Analysis and Mitigation Strategies of Croissant Production at PT XYZ
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This purpose of this research is to identify risk, analyzes risk priorities, and formulate alternative strategies and determine the priority strategies that can be applied to minimize the risk in production process of croissant at PT XYZ. The methods used in this research were the Failure Mode and Effect Analysis (FMEA) method and Analytical Hierarchy Process (AHP). The FMEA method is used to asses and determine risk priorities, while the AHP method is used to determine the priority of risk mitigation strategies. Based on the result, there are 19 risks which are divided into 3 risk factors, namely: raw materials, production process, and deliveries. The result from risk assessment and determination of risk priorities were the risk that have a high-Risk Priority Number (RPN), namely the risk of damage to raw materials during storage in the warehouse (52.6), machines and equipment are not working optimally (292.3), and delivery vehicles have problems (73.1). Priority strategies that can be used to minimize risk, namely on raw material risk factors are to make improvements to the placement and separation of clear types of raw materials (0.384), while in the production process risk factor are to replace machines and equipment that have a long life (0.435), and in delivery risk factor is to improve performance control and maintenance of vehicles on a regular basis (0.610).
Kamaruddin, R. and K. Jusoff. 2009. An ARDL approach in food and beverages industry growth process in Malaysia. International Business Research. 2(3):98-107.
Calvel, R. 2001. The Taste of Bread. Springer, New York.
International Standard Organization. 2009. Risk Management–Principles and Guidelines. ISO 31000:2009. ISO, Geneva.
Stamatis, D. H. 2003. Failure Mode and Effect Analysis: FMEA from Theory to Execution. 2nd Edition. ASQ Quality Press, Milwaukee.
Tsany, F., I. Santoso, and D. M. Ikasari. 2017. Identification and risk analysis of mozzarella cheese production process. Journal of Industrial and Information Technology in Agriculture. 1(2):8-26.
Parsana, T. S. and M. T. Patel. 2014. A case study: A process FMEA tool to enhance quality and efficiency of manufacturing industry. Bonfring International Journal of Industrial Engineering and Management Science. 4(3):145-152.
Wessiani, N. A. and S. O. Sarwoko. 2015. Risk analysis of poultry feed production using fuzzy FMEA. Procedia Manufacturing. 4(2015): 270-281.
Szováti K., P. Biacs, and A. Kiss. 2008. Application of Food Quality Methods in Case Bakery Products. Journal of the Ministry of Agriculture and Rural Development Hungary. 17(2-3): 21-23.
Ozilgen, S. 2012. Failure Mode and Effect Analysis (FMEA) for confectionery manufacturing in developing countries: Turkish delight production as a case study. Ciência e Tecnologia de Alimentos. 32(3): 505-514.
Ishizaka, A. and A. Labib. 2009. Analytic hierarchy process and expert choice: benefits and limitations. OR Insight. 22(4): 201-220.
Rucitra, A. L. 2018. Application of multi attribute failure mode analysis of milk production using analytical hierarchy process method. IOP Conference Series: Earth and Environmental Science. IOP Publishing. 131(2018):012022.
Heragu, S. S. 1997. Facilities Design. PWS Publishing Company, Boston.
Sahu, A. K., H. K. Narang, A. K. Sahu, and N. K. Sahu. 2016. Machine economic life estimation based on depreciation-replacement model. Cogent Engineering. 3(1): 1-15.
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