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Quality Management And Productivity Simulation Essay

1491 words - 6 pages

Quality management determines and implements the quality policy of the organization (UOP, n.d.). The simulation ‘Quality Management and Productivity’ focused on the use of total quality management tools to analyze problems and resolve them short term. Furthermore, the simulation focused on designing a human resource program to promote quality culture in an organization in the long-term. “A well-implemented quality management policy reduces cost arising out of defects and waste” (UOP, n.d.). The simulation required an investigation of Seguro’s defect rates. This required the use of quality tools like Control Charts, Pareto Charts, and Cause and Effect Diagrams to analyze date given for the four processes of manufacturing of Seguro’s cabinets. Interpretation of the data correctly narrowed down the defective process area.Company OverviewEstablished in the 1980s, Seguro Corporation is a manufacturer of computer cabinets with current revenue of 25 million dollars. Despite of all the quality control processes in place, Seguro Corporation still has quality obstacles that company must resolve for their consumer to maintain high quality standards. CaseSys Inc. is one of Seguro’s leading customers. CaseSys Inc. accounts for 24 percent of Seguro’s total sales and has rejected a large shipment of cabinets because of non-conformance to specifications. The sudden surge that the company faces can affect the corporation reaching overall goals and objectives.Defective AreasThe four processes involved in the manufacture of Serguro’s computer cabinets are stamping, welding, riveting, and injection molding. The first challenges that the company faced was a high rework rate from the stamping process. The stamping process had allocated 351 million dollars in rework costs and was the number one contributor of the Total Cost of Quality within the process. Although, Welding showed special cause variation of the process by going out of control for three data points, the overall rework showed that stamping was a bigger factor in the process variation. The Control Chart for Stamping showed instances of the fraction of the defective rate exceeding the Upper Control Limit (UCL). Stamping also shown special cause variation in the process by showing two data points out of control. Between the periods of 13 and 18, there was a run of five points over the centerline, almost breaching the UCL. Although the Control Chart indicated Welding as the defective area, the Pareto Chart showed the rework cost much higher in Stamping. Analyzing all aspects of the processes, Stamping seemed to be a strong factor in the root cause and possibly effecting other process variations. Bringing down the defect rate along with maximizing cost savings in Stamping would be the effective solution.Cause and EffectOnce the identification of Stamping as the defective process area was completed, next was identifying the factors that cause and effect of the output...

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