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# Programmable Logic Controller Lab Report

 ✅ Paper Type: Free Essay ✅ Subject: Engineering ✅ Wordcount: 2433 words ✅ Published: 8th Feb 2020

1. Introduction

A Programmable Logic Controller (PLC) is a microprocessor-based controller, similar to an Arduino, which uses a programmable memory to store instruction for counting, sequencing, and timers. “Programmable Logic Controllers are commonly used in industrial applications for process automation, event recording, and safety equipment monitoring” [1]. PLCs are also widely used because they can do more than just receive system inputs. They also can display system outputs and communicate with HMIs during a test cycle. A Human Machine Interface, commonly referred to as an HMI, allow for humans to be able to interact with the PLC. HMIs enable the user to monitor the status of the system and help in controlling the operations of the system.  The benefits to using a PLC/HMI combination is they are able to replace “thousands of individual relays, cam timers, and drum sequencers” [1], PLCs are also reprogrammable and therefore are able to be used with multiple different machines and different processes.

In this lab, a new control process is needed so that a total of 2700 cycles of a program could be run over the course of a 24-hour period. The process required a SIMATIC S7-1200 PLC and HMI to be used to make a DC motor perform 10 revolutions per cycle and calculate the time it required to do so. To program the PLC, a ladder logic program was created to tell the machine to perform each cycle. Statistical analysis was performed to calculate with 99% confidence level that 2700 cycles would be performed in 24 hours.

1. Methods
1. Programming

PLCs can communicate with systems through ladder logic, which allows for a set amount of inputs to be converted into outputs using rungs which contains logic operators, timers and counters [1]. Shown below, in Figure 1, is a ladder logic which was created to achieve the desired outcome of the new control process. The new control process calls for a system process which, “initially takes 10 seconds to warm up and should display a green light… [this process] must be initiated by pressing a button on the HMI screen… [After the warm up] a yellow light should then inform the operator the system is ready… [so the operator can] press a button to start the operation of the DC motor” [1]. The new process also called for an emergency stop which is to be put into place so that the DC motor would stop immediately upon the emergency stop button being pressed.

Figure 1: Ladder Logic for New Process

In the above ladder logic, the first three rungs of the ladder are the “warm-up” process. The first rung is composed of a normally open contact which is denoted with two parallel blue bars and a set coil, represented with parentheses and an “S”. This line is activated when the start button is pressed and then moves to the set coil which acts as a latch, keeping the warm up button pressed until another button is pressed. When the set coil is activated in the first rung, it turns on the timer which counts to ten seconds. When the timer is initiated, the green light comes on which is showed via the third line. Once ten seconds is reached, the yellow light turns on through a general coil operator, denoted by the set of parentheses located in rung 4. The fifth rung acts similar to the first rung, in which the start button for the motor is pressed and then stays pressed via the set coil. On the sixth and seventh rung, the DC motor and sensor are started along with a counter, which is used to count 10 rotations of the DC motor. Once ten rotations are met, the motor automatically cuts off. The eighth and ninth rung programs for the emergency stop, which resets the timer, warm up button, and the counter, when pressed. This process also resets the emergency stop button, as well. Resets are performed in ladder logic through a reset coil and are denoted by the parentheses with an “R” in the middle.

2.2  Test Plan

2.2.1        Parameter Design

A test plan is a document that discusses the objectives of a test by laying specific parameters, tolerances, and data reduction methods. In this experiment, a test plan was created to outline the process used to obtain the time it took for 2700 cycles to occur. The first step in creating a test plan is to outline the specific parameters of the experiment. During this simulation, the independent variable is the reaction time of each worker. Therefore, the dependent variable will be the time it takes to complete one cycle of the test. Some constants also outlined in the test plan were the ladder logic code, DC motor with a photoelectric sensor, PLC, and HMI, and the timer for each cycle.

2.2.2        System and Tolerance Design

The next section of the test plan outlined the system and what tolerances would be allowed. The test plan considered that there would be three different shifts during the day, each shift having a different operator with different reaction time. The design plan also considered that an employee would be performing the operation for close to 8 hours and would most likely not be pressing the button immediately due to outside distractions or fatigue. Furthermore, often machines and parts breakdown or malfunctions causing production time to increase.

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To emulate an industrial setting, there were three separate test subjects, representing the three different shifts and a set timer. During each “shift,” the test subject performed 20 different cycles. The test plan also outlined that there would be a 30-minute break during each shift and accounted for 10 minutes between each shift to represent a reset which might occur in an industrial setting.  To account for the extra time to perform a cycle due to distractions, the buttons on the HMI were pressed somewhat leisurely to start each test. To represent a malfunction during the shift, an emergency shut down occurred at least two times during each “shift” the test subject performed. This allowed the time to perform a cycle as accurate as possible.

2.2.3        Data Reduction

The final step in creating a test plan is to figure out how data is going to be analyzed and the user to draw a conclusion. In this lab, the time for each cycle to occur was averaged to together (3.1) so that the standard deviation (3.2) could be found. Once the standard deviation was found, a probability density function (3.3)  was created such that the time that would be needed to complete a cycle would occur at a 99% confidence. The time to complete a cycle was recorded in minutes and then applied to the information to show how many cycles would occur each day.

1. Statistics and Analysis

Once all 60 trials were run, the mean time for a cycle to occur was calculated using the equation:

$\stackrel{̅}{x}=\frac{\sum _{i=0}^{n}{x}_{i}}{n}$

(3.1)

and then used to find the standard deviation of the data points. The equation used to find the standard deviation is:

(3.2)

In the above equation Sxrepresents standard deviation, N is the total number of data points used, xiis an individual data point, and $\stackrel{̅}{x}$

is mean time for a cycle to occur.

Once the standard deviation is found, the calculation to find the value of the number of cycles such that 99% of the cycles are less than the cycle time found is [1]:

(3.3)

Where PDF stands for probability density function,

represents the average time to complete a cycle and Sxis the standard deviation which was found using equation (1).  This calculates the time for 99% of all trials to be calculated. To determine the number of cycles that can occur within the 99% confidence level the total work time has to be divided by the probability density function, shown by equation 2. The total work time, in seconds, was calculated using:

(3.4)

The 1.5 hours is for breaks, and the 30 minutes is for the time between the shifts. Once total work time is found, the number of cycles that can be completed at 99% confidence is found using:

(3.5)

Once all 60 trials were completed, the mean time to complete each trial was calculated to be 0.363 minutes, using Equation 1. After finding the mean, the standard deviation was found to be 0.0512 minutes, using Equation 2. The PDF was then found, using Equation 3, to be 0.516 minutes. It can be said with 99% confidence that all cycles run will be completed in 0.516 minutes or less. After finding the PDF, the number of cycles completed in a 24-hour work day was able to be calculated with a 99% confidence, which is done using Equation 5 and was found to be 2556 cycles.

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At a 99% confidence, the amount of cycles that can be performed is 144 less than the process requirements. One way to increase total production would be to decrease the time between shifts, in the current model there are 30 minutes built in for a shift change, 10 minutes between each shift.  If shift change occurred more efficiently, it would keep total work time at the factory reasonable at 22.5 hours a day, since this time includes breaks and emergency shutdowns were already averaged into the mean time to complete a cycle. With the time between shifts being minimized, it would allow for the needed 2700 cycles to be performed as needed. Also, if the machines were to run without malfunction, the number of cycles that would be able to be performed would be close to 3500 cycles, which is well over the needed cycles for the new process.

1. Conclusion

The application of the PLC and the new test process is an accurate example of a real-world industrial setting and tests that might go along with implementing new procedures.  The calculation for the probability density function to find the cycle time for 99% of all cycle time allowed for the average cycle time to be applied which allowed for revision of the test plan to occur. With the advances in technology, the application of PLCs and HMIs are becoming more relevant. This equipment allows for communication between humans and machines to occur with ease and help in promoting new processes into the industrial setting.

References

1)     Todd Schweisinger and Beau Pollard. ME 2220 – Mechanical Engineering Lab 1 Student Manual. Clemson University. 2018.

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