Application of a Genetic-Fuzzy FMEA to Rainfed Lowland Rice Production in Sarawak: Environmental, Health, and Safety Perspectives

• Main Authors: Anisia Jati Sang, Kai Meng Tay, Chee Peng Lim, Saeid Nahavandi
• Format: Article
• Language: English
• Published: IEEE 2018-01-01
• Series: IEEE Access
• Subjects: Borneo; fuzzy failure mode and effect analysis; genetic algorithm; monotone fuzzy rule relabeling; rice production; safety
• Online Access: https://ieeexplore.ieee.org/document/8543779/

Rainfed lowland rice is the most popular choice for rice cultivation in Sarawak, Borneo. In general, rice production in Sarawak consists of seven phases, namely, preparing land, establishing crop, transplanting, managing crop, harvesting, post-harvesting, and milling. Most farmers in Sarawak depend on indigenous knowledge and experience for rice cultivation. In this paper, an improved fuzzy failure mode and effect analysis (FMEA) with genetic algorithm-based design of fuzzy membership functions and monotone fuzzy rules relabeling is employed as a knowledge-based tool for risk analysis and assessment pertaining to rice production in Sarawak. The specific focus is on issues related to the environment as well as health and safety of farmers and consumers. With the support from the Sarawak Government, we analyze useful data and information pertaining to various rice fields from experienced farmers to develop the fuzzy FMEA model. Specifically, we develop fuzzy FMEA to inculcate the best practices for farmers to improve yield and enhance food safety. Through this paper, we identify that musculoskeletal disorders due to bad postures is the most noticeable occupational health hazard; as a result, new techniques and tools are invented and introduced to mitigate this risk. In summary, this is a new attempt to implement a quality and risk assessment tool that contributes toward enhancing rice productivity in Sarawak, and modernizing the local agricultural sector.