A fuzzy association rule-based knowledge management system for occupational safety and health programs in cold storage facilities

This paper aims to improve operational efficiency and minimize accident frequency in cold storage facilities through adopting an effective occupational safety and health program. The hidden knowledge can be extracted from the warehousing operations to create the comfortable and safe workplace environment.,A fuzzy association rule-based knowledge management system is developed by integrating fuzzy association rule mining (FARM) and rule-based expert system (RES). FARM is used to extract hidden knowledge from real operations to establish the relationship between safety measurement, personal constitution and key performance index measurement. The extracted knowledge is then stored and adopted in the RES to establish an effective occupational and safety program. Afterwards, a case study is conducted to validate the performance of the proposed system.,The results indicate that the aforementioned relationship can be built in the form of IF-THEN rules. An appropriate safety and health program can be developed and applied to all workers, so that they can follow instructions to prevent cold induced injuries and also improve the productivity.,Because of the increasing public consciousness of occupational safety and health, it is important for the workers in cold storage facilities where the ambient temperature is at/below 10°C. The proposed system can address the social problem and promote the importance of occupational safety and health in the society.,This study contributes to the knowledge management system for improving the occupational safety and operational efficiency in the cold storage facilities.

[1]  Tzung-Pei Hong,et al.  Fuzzy data mining for interesting generalized association rules , 2003, Fuzzy Sets Syst..

[2]  William J. Clancey,et al.  Rule-based expert systems , 2017, Radiopaedia.org.

[3]  J. Kuo,et al.  Developing an advanced Multi-Temperature Joint Distribution System for the food cold chain , 2010 .

[4]  Venkat Venkatasubramanian,et al.  Intelligent systems for HAZOP analysis of complex process plants , 2000 .

[5]  Tiina M Mäkinen,et al.  Health problems in cold work. , 2009, Industrial health.

[6]  Ajith Abraham,et al.  130: Rule-based Expert Systems , 2005 .

[7]  Lulin Wang,et al.  A Quality Research Analysis of Logistics Distribution Process of Fresh Meat Cold Chain in Beijing , 2015 .

[8]  Li-xin Lu,et al.  Development and Application of Time–temperature Indicators Used on Food during the Cold Chain Logistics , 2013 .

[9]  G. Emre Gürcanli,et al.  An occupational safety risk analysis method at construction sites using fuzzy sets , 2009 .

[10]  Ali Azadeh,et al.  Design and implementation of a fuzzy expert system for performance assessment of an integrated health, safety, environment (HSE) and ergonomics system: The case of a gas refinery , 2008, Inf. Sci..

[11]  C. James,et al.  The food cold-chain and climate change , 2010 .

[12]  J J Sheu,et al.  Diagnosis and monetary quantification of occupational injuries by indices related to human capital loss: analysis of a steel company as an illustration. , 2000, Accident; analysis and prevention.

[13]  Thomas Küpper,et al.  Cold exposure during helicopter rescue operations in the Western Alps. , 2003, The Annals of occupational hygiene.

[14]  Emily Seto,et al.  Developing healthcare rule-based expert systems: Case study of a heart failure telemonitoring system , 2012, Int. J. Medical Informatics.

[15]  A. Lansink,et al.  Performance measurement in agri‐food supply chains: a case study , 2007 .

[16]  Om Prakash Vyas,et al.  Using Associative Classifiers for Predictive Analysis in Health Care Data Mining , 2010 .

[17]  Henry C. W. Lau,et al.  Development of an intelligent quality management system using fuzzy association rules , 2009, Expert Syst. Appl..

[18]  Karin Reinhold,et al.  Hazard profile in manufacturing: Determination of risk levels towards enhancing the workplace safety/Pavojai pramonėje. Rizikos lygio nustatymas ir darbo vietų saugumo didinimas/ , 2009 .

[19]  K L Choy,et al.  Providing decision support functionality in warehouse management using the RFID-based fuzzy association rule mining approach , 2010, 2010 8th International Conference on Supply Chain Management and Information.

[20]  B Griefahn Limits of and possibilities to improve the IREQ cold stress model (ISO/TR 11079). A validation study in the field. , 2000, Applied ergonomics.

[21]  Ingvar Holmér,et al.  Evaluation of cold workplaces: an overview of standards for assessment of cold stress. , 2009, Industrial health.

[22]  M. Bogataj,et al.  Stability of perishable goods in cold logistic chains , 2005 .

[23]  Daniel Sánchez,et al.  Mining association rules with improved semantics in medical databases , 2001, Artif. Intell. Medicine.

[24]  King Lun Choy,et al.  A RFID-based recursive process mining system for quality assurance in the garment industry , 2014 .