• Vol 6, No 2 (2015)
  • Industrial Engineering

Optimization and Improvement of Gas Spring Design in An Energy Storing Prosthetic Knee

Cucuk Nur Rosyidi, Rahmaniyah Dwi Astuti, Ilham Priadythama

Corresponding email: cucuk@uns.ac.id


Published at : 30 Apr 2015
IJtech : IJtech Vol 6, No 2 (2015)
DOI : https://doi.org/10.14716/ijtech.v6i2.741

Cite this article as:

Rosyidi, C.N., Astuti, R.D., Priadythama, I., 2015. Optimization and Improvement of Gas Spring Design in An Energy Storing Prosthetic Knee. International Journal of Technology. Volume 6(2), pp. 273-283

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Cucuk Nur Rosyidi Department of Industrial Engineering, Faculty of Engineering Universitas Sebelas Maret, Surakarta 57126, Indonesia
Rahmaniyah Dwi Astuti Department of Industrial Engineering, Faculty of Engineering Universitas Sebelas Maret, Surakarta 57126, Indonesia
Ilham Priadythama Department of Industrial Engineering, Faculty of Engineering Universitas Sebelas Maret, Surakarta 57126, Indonesia
Email to Corresponding Author

Abstract
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In this research, an optimization and improvement of gas spring design is discussed. The gas spring is used as a suspension component of an energy storing prosthetic knee. The gas spring replaces the quadricep muscles of transfemoral amputee. A deterministic and a stochastic optimization is proposed in this research. Both models are used to determine the optimal design variables of the gas spring: cylinder diameter, cylinder length, extension stroke, and compression stroke. The optimal design variables resulted from the deterministic optimization model must be further analyzed to determine the effect of its variation to the objective function. Monte Carlo simulation is used to determine the effect of such variation and making improvement when necessary. Process capability index (Cp) is used as a criteria to make such improvement considering the contribution to variation of design variables to the objective function. Stochastic optimization is proposed to find the optimal design variables by taking into consideration the randomness of its parameters. The objective function of the stochastic optimization is to maximize the capability process. Both Monte Carlo simulation and stochastic optimization was solved using Oracle Crystal Ball Software. From the simulation, the reduction of compression stroke and extension stroke standard deviations resulted in 30% improvement of energy storage standard deviation. The Cp is also improved about 70% from 0.99 to 1.44. The stochastic optimization resulted in extension stroke and compression stroke which are shorter than deterministic optimization with 1.25 process capabilty.

gas spring, improvement , stochastic optimization, Monte Carlo simulation

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