Factors When Designing and Implementing Material Handling System in Fms

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Factors when designing and implementing Material Handling system in FMS
Introduction
Material handling equipment selection is vital in the design of an effective and efficient flexible manufacturing system (Kulak*, 2005). There are many factors to consider when designing MHS system. A properly designated MHS would be able to decrease manufacturing lead times, increase efficiency of material flow, and improve facility utilization and increase productivity (Kulak*, 2005). According to (Sule, 1994 ) material handling cost accounts for 30-70% of total operating cost, hence it is crucial to determine the best option for MHS. However, different MHS component would have their specific advantages and disadvantages, and there is no absolute formula in determining the type of MHS to be used, and the vast amount of variables to be consider leads to complexity while designing the MHS system.

The sole objective of this review paper is to explore various methods used during the designing of MHS system to be used in manufacturing plant, and also relating human factors role and influence in implementing successful MHS system. These methods apply various mathematical modelling and decision trees to simplify multi variables of MHS components. Various methods would be then laid out and the strengths and weakness of each of these methods would be visited.

Types of MHS
Material handling system is an automated system that assists and transfer material in the manufacturing line. It functions as a continuous, intelligent system that load raw materials to CNC machines, interconnecting the in process product to other machines for additional processes, transfer it to inspection machine for quality surveillance and finally unloading it into automated Storage and retrieval system (AS/RS) . Material handling equipment commonly categorised as industrial trucks, conveyors, Automated guided vehicles, cranes, storage/retrieval system, and robotic arms.

Journal 1 : A decision support



References: Devise, O., & Pierreval, H. (2000). Indicators for measuring performance of morphology and material handling systems in flexible manufacturing systems. International Journal of Production Economics, 64, 209-218. Cho, C., & Egbelu, P. J. (2005). Design of a web-based integrated material handling system for manufacturing applications. International Journal of Production Research, 43(2), 375-403. Hassan, M. M. D., Hogg, G. L., & Smith, D. R. (1985). A construction algorithm for the selection and assignment of materials handling equipment. International Journal of Production Research, 23(2), 381-392. Mirhosseyni, S. H. L., & Webb, P. (2009). A Hybrid Fuuzy Knowledge-Based Expert System and Genetic Algorithm for efficient selection and assignment of Material Handling Equipment. Expert Systems with Applications, 36, 11875-11887. Welgama, P. S., & Gibson, P. R. (1995). Hybrid knowledge based/optimization system for automated selection of materials handling system. Computers and Industrial Engineering, 28(2), 205-217. Kulak*, O. (2005). A decision support system for fuzzy multi-attribute selection of material handling equipments SatyaS.Chakravorty. (2008). Improvingdistributionoperations:Implementationofmaterial handling systems Sule, D. R. (1994 ). Manufacturing facilities: Location, planning and design Boston: PWS Publishing Company, 2nd ed. Welgama, P. S., & Gibson, P. R. (1995). Hybrid knowledge based/optimization system for automated selection of materials handling system. Computers and Industrial Engineering, 28(2), 205-217.

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