Assessing Shop Floor Layouts in the Context of Process Plans

Results for each layout

In order to facilitate the understanding of the results, a summary is presented in Table 8 , which shows the relationship between each control factor and the response variables for each of the three layouts. It should be mentioned that the analysis of statistical significance was done by using ANOVA. The "s" was used to represent the statistical significance between the control factor and the response variable, while "ns" illustrates the non-existence of statistical significance. In both cases the level of significance was 0.05.

Table 8 Comparison between control factors and response variables for each layout.

		Responsable Variables
		Final Time (h)			Throughput (parts/h)			WIP (parts)			Resource Utilization (%)			Waiting Total Time (h)			Lead Time (h)
Control Factors		JS	TC	VC	JS	TC	VC	JS	TC	VC	JS	TC	VC	JS	TC	VC	JS	TC	VC
Features per part		s	s	s	s	s	s	s	s	s	s	ns	s	s	s	s	s	s	s
Duplicated features		s	s	s	s	s	s	ns	ns	ns	s	s	s	s	s	s	s	s	s
Batch size		s	s	s	s	s	s	s	s	s	s	s	s	s	s	s	s	s	s
Type of demand		ns	ns	ns	ns	s	s	ns	s	ns	s	ns	ns	ns	s	ns	ns	s	ns
Type of plan		ns	ns	ns	ns	ns	s	ns	ns	s	s	s	s	ns	ns	ns	ns	ns	ns
Simulated batches		s	s	s	s	s	s	s	s	s	s	s	s	s	s	s	s	s	s
Arrived time		s	ns	s	s	s	s	s	s	s	s	s	s	s	s	s	s	s	s
Maintenance		ns	ns	ns	ns	ns	ns	ns	ns	s	s	s	s	ns	ns	ns	ns	ns	ns
JS – job shop layout; TC – Traditional Cell layout						s – with statistical significance

For the final time response variable (h), the job shop and virtual cell layouts had very similar behavior. They differ from the traditional cell layout in the demand type factor, where the job shop and the virtual cell have a slight increase in the final time when the type of demand is controlled. On the other hand, in the traditional cell layout the final time decreases when the type of demand is controlled, which is in line with the results obtained with traditional cells. However, the average value of the total time for the traditional cell layout was 5000h, while the average value of the total time for the virtual cell layout was 4,000 h, a significant difference.

For the throughput variable (parts/h), the three layouts had similar behaviors. However, the average value of throughput found for the virtual cell layout was better than the traditional cell layout. This is due to the complexity of batches of parts, showing that the virtual cell layout presents greater flexibility. The variable average work in process (parts) presents as key control factor among the three layouts the type of demand, once again evidencing that the formation of the cells dedicated to the type of demand is important. However, the average value of the work in process for the virtual cell layout was smaller than the traditional cell layout. It is noticed that despite the large variation in the demand type, the behavior of the virtual cell layout was more flexible.

For the variable utilization of resources (%), the virtual cell layout had a performance around 5% to 10% higher than the traditional cell layout for some factors. The virtual cell layout had a slight gain in the factor arrival time between batches. That is, the job shop layout had a smaller variation when the level of this factor increased.

As for the factor type of demand, the virtual cell layout proved to be better than the job shop and the traditional cell layout. That is, it was more efficient when the level of this factor was changed, showing that the virtual cell layout really can present the virtues of the other two layouts.

It should be noticed the increase in resource utilization when the systems were managed with a maintenance plan, which left the machines always available. This shows that maintenance is a very important factor for production systems.

The response variable total waiting time (hours) also had different results for the three layouts. The virtual cell layout had an average value of waiting time lower than the other two layouts.

Finally, for the variable lead time, which corresponds to the total time for moving from the entry of the raw material to the finished product, it presented very similar results for the three models. The virtual cell layout underwent fewer variations when the levels of each factor were changed. This shows that this type of layout has greater robustness when variations in some factors take place.