology and manual assembly, then identify the optimal design and settings of the F‐FAS, according to the needs of a specific application. As a result, not only can the investment on the automated assembly system be accurately evaluated in advance, but also the return on investment can be maximized. }
}
@article{donath1988flexible,
  title={Flexible assembly systems: an approach for near real-time scheduling and routeing of multiple products},
  author={Donath, Markus and GRAVES, ROBERT J},
  journal={The International Journal Of Production Research},
  volume={26},
  number={12},
  pages={1903--1919},
  year={1988},
  publisher={Taylor \& Francis}
}
@inproceedings{jager2014assessing,
  title={Assessing neural networks for sensor fault detection},
  author={J\"ager, Georg and Zug, Sebastian and Brade, Tino and Dietrich, Andre and Steup, Christoph and Moewes, Christian and Cretu, Ana-Maria},
  booktitle={Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA), 2014 IEEE International Conference on},
  pages={70--75},
  year={2014},
  organization={IEEE}
}
@misc{lecun-mnisthandwrittendigit-2010,
  added-at = {2010-06-28T21:16:30.000+0200},
  author = {LeCun, Yann and Cortes, Corinna},
  biburl = {http://www.bibsonomy.org/bibtex/25c6723dcce8057a5a41a5d7e12684930/mhwombat},
  groups = {public},
  interhash = {21b9d0558bd66279df9452562df6e6f3},
  intrahash = {5c6723dcce8057a5a41a5d7e12684930},
  keywords = {MSc _checked character_recognition mnist network neural},
  lastchecked = {2010-02-22 00:36:34},
  timestamp = {2012-04-25T14:48:25.000+0200},
  title = {{MNIST} handwritten digit database},
  url = {http://yann.lecun.com/exdb/mnist/},
  username = {mhwombat},
  year = 2010
}
@misc{transmission,
  added-at = {2015-07-16},
  author = {Cars},
  title = {Chrysler Transmission Assembly Line},
  url = {https://www.youtube.com/watch?v=447sSED91v0},
  year = 2014
}
@article{fatigue,
  author = { Christopher S. Pan and Richard L. Shell and Lawrence M. Schleifer },
  title = {Performance variability as an indicator of fatigue and boredom effects in a VDT data-entry task},
  journal = {International Journal of Human-Computer Interaction},
  volume = {6},
  number = {1},
  pages = {37-45},
  year = {1994},
  doi = {10.1080/10447319409526082},
  URL = { 
        http://dx.doi.org/10.1080/10447319409526082
  },
  eprint = { 
        http://dx.doi.org/10.1080/10447319409526082
  }
}
@article{tsarouhas2009classification,
  title={Classification and calculation of primary failure modes in bread production line},
  author={Tsarouhas, Panagiotis H},
  journal={Reliability Engineering \& System Safety},
  volume={94},
  number={2},
  pages={551--557},
  year={2009},
  publisher={Elsevier}
}
@inproceedings{pang2005large,
  title={Large-scale conveyor belt system maintenance decision-making by using fuzzy causal modeling},
  author={Pang, Yusong and Lodewijks, Gabriel},
  booktitle={Intelligent Transportation Systems, 2005. Proceedings. 2005 IEEE},
  pages={563--567},
  year={2005},
  organization={IEEE}
}
@article{stuxnet,
  title={The Real Story of Stuxnet},
  author={David Kushner},
  journal={IEEE Spectrum},
  year=2013,
  publisher={IEEE Spectrum},
  url={http://spectrum.ieee.org/telecom/security/the-real-story-of-stuxnet}
}
@misc{nasaames,
  title={NASA Ames Prognostics Center of Excellence - Data Repository},
  url={http://ti.arc.nasa.gov/tech/dash/pcoe/prognostic-data-repository/}
}
@misc{milldataset,
  title={Documentation for Mill Data Set},
  author={Goebel, Kai and Agogino, Alice},
  url={http://ti.arc.nasa.gov/tech/dash/pcoe/prognostic-data-repository/}
}
@article{eker2012major,
  title={Major challenges in prognostics: Study on benchmarking prognostics datasets},
  author={Eker, OF and Camci, F and Jennions, IK},
  journal={PHM Europe, 6th--8th July},
  year={2012}
}
@misc{lecun-mnisthandwrittendigit-2010,
  added-at = {2010-06-28T21:16:30.000+0200},
  author = {LeCun, Yann and Cortes, Corinna},
  biburl = {http://www.bibsonomy.org/bibtex/25c6723dcce8057a5a41a5d7e12684930/mhwombat},
  groups = {public},
  interhash = {21b9d0558bd66279df9452562df6e6f3},
  intrahash = {5c6723dcce8057a5a41a5d7e12684930},
  keywords = {MSc _checked character_recognition mnist network neural},
  lastchecked = {2010-02-22 00:36:34},
  timestamp = {2012-04-25T14:48:25.000+0200},
  title = {{MNIST} handwritten digit database},
  url = {http://yann.lecun.com/exdb/mnist/},
  username = {mhwombat},
  year = 2010
}
@book{duch2005artificial,
  title={Artificial Neural Networks: Formal Models and Their Applications--ICANN 2005: 15th International Conference, Warsaw, Poland, September 11-15, 2005, Proceedings},
  author={Duch, Wlodzislaw},
  year={2005},
  publisher={Springer Science \& Business Media},
  pages={378}
}
@article{Angluin,
 author = {Angluin, Dana},
 title = {Learning Regular Sets from Queries and Counterexamples},
 journal = {Inf. Comput.},
 issue_date = {November 1, 1987},
 volume = {75},
 number = {2},
 month = nov,
 year = {1987},
 issn = {0890-5401},
 pages = {87--106},
 numpages = {20},
 url = {http://dx.doi.org/10.1016/0890-5401(87)90052-6},
 doi = {10.1016/0890-5401(87)90052-6},
 acmid = {36889},
 publisher = {Academic Press, Inc.},
 address = {Duluth, MN, USA},
} 
@incollection{berglund2011recognizing,
  title={Recognizing shuffled languages},
  author={Berglund, Martin and Bj{\"o}rklund, Henrik and H{\"o}gberg, Johanna},
  booktitle={Language and Automata Theory and Applications},
  pages={142--154},
  year={2011},
  publisher={Springer}
}
@techreport{procedure1949procedures,
  title={Procedures for Performing a Failure Modes, Effects and Criticality Analysis},
  author={Procedure, US Military},
  year={1949},
  institution={MIL-P-1629}
}
@article{teng1996failure,
  title={Failure mode and effects analysis: an integrated approach for product design and process control},
  author={Teng, Sheng-Hsien and Ho, Shin-Yann},
  journal={International Journal of Quality \& Reliability Management},
  volume={13},
  number={5},
  pages={8--26},
  year={1996},
  publisher={MCB UP Ltd}
}
@article{wen2007mining,
  title={Mining process models with non-free-choice constructs},
  author={Wen, Lijie and van der Aalst, Wil MP and Wang, Jianmin and Sun, Jiaguang},
  journal={Data Mining and Knowledge Discovery},
  volume={15},
  number={2},
  pages={145--180},
  year={2007},
  publisher={Springer}
}
@article{saitou2002robust,
  title={Robust design of flexible manufacturing systems using, colored Petri net and genetic algorithm},
  author={Saitou, Kazuhiro and Malpathak, Samir and Qvam, Helge},
  journal={Journal of intelligent manufacturing},
  volume={13},
  number={5},
  pages={339--351},
  year={2002},
  publisher={Springer}
}
@misc{transmission,
  added-at = {2015-07-16},
  author = {Cars},
  title = {Chrysler Transmission Assembly Line},
  url = {https://www.youtube.com/watch?v=447sSED91v0},
  year = 2014
}
@misc{PHONOZATION,
  added-at = {2016-01-24},
  author = {Tero Keski-Valkama},
  title = {A visualization animation of a simulated FAS event log with sound.},
  url = {https://www.youtube.com/watch?v=9oVP05pi4QI}
  year = 2016
}
@inproceedings{cong1997fault,
  title={Fault diagnosis system for automated assembly line},
  author={Cong, Ming and Zhang, Jianzhi and Qian, Wenhan},
  booktitle={Intelligent Processing Systems, 1997. ICIPS'97. 1997 IEEE International Conference on},
  volume={2},
  pages={1478--1482},
  year={1997},
  organization={IEEE}
}
@inproceedings{falkman2001combined,
  title={Combined process algebra and petri nets for specification of resource booking problems},
  author={Falkman, Petter and Lennartson, Bengt},
  booktitle={American Control Conference, 2001. Proceedings of the 2001},
  volume={6},
  pages={4949--4955},
  year={2001},
  organization={IEEE}
}
@inproceedings{falkman2001modeling,
  title={Modeling and specification of discrete event systems using combined process algebra and Petri nets},
  author={Falkman, Petter and Lennartson, Bengt and Tittus, Michael},
  booktitle={Advanced Intelligent Mechatronics, 2001. Proceedings. 2001 IEEE/ASME International Conference on},
  volume={2},
  pages={1011--1016},
  year={2001},
  organization={IEEE}
}
@article{able2016model,
  title={A model for preemptive maintenance of medical linear accelerators—predictive maintenance},
  author={Able, Charles M and Baydush, Alan H and Nguyen, Callistus and Gersh, Jacob and Ndlovu, Alois and Rebo, Igor and Booth, Jeremy and Perez, Mario and Sintay, Benjamin and Munley, Michael T},
  journal={Radiation Oncology},
  volume={11},
  number={1},
  pages={1},
  year={2016},
  publisher={BioMed Central}
}
@book{scheffer2004practical,
  title={Practical machinery vibration analysis and predictive maintenance},
  author={Scheffer, Cornelius and Girdhar, Paresh},
  year={2004},
  publisher={Elsevier}
}
@book{hunt1993handbook,
  title={Handbook of wear debris analysis and particle detection in liquids},
  author={Hunt, Trevor M},
  year={1993},
  publisher={Springer Science \& Business Media}
}
@book{mobley2002introduction,
  title={An introduction to predictive maintenance},
  author={Mobley, R Keith},
  year={2002},
  publisher={Butterworth-Heinemann}
}
@article{hashemian2011state,
  title={State-of-the-Art Predictive Maintenance Techniques*},
  author={Hashemian, Hashem M and Bean, Wendell C},
  journal={Instrumentation and Measurement, IEEE Transactions on},
  volume={60},
  number={10},
  pages={3480--3492},
  year={2011},
  publisher={IEEE}
}
@article{chandola2012anomaly,
  title={Anomaly detection for discrete sequences: A survey},
  author={Chandola, Varun and Banerjee, Arindam and Kumar, Vipin},
  journal={Knowledge and Data Engineering, IEEE Transactions on},
  volume={24},
  number={5},
  pages={823--839},
  year={2012},
  publisher={IEEE}
}
@article{thomson2001current,
  title={Current signature analysis to detect induction motor faults},
  author={Thomson, William T and Fenger, Mark},
  journal={Industry Applications Magazine, IEEE},
  volume={7},
  number={4},
  pages={26--34},
  year={2001},
  publisher={Ieee}
}
@inproceedings{landwehr2008modeling,
  title={Modeling interleaved hidden processes},
  author={Landwehr, Niels},
  booktitle={Proceedings of the 25th international conference on Machine learning},
  pages={520--527},
  year={2008},
  organization={ACM}
}
@book{kramer1993auditory,
  title={Auditory display: Sonification, audification, and auditory interfaces},
  author={Kramer, Gregory},
  year={1993},
  publisher={Perseus Publishing}
}
@article{weston2014memory,
  title={Memory networks},
  author={Weston, Jason and Chopra, Sumit and Bordes, Antoine},
  journal={arXiv preprint arXiv:1410.3916},
  year={2014}
}
@inproceedings{kumar2011mining,
  title={Mining message sequence graphs},
  author={Kumar, Sandeep and Khoo, Siau-Cheng and Roychoudhury, Abhik and Lo, David},
  booktitle={Proceedings of the 33rd International Conference on Software Engineering},
  pages={91--100},
  year={2011},
  organization={ACM}
}
@inproceedings{mining-program-workflow-from-interleaved-traces,
author = {Jian-Guang Lou, Qiang Fu, Shengqi Yang, Jiang Li, Bin Wu},
title = {Mining Program Workflow from Interleaved Traces},
booktitle = {SigKDD'10 (full paper)},
year = {2010},
month = {July},
abstract = {Successful software maintenance is becoming increasingly critical due to the increasing dependence of our society and economy on software systems. One key problem of software maintenance is the difficulty in understanding the evolving software systems. Program workflows can help system operators and administrators to understand system behaviors and verify system executions so as to greatly facilitate system maintenance. In this paper, we propose an algorithm to automatically discover program workflows from event traces that record system events during system execution. Different from existing workflow mining algorithms, our approach can construct concurrent workflows from traces of interleaved events. Our workflow mining approach is a three-step coarse-to-fine algorithm. At first, we mine temporal dependencies for each pair of events. Then, based on the mined pair-wise temporal dependencies, we construct a basic workflow model by a breadth-first path pruning algorithm. After that, we refine the workflow by verifying it with all training event traces. The refinement algorithm tries to find out a workflow that can interpret all event traces with minimal state transitions and threads. The results of both simulation data and real program data show that our algorithm is highly effective.},
publisher = {Association for Computing Machinery, Inc.},
url = {https://www.microsoft.com/en-us/research/publication/mining-program-workflow-from-interleaved-traces/},
address = {},
pages = {},
journal = {},
volume = {},
chapter = {},
isbn = {},
}
@article{camarinha1996integration,
  title={Integration and learning in supervision of flexible assembly systems},
  author={Camarinha-Matos, Luis M and Lopes, Luis Seabra and Barata, Jos{\'e}},
  journal={IEEE Transactions on Robotics and Automation},
  volume={12},
  number={2},
  pages={202--219},
  year={1996},
  publisher={IEEE}
}
@article{el1989simulation,
  title={A simulation study of part sequencing in a flexible assembly cell},
  author={El-Tamimi, AM and SULIMANJ, SMA and Williams, DF},
  journal={THE INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH},
  volume={27},
  number={10},
  pages={1769--1793},
  year={1989},
  publisher={Taylor \& Francis}
}