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 that define the nature of the final finite schedule. Through these parameters, organizations can decide what sort of optimizations that they want to achieve. Simply you can choose from Optimization Goals to schedule operations.
Optimization Goals can be specified using Site setting in the Finite Scheduling Basic Data page (Applicable for both Manual and 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 belonging to selection would be rescheduled prioritizing if there are any passed due shop orders at the time of selective optimization.
Under the Optimization Goals group, you can enable the 'Use Setup Matrices for Scheduling' Option.
Once after enabling you can set a selection window. This is used to define
the number of days that 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 the 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 on the shop floor 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 the 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 work centers of the site at 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 |
| Color | Red | Blue | Green | Blue | Red | Green | Blue | Blue | Red | Red |
| Viscosity | High | High | Low | High | High | High | Low | Low | Low | High |
These operations are scheduled in same finite work center which has same discrete characteristics 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 the highest setup time when scheduling Low to High (5 Hours). Same viscosity transitions have 0 times.
We need to schedule high-viscosity operations first to achieve the least setup time.
Then in Color based set up matrix, Red to Green and Red to Blue/Green are have the highest time (3 Hours) and then Blue to Red/Green (2 Hours). Lowest is when starting from Green. Same color 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 color setup matrix.
| Part/Operation | A | B | C | D | E | F | G | H | I | J |
| Color | Green | Blue | Blue | Red | Red | Red | Green | Blue | Blue | Red |
| Viscosity | High | High | High | High | High | High | Low | Low | Low | Low |
| Accumulated 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 highest setup time when there are two transitions at the same time. In Part F to G transition, we consider 3 hours for Color transition. We assume the 1 hour time taken for Viscosity transition can be consumed at the same time)
According to native behavior in MSO when scheduling similar characteristic operations MSO would prioritize shorter operations first based on the scheduling direction of shop order.
The Least Amount of Accumulated Operation Setup Time for this example is 9 hours.