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Six-Sigma Quality and Application of Lean Management Tools

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Six-Sigma Quality and Application of Lean Management Tools
Six-Sigma refers to the philosophy and methods companies such as Toyota use to improve manufacturing processes and eliminate product defects. Besides, there are seven wastes found in manufacturing that provides information on how managers can reduce or eliminate waste in order to become a lean organization. For instance, Toyota Company makes use of lean production and supply to improve their productivity and profitability. Above all, by implementing Six-Sigma philosophy and methodology such as DMAIC, Cause-and-Effect Diagram and Visual Management tools, Toyota is able to aid in the continuous improvement of its processes.
Similarly, Six-Sigma helps Toyota’s processes to meet specifications and reduce variability in the assembly processes. Also, Toyota has its focus on continuous processes improvement to achieve efficiency and make cars at the lowest possible cost. As a result, process capabilities and customer needs are met, and Toyota is able to give its customers a better car at a lower price. Additionally, in order to reduce automobile variation and defects, Toyota makes continuous use of quality training programs to efficiently direct employees in daily assembly tasks.
Equally important, the DMAIC (Define, Measure, Analyze, Improve and Control) process is the perfect Six-Sigma statistical tool to solve defect, variability, and capability issues. For instance, a recall due to a fire within Toyota assembly plant has caused only 50% of their weekly inventory to be produced. Consequently, to make up for the failure, Toyota utilized the DMAIC process approach, among other Six-Sigma processes, to drive defects produced by all processes down into parts per million levels of performance. By measuring defects per million, Toyota managers were able to describe the performance of a process in terms of its variability.
By implementing DMAIC, Toyota’s lean management team organized to brainstorm and define what was abnormal within the manufacturing processes that led

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