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Evolutionary Operation experiment: EVOP is SPC technique is used for industrial settings to improve the system performance- optimizing – operation conditions. The method is helping to us making incremental changes of system input variables and Impacting on output. Again monitoring the output, and then select best combination of variables to get best output. The process is repeated process on based on real time, with the goal of continuously improving the system's performance. Implementing an Evolutionary Operation experiment Method 1. Define the problem: Clearly define the problem that for solution. This required process or system optimize and identifying the objectives and constraints 2. Identify the factors: Identify the factors that affect the performance of the process or system. Example process parameters, machine setting, raw material specification, Parts specification etc. 3. Define the experimental design: The experiment should be designed in such a way that it can show the main effects of the factors and any interactions between the factors 4. After that we need to carry out experiment. This will involve running the process or system under different combinations of the factors and measuring the performance. 5. After the experiment is completed, we need to analyse, which factor have maximum impact on performance of the process or system. 6. Optimize the process: Based on the results of the analysis, we can implement required change for best process or system to optimize its performance. Example Part specification / tolerance, RM change/ machine parameter 7. Verify the results: After required changes – need to verify result of process/ system. Advantages: 1. EVOP - Identifying and reducing the variability in the process, resulting in improved process efficiency. 2. Can be implement without using complex machine/ software 3. Cost effective solution for process optimization as compare to other approach 4. EVOP- Output- High Quality product 5. EVOP process gives quick result for process optimization. Disadvantages: 1. The EVOP lengthy process. if the process has multiple input variables than process requires multiple iterations 2. EVOP Limited used : it is suitable to improving a single process, and it may not be effective for complex systems with interdependent processes. 3. Process complexity: EVOP not sutable for complex process 4. Limited applicability: EVOP may not be effective for processes with low variability. 5. Limited precision: EVOP may not provide precise results as it relies on trial and error testing, and the optimal solution may not be reached. Evolutionary Operation example Appliance Manufacturing Example Issue: 10% of machine is rejected due to clamping Pressure and line speed >>As per mgf process process – we find out there are 2 process parameter which are more critical for Process rejection Clamping Pressure Kg/cm2 & Line Speed cm/sec. Let us take trial run 1,2,3 as per below table and % rejection of each trial >>Trial 4th condition will be: 3rd Trail+2nd trail – 1st trial. Then Pressure will be 10.4 and time 60sec and rejection rate 6% >>by similar method - Trial 5th , 6 & 7th trial result are here Finally we got best conditions are Clamping Pressure 10.7 Kg/cm2 & Line Speed 40 cm/sec & 0.1% rejection.