This activity is used to optimize the sequence of shop order operations using the MSO (Manufacturing Scheduling and Optimization). This task is to be performed by a manufacturing planner or equivalent person. These parameters are functional parameters which will define the nature of the final finite schedule. Through these parameters organizations can decide what sort of optimizations that they would like to active. Simply you can choose from Optimization Goals to schedule operations.
Optimization Goals can be specified using Site Setting in Finite Scheduling Basic Data page (Applicable for both Manual & Automatic Scheduling modes)
By enabling this option Scheduling Service will give a higher opportunity to schedule passed due shop orders. This opportunity to schedule will be based on the Number of late days from particular Shop Order Need dates
The shop order operations belongs to selection would be rescheduled prioritizing if there are any pass-due shop order at the time of selective optimization.
Under Optimization Goals group you can enable 'Use Setup Matrices for Scheduling' Option.
Once after enabling you can set a Selection Window. This is used to define
the number of days which will be used to select operations considering the Shop
Order Need date starting from the Scheduling date (Current Date). For example,
if the Selection window is 10 and Scheduling date is 2023/01/01 then all the
operations until 2023/01/10 (i.e. scheduling date +10 ) will be selected for
scheduling optimization.
After enabling MSO dataset this setting will be
applied for each and every scheduling request that you send to Scheduling Service
in MSO.
With resource-limited scheduling, the overall sequence in which jobs are scheduled into the shopfloor is important for the overall production performance. If jobs are scheduled strictly by the standard constraint then the average tardiness of the schedule should be minimized, but possibly at the expense of setup cost, especially if setups are sequence-dependent. Combining shop orders with the same or similar setup characteristics into batches reduces those costs, but can result in delivery delays. This kind of problem is often present in process-like industries, e.g., printing where the objective is often to sequence jobs, e.g., from light colors to dark.
When sequencing considering the Setup matrices the Operations in different characteristics such as color, length, temperature and so on, connected to the part being manufactured optimizing the schedule to get Least Amount of Accumulated Operation Setup time. A given part can have more than one characteristic as well as the Sequencing can be based on more than one characteristic as well. Optimizing all finite workcenters of site in the Same time is one of the Key functionality in MSO.
Limitations in Use Setup Matrices option :
Example: Planner has 10 Operations from different parts which have Color and Viscosity as discrete characteristics.
| Part/Operation | A | B | C | D | E | F | G | H | I | J |
| Colour | Red | Blue | Green | Blue | Red | Green | Blue | Blue | Red | Red |
| Viscosity | High | High | Low | High | High | High | Low | Low | Low | High |
These operations are scheduling in same finite workcenter which has same descrete characterisitcs as constraints with predefined setup matrices as below.
| Color From | Color To | Setup Time |
| Red | Red | 0 Hours |
| Red | Green | 3 Hours |
| Red | Blue | 3 Hours |
| Green | Red | 1 Hours |
| Green | Green | 0 Hours |
| Green | Blue | 1 Hours |
| Blue | Red | 2 Hours |
| Blue | Green | 2 Hours |
| Blue | Blue | 0 Hours |
| Viscosity From | Viscosity To | Setup Time |
| High | High | 0 Hours |
| High | Low | 1 Hours |
| Low | High | 5 Hours |
| Low | Low | 0 Hours |
Here we have two setup Matrices.
If we consider the Least Amount of Accumulated Operation Setup time here we need to sequence based on Viscosity first since it has highest setup time when scheduling Low to High (5 Hours). Same viscosity transitions are having 0 time.
We need to schedule high viscosity operations first to achive the least setup time.
Then in Color based setup matrix Red to Green and Red to Blue/Green are having highest time (3 Hours) and then Blue to Red/Green (2 Hours). Lowest is when starting from Green. Same colour transitions are having 0 time.
In this example if we start from Green and then Blue and finally Red then we can get the least amount of setup time in colour setup matrix.
| Part/Operation | A | B | C | D | E | F | G | H | I | J |
| Colour | Green | Blue | Blue | Red | Red | Red | Green | Blue | Blue | Red |
| Viscosity | High | High | High | High | High | High | Low | Low | Low | Low |
| Accumilated Setup Time | (+1) | (+2) | (+3) & (+1) | (+1) | (+2) | |||||
| 0 hours | 1 hour | 1 hour | 3 hours | 3 hours | 3 hours | 6 hours | 7 hours | 7 hours | 9 hours | |
Note:
We consider the higest setup time when there are two transitions in same time. In Part F to G transition we are considering 3 hours time taking for Color transition. We assume the 1 hour time taking for Viscosity transition can be consumed in the same time )
According to native bahavior in MSO when scheduling similar characteristic operations MSO would prioratize shorter operations first based on the Scheduling direction of shop order.
Least Amount of Accumulated Operation Setup time for this example is 9 hours.