APPLICATION OF RESPONSE SURFACE METHODOLOGY FOR THE OPTIMIZATION MODELING OF DELIVERY FLEXIBILITY FOR SMEs IN NIGERIA
Keywords:
Response surface methodology, Machine, Mathematical model, Delivery flexibility, Agile manufacturingAbstract
The agile manufacturing system is a manufacturing methodology that improves the system’s operational efficiency which enhances the response to uncertainties, customers’ demand, and the dynamic competitiveness of the market trends. This study model and optimise agile manufacturing flexibility variables using response surface methodology (RSM) based on centre composite design (CCD). Pertinent parameters such as machine flexibility index, probability of operation, volume ordered, and flow index production volume each representing rain and dry season were obtained from Roswell Table Waters located at Oghara in Delta State. The data served as input parameters for the Minitab Software to model and optimize the agile manufacturing flexibility variables, namely; average flow time, volume flexibility, delivery flexibility, and routing flexibility index. The results show that routing flexibility is greatly dependent on production volume (1.0 – 2.0), probability of operation (0.5 – 2.0), and probability of volume (0.5 – 2.0) against constant machine
flexibility index and flow index. Volume flexibility increased by 0.02 – 0.15 as production volume increased from 0 – 600. The results showed that delivery flexibility is dependent on the volume ordered and machine index. In addition, the calculated data obtained from the data collected and predicted values for delivery flexibility are in agreement. Hence, the model reproduced the experimental results
accurately. The response optimization result showed that varying independent variables such as the production volume, period time, and volume ordered had delivery flexibility peak (2.0) at Delivery flexibility peaked (2.0) when the volume ordered, machine flexibility index, flow index, and the probability of operation was 242, 0.6, 0.7 and 0.8, respectively. Any values outside of this range will reduce the target outputs.
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