Overview The Production Process at a Manufacturing Facility Research Paper

Introduction

The objective of this report is to review the production process at a manufacturing facility. The dataset considered in the report includes daily production characteristics of 116 presses recorded at the target manufacturing facility. The factors of interest for this analysis are production rates, identification of machines that need adjustment or maintenance, and identifying the expected down time. The report contains summaries of daily production records, comparison of official and actual production rates for three types of machines, analysis of data collection process and potential issues, followed by recommendations for the facility manager.

Summaries of daily production records

The majority of presses used are of type 3 (45.7%); there are 30.2% of type 2 machines, and only 24.1% of type 1 machines. Mean number of parts produced is 97610.26; however, the number of parts produced has a very high variance, which means that this characteristic should be reviewed separately for each machine type. The distribution of the number of parts produced is shown on Fig. 1. It is possible to see that type 1 machines belong to the right cluster of values, and type 2 and type 3 belong to the left cluster of values.

Figure 1. Distribution of the number of parts produced

Average number of operational hours is 5.78; it is notable that minimal number of operational hours is 0.58, while maximal number is 7.75. In other words, there were machines that did not work most of the time. Mean number of non-operational hours is 1.49, but it is important to note that while minimal value of non-operational hours was 0, maximal value was 7.17. This value clearly points out that there were almost non-functional machines that need maintenance or replacement.

For type 1 machines, mean number of parts produced is 259,627.54 with SD=58,444.89, mean hours of production time value is 6.77 with SD=1.38 and mean hours that the press was down value is 0.96 with SD=1.86. For type 2 machines, mean number of parts produced is 43,210.43 with SD=17,238.35, mean hours of production time value is 5.89 with SD=2.17 and mean hours that the press was down value is 1.86 with SD=2.17. For type 3 machines, mean number of parts produced is 47,940.64 with SD=24,976.66, mean hours of production time value is 5.18 with SD=2.42 and mean hours that the press was down value is 1.52 with SD=1.81.

It is possible to conclude that type 1 machines have high performance with medium variability, are very stable and most of them work during the whole day. High SD of hours that the press was down for these machines means that some of these machines need maintenance or adjustment. For type 2 machines, daily production rate is almost 6 times lower than for type 1 machines, production time is also lower and has notably higher SD, and the number of hours the press was down is quite high with a very high SD. Some type 2 machines seem to be unreliable and poorly operating; moreover, the performance and reliability of type 2 machines is low and should be reviewed. As for type 3 machines, their average daily production is highly compared to type 2 machines, but mean operational time is lower. It is notable that both average operational time and average non-operational time for type 3 machines is lower compared to type 2 machines. This might indicate at either shorter operational day for type 3 machines or data recording issues for some of these machines.

The machines that need replacement or maintenance can be identified visually by reviewing the distribution of the number of parts produced for every group of machines. Leftmost segments on fig. 2-4 demonstrate the classes of machines that are potential candidates for reviewing and fixing.

Figure 2. Distribution of the number of parts produced for type 1 machines

Figure 3. Distribution of the number of parts produced for type 2 machines

Figure 4. Distribution of the number of parts produced for type 3 machines

Dataset outliers

The dataset clearly has certain outliers and data with errors. This can be found by comparing the data for operational and non-operational hours. Particularly, very low operational time is for case numbers 7, 76, 99, 101 and 116. It is notable that the numbers of cases with highest non-operational hours are 7, 26, 29, 34 and 85. This means that cases 76, 99, 101 and 116 had either understated operational time or overstated non-operational time, and there are potential outliers and data distortions related to these mismatching data. Furthermore, there are clear outliers in the number of parts produced since there are unexpectedly high records for some type 2 and type 3 machines (e.g. cases 1, 22, 28, 9, 14, 2, 12). Therefore, it is necessary to remove outliers from data in order to have more precise analysis results.

Comparison of actual and official production rates

Official production rate for type 1 machines is 700 ppm, for type 2 machines is 200 ppm and for type 3 machines is 155 ppm. Using existing average values, it is possible to determine actual production rates in ppm. These rates can be calculated as average number of parts per day divided by average operational time multiplied by 60 minutes. Actual production rates are 639.46 ppm for type 1 machines, 122.26 ppm for type 2 machines and 154.19 ppm for type 3 machines. Therefore, actual production rates for type 1 machines are slightly lower compared to official rates, are as expected for type 3 machines and are significantly below official rates for type 2 machines.

For identifying statistical differences between actual and official ratings, it is necessary to make the following assumptions – the data for the sample were randomly selected and the ratings are normally distributed (since the number of machines of type 1 and type 2 does not exceed 50). Two-tailed t-test can be used for testing statistical significance of difference between actual and official ratings. Significance level is 0.05. T-test value for type 1 machine is -2.22, for type 2 machine is -9.43, for type 3 machine is -0.07; p-value for type 1 machine is 0.0171, for type 2 machine is 0 and for type 3 machine is 0.4722. This means that type 1 and type 2 machines have production rates significantly different from their official ratings.

Review of data collection process

The data collected in this study allow assessing the average performance of three types of machines, their average operational time and the time when machines were down. The dataset also allows to assess whether the machines perform according to their official specifications. However, the scope of analysis also implied analyzing the factors that reduce production rates and/or make machines inoperative. The process of recording time when the machines were down has two key issues. First of all, the reason of the machine being non-operational is not recorded. Secondly, non-operational time is recorded manually by workers, which means that it is not precise and is very vulnerable to human error (for example, if a worker forgets to mark this time or puts incorrect time, statistical results will be significantly affected). So, it is recommended to change the process of recording the hours of operation and non-operation automatically.

Conclusions and recommendations

In terms of performance and production speed, type 1 machines are performing slightly lower than expected, but these machines have good reliability and operational time. These machines are mostly efficient, yet it is necessary to review them as non-operational time for several type 1 machines is higher than expected. Type 3 machines have production speed characteristics according to their specification, but their operational time is low and non-operational time varies greatly, so type 3 machines with high non-operational times should be fixed. Type 2 machines have poorer reliability, their non-operational times are high and production speed is significantly lower than expected. It is necessary to review these machines and their functionality in general; it might be better to replace them with type 3 machines.

Furthermore, it is recommended to link machine performance with production costs and servicing costs. Since the company largely uses low-performing machines with varying operational time and performance, it is necessary to review the reasons of using predominantly such machines (type 2 and 3) and using only 24.1% of type 1 machines. For further analysis it is necessary to include economic variables into the data set.

 

 

Works Cited

Bryant, P. G., and Smith, M. A. (1998), Practical Data Analysis: Case Studies for Business Statistics (2nd ed.), New York: McGraw Hill.

The terms offer and acceptance. (2016, May 17). Retrieved from

[Accessed: March 28, 2024]

"The terms offer and acceptance." freeessays.club, 17 May 2016.

[Accessed: March 28, 2024]

freeessays.club (2016) The terms offer and acceptance [Online].
Available at:

[Accessed: March 28, 2024]

"The terms offer and acceptance." freeessays.club, 17 May 2016

[Accessed: March 28, 2024]

"The terms offer and acceptance." freeessays.club, 17 May 2016

[Accessed: March 28, 2024]

"The terms offer and acceptance." freeessays.club, 17 May 2016

[Accessed: March 28, 2024]

"The terms offer and acceptance." freeessays.club, 17 May 2016

[Accessed: March 28, 2024]
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