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(2-3 min read)
During scheduling of orders on the shop floor as a scheduler/planner, the main objective is to generate a schedule, which follows a sequence in which the resources are utilized optimally. In a manufacturing process, most of the time a scheduler/planner wants to make sure that the generated schedule has minimal ‘Change Overs’. These changes can be due to factors related to flavours, allergens, colours, cleaning between orders, tooling changes etc. depending on the industry. If these factors are not managed efficiently, it results in loss of capacity, and lowers asset utilization. These changes are commonly referred to as ‘Change Over’ or ‘Setup’.
By managing changeover times, you can increase the efficiency of the manufacturing asset and increase productivity.
The traditional way to represent change overs in SAP is via an object/master data called ‘Setup Matrix’. Here the transitions between different parameters/characteristics of the products being manufactured are represented.
When used in conjunction with PPDS Optimiser methods, this can lead to an optimum production sequence which minimises change over losses.
Business example of the Problem
Let us take a simple case; we have a characteristic called “Colour”. There are 4 colours which would mean a total of 4x4 transitions (change overs), i.e. 16 changeovers. Transitioning from Light to Dark orders has short changeover times, whereas transitioning from Dark to Light orders will incur a longer change-over time.
Fig 1. – the more efficient changeover sequence is light to dark, rather than dark to light.
The problem becomes more complex when we have multiple characteristics. In a conventional SAP setup matrix, only two dimensions can be represented. In case of multiple characteristics, there is a need to be combine.
For example, with 2 characteristics.
- Colours = Blue and Yellow
- Format = 200ml and 500ml
In a conventional setup matrix, the characteristic values must be combined and assigned to Production Routings / Recipes as Setup Groups, i.e. Blue_200ml, Yellow_200ml, Blue_500ml, Yellow_500ml = 4 setup groups.
If there were 10 colours and 10 formats, this would require up to 10x10 = 100 setup groups and the setup matrix would require 100 x 100 = 10,000 transitions in the setup matrix.
Now looking at a complex manufacturing environment where there can be multiple characteristics that need to be considered when deriving an optimum changeover sequence. The combination of characteristics can lead to an infeasibly large number of changeovers.
For example, consider the following characteristics that affect changeovers:
In a conventional 2-dimensional setup matrix, this would imply
- Number of setup groups = 10*10*10*10*10 = 100,000
- Number of setup transitions = 100,000 x 100,000 = 10.000.000.000
This implies up to 10 billion transitions to maintain in a setup matrix!
This is not a feasible option either to maintain or from a system performance perspective.
Solution: Concept of Generated Setup Matrix
The concept behind the ‘Generated Setup Matrix’ is to initially create several smaller matrices for each characteristic being represented and then through a series of logical rules and automation steps, the system will generate a combined larger matrix.
Fig 2. Steps for creating and using a Generated Setup Matrix
Advantages of using the Generated Setup Matrix method
- User maintenance is simple and logical – only need to maintain characteristic values against Material Master
- Allows complex relationships between up to 6 characteristics to be represented in a feasible manner
- Allows for a more accurate representation of change over capacity losses which when combined with PPDS Optimiser setup minimisation methods will lead to a more efficient utilisation of the production assets
- Selection of using Maximum or Total of the setup time for the characteristic value
- Automatic assignment of setup groups on creation of production orders
- Maintenance of change over time only at the smaller matrices
- Avoids additional effort involved in preconfiguring setup groups in ECC
Olivehorse Consulting Services specialise in solving complex SAP supply chain planning challenges. Please contact us for more examples of best practise in PPDS and how we can help.
Sasibhushan Padmanabhan is a Senior SCM consultant. In total, he has 17 years of manufacturing and IT experience. SAP certified in the areas of S/4 Hana Production Planning and Manufacturing, SAP IBP, SAP-ARIBA Supply Chain Collaboration(SCC).