RTP Industries - Term Paper Example

Summary RTP Industries is a leading international brand recognized for manufacturing steel and aluminum products. Due to severe competition in the industry, the company has adopted a differentiation strategy by focusing on innovation. The company employs a Total Quality Management approach to ensure that its products are meeting the standards. Due to recent customer complaints about hydraulic leakages, the company used a statistical process analysis to study that whether its size of diameters and the number of surface errors in steel rods are within control. The analysis revealed that the sizes of diameters of steel rods are out of control therefore they are the root cause of the problem Table of Contents Introduction & Problem Description: 2 Methodology: 3 Results: 4 Three (3) Sigma control: 4 Discussion and recommendations: 7 Conclusion: 7 Bibliography: 8 Introduction & Problem Description: RTP Industries is a leading international brand recognized for manufacturing steel and aluminum products. Recently, it has faced severe competition from the low cost manufacturers in China and India. The company has chosen a differentiation strategy by innovating new products in order to compete with its competitors. For implementing this vision, the company has formed a research and development department which has been able to develop six new products for the market. To ensure consistent quality within the new products, the company has started a company-wide quality and efficiency improvement plan. The aim of this plan was to satisfy the needs of the customer in a better way. Few of the customers have been complaining about leakages in hydraulic products. To identify the issue, the company employed a quality management tool known as Statistical Process Control which measured the performance of the manufacturing process against the set standards. Methodology: The company believed that the leakages in its hydraulic products were due to the size of steel rods and its surface quality. To control the process, a quality manager was assigned who conducted an analysis using the Statistical Process Control Tool. He gathered two types of data daily for a sample of three steel rods for 25 days. The data contains information about The diameter of the selected steel rods was measured and recorded in centimeters over a 25 day period. The number of surface errors in the selected steel rods was calculated and recorded over a 25 day period. Results: The quality manager collected two different types of data given. The data regarding diameters of the steel rods are continuous variables as they can take any values therefore we will use an x chart as a statistical process control tool to monitor the data. The second type of data contains information about number of surface errors in each steel rod. This set of data contains information about attributes as there could be either a surface error or not and furthermore since there could be more than one surface error therefore we will use a c-chart for statistical process control analysis. We will use the number of errors per day as a measure for drawing the c-chart. Three (3) Sigma control: Diameters of rods: The x charts have an Upper Control Limit and Lower Control Limit which can be defined as Upper Control Limit = UCLx= X’’ + zSx Lower Control Limit = LCLx= X’’ - zSx Where, X’’ = sample of all the means Sx = Standard error = S / n1/2 S = Standard deviation of the sample = n = sample size z = number of standard deviations away from the mean X = 10.58 S = 0.20 n = 25 The data for all the values are calculated in the excel using the built-in formulas. By inputting the data into excel sheet we find that Sx = 0.20 / 5 Sx = 0.04 To identify the 3 sigma control process, we input z = 3 UCLx= 10.58 + 3(0.04) = 10.70 LCLx= 10.58 + 3(0.04) = 10.46 Figure 1: X chart for the diameters of steel rods The figure shows that the process is out of control since there are 7 observations of daily sample which are lying outside the control limits. Number of surface errors: The upper and lower control limits for surface errors can be derived by c-chart Upper Control Limit = UCLx= c’’ + z(c’’)1/2 Lower Control Limit = LCLx= c’’ - z(c’’)1/2 c’’ = Mean number of daily surface errors c’’ = 0.453 UCLx= 0.45 + 3(0.45)1/2 UCLx= 2.46 LCLx= 0.45 - 3(0.45)1/2 LCLx= 0 Figure 1: C chart for the surface errors in steel rods From the above graph we find that none of the sample is out of control as all of the figures lie within the control limits. Discussion and recommendations: The above statistical process control analysis about two different kinds of data have revealed important information about which of the processes is under control. The data about the diameters of the rods showed that they are out of control therefore they can be the main cause of leakages in the hydraulic products. To improve the quality of its product and reduce customer complaints about leakages we recommend the following suggestions. The diameters of the rods have significant discrepancies and it can be inferred that the variations in the diameters of the rods can be due to some assignable reasons or specific causes. To find the assignable reasons, it is recommended that the company should use a cause and effect diagram to study the cause of the problem. The whole process of making steel rods should be thoroughly studied and the quality manager should inspect every possible aspect from any the initiation (poor vendor selection to acquire raw materials) to the equipments that are being used in the manufacturing process. Conclusion: We can infer from the statistical control process analysis of the data that the size of the diameters are out of control. The reasons can be traced to some specific causes which are deteriorating the process of manufacturing steel rods. These causes should be quickly identified in order to get to grips with the problem as otherwise it will have serious consequences on companies profitability. Bibliography: Heizer, J. & Render, B. (2010). Operations Management. New York: Pearson Education Read More