DMAIC is a method focused on data quality used in process improvement. It is an essential part of the Six Sigma initiative. Still, it may typically be implemented as a stand-alone form of quality assurance or as part of other projects for process improvement. Camacho (2015) uses the DMAIC six sigma breakthrough methodology with the objective to reengineer the Guidewire Packaging Production process. DMAIC roadmap involves different phases used to improve a process from definition, measurement, analysis, improvement, to control phase. Team members at the Amplatz Super Stiff Guidewires project used the DMAIC model to save money, increase safety, and improve efficiency. The essay discusses some of the tools used in every DMAIC phase of the Amplatz project and their impact on cost and process capabilities.
Tools Used in DMAIC Phases
During the definition phase of DMAIC, the team used high-level process maps to determine areas that needed improvement. SIPOC diagram also summarized the inputs and outputs of different processes within the organization that was to be improved. A high-level process map revealed that the hooping, packaging, and boxing areas of the project were improved. The team used a work content graph during the measurement phase of DMAIC to determine the output of the process (Camacho, 2015). The work content graph also revealed the number of operators needed and the total amount of product transportation. To analyze the process, the team used a process simulation to determine optimal conditions for the process. Based on the potential simulation tool, the team identified a potential target of 4100 units per shift. The team believed that the optimal conditions would increase the site’s efficiency.
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The team used a contour plot and a Pareto chart to represent the data in the improvement phase. The contour plot helped redesign the boxing area to balance with the packaging work stations, reduce space, and be more economical (Camacho, 2015). Lastly, in the control phase, the team conducted a process validation to confirm the results obtained from the previous process. The team also conducted a dry run after completing the process validation activities.
Table 1: Summary of Tools
| DMIAC Phase | Tools Used |
| Define | High-level process map |
| Measure | Work content graph |
| Analyze | Process simulation |
| Improve | Contour plot and Pareto chart |
| Control | Process validation and dry run |
I do not find any tool redundant as they are used to address a specific problem in different DMAIC phases. I may use some other important tools such as customer service, measurement system analysis, and stakeholder analysis in order to complement the DMAIC phases (Park et al., 2020). Since there are different parties responsible for the project's success, the use of stakeholder analysis would assess the system and possible changes to it. It also analyses the relationship between the system and interested parties (Park et al., 2020; Smętkowska & Mrugalska, 2018). This tool ensures that the project plan addresses the interest of stakeholders. DMAIC reduced operational costs of the Mega Pack Blow-Up project, equivalent to an annual saving of about $114,600 (Camacho, 2015). Besides, the model also enhanced safety since the team could design and implement an automated band sealer machine. Material transportation was reduced to 120 feet from 258 feet, which enhanced efficiency, courtesy of DMAIC.
Conclusion
The case study reveals that DMAIC can improve the Guidewire Packaging production process by reducing transportation of materials, reducing direct labor to eliminate some activities that do not add value to the company. The model also eliminates redundant activities, which optimizes inspections and process flow. DMAIC enhances the efficiency of the process by eliminating unnecessary operations; thereby, streamlining the underlying processes. Therefore, it left an opportunity to install new workstations, which includes the installation of a mechanical carousel.
References
Camacho, D. C. (2015). Mega Pack Line Blow-Up: DMAIC Roadmap Leads Boston Scientific Heredia to Reengineer Packaging Lines.
Park, S. H., Dahlgaard-Park, S. M., & Kim, D. C. (2020). New Paradigm of Lean Six Sigma in the 4th industrial revolution era. Quality Innovation Prosperity , 24 (1), 1-16. https://doi.org/10.12776/qip.v24i1.1430
Smętkowska, M., & Mrugalska, B. (2018). Using Six Sigma DMAIC to improve the quality of the production process: a case study. Procedia-Social and Behavioral Sciences , 238 , 590-596. https://doi.org/10.1016/j.sbspro.2018.04.039
