Journals / Ege Akademik Bakış / 2012 / Cilt: 12 - Sayı: 3

The measurement of plant manufacturing performance with fuzzy analytic hierarchy process

Bulanık analitik hiyerarşi prosesi ile fabrika imalat performansının ölçümü

Pages
323–338
Publication Date
2022-10-12
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Thesix-month manufacturing performance of the plant has beenmeasured via proposed method; performance measurementresults have been compared.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The performance measurement system plays a critical role inachieving the competitiveness of manufacturing systems.
📊
Key Findings & Data:Forthat reason the manufacturers are conducting performancemeasurements via several methods in order to analyze theircurrent situations and determine recoverable and improvablefields.
💡
Conclusion & Impact:Thesix-month manufacturing performance of the plant has beenmeasured via proposed method; performance measurementresults have been compared.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

The performance measurement system plays a critical role inachieving the competitiveness of manufacturing systems. Forthat reason the manufacturers are conducting performancemeasurements via several methods in order to analyze theircurrent situations and determine recoverable and improvablefields. In present study, a model which can measuremanufacturing performance of a plant in glass industryhas been proposed. The coefficients of the performancedimensions and indicators used in this model have beendetected via Fuzzy Analytic Hierarchy Process method. Thesix-month manufacturing performance of the plant has beenmeasured via proposed method; performance measurementresults have been compared.

Özet

İmalat sistemlerinin rekabetçiliğini artırmada performans öl çüm sistemleri kritik rol oynamaktadır. Bu nedenle imalatçılar,mevcut durumlarını analiz etmek, iyileştirilebilir ve geliştiri lebilir alanları belirlemek için çeşitli yöntemlerle performansölçümleri yapmaktadır. Bu çalışmada, cam endüstrisindeki birfabrikanın imalat performansını ölçen bir model önerilmiştir.Modelde kullanılan performans boyut ve göstergelerinin kat sayıları Bulanık Analitik Hiyerarşi Prosesi (BAHP) yöntemi ilebelirlenmiştir. Önerilen model ile fabrikanın altı aylık imalatperformansı ölçülmüş, performans ölçüm sonuçları karşılaştı rılmıştır.

🔖

Cite This Article

AKYÜZ, G. (2022). The measurement of plant manufacturing performance with fuzzy analytic hierarchy process. Ege Akademik Bakış, Cilt: 12 - Sayı: 3, 323–338. https://ajindex.com/articles/495450

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (16)

  1. Abdel-Kader, M.G. ve Dugdale, D. (2001) “Evaluating Investments in Advanced Manufacturing Technology: A Fuzzy Set Theory Approach” British Accounting Review, 33 (4): 455-489.
  2. Agrell, P.J. ve West, B.M. (2001) “A Caveat on the Measurement of Productive Efficiency” International Journal of Production Economics, 69(1):1-14.
  3. Ahmad, M. ve Dhafr, N. (2002) “Establishing and Improving Manufacturing Performance Measures” Robotics and Computer-Integrated Manufacturing, 18(3- 4):171-176.
  4. Bamber, C.J., Castka, P., Sharp, J.M. ve Motara, Y. (2003) “Cross-Functional Team Working for Overall Equipment Effectiveness (OEE)” Journal of Quality in Maintenance Engineering, 9 (3):223-238.
  5. Bititci, U.S., Suwignjo, P. ve Carrie, A.S. (2001) “Strategy Management Through Quantitative Modelling of Performance Measurement Systems” International Journal of Production Economics, 69(1):15-22.
  6. Bozbura, F.T., Beskese, A. ve Kahraman, C. (2007) “Prioritization of Human Capital Measurement Indicators Using Fuzzy AHP” Expert Systems with Applications, 32(4):1100-1112.
  7. Buckley, J.J. (1985) “Fuzzy Hierarchical Analysis” Fuzy Sets and Systems, 17(3): 233-247.
  8. Çakır, O. ve Canbolat, M.S. (2008) “A Web-Based Decision Support System for Multi-Criteria Inventory Classification Using Fuzzy AHP Methodology” Expert Systems with Applications, 35(3):1367-1378.
  9. Chamodrakas, I., Batis, D. ve Martakos, D. (2010) “Supplier Selection in Electronic Marketplaces Using Satisficing and Fuzzy AHP” Expert Systems with Applications, 37(1): 490-498.
  10. Chan, D.C.K., Yung, K.L. ve Ip, A.W.H. (2002) “An Application of Fuzzy Sets to Process Performance Evaluation” Integrated Manufacturing Systems, 13(4):237-246.
  11. Chan, F.T.S., Kumar, N., Tiwari, M.K. Lau, H.C.W. ve Choy, K.L. (2008) “Global Supplier Selection: A Fuzzy-AHP Approach” International Journal of Production Research, 46(14): 3825-3857.
  12. Chang, D.Y. (1996) “Applications of the Extent Analysis Method on Fuzzy AHP” European Journal of Operational Research, 95(3): 649-655.
  13. Chen, C.C. (2008) “An Objective-Oriented and Product- Line-Based Manufacturing Performance Measurement” International Journal of Production Economics, 112(1):380-390.
  14. Chen, S.H. (1985) “Ranking Fuzzy Numbers with Maximizing Set and Minimizing Set” Fuzzy Sets and Systems, 17(2):113-129.
  15. Cheng, C.H. (1998) “A New Approach for Ranking Fuzzy Numbers by Distance Method” Fuzzy Sets and Systems, 95(3):307-317.
  16. Chenhall, R.H. (1996) “Strategies of Manufacturing Flexibility, Manufacturing Performance Measu