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Derivation of a Cost Model to Aid Management of CNC Machine Tool Accuracy Maintenance

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Manufacturing industries strive to produce improved component accuracy while not reducing machine tool availability or production throughput. The accuracy of CNC production machines is one of the critical factors in determining the quality of these components. Maintaining the capability of the machine to produce in-tolerance parts can be approached in one of two ways: run to failure or periodic calibration and monitoring. The problem is analogous to general machine tool maintenance, but with the clear distinction that the failure mode of general machine tool components results in a loss of production, whereas that of accuracy allows parts to be produced, which are only later detected as non-conforming as part of the quality control processes. This distinction creates problems of cost-justification, since at this point in the manufacturing chain, any responsibility of the machine is not directly evident. Studies in the field of maintenance have resulted in cost calculations for the downtime associated with machine failure. This paper addresses the analogous, unanswered problem of maintaining the accuracy of CNC machine tools. A mathematical cost function is derived that can form the basis of a strategy for either running until non-conforming parts are detected or scheduling predictive CNC machine tool calibrations. This is sufficiently generic that it can consider that this decision will be based upon different scales of production, different values of components etc. Therefore, the model is broken down to a level where these variables for the different inputs can be tailored to the individual manufacturer.
Rocznik
Strony
17--43
Opis fizyczny
Bibliogr. 24 poz., tab., rys.
Twórcy
autor
  • Centre for Precision Technologies, University of Huddersfield, UK
  • Centre for Precision Technologies, University of Huddersfield, UK
autor
  • Centre for Precision Technologies, University of Huddersfield, UK
Bibliografia
  • [1] BS EN ISO 14253-1:2013: Geometrical product specifications (GPS). Inspection by measurement of workpieces and measuring equipment. Decision rules for proving conformity or nonconformity with specification," ed: British Standards Institute, 2013.
  • [2] ACHELKER C., RAO N.S., RAJENDRA R., KRISHANIAH A., 2014, Performance Evaluation of Machine Tool Probe for In-process Inspection of 2D and 3D Geometries, Procedia Technology, 14, 244−251.
  • [3] BIN L., DUROCHER D., STEMPER P., 2009, Predictive maintenance techniques, IEEE Industry Applications Magazine, 15, 52−60.
  • [4] IBM Corporation., 2008, Assessing the financial impact of downtime, In: Understand the factors that contribute to the cost of downtime and accurately calculate its total cost in your organization, ed: Vision Solution, 1−14.
  • [5] CRUMRINE D., POST D., 2006, When true cost of downtime is unknown, bad decisions ensue, 2006 ed: Intech, 53−55.
  • [6] FOX J.P., BRAMMALL J.R., YARLAGADDA P.K., 2008, Determination of the financial impact of machine downtime on the Australia Post large letters sorting process. Journal of Achievements in Materials and Manufacturing Engineering, 31/2, 732−738.
  • [7] JANTUNEN E., ARNAIZ A, BAGLEE D., FUMAGALLI L., 2014, Identification of wear statistics to determine the need for a new approach to maintenance, Euromaintenance, May 5th −8th, Helsinki Finland.
  • [8] KUMAR K., SHAH R., FITZROY P.T., 1998, A review of quality cost surveys, Total Quality Management, 9, 479−486.
  • [9] LONGSTAFF A.P., FLETCHER S., POXTON A., MYERS, A., 2009, Comparison of volumetric analysis methods for machine tools with rotary axes, In: Laser Metrology and Machine Performance. Euspen Ltd, Euspen Headquarters, Cranfield University, 87−96.
  • [10] MA Z., 2011, Research and practice on the process cost estimation based on working procedure of railway transportation equipments, iBusiness, 3, 97−106.
  • [11] MIKLER J., FRANGOUDIS C., LINDBERG B., 2011, On a systematic approach to development of maintenance plans for production equipment. Journal of Machine Engineering, 11, 102−119.
  • [12] PARKINSON S., LONGSTAFF A.P., FLETCHER S., 2014, Automated planning to minimise uncertainty of machine tool calibration, Engineering Applications of Artificial Intelligence, 30, 63−72.
  • [13] PASCUAL R., REY P., MERUANE V., 2006, On the Effect of downtime costs and budget constraint on preventive and replacement policies, Reliability Engineering and System Safety, 9/1, 144−151.
  • [14] RENISHAW., 2007, Evolution of the renishaw productivity system, In: White Paper, ed. Gloucestershire, UK: Renishaw, 1−12.
  • [15] SCHWENKE H., KNAPP W., 2008, Geometric error measurement and compensation of machines—an update, CIRP Annals-Manufacturing Technology, 57, 660−675.
  • [16] SHAGLUF A., LONGSTAFF A.P., FLETCHER S., 2014, Maintenance strategies to reduce downtime due to machine positional errors, Presented at the Maintenance Performance Measurement and Management Conference Coimbra, Portugal.
  • [17] SHAGLUF A., LONGSTAFF A. P., FLETCHER S., DENTON P., 2013, Towards a downtime cost function to optimise machine tool calibration schedules, Presented at the International Conference on Advanced Manufacturing Engineering and Technologies, NEWTECH 2013, KTH Royal Institute of Technology in Stockholm, Sweden.
  • [18] SHAGLUF A., LONGSTAFF A.P., FLETCHER S., DENTON P., MYERS A., 2013, The importance of assessing downtime cost related factors towards an optimised machine tool calibration schedule, presented at the Computing and Engineering Diamond Jubilee Annual Researchers’ Conference The University of Huddersfield.
  • [19] SHAGLUF A., LONGSTAFF, A.P., FLETCHER, S., 2015, A Preliminary Study of Applying Lean Six Sigma Methods to Machine Tool Measurement, In: SDM, Second International Conference on Sustainable Design and Manufacturing, Seville, Spain, 1−13.
  • [20] SHUM Y.S., GONG D.C., 2004, Development of a preventive maintenance analytic model, In: Fifth Asia Pacific Industrial and Management Systems Conference, Gold Coast Australia, 38.5.1−38.5.12.
  • [21] TIAN YING L.B., HONGQI L., 2010, A Fast Error Measurement System for CNC Machine Tools Based on Step-gauge, Presented at the 2nd International Conference on Mechanical and Electronics Engineering (ICMEE 2010), National NC System Engineering Research Center, China.
  • [22] VAN DIJKHUIZEN G., VAN HARTEN A., 1997, Optimal clustering of frequency-constrained maintenance jobs with shared set-ups, European Journal of Operational Research, 99, 552−564.
  • [23] VAN DIJKHUIZEN G.C., VAN HARTEN A., 1998, Two-stage generalized age maintenance of a queue-like production system, European Journal of Operational Research, 108/2, 363−378.
  • [24] YAM K. L., 2010, The Wiley encyclopedia of packaging technology, John Wiley & Sons.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-4a500af8-8619-4845-88d9-fcfdd97e1fac
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