Model for decision making in implementing process improvement
| dc.contributor.author | Low, Shye Nee | |
| dc.date.accessioned | 2016-11-02T02:51:43Z | |
| dc.date.available | 2016-11-02T02:51:43Z | |
| dc.date.issued | 2014-08 | |
| dc.description.abstract | Industries, especially the manufacturing industry, must respond quickly and efficiently to customer needs and to be market competitive. In response to the advanced rapid changes in the market, the industries needed to continuously refine their operational processes to reduce waste in production department. The process of selecting a solution to solve problems from a set of alternatives is critical in determining the success or failure of process improvement. Hence, an effective improvement model should be considered in introducing improvements in production through a structure solution selection process. However, prioritization and selection in focus areas and improvement measures were ignored in previous improvement models. Based on the literature study, five design requirements of model development had been found for supporting the solution selection. By fulfilling the design requirements, a new improvement model, called as Improvement Process Selection (IPS) model was developed in three stages: identification, prediction, and selection, which used to facilitate decision making regarding the selection of the best improvement solution in process improvement. The identification stage used the modified quality deployment function, the prediction stage used the integration design of experiments with discrete event simulation, and the selection stage involved multiple criteria decision making with statistical analysis. The IPS model was systematically built by incorporating those suitable tools required with aspects of stage-by-stage decision criteria to improve solution selection. The IPS model was then verified and validated in total six different case study environments to achieve respective process improvement goals. The model successfully achieved the desired results of the case studies, such as reduced costs, increased operator utilization, fewer assigned operators, and shortened production time. For example, 20% reduction of set up time in Case study (CS) 1, 16% increment of line efficiency in CS 2; 40% saving of the total number of operators in CS 3, 21 % increment of line balance rate in CS 4; 11% reduction of the total production time in CS 5 and cost saving of RM 134,400 in CS6. Validation of the real-life case studies enabled the tailoring of the structure of the decision-making process used in the model to the effective selection of process improvement in a company, which for different improvement areas related to man, machine and method issues. Therefore, the IPS model enables the comprehensive analysis of improvement solution alternatives by considering multiple performance metrics to select the best improvement solutions. | en_US |
| dc.identifier.uri | http://hdl.handle.net/123456789/2957 | |
| dc.subject | Manufacturing industry must respond quickly and efficiently | en_US |
| dc.subject | to customer needs and to be market competitive | en_US |
| dc.title | Model for decision making in implementing process improvement | en_US |
| dc.type | Thesis | en_US |
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