Application of the fuzzy Failure Mode and Effect Analysis methodology to edible bird nest processing

Abstract

This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution and sharing with colleagues.Other uses, including reproduction and distribution, or selling or licensing copies, or posting to personal, institutional or third party websites are prohibited. b s t r a c tThe focus of this paper is on the production processes of Edible Bird Nest (EBN) in Sarawak, Malaysia. Sarawak and Sabah (two states of Malaysia in the Borneo Island) are known as the second ranked resource area (after Indonesia) of the world for EBN production. In spite of the popularity of EBN as a food source and the important economic status of the EBN industry, the use of a quality and risk assessment tool for the production of EBN is new. As such, the implementation of an advanced quality and risk assessment tool, i.e., the fuzzy Failure Mode and Effect Analysis (FMEA) methodology, for EBN processing is described in this paper. Data and information are gathered from several EBN production sites, and fuzzy FMEA is adopted to analyze the collected data/information. It is worth mentioning that the EBN production in Sarawak is relatively traditional. As such, this work makes an important contribution to modernization of the EBN production industry in Sarawak, i.e., to improve the production process and ensure the quality of EBN via the use of a formal quality and risk assessment tool. Besides, this paper contributes to a new application of fuzzy FMEA to the agriculture and food domain.

Clustering and visualization of failure modes using an evolving tree

“…Based on the findings, we have proven the importance of maintaining the monotonicity relationship between inputs (S, O, D) and the output (RPN score) (Tay & Lim, 2008a, 2008bJee et al, 2015). Our works (Tay & Lim, 2006;Jong et al, 2013Jong et al, , 2014Jee et al, 2015) focus on the development of fuzzy inference system-based frameworks for risk evaluation, with the aim of reducing the number of fuzzy rules while maintaining the monotonicity property. Fuzzy ART was used by Keskin and Özkan (2009) as a clustering method to tackle the problem whereby different combinations of S, O, and D could produce the same RPN scores.…”

“…In our previous research, fuzzy inference systems (Tay & Lim, 2006;Jong et al, 2013Jong et al, , 2014Jee et al, 2015) and an adaptive clustering method, i.e., fuzzy adaptive reasoning theory (Tay, Jong, & Lim, 2015), have been applied to FMEA. Based on the findings, we have proven the importance of maintaining the monotonicity relationship between inputs (S, O, D) and the output (RPN score) (Tay & Lim, 2008a, 2008bJee et al, 2015).…”

Pengujian Suhu Lemari Es Dengan Metode Terintegrasi Fuzzyfailure Mode and Effect Analysis (Fuzzy-Fmea)

“…Logika fuzzy dipilih karena menurut Silva, dkk. (2014), Mandal & Maiti (2014), Kumru & Kumru (2013), Jong, dkk. (2013), Dinmohamadi & Safiee (2013), dan Chang & Cheng (2010), mampu menyelesaikan permasalahan yang terdapat pada analisis risiko dengan FMEA.…”

PENERAPAN METODE PENCUCIAN DENGAN AIR MENGALIR UNTUK MENURUNKAN KADAR NITRIT PADA SARANG BURUNG WALET (Application of Washing Method under Running Water to Reduce Nitrit Level of Edible Bird’s Nest)

“…Sebelum dikonsumsi, sarang burung walet membutuhkan beberapa tahapan proses produksi (Jong et al, 2013). Kadar nitrit sarang burung walet dapat turun setelah dilakukan proses pencucian (Ramli dan Azmi, 2012;Chan et al, 2013;Hamzah et al, 2013) dan perendaman (Ramli dan Azmi, 2012).…”