Needs revision and correction
Process Evaluation Process evaluation is a crucial part of project management which basically emphases on the project’s implementation process and tries to evaluate how successfully the project followed the designed strategy which is planned in the logic model. The main steps involved in the process evaluation are-Description of the intervention, defining the acceptable features of delivery, formulation of related questions, determination of project methodology, planning of the required resources and finalisation of the project management plan..It can be performed by different methods like using the lean concept that provides the suitable ways to eliminate the waste and helps in the improvement of the process or by the use of SPC or Six Sigma method to decrease the defects or variances generated in the process. Executive summary: In this competency, I am taking the example of a drug manufacturing company which is producing the drugs against bacterial infections. Here, I am discussing the process strategy of his company and perform its process evaluation by Six Sigma method to reduce defects or variances in the process. Six sigma methods are selected here because it improves the organization’s performance by its statistical, data-driven and problem-solving method. Let’s begin with the process strategy of the pharmaceutical company- The Company X is producing antibiotics using the same raw material and machines for 30 days but the quantity of drugs produced each day vary from each other as shown in the table below, which is turn affects the company’s productivity and lowers the yield. Table 1: Drug production by Company X before optimization by six sigma method Days Number of drugs produced 1 117 2 123 3 119 4 94 5 125 6 120 7 121 8 127 9 146 10 120 11 113 12 121 13 143 14 118 15 121 16 120 17 92 18 128 19 114 20 95 21 120 22 150 23 121 24 112 25 149 26 144 27 120 28 142 29 110 30 139 From this table, this is clear that even after utilizing the same material there is significant difference in the number of drugs produced per day i.e., there are faults in the process strategy due to which the production and yield of drugs varies. To improve the per day productivity and reduction of wastage of raw material, we uses here the six sigma methodology . The Six Sigma method uses a defined sequence of steps – DMAIC steps which are Define, Measure, Analyse, Improve, and Control and improves the process strategy. This method statistically analyse the existing process steps and determines exactly which process elements need the improvement. Later, new alternatives were developed for improvement, select and implemented as shown below: · In the first step define- the problem of six sigma method here , the problem was defined as the non-uniform production of drugs each day. · In the second step measure- by performing the statistical analysis the variation among each days and average productivity was assessed as shown below with the help of statistical calculation and control chart. Figure1: Control chart for drug production before applying the six sigma method The curve here is very irregular which means there is a significant difference in drug production at each day while using the same raw material and machines. And by statistical evaluation we find that the average or mean production is 122.8 drugs per day with the lower limit of 107.67, upper limit of 137.92 and very high standard deviation of 15.12. This shows that lots of raw material and manpower is wasting on those days when less number of drugs are produced. · In the third step analyse- the different parameters used for the drug production each day like machine temperature, rotation, mixing characters, input of raw materials, process holding time and operational characteristics were assessed and check for related variations each day. · In the fourth step improve - when the parameters that are causing the variations or the operational errors identified then different strategies to improve them were designed like using same operational parameters and material inputs each day etc. · In the fifth step – These new parameters were implemented and the faults were corrected to achieve the uniform production. The drug production data of Company X by implementing the Six sigma methodology is as follows: Table 2: Drug production by Company X after optimization by six sigma method Days Data 1 135 2 136 3 135 4 134 5 135 6 136 7 134 8 136 9 134 10 135 11 135 12 135 13 134 14 134 15 133 16 135 17 134 18 135 19 134 20 134 21 135 22 135 23 134 24 135 25 134 26 135 27 134 28 135 29 135 30 134 From this table, this is clear that after optimization of six sigma method there is uniformity in the number of drugs produced per day and the wastage is reduced. By statistical evaluation we find that the average or mean production is 134.63 drugs per day with the lower limit of 133.9, upper limit of 139.5 and very low standard deviation of 0.7. The process evaluation parameters are calculated as shown below: 1. Coefficient of variation = STD/mean=0.00533594 2. Process capability ration, Cp = UCL-LCL/6*STD = 1.436790805 = 0.333333333 3. Process capability index, CPk = Minimum of (UCL-mean)/3*STD, (mean-LCL)/3*STD)=0.718 =0.33, 0.718,0.33 4. Minimum of (0.33, 0.33) = 0.33 here, cp is equal to Cpk means process is centered at midpoint of the data and same value of Cp and Cpk also denotes the same tolerance range and process range as shown in the control chart Figure2: Control chart for drug production after applying the six sigma method 2. Summary of the Evaluation of Control Chart and Process metrics based on SPC In control chart most points are near the average and few points are near the control limits or beyond, it shows the process is centred in the middle and optimized. 3. Summary of evaluation and explanation about whether the process would benefit from the use of Six Sigma methods Results shows that use of six sigma can improved the process and bring most of the points near the average and therefore provides the uniform production of each day, increases the yield and minimize the waste of raw materials and power consumption. Description of the SPC project and recommendations for improvement The statistical process control or SPC tools and its statistical procedures when applied in this process helps us in identifying the errors incorporated during the operational parameters and provides the solution of that which when implemented on the real time basis our production methodology was improved and we achieve high yield and uniform productivity. Therefore, six sigma methods provide the solutions for potential production and the SPC tools are highly recommendations for project improvement. Control Chart Data123456789101112131415161718192021222324252627282930117123119941251201211271461201131211431181211209212811495120150121112149144120142110139 Sheet1 DaysData 1117 2123calculation: 3119Coefficient of variation = STD/mean0.1231361579 494Process capability ration, Cp = UCL-LCL/6*STD30.24224038410.3333333333 5125 6120 7121 8127 9146 10120 11113 12121 13143 14118 15121 16120 1792 18128 19114 2095 21120 22150 23121 24112 25149 26144 27120 28142 29110 30139 122.8Average or mean (B2:B31) 15.121120192Stdev S (B2:B31) 45.36336057613*STD 107.678879808LCL 137.921120192UCL 90.72672115226*STD Data Mean LCL UCL Control Chart Data123456789101112131415161718192021222324252627282930117123119941251201211271461201131211431181211209212811495120150121112149144120142110139 Sheet2 DaysData 1135 2136calculation: 3135Coefficient of variation = STD/mean0.0053359401 4134Process capability ration, Cp = UCL-LCL/6*STD1.43679080460.3333333333 5135Process capability index, CPk = Minimum of (UCL-mean)/3*STD, (mean-LCL)/3*STD)0.71839540230.33333333330.71839540230.3333333333 6136minimum of (0.33, 0.33) = 0.33 7134here cp is equal to CPk means process is centered at midpoint of the data. 8136 9134same value of Cp and Cpk also denotes the same tolerance range and process range. 10135 11135 12135 13134 14134In control chart most points are near the average 15133Few points are near the contol limits or beyond 16135 17134 18135It shows process is centered in the middle 19134 20134it shows that use of six sigma can imporoved the process and bring most of the points near the average. 21135 22135 23134 24135 25134 26135 27134 28135 29135 30134 134.6333333333Average or mean (B2:B31) 0.7183954023Stdev S (B2:B31) 2.15518620693*STD 133.914937931LCL 135.3517287356UCL 4.31037241376*STD Data Mean LCL UCL Control chart Drug Production Vs. Days Data123456789101112131415161718192021222324252627282930135136135134135136134136134135135135134134133135134135134134135135134135134135134135135134