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Information Journal Paper

Title

APPLICATION OF DESIGN FOR SIX SIGMA TO OPTIMIZE MIXEDCONTENT PARAMETERS IN CELLULAR LIGHTWEIGHT CONCRETE

Pages

 Start Page 125 | End Page 133

Abstract

 Although most companies spend less on product design, experience shows that, these companies have to pay higher costs due to production problems or loss of market. Literature studies show that the DESIGN FOR SIX SIGMA is a powerful approach for designing products, processes and services. While the tools used in Six Sigma require a process to be in place and functioning, DFSS has the objective of determining the needs of customers and the business, and driving those needs into the product solution so created. DFSS is relevant to the complex system/product synthesis phase, especially in the context of unprecedented system development The aim of this project is to provide a global method for designing robust products based on the DESIGN FOR SIX SIGMA methodology. The methodology integrates three concepts: RELIABILITY-based OPTIMIZATION, ROBUST DESIGN and multi-objective OPTIMIZATION. The methodology proposed for the design of Six Sigma can be explained in four stages: formulation, OPTIMIZATION, simulation and selection. The algorithm is to generate several Pareto optimal solutions at the OPTIMIZATION stage. The algorithm was applied to the design of LIGHTWEIGHT CONCRETE BLOCKs, with consideration of customer need, in three main areas: weight blocks, cost blocks and strength blocks. First, considering expert preferences, the mathematical modeling of the blocks was determined. Second, interactive multi-objective algorithms, taking the decision maker's preferences into account, were developed to generate twelve Pareto-optimal solutions that maintain a probability of constraint satisfaction. Then, 1s solution OPTIMIZATION (per cubic meter of: 409 kg of cement, 1.4 kg of Polypropylene fibers, 12.14 kg of silica and 8.8l of foam) was adopted for implementation as a compromise between the three criteria (the savings compared to the baseline solution, the coefficient of variance (robustness), and the degrees of desirability). The results show that the variable Polypropylene fibers cause the most variations in cost functions, while Polypropylene fibers, silica, water and foam are the most critical variables for the constraint. Blocks were built and compressive strength was obtained that was consistent with the calculated result.

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