Chapter 2: RGA Case Studies

This chapter is dedicated to present some examples of using R4All platform to perform an RGA analysis.

2.1 Case Study 1: Electronical System Test

An electronical system was submitted to a testbench, and during this test several failures were reported. After each failure, the design of this item was improved after a series of continuous improvement. This test was interrupted at 6000 cycles.

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The test team wanted to know if the implemented changes on the project were effective, so they investigated the reliability growth of the system.

Note, to input the data for the reliability growth analysis is necessary to accumulate the time between failures.

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The parameters values are indicating that the applied redesign of this electronical system was effective, and the cumulative mean time between failures increased as the cumulative intensity of failures decreased.

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In the analysis results shown, the demonstrated mean time between failure is 355 cycles and the growth rate is about 0.4732. Now, let’s say that the reliability goal of this test was to have a 500-cycle as MTBF. If so, this electronical system is still not meeting the design requirements, and thus it must go through more redesigns and tests.

 2.2 Case Study 2: Combine Harvesters

A company is designing a new combine model harvester vehicle, and so six prototypes were made and are running on a field as a sample test. Each one of these vehicles was dropped on different farms, but still the operating conditions are remarkably similar.

These vehicles did not start operating at the same time for a series of reasons, however with each failure reported, the entire sample received the same improvements; even those harvesters which were still not operating at all would get updated.

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Each vehicle will be treated as one system so that this reliability growth analysis can be made for the prototypes redesign. The analysis will then return the results for each individual harvester, as also will the result of the entire multiple system.

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As the designers wanted to evaluate the evolution of their prototypes’ reliability, it is also apparent in the analysis results that the updates applied to this sample of 6 vehicles already had a positive impact on the vehicle’s life cycle.

Considering that the goal of this test was to have a 350-hour MTBF, the changes are not enough for the releasing of this model to production.

For the desired DMTBF to be reached and considering that the growth rate and the parameters stay the same for the entirety of this test, the test must take an additional of 32,242 hours. The image below presents this calculation:

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2.3 Case Study 3: Shipping Company Fleet

A shipping company has a replacement policy based on its vehicles’ age. In this current policy, all trucks that reach 5 years of usage or 1,200,000 Km run must be replaced by a new truck.

To optimize its investments, this company wishes to analyze the optimum time to replacement based on the relation of cost x benefits. To evaluate this, it is required that the reliability of the vehicles be known. So, the management board investigated the maintenance histories to determine the optimum period of overhaul.

For this analysis, a sample of 5 cars was chosen.

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The current mileage reading in each truck, from 1 to 5, in that order: 510,000, 500,000, 495,000, 475,000 and 540,000.

It is known that the average repair cost of this car model in the last months was about $5,000, considering part costs and labor costs. The mean time to repair is about 8 hours and, when the truck is parked, it is also known that the profit losses are, in average, $1,000 per hour. A new truck costs $150,000.

The data for all five trucks need to be entered individually in the system data sheet (one per system).

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After analyzing the data, the ideal revision time can be calculated, since the beta parameter is greater than 1. This calculation is done by the RGA Calculator. See the image below:

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The optimum overhaul time calculated is about 623,000 kilometers.

2.4 Case Study 4: Selling a Personal Used Car

An engineer, who wants to sell his car so that he can buy himself a new model, but who is still not quite sure if it is the right time, decides to determine if it is the best time based on how much he is spending on his car’s maintenance cost. He checks the odometer and finds that his car has already run 48,000 km.

After checking his last car maintenance receipts, the average cost per repair is about $ 750, and the new car model he wants is valued at $ 24,990.

See below the car maintenance history in mileage.

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After using the R4All platform for a quick analysis, he determines that the optimum time for replacing his car is around 64,400 Km. See this calculation below:

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