Classification of product quality with multiple criteria decision making: an example of furniture industry
Abstract
When
the critical success factors for a company operating in the furniture sector
are weighted and their scores are analyzed; The most critical factor is
determined as of quality, and a selected product group is considered in line
with this factor. The study aims to classify the final product concerning quality
in the selected product group. Observation of parameters affecting the
separation of the selected product as first and second quality; The main steps
of the study are the determination of the reasons of the products separated as
second quality and classification of these reasons according to their
importance levels by taking into account the after-sales service and customer
complaints. In order to determine the importance levels of the products
identified as second quality, Analytical Hierarchy Process (AHP) method which
is one of the multi-criteria decision-making techniques has been used. Then,
which type of error is encountered most in the second quality products, how to
determine the root cause of these errors, how the faulty products can
contribute positively to the business, what needs to be done to minimize the
margin of error and thus the efficient use of raw materials can be maintained. Results
provide that the firms operating in the field of furniture will guide the work
done in order to provide maximum satisfaction to the customer/operation.
Keywords
References
- Chang, J., Han, G., Valverde, J. M., Griswold, N. C., Duque-Carrillo, J.-F., and Sanchez-Sinencio, E. (1997), Cork quality classification system using a unified image processing and fuzzy-neural network methodology, IEEE Transactions on Neural Networks, 8(4), 964-974.
- Kaya, İ., Oktay, S., and Engin, O. (2005), Kalite kontrol problemlerinin çözümünde yapay sinir ağlarinin kullanimi, Erciyes Üniversitesi, Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi, 21(1), 92-107.
- Kozlov, A., Al-jonid, K. M., Kozlov, A., and Antar, S. D. (2018), Product quality management based on CNC machine fault prognostics and diagnosis, Paper presented at the IOP Conference Series: Materials Science and Engineering.
- Ngendangenzwa, B. (2018), Defect detection and classification on painted specular surfaces.
- Saaty, T. L. (1980), The analytic hierarchy process: planning, priority setting, resources allocation. New York: McGraw, 281. Saaty, T. L. (1989), Group decision making and the AHP, The analytic hierarchy process (pp. 59-67): Springer.
- Tello, G., Al-Jarrah, O. Y., Yoo, P. D., Al-Hammadi, Y., Muhaidat, S., and Lee, U. (2018), Deep-structured machine learning model for the recognition of mixed-defect patterns in semiconductor fabrication processes, IEEE Transactions On Semiconductor Manufacturing, 31(2), 315-322.
- Wan, Y. N., Lin, C. M., and Chiou, J. F. (2002), Rice quality classification using an automatic grain quality inspection system. Transactions of the ASAE, 45(2), 379.
- Wheelen, T. L., and Hunger, J. D. (2011), Concepts in strategic management and business policy: Pearson Education India.
Details
Primary Language
English
Subjects
Engineering
Journal Section
Research Article
Publication Date
June 28, 2019
Submission Date
January 21, 2019
Acceptance Date
April 20, 2019
Published in Issue
Year 2019 Volume: 2 Number: 1