Prepare input data
Last updated
Last updated
Before analyzing the methodology in detail, it is important to show the structure of the following explanation: first of all a general approach will be adopted, analysing the general templates of the input files, explaining all the single steps in order to fill in it; secondly a specific example will be proposed to show practically the execution of the described steps and to have a real case of application.
The input of the procedure will be as already said an Excel file, whose general model can be found by following the path (folders): PROCESSING TIME ESTIMATION - MOST - PYTHON CODE, with the name 'MOSTgen.xlsx'. To start the evaluation of a completely new process, it is necessary to 'copy and paste' this Excel file, that is the model, in the same folder where the python code will be run. It is advisable to change the name of the file with a name related to the process to be analysed, clear, univocal and without spaces. After this, it is possible to go into the details of this file, where there is only one sheet to be filled in: its name is 'MOST', and it contains many different sections including many different columns to be filled in, that can be analysed by considering 4 different sections. The first one is comprehensive of the first three columns of the table, as shown in Figure 6:
the first is named ID and it requires the ID of the activity considered, that has to be a univocal number, put in the order of execution, starting from 1 until a maximum of 100, that is the maximum number of activities that this toolkit can analyse in a single process;
the second column is for the NAME, that requires a complete, well identifying and univocal name of the activity considered (if one name is repeated twice, this means that the activities are exactly the same);
the third column, TYPE, is very important since it provides the selection of the section to which each single activity is related, like shown in the previous chapter: there are three options, 'G' for general move, 'T' for tool use and 'C' for controlled move; the choice can be done by selecting the letters in the drop down menu.
The next three sections to be explained are of course related to the main divisions of the methodology: so starting from Figure 7 it can be seen the general move sequence model table;
First of all the lines of this section have to be completed only if the Type Code of the considered activity row is 'G': if it is different, the respective line must be left blank, without selecting any code from the drop down menu. If instead it has to be filled in, the assessor needs to insert the right number (1-3-6-10-16) of the list by looking at the MOST table seen before and reported hereafter (Figure 2), one for each column, correspondent to the different subactivities: if one subactivity is evaluated as not necessary for that specific action, the number 0 has to be selected in the cell.
The next section of the table, as shown in Figure 8, is related to the tool use sequence model:
First of all the lines of this section have to be completed only if the Type Code of the considered activity row is 'T': if it is different, the respective line must be left blank, without selecting any code from the drop down menu. If instead it has to be filled in, a distinction has to be done between two different group of letters:
for what regards the columns A, B, G and P the assessor needs to insert the right number in the list 1-3-6-10-16, by looking at the MOST table about the general move shown above (Figure 2), one for each column, correspondent to the different subactivities: if one subactivity is evaluated as not necessary for that specific action, the number 0 has to be selected in the cell;
for what regards instead the columns F/L, C. S, R, M and T the assessor needs to insert the right number from the list 1-3-6-10-16-24-32-54, by looking at the MOST tables seen before about the tool use and reported hereafter (Figure 3-4), one for each column, correspondent to the different subactivities: if one subactivity is evaluated as not necessary for that specific action, the number 0 has to be selected in the cell: it has to be specified that generally only one of this cells will contain a value different than zero, for each activity.
The next and last section of the table, shown in Figure 9, is related to the controlled move sequence model:
First of all the lines of this section have to be completed only if the Type Code of the considered activity row is 'C': if it is different, the respective line must be left blank, without selecting any code from the drop down menu. If instead it has to be filled in, a distinction has to be done between two different group of letters:
for what regards the columns A, B, and G the assessor needs to insert the right number in the list 1-3-6-10-16, by looking at the MOST table about the general move shown above (Figure 2), one for each column, correspondent to the different subactivities: if one subactivity is evaluated as not necessary for that specific action, the number 0 has to be selected in the cell;
for what regards instead the columns M, X and I the assessor needs to insert the right number from the list 1-3-6-10-16, by looking at the MOST table seen before about the controlled move and reported hereafter (Figure 5), one for each column, correspondent to the different subactivities: if one subactivity is evaluated as not necessary for that specific action, the number 0 has to be selected in the cell.
As a general statement, as already said in the limitations of this methodology, it is important not to have redundancy in the selection of the numbers, putting attention in not to replicate some sub-activities in different macro-activities, and so avoiding an overestimation of the processing times. To better explain this, in the Figure 10 is shown a tyical error in the assaignment, that if done along the whole cycle it can lead to a considerable rise of the total time:
The two cells highlighted in yellow are actually related to the same movement: in fact, the 1 put in the last column of the 'release tool A' activity would mean that the operator moves back in the base position after the movement, while the 1 put in the first column of the 'unload WIP 1' activity would mean that the operator moves from the base position to the position of the WIP 1: this is an unuseful repetition, since the operator concretely doesn't need to move back in position after having realesed the tool, for then moving again from the base position to the next position to be reached; the real movement is that of moving directly after having realesed the tool to the position of the WIP1, selecting in this way only the 1 of the second activity and deleting that of the previous. Before passing to the analysis of the Python code, an example to clarify the approach is showed.
The example provided from the layout 2 of the Catenaccio case analysed in the VLFT project is very important to understand how to practically apply this part of the toolkit, and to clearly get the flow of reasoning required by it. In the Figures 11, 12, 13 and 14 the just described sections of the Excel input file table are shown, properly filled by the assessor with all the data needed.
