A decision model for setting target levels in quality function deployment using nonlinear programming-based fuzzy regression and optimization

2009 ◽  
Vol 48 (9-12) ◽  
pp. 1173-1184 ◽  
Author(s):  
Zeynep Sener ◽  
E. Ertugrul Karsak
Keyword(s):  
Nonlinear Programming ◽  
Quality Function Deployment ◽  
Decision Model ◽  
Fuzzy Regression ◽  
Quality Function

Rating TAs in fuzzy QFD by objective penalty function and fuzzy TOPSIS based on weighted Hamming distance

2020 ◽  
Vol 39 (3) ◽  
pp. 3665-3679
Author(s):  
Jing Wang ◽  
Bing Yan ◽  
Guohao Wang ◽  
Liying Yu
Keyword(s):  
Nonlinear Programming ◽  
Penalty Function ◽  
Quality Function Deployment ◽  
Hamming Distance ◽  
Decision Makers ◽  
Programming Models ◽  
Ideal Solution ◽  
Quality Function ◽  
Order Preference ◽  
Objective Penalty Function

Quality function deployment (QFD) is an useful tool to solve Multi-criteria decision making, which can translate customer requirements (CRs) into the technical attributes (TAs) of a product and helps maintain a correct focus on true requirements and minimizes misinterpreting customer needs. In applying quality function deployment, rating technical attributes from input variables is a crucial step in fuzzy environments. In this paper, a new approach is developed, which rates technical attributes by objective penalty function and fuzzy technique for order preference by similarity to an ideal solution (TOPSIS) based on weighted Hamming distance under the case of uncertain preference characteristics of decision makers in fuzzy quality function deployment. A pair of nonlinear programming models with constraints and a relevant pair of nonlinear programming models with unconstraints called objective penalty function models are proposed to gain the fuzzy important numbers of technical attributes. Then, this paper compares the fuzzy numbers by fuzzy technique for order preference by similarity to an ideal solution (TOPSIS) method based on weighted Hamming distance in consideration of the uncertain preference characteristics of decision makers. To end with, the developed method is examined with the numerical examples.

Peningkatan Kualitas Layanan Konsumen Dengan Metode Servqual Dan Quality Function Deployment

2019 ◽  
Vol 3 (2) ◽  
pp. 60
Author(s):  
Chistofora Desi Kusmindari
Keyword(s):  
Customer Satisfaction ◽  
Quality Function Deployment ◽  
Quality Function

Permasalahan dalam penelitian ini adalah bagaimanakah peningkatan kualitas layanan konsumen CV. Sinar Jaya Agung dengan metode servqual dan quality function deployment dengan tujuan untuk mengetahui persepsi konsumen dengan metode servqual, untuk menentukan nilai gap servqual antara persepsi dan harapan konsumen, dan untuk meningkatkan kualitas layanan sesuai dengan kebutuhan dan keinginan konsumen dengan menggunakan metode quality function deployment. Hasil penelitian ini menunjukkan bahwa semakin tinggi nilai customer satisfaction performancemaka semakin tinggi pula tingkat persepsi konsumen terhadap atribut oleh responden, nilai gap servqual diperoleh nilai tertinggi sebesar 0,35 pada atribut karyawan memiliki kompetensi dan profesional dalam melayani pelanggan. Dengan demikian dapat diartikan bahwa kualitas layanan konsumen yang diberikan sudah bisa dikatakan baik. Hasil pengujian quality function deployment menunjukkan bahwa untuk meningkatkan kualitas layanan sesuai dengan kebutuhan dan keinginan konsumen, maka perusahaan harus melakukan beberapa perbaikan, antara lain: lokasi perusahaan harus mudah dijangkau oleh konsumen, penyediaan checklist pembersihan, pemberian pelatihan rutin kepada karyawan, serta service yang baik dari karyawan pada konsumen.

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