Control Charts and Process Control in SAP, a White Paper
By Shashank Shekhar, Deloitte Consulting
Statistical Process Control is a technique for ensuring any process used to deliver a service or produce goods has the fidelity to meet standards and predefined specifications. All processes are subject to variability and it has been established that these variations can be attributed to common and special cause for variations called natural and assignable cause. Control Chart is a statistical tool developed to separate the two types of variations.
Natural variations affect almost every production process and are to be expected. This is variations that has several common causes and are very difficult to identify and correct. Natural variations, behave like a constant system of chance causes. In effect this variability is inherent in the process. Although individual values measured in a process are different, as a group they form a pattern that can be described as a distribution. When distributions are normal and remain within specified limits, the process is said to be in control and natural variations are tolerated.
Assignable or special variations are those effects on a process that are not built in. Causes of the assignable variations are unpredictable and can be directly identified and corrected (particularly when the time they occur is identified) to bring the process into control. Assignable variation can be traced to a specific reason. Factors such as machine wear, incorrect machine settings, fatigued or untrained workers or issues related to raw material are all potential sources of assignable variation. The objective of management is to identify and eliminate assignable variations so that processes will remain in control. The Control Charts are important statistical tools employed for filtering the assignable causes from the natural variations and help stabilize the process.
Process Control: A process that is in control will consistently produce parts or service within its own natural tolerance limits. This is done by eliminating all of the special causes of variation that exist. The first objective of SPC is to get the process in control, which means the identification and elimination of special causes of variation.
Process Capability Ratio is calculated as Six Sigma divided
By Total Tolerance, where Sigma represents Standard Deviation.
Control Charts: Control charts are the best tool to bring a process into control. These charts are simple statistical charts for detecting special causes of variation in the process at the time they exist. In addition these charts also measure the natural tolerance of the process due to normal variation or common causes. Control charts are the main tool to distinguish between random, natural variability and nonrandom variability. The basis for building a control chart is the concept of sampling and distribution which describes random (natural) variability. Sample measurements are made and plotted on the chart.
Control Charts and Process Control in SAP:
SAP Quality Management module supports control charts and process control using control charts. The control charts in SAP is designed based on the concept of Shewhart Control Chart and Acceptance Chart. In Shewhart Chart the control limits are based on process mean but in the Acceptance Chart the control limits are based on specification limits. Different control charts designed by SAP are primarily based on the control variables like Mean Value, Standard Deviation, Median Value, Range, Original Value of Sample, number of defects, number of non-confirming units…
Following is the sample representation of the different control charts provided by SAP
Control Char Picture 1 in Attachment
Master Data Requirement for the Control Charts:
The following Master Data is required to be maintained for using control charts in SAP
1. Maintain the Sampling Procedure for the Control Charts
2. Maintain Master Inspection Characteristics for the Control Chart
Sampling Procedure
Picture 2 in Attachment
A Sampling Procedure with Fixed Sample and valuation mode as SPC Inspection should be maintained while creating the sampling Procedure.
Master Inspection Characteristics:
The MIC control Indicators must be set for the Sampling Procedure and SPC characteristics.
Picture 3 in Attachment
Control Chart Configuration Details:
Standard SAP provides number of preconfigured control charts but based on the business requirements additional control charts can be configured as well as the existing control charts can be modified. The configuration of “SPC Criteria Settings” and “Control Charts Types” governs the required control chart functionalities.
The SPC Criteria Settings: The SPC criteria can be Master Inspection Characteristics, Task List Characteristics, and Task List Characteristics/Material etc.
Each SPC criteria contains the Function Module used in the Program for to maintain the control charts. The system calls the function module automatically during inspection processing when it calculates the sample size, in order to assign the selected criteria to the open control chart.
Control Chart Types: The control Chart Types contains the definition of control charts, the reference axis to be used in the control chart ( sap provides object number, time of creation, time of last change, time of inspection as the reference axis). If the “object number” is selected as the reference axis then the control chart will display “Inspection Lots” on the X axis of the control chart. Characteristics types related settings are made based on the Function Module used in the definition.
Using Control Charts: Control Charts can be called from the result recording screen or it can also be called using separate SAP transactions for the control charts,
QGC1: Control Chart for Inspection Lot
QGC2: Control Chart for Inspection Characteristics
QGC3: Control Chart for Master Inspection Characteristics
When transaction QGC1 is executed, a selection screen appears and based on the selection made a list of control chart appears and the control Chart can be called,
The control chart displays the Central Line, Upper Control Limit, Lower Control Limit and the process variations based on the result recording for the samples.
The Tolerances, Mean Values and the standard deviations can also be displayed for the control charts.
For Process Control the control charts can also display the Upper Warning Limit, Upper Action Limits, Lower Warning Limits and Lower Action Limits.
Possible Developments & Interfaces: Additional configuration and developments to meet the business requirements are supported in the control charts. For a global pharmaceutical client I modified the reference axis based on their requirements (they wanted to display batch numbers on the reference axis). Additional control chart types can be configured based on the existing control chart and the related program can be modified to include the additional functionalities.
For the Detailed Analysis of the QM results (which are not supported in SAP) Statistical Data Interface (QM – STI) can be used to link QM application to the external data evaluation system. Quality Control Charts can also be used to export the result data using QM – Statistical Interface to the evaluation system by choosing QM-STI evaluation from the menu option.
