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GİRİŞ KALİTE KONTROL SÜREÇLERİNDE DEĞİŞKENLERE YÖNELİK BİR KABUL ÖRNEKLEMESİ SİSTEMATİĞİ

Year 2017, Volume: 16 Issue: 32, 27 - 42, 31.12.2017

Abstract




Tedarik edilen parçalarda tespit edilemeyen kusurlar üretim hattında
büyük kayıplara neden olmakta ve müşteri memnuniyetinde olumsuz etki
oluşturmaktadır. Bu nedenle, kusurlu ürünlerin üretim sistemine girmesine engel
olunması amacı ile  uygulanan giriş kalite
kontrol faaliyetleri üretim sistemlerinde oldukça önem kazanmaktadır. Bir diğer
yandan, geleneksel yaklaşımlar kaliteyi sadece spesifikasyonlara uygunluk
olarak tanımlamışlardır. Ancak güncel yaklaşımlar, süreç ve üründe
değişkenliğin azaltılması yönündendir. Çalışma kapsamında giriş kalite kontrol
süreçlerinde kullanılmak üzere değişkenlere yönelik bir kabul örneklemesi sistematiği
önerilmiştir. 414 askeri standardını (ANSI/ASQC Z1.9) dikkate alan bu
çalışmada, ilgili literatürde yer alan çalışmalardan farklı olarak süreç
değişkenliği ve talep koşulları da muayene türlerinin belirlenmesi amacı ile
göz önünde bulundurulmuştur.  Önerilen
yöntem bir soğutucu fabrikasında uygulanmış ve hataların üretim hattına
girmeden yakalanmasında daha etkili olduğu görülmüştür.




References

  • Al-Salamah, M., (2016), “Economic Production Quantity in Batch Manufacturing with Imperfect Quality, Imperfect Inspection, and Destructive and Non-Destructive Acceptance Sampling in A Two-Tier Market”, Computers and Industrial Engineering, 93, 275-285.
  • Aslam, M., Lio, Y. L., Jun, C.-H., (2013), “Repetitive acceptance sampling plans for burr type XII percentiles”, International Journal of Advanced Manufacturing Technology, 68, 495-507.
  • Aslam, M., Wu, C.-W., Azam, M., Jun, C.-H., (2013), “Variable Sampling Inspection for Resubmitted Lots Based on Process Cpk”, Applied Mathematical Modelling 37, 667-675.
  • Bhattacharya, R., Pradhana, B., Dewanji, A., (2015), “Computation of Optimum Reliability Acceptance Sampling Plans in Presence of Hybrid Censoring”, Computational Statistics and Data Analysis, 83, 91-100.
  • Fournel, I., Tiv, M., Hua, C., Soulias, M., Astruc, K., (2010), “Randomisation and Sample Size for Clinical Audit on Infection Control”, Journal of Hospital Infection,76, 292-295.
  • Hradesky, J. L., (1998), “Productivity and Quality Improvement”, Mc Graw Hill Book Company, New York.
  • Jaraiedi, M., & Segall, R. S. (1990). “Mathematical Modelling of Dodge-Romig Sampling Plans for Random Incoming Quality”, Applied Mathematical Modelling, 14, 264-270.
  • Kent, R., (2016), “Acceptance Sampling”, Quality Management in Plastics Processing, 193-196.
  • Klufa, J., (2014), “Dodge-Romig AOQL Sampling Plans for Inspection by Variables – Optimal Solution”, Procedia Economics and Finance ,12, 302-308.
  • Kobilinskya, A., Bertheaub, Y., (2005), “Minimum Cost Acceptance Sampling Plans for Grain Control with Application to GMO Detection”, Chemometrics and Intelligent Laboratory Systems, 75, 189-200.
  • Lam, Y., Li, K.-H., Ip, W.-C., (2006), “Sequential Variable Sampling Plan for Normal Distribution”, European Journal of Operational Research, 172, 127-145.
  • Mussidaa, A., Gonzales-Barron, U., Butler, F., (2011), “Operating Characteristic Curves for Single, Double and Multiple Fraction Defective Sampling Plans Developed for Cronobacter”, Procedia Food Science, 1, 979- 986.
  • Montgomery, D. C., (2009), “Introduction to statistical quality control”, Wiley, United States of America.
  • Nezhad, M. F., Nasab, H. H., (2012), “A new Bayesian Acceptance Sampling Plan Considering Inspection Errors”. Scientia Iranica E ,19(6), 1865-1869.
  • Öner, M., Karaman, R., (2004), “Nitel Özelliklere Göre Yapilan Kabul Muayenelerinde Tekli Örnekleme Planının Tasarımı”, Selçuk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 499-511.
  • Peng, C.-Y., T. Khasawneh, M., (2014), “A Markovian Approach to Determine Optimum Process Means”, International Journal of Advanced Manufacturing Technology, 72, 1299–1323.
  • Robertson, B.L., McDonald, T., Price, C.J., J.A. Brown., (2017), “A Modification of Balanced Acceptance Sampling”, Statistics and Probability Letters 129, 107-112
  • Santos-Fernández, E., Govindaraju, K., Jon, G., (2014), “A New Variable Acceptance Sampling Plan for Food Safety”, Food Control, 44, 249-257.
  • Santos-Fernandez, E., Govindaraju, K., Jones, G., (2015), “Variables Sampling Plans Using Composite Samples for Food Quality Assurance”, Food Control, 50, 530-538.
  • Shiau, Y.-R., (2003), “Inspection Allocation Planning for a Multiple Quality Characteristic Advanced Manufacturing System”, International Journal of Advanced Manufacturing Technology, 21, 494–500.
  • Shiau, Y.-R., Lin, M.-H., & Chuang, W.-C., (2007), Concurrent Process/Inspection Planning for a Customized Manufacturing System Based on Genetic Algorithm”, International Journal of Advanced Manufacturing Technology, 33, 746–755.
  • Wu, C.-W., Liu, S.-W., (2014), “Developing a Sampling Plan by Variables Inspection for Controlling Lot Fraction of Defectives”, Applied Mathematical Modelling, 38, 2303-2310.
  • Wu, C.-W., W.L., P., (2008), “A Variable Sampling Plan Based on Cpmk for Product”, European Journal of Operational Research, 184, 549-560.
  • Yen, C.-H., Aslam, M., Jun, C.-H. (2014). “A Lot Inspection Sampling Plan based on EWMA Yield Index”, International Journal of Advanced Manufacturing Technology, 75, 861-868.
  • Zhou,W., Lian, Z., (2011), Optimum Design of a Newvss-NP Chart with Adjusting Sampling Inspection, International Journal of Production Economics, 129, 8-13.
Year 2017, Volume: 16 Issue: 32, 27 - 42, 31.12.2017

Abstract

References

  • Al-Salamah, M., (2016), “Economic Production Quantity in Batch Manufacturing with Imperfect Quality, Imperfect Inspection, and Destructive and Non-Destructive Acceptance Sampling in A Two-Tier Market”, Computers and Industrial Engineering, 93, 275-285.
  • Aslam, M., Lio, Y. L., Jun, C.-H., (2013), “Repetitive acceptance sampling plans for burr type XII percentiles”, International Journal of Advanced Manufacturing Technology, 68, 495-507.
  • Aslam, M., Wu, C.-W., Azam, M., Jun, C.-H., (2013), “Variable Sampling Inspection for Resubmitted Lots Based on Process Cpk”, Applied Mathematical Modelling 37, 667-675.
  • Bhattacharya, R., Pradhana, B., Dewanji, A., (2015), “Computation of Optimum Reliability Acceptance Sampling Plans in Presence of Hybrid Censoring”, Computational Statistics and Data Analysis, 83, 91-100.
  • Fournel, I., Tiv, M., Hua, C., Soulias, M., Astruc, K., (2010), “Randomisation and Sample Size for Clinical Audit on Infection Control”, Journal of Hospital Infection,76, 292-295.
  • Hradesky, J. L., (1998), “Productivity and Quality Improvement”, Mc Graw Hill Book Company, New York.
  • Jaraiedi, M., & Segall, R. S. (1990). “Mathematical Modelling of Dodge-Romig Sampling Plans for Random Incoming Quality”, Applied Mathematical Modelling, 14, 264-270.
  • Kent, R., (2016), “Acceptance Sampling”, Quality Management in Plastics Processing, 193-196.
  • Klufa, J., (2014), “Dodge-Romig AOQL Sampling Plans for Inspection by Variables – Optimal Solution”, Procedia Economics and Finance ,12, 302-308.
  • Kobilinskya, A., Bertheaub, Y., (2005), “Minimum Cost Acceptance Sampling Plans for Grain Control with Application to GMO Detection”, Chemometrics and Intelligent Laboratory Systems, 75, 189-200.
  • Lam, Y., Li, K.-H., Ip, W.-C., (2006), “Sequential Variable Sampling Plan for Normal Distribution”, European Journal of Operational Research, 172, 127-145.
  • Mussidaa, A., Gonzales-Barron, U., Butler, F., (2011), “Operating Characteristic Curves for Single, Double and Multiple Fraction Defective Sampling Plans Developed for Cronobacter”, Procedia Food Science, 1, 979- 986.
  • Montgomery, D. C., (2009), “Introduction to statistical quality control”, Wiley, United States of America.
  • Nezhad, M. F., Nasab, H. H., (2012), “A new Bayesian Acceptance Sampling Plan Considering Inspection Errors”. Scientia Iranica E ,19(6), 1865-1869.
  • Öner, M., Karaman, R., (2004), “Nitel Özelliklere Göre Yapilan Kabul Muayenelerinde Tekli Örnekleme Planının Tasarımı”, Selçuk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 499-511.
  • Peng, C.-Y., T. Khasawneh, M., (2014), “A Markovian Approach to Determine Optimum Process Means”, International Journal of Advanced Manufacturing Technology, 72, 1299–1323.
  • Robertson, B.L., McDonald, T., Price, C.J., J.A. Brown., (2017), “A Modification of Balanced Acceptance Sampling”, Statistics and Probability Letters 129, 107-112
  • Santos-Fernández, E., Govindaraju, K., Jon, G., (2014), “A New Variable Acceptance Sampling Plan for Food Safety”, Food Control, 44, 249-257.
  • Santos-Fernandez, E., Govindaraju, K., Jones, G., (2015), “Variables Sampling Plans Using Composite Samples for Food Quality Assurance”, Food Control, 50, 530-538.
  • Shiau, Y.-R., (2003), “Inspection Allocation Planning for a Multiple Quality Characteristic Advanced Manufacturing System”, International Journal of Advanced Manufacturing Technology, 21, 494–500.
  • Shiau, Y.-R., Lin, M.-H., & Chuang, W.-C., (2007), Concurrent Process/Inspection Planning for a Customized Manufacturing System Based on Genetic Algorithm”, International Journal of Advanced Manufacturing Technology, 33, 746–755.
  • Wu, C.-W., Liu, S.-W., (2014), “Developing a Sampling Plan by Variables Inspection for Controlling Lot Fraction of Defectives”, Applied Mathematical Modelling, 38, 2303-2310.
  • Wu, C.-W., W.L., P., (2008), “A Variable Sampling Plan Based on Cpmk for Product”, European Journal of Operational Research, 184, 549-560.
  • Yen, C.-H., Aslam, M., Jun, C.-H. (2014). “A Lot Inspection Sampling Plan based on EWMA Yield Index”, International Journal of Advanced Manufacturing Technology, 75, 861-868.
  • Zhou,W., Lian, Z., (2011), Optimum Design of a Newvss-NP Chart with Adjusting Sampling Inspection, International Journal of Production Economics, 129, 8-13.
There are 25 citations in total.

Details

Journal Section Research Articles
Authors

Emre Çevikcan

Sevcan Yıldırım Özer This is me

Publication Date December 31, 2017
Submission Date August 15, 2017
Published in Issue Year 2017 Volume: 16 Issue: 32

Cite

APA Çevikcan, E., & Yıldırım Özer, S. (2017). GİRİŞ KALİTE KONTROL SÜREÇLERİNDE DEĞİŞKENLERE YÖNELİK BİR KABUL ÖRNEKLEMESİ SİSTEMATİĞİ. İstanbul Ticaret Üniversitesi Fen Bilimleri Dergisi, 16(32), 27-42.
AMA Çevikcan E, Yıldırım Özer S. GİRİŞ KALİTE KONTROL SÜREÇLERİNDE DEĞİŞKENLERE YÖNELİK BİR KABUL ÖRNEKLEMESİ SİSTEMATİĞİ. İstanbul Ticaret Üniversitesi Fen Bilimleri Dergisi. December 2017;16(32):27-42.
Chicago Çevikcan, Emre, and Sevcan Yıldırım Özer. “GİRİŞ KALİTE KONTROL SÜREÇLERİNDE DEĞİŞKENLERE YÖNELİK BİR KABUL ÖRNEKLEMESİ SİSTEMATİĞİ”. İstanbul Ticaret Üniversitesi Fen Bilimleri Dergisi 16, no. 32 (December 2017): 27-42.
EndNote Çevikcan E, Yıldırım Özer S (December 1, 2017) GİRİŞ KALİTE KONTROL SÜREÇLERİNDE DEĞİŞKENLERE YÖNELİK BİR KABUL ÖRNEKLEMESİ SİSTEMATİĞİ. İstanbul Ticaret Üniversitesi Fen Bilimleri Dergisi 16 32 27–42.
IEEE E. Çevikcan and S. Yıldırım Özer, “GİRİŞ KALİTE KONTROL SÜREÇLERİNDE DEĞİŞKENLERE YÖNELİK BİR KABUL ÖRNEKLEMESİ SİSTEMATİĞİ”, İstanbul Ticaret Üniversitesi Fen Bilimleri Dergisi, vol. 16, no. 32, pp. 27–42, 2017.
ISNAD Çevikcan, Emre - Yıldırım Özer, Sevcan. “GİRİŞ KALİTE KONTROL SÜREÇLERİNDE DEĞİŞKENLERE YÖNELİK BİR KABUL ÖRNEKLEMESİ SİSTEMATİĞİ”. İstanbul Ticaret Üniversitesi Fen Bilimleri Dergisi 16/32 (December 2017), 27-42.
JAMA Çevikcan E, Yıldırım Özer S. GİRİŞ KALİTE KONTROL SÜREÇLERİNDE DEĞİŞKENLERE YÖNELİK BİR KABUL ÖRNEKLEMESİ SİSTEMATİĞİ. İstanbul Ticaret Üniversitesi Fen Bilimleri Dergisi. 2017;16:27–42.
MLA Çevikcan, Emre and Sevcan Yıldırım Özer. “GİRİŞ KALİTE KONTROL SÜREÇLERİNDE DEĞİŞKENLERE YÖNELİK BİR KABUL ÖRNEKLEMESİ SİSTEMATİĞİ”. İstanbul Ticaret Üniversitesi Fen Bilimleri Dergisi, vol. 16, no. 32, 2017, pp. 27-42.
Vancouver Çevikcan E, Yıldırım Özer S. GİRİŞ KALİTE KONTROL SÜREÇLERİNDE DEĞİŞKENLERE YÖNELİK BİR KABUL ÖRNEKLEMESİ SİSTEMATİĞİ. İstanbul Ticaret Üniversitesi Fen Bilimleri Dergisi. 2017;16(32):27-42.