# Efficiency Analysis of Manufacturing Line with Industrial Robots and Human Operators
## 6 Simulation Experiments  
In order to test the productivity and stability of the models of the manufacturing line, some simulation experiments were performed. The simulation scenario includes work in three shifts per day, 48 weeks per year (5760 h). Because of the change of production plans of some parts from the parts family and tools wear, a complete changeover of machine equipment is required once a week. Therefore, the simulation scenario includes one whole shift for machine changeover and preparing the line for production for 5 working days (simulation of 120 h with 8 h warm-up). After 5 days of work, the line is completely stopped for a weekend and in the next week a new warmup is required. Available work time is reduced by cleaning and calibration of the machines (15 min per shift) and a rest pause for the operators (15 min per shift) and is equal to 465 min per shift for the robotic line, and 450 min for the human-operated line. The results from the first part of the experiments are presented in the Table 2.  
The value of the production limit (PL) describes the production volume that can be obtained in a given time under ideal conditions. The average production _Pavg_ is the production of good quality products obtained from simulation experiments. Since the model was built based on the _OEE_ components and contains parameters of availability, performance and quality, then according to Equation (9), the production value from the simulation can be directly used to calculate the _OFE_ metric. Figure 6: Model of robotic line. \[OFE=\frac{Average\ production}{Production\ limit} \tag{10}\]  
Reliability and failures can have a significant effect on the productivity, therefore the second part of the simulation experiment was performed with the reliability of human operators and robots included. Reliability of machines was not considered because it will be the same in both examples. Assuming human unreliability on the basis of HEART (human error assessment and reduction technique) for \"routine and highly practiced rapid tasks involving a relatively low level of skill\", the nominal value of a human error equals 0.01 [50]. Therefore, the human error rate in this case can be described by parameters: \(MTBFh\) = 8 h and \(MTTRh\) = 5 min. Robot reliability was assumed based on data from industry survey [4] including \(MTBFr\) = 1000 h and \(MTBFr\) = 8 h. It was assumed that sick and absent operators can be replaced, but fallible robots require repairing. The results from the second part of experiments are presented in Table 3. The scenario parameters include: 8 hours warmup per week, human \(MTBFh\) = 8 h and \(MTTRh\) = 5 min, robot \(MTBFr\) = 1000 h and \(MTTRr\) = 8 h, (with exponential distribution). Results obtained show a much greater production value for the robotic line (about 30% more) compared to the human operated line. The summarized effect of failures is very small but significant. The comparison of the results is presented in Table 4. There is an average difference \(\Delta agg\) of about 0.2% for human operators (\(\Delta OFEh\) with only short time failures) and about 0.8% for robots (\(\Delta OFEr\) with long time failures).