PENENTUAN PRIORITAS PENGENDALIAN PROSES KEY CHARACTERISTICS - Nur Rosyidi, Cucuk
Abstract: Product complexity enforces manufacturer to determine effectively which dimensions, tolerances or processes (key characteristics) need to be controlled both at design and production stage. Thornton (1999) developed key characteristic (KC) flowdown method to identify product KC, which then utilized to identify component and processes KCs. Thornton also developed a mathematical model to set priority of those KCs following two steps: identification and reaction. Unfortunately, in Thornton\'s model, no step in determining the bias and standard deviation target which will be used as a reference to calculate the total quality loss. Lamghabbar et. al. (2004) developed a mathematical model optimizing the value of component and process characteristics while minimizing the loss expectation of Taguchi Loss Function (TLF) and manufacturing cost. Unfortunately, Lamghabbar\'s model do not discuss the identification stage resulting the lack of total quality loss. The main goal of this research is to enhance the Thornton\'s KC flowdown by incorporating Lamghabbar\'s optimization model and Thornton\'s mathematical model for setting the priority of selected KCs at product, component and process level. Modifications of Lamghabbar\'s model are made due to the specific product selected as an implementation model. The priority setting of those selected key characteristics based on the KC cost percentage. The model development consists of identification, optimization of component and process characteristics and reaction phases. Software LINGO 8.0 is utilized to find the optimal standard deviations and tolerances. The optimal solution is then used to list the percentage of KC cost as a basis for the KC process control priority setup. The priority setting is conducted by using the pareto diagram. In this research, a vise is used as an implementation model. The results established an enhanced Thornton\'s KC flowdown which consists of identification, optimization of component and process characteristics and reaction stages. The model optimize the process characteristics and tolerances simultaneosly which is used as a basis in setting the priority of the KC. The priority setting is based on the percentage of the KC cost. Sensitivity analysis shows that the the level one of KCs are sensitive to the change of the parameter value of Cp while the second level of KC is not sensitive to the change of the Cp.