SAP APO - Managing large setup matrices in a complex manufacturing environment

Posted by Satish Satyamurthy on 12-Sep-2017 13:40:27

When scheduling production order sequences in a manufacturing process, there are times when capacity losses are incurred when transitioning between orders. This can be due to changes in materials, cleaning between production, tooling changes etc. This loss in capacity can be referred to as ‘Change Over’ or ‘Setup’.

By reducing changeover times, you can increase the efficiency of the manufacturing asset and the productive manufacturing time.

A common way to represent change over losses is via a ‘Setup Matrix’. Here the transitions between different characteristics of the products being manufactured are represented.

When used in conjunction with PP/DS Optimiser methods, this can lead to an optimum production sequence which minimises change over losses.

Consider the simple example below with the characteristic transition of Colour. There are four colours which means a total of 4x4 transitions, i.e. 16 transitions. Transitioning from light to dark orders incurs a short change-over time, 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

In a conventional SAP setup matrix only two dimensions can be represented, meaning multiple Characteristics must be combined. Take a simple example with two 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 and Yellow_500ml which equals four 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 look to a more complex manufacturing environment where there can be multiple characteristics that need to be considered when deriving an optimum changeover sequence. When combined, the characteristics can lead to an unfeasibly large number of transitions.

For example, consider the following characteristics that affect changeovers:

  • Colour, Flavour, Format, Family & Allergen

Each of the 10 characteristics above have 10 values, and 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! Clearly this is not a feasible option either to maintain or for systems performance. SAP do however provide a solution for this scenario in the form of Generated Setup Matrix.

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 PP/DS 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 PP/DS and how we can help solve your Supply Chain issues.

Satish Satyamurthy

Senior SCM Consultant, Olivehorse Consulting

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